ALBERT

Description: Habitat degradation not only disrupts habitat-forming species, but alters the sensory landscape within which most species must balance behavioural activities against predation risk. Rapidly developing a cautious behavioural phenotype, a condition known as neophobia, is advantageous when entering a novel risky habitat. Many aquatic organisms rely on damage-released conspecific cues (i.e. alarm cues) as an indicator of impending danger and use them to assess general risk and develop neophobia. This study tested whether settlement-stage damselfish associated with degraded coral reef habitats were able to use alarm cues as an indicator of risk and, in turn, develop a neophobic response at the end of their larval phase. Our results indicate that fish in live coral habitats that were exposed to alarm cues developed neophobia, and, in situ , were found to be more cautious, more closely associated with their coral shelters and survived four-times better than non-neophobic control fish. In contrast, fish that settled onto degraded coral habitats did not exhibit neophobia and consequently suffered much greater mortality on the reef, regardless of their history of exposure to alarm cues. Our results show that habitat degradation alters the efficacy of alarm cues with phenotypic and survival consequences for newly settled recruits.

Description: Watershed managers are challenged by the need for predictive temperature models with sufficient accuracy and geographic breadth for practical use. We described thermal regimes of New England rivers and streams based on a reduced set of metrics for the May to September growing season (July or August median temperature, diurnal rate of change, and magnitude and timing of growing season maximum) chosen through principal component analysis of 78 candidate metrics. We then developed and assessed spatial statistical models for each of these metrics, incorporating spatial autocorrelation based on both distance along the flow network and Euclidean distance between points. Calculation of spatial autocorrelation based on travel or retention time in place of network distance yielded tighter-fitting Torgegrams with less scatter but did not improve overall model prediction accuracy. We predicted monthly median July or August stream temperatures as a function of median air temperature, estimated urban heat island effect, shaded solar radiation, main channel slope, watershed storage (percent lake and wetland area), percent coarse-grained surficial deposits, and presence or maximum depth of a lake immediately upstream, with an overall root-mean-square prediction error of 1.4 and 1.5 ○ C, respectively. Growing season maximum water temperature varied as a function of air temperature, local channel slope, shaded August solar radiation, imperviousness, and watershed storage. Predictive models for July or August daily range, maximum daily rate of change, and timing of growing season maximum were statistically significant but explained a much lower proportion of variance than the above models (5-14% of total) . This article is protected by copyright. All rights reserved.

Description: Spontaneous counter-current imbibition into a finite porous medium is an important physical mechanism for many applications, included but not limited to irrigation, CO 2 storage and oil recovery. Symmetry considerations that are often valid in fractured porous media allow us to study the process in a one-dimensional domain. In 1D, the onset of imbibition can be captured by self-similar solutions and the imbibed volume scales with . At later times, the imbibition rate decreases and the finite size of the medium has to be taken into account. This requires numerical solutions. Here, we present a new approach to approximate the whole imbibition process semi-analytically. While the onset is captured by a semi-analytical solution. We also provide an a priori estimate of the time until which the imbibed volume scales with . This time is significantly longer than the time it takes until the imbibition front reaches the model boundary. The remainder of the imbibition process is obtained from a self-similarity solution. We test our approach against numerical solutions that employ parametrizations relevant for oil recovery and CO 2 sequestration. We show that this concept improves common first order approaches that heavily underestimate early-time behaviour and note that it can be readily included into dual porosity models. This article is protected by copyright. All rights reserved.

Description: Water extraction for anthropogenic use has become a major flux in the hydrological cycle. With increasing demand for water and challenges supplying it in the face of climate change, there is a pressing need to better understand connections between human populations, climate, water extraction, water use, and its impacts. To understand these connections, we collected and analyzed stable isotopic ratios of more than 800 urban tap water samples in a series of semiannual water surveys (spring and fall, 2013 to 2015) across the Salt Lake Valley (SLV) of northern Utah. Consistent with previous work, we found that mean tap water had a lower 2 H and 18 O concentration than local precipitation, highlighting the importance of nearby montane winter precipitation as source water for the region. However, we observed strong and structured spatiotemporal variation in tap water isotopic compositions across the region which we attribute to complex distribution systems, varying water management practices and multiple sources used across the valley. Water from different sources was not used uniformly throughout the area and we identified significant correlation between water source and demographic parameters including population and income. Isotopic mass balance indicated significant inter- and intra-annual variability in water losses within the distribution network due to evaporation from surface water resources supplying the SLV. Our results demonstrate the effectiveness of isotopes as an indicator of water management strategies and climate impacts within regional urban water systems, with potential utility for monitoring, regulation, forensic and a range of water resource research. This article is protected by copyright. All rights reserved.

Description: As the prospect for more frequent and severe extreme weather events gains scientific support, many nations are evaluating mitigation and adaptation options. Insurance and home retrofits could reduce household welfare losses due to flood events. Yet, even after disasters, households often fail to take risk mitigation actions. This paper presents the first randomized field experiment that tests the effect of information provision on household uptake of flood insurance and home retrofits. A sample of 364 flood-prone households in Bangkok was randomly split into treatment and control groups. The treatment group received practical details on home retrofits and flood insurance as well as social information regarding the insurance purchase decisions of peers. Results indicate that the information intervention increased insurance purchases by about five percentage points, while no effect was detected for home retrofits. This effect is nearly equal to the increase in uptake that the national insurance program in Thailand has achieved through all other means since its establishment in 2012. If scaled up to include all uninsured, flood-prone households in Bangkok, nearly 70,000 additional households could be insured. The results suggest that well-designed information interventions could increase uptake of flood insurance, without additional premium subsidies or mandates. This article is protected by copyright. All rights reserved.

Description: The need to understand potential climate impacts and feedbacks in Arctic regions has prompted recent interest in modeling of permafrost dynamics in a warming climate. A new fine-scale integrated surface/subsurface thermal hydrology modeling capability is described and demonstrated in proof-of-concept simulations. The new modeling capability combines a surface energy balance model with recently developed three-dimensional subsurface thermal hydrology models and new models for nonisothermal surface water flows and snow distribution in the microtopography. Surface water flows are modeled using the diffusion wave equation extended to include energy transport and phase change of ponded water. Variation of snow depth in the microtopography, physically the result of wind scour, is modeled phenomenologically with a diffusion wave equation. The multiple surface and subsurface processes are implemented by leveraging highly parallel community software. Fully integrated thermal hydrology simulations on the tilted open book catchment, an important test case for integrated surface/subsurface flow modeling, are presented. Fine-scale 100-year projections of the integrated permafrost thermal hydrological system on an ice wedge polygon at Barrow Alaska in a warming climate are also presented. These simulations demonstrate the feasibility of microtopography-resolving, process-rich simulations as a tool to help understand possible future evolution of the carbon-rich Arctic tundra in a warming climate. This article is protected by copyright. All rights reserved.

Description: Despite covering only approximately 138,000 km 2 , mangroves are globally important carbon sinks with carbon density values 3-4 times that of terrestrial forests. A key challenge in evaluating the carbon benefits from mangrove forest conservation is the lack of rigorous spatially resolved estimates of mangrove sediment carbon stocks; most mangrove carbon is stored belowground. Previous work has focused on detailed estimations of carbon stores over relatively small areas, which has obvious limitations in terms of generality and scope of application. Most studies have focused only on quantifying the top 1m of belowground carbon (BGC). Carbon stored at depths beyond 1m, and the effects of mangrove species, location and environmental context on these stores, is poorly studied. This study investigated these variables at two sites (Gazi and Vanga in the south of Kenya) and used the data to produce a country-specific BGC predictive model for Kenya and map BGC store estimates throughout Kenya at spatial scales relevant for climate change research, forest management and REDD+ (Reduced Emissions from Deforestation and Degradation). The results revealed that mangrove species was the most reliable predictor of BGC; Rhizophora muronata had the highest mean BGC with 1485.5t C ha −1 . Applying the species-based predictive model to a base map of species distribution in Kenya for the year 2010 with a 2.5m 2 resolution, produced an estimate of 69.41 Mt C (± 9.15 95% C.I.) for BGC in Kenyan mangroves. When applied to a 1992 mangrove distribution map, the BGC estimate was 75.65 Mt C (± 12.21 95% C.I.); an 8.3% loss in BGC stores between 1992 and 2010 in Kenya. The country level mangrove map provides a valuable tool for assessing carbon stocks and visualising the distribution of BGC. Estimates at the 2.5m 2 resolution provide sufficient detail for highlighting and prioritising areas for mangrove conservation and restoration. This article is protected by copyright. All rights reserved.

Description: In light of daunting global sustainability challenges such as climate change, biodiversity loss and food security, improving our understanding of the complex dynamics of the Earth system is crucial. However, large knowledge gaps related to the effects of land management persist, in particular those human-induced changes in terrestrial ecosystems that do not result in land cover conversions. Here we review the current state of knowledge of ten common land management activities for their biogeochemical and biophysical impacts, the level of process-understanding and data availability. Our review shows that ca. one tenth of the ice free land surface is under intense human management, half under medium and one fifth under extensive management. Based on our review, we cluster these ten management activities into three groups: (1) management activities for which datasets are available, and for which a good knowledge base exists (cropland harvest and irrigation); (2) management activities for which sufficient knowledge on biogeochemical and biophysical effects exists but robust global datasets are lacking (forest harvest, tree species selection, grazing and mowing harvest, N-fertilization); and (3) land management practices with severe data gaps concomitant with an unsatisfactory level of process understanding (crop species selection, artificial wetland drainage, tillage and fire management and crop residue management, an element of crop harvest). Although we identify multiple impediments to progress, we conclude that the current status of process understanding and data availability is sufficient to advance with incorporating management in e.g. Earth System or Dynamic Vegetation models in order to provide a systematic assessment of their role in the Earth system. This review contributes to a strategic prioritization of research efforts across multiple disciplines, including land system research, ecological research and Earth system modelling. This article is protected by copyright. All rights reserved.

Description: Species compositional shifts have important consequences to biodiversity and ecosystem function and services to humanity. In boreal forests, compositional shifts from late-successional conifers to early-successional conifers and deciduous broadleaves have been postulated based on increased fire frequency associated with climate change truncating stand age-dependent succession. However, little is known about how climate change has affected forest composition in the background between successive catastrophic fires in boreal forests. Using 1797 permanent sample plots from western boreal forests of Canada measured from 1958 to 2013, we show that after accounting for stand age-dependent succession, the relative abundances of early-successional deciduous broadleaves and early-successional conifers have increased at the expense of late-successional conifers with climate change. These background compositional shifts are persistent temporally, consistent across all forest stand ages and pervasive spatially across the region. Rising atmospheric CO 2 promoted early-successional conifers and deciduous broadleaves, and warming increased early-successional conifers at the expense of late-successional conifers, but compositional shifts were not associated with climate moisture index. Our results emphasize the importance of climate change on background compositional shifts in the boreal forest and suggest further compositional shifts as rising CO 2 and warming will continue in the 21st century.

Description: A cross-site analysis was conducted on seven diverse, forested watersheds in the northeastern U.S. to evaluate hydrological responses (evapotranspiration, soil moisture, seasonal and annual streamflow, and water stress) to projections of future climate. We used output from four Atmosphere-Ocean General Circulation Models (AOGCMs) (CCSM4, HadGEM2-CC, MIROC5, and MRI-CGCM3) included in Phase 5 of the Coupled Model Intercomparison Project, coupled with two Representative Concentration Pathways (RCP 8.5 and 4.5). The coarse resolution AOGCMs outputs were statistically downscaled using an asynchronous regional regression model to provide finer resolution future climate projections as inputs to the deterministic dynamic ecosystem model PnET-BGC. Simulation results indicated that projected warmer temperatures and longer growing seasons in the northeastern U.S. are anticipated to increase evapotranspiration across all sites, although invoking CO 2 effects on vegetation (growth enhancement and increases in water use efficiency (WUE)) diminish this response. The model showed enhanced evapotranspiration resulted in drier growing season conditions across all sites and all scenarios in the future. Spruce-fir conifer forests have a lower optimum temperature for photosynthesis, making them more susceptible to temperature stress than more tolerant hardwood species, potentially giving hardwoods a competitive advantage in the future. However, some hardwood forests are projected to experience seasonal water stress, despite anticipated increases in precipitation, due to the higher temperatures, earlier loss of snowpacks, longer growing seasons and associated water deficits. Considering future CO 2 effects on WUE in the model alleviated water stress across all sites. Modeled streamflow responses were highly variable, with some sites showing significant increases in annual water yield, while others showed decreases. This variability in streamflow responses poses a challenge to water resource management in the northeastern U.S. Our analyses suggest that dominant vegetation type and soil type are important attributes in determining future hydrologic responses to climate change. This article is protected by copyright. All rights reserved.

Description: Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies, and quantifying the impacts of land cover change on the climate system. Here we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover. This article is protected by copyright. All rights reserved.

Description: Understanding the evolutionary consequences of the Green Revolution, particularly in wild populations, is an important frontier in contemporary biology. Because human impacts have occurred at varying magnitudes or time periods depending on the study ecosystem, evolutionary histories may vary considerably among populations. Paleogenetics in conjunction with paleolimnology enable us to associate microevolutionary dynamics with detailed information on environmental change. We used this approach to reconstruct changes in the temporal population genetic structure of the keystone zooplankton grazer, Daphnia pulicaria , using dormant eggs extracted from sediments in two Minnesota lakes (South Center, Hill). The extent of agriculture and human population density in the catchment of these lakes has differed markedly since European settlement in the late 19 th century, and is reflected in their environmental histories reconstructed here. The reconstructed environments of these two lakes differed strongly in terms of environmental stability and their associated patterns of Daphnia population structure. We detected long periods of stability in population structure and environmental conditions in South Center Lake that were followed by a dramatic temporal shift in population genetic structure after the onset of European settlement and industrialized agriculture in its watershed. In particular, we noted a 24.3-fold increase in phosphorus (P) flux between pre-European and modern sediment P accumulation rates (AR) in this lake. In contrast, no such shifts were detected in Hill Lake, where the watershed was not as impacted by European settlement and rates of change were less directional with a much smaller increase of sediment P AR (2.3-fold). We identify direct and indirect effects of eutrophication proxies on genetic structure in these lake populations, and demonstrate the power of using this approach in understanding the consequences of anthropogenic environmental change on natural populations throughout historic time periods. This article is protected by copyright. All rights reserved.

Description: A general probabilistic prediction network is proposed for hydrological drought examination and environmental flow assessment. This network consists of three major components. First, we present the joint streamflow drought indicator (JSDI) to describe the hydrological dryness/wetness conditions. The JSDI is established based on a high-dimensional multivariate probabilistic model. In the second part, a drought-based environmental flow assessment method is introduced, which provides dynamic risk-based information about how much flow (the environmental flow target) is required for drought recovery and its likelihood under different hydrological drought initial situations. The final part involves estimating the conditional probability of achieving the required environmental flow under different precipitation scenarios according to the joint dependence structure between streamflow and precipitation. Three watersheds from different countries (Germany, China, and United States) with varying sizes from small to large were used to examine the usefulness of this network. The results show that the JSDI can provide an assessment of overall hydrological dryness/wetness conditions and performs well in identifying both drought onset and persistence. This network also allows quantitative prediction of targeted environmental flow required for hydrological drought recovery and estimation of the corresponding likelihood. Moreover, the results confirm that the general network can estimate the conditional probability associated with the required flow under different precipitation scenarios. The presented methodology offers a promising tool for water supply planning and management and for drought-based environmental flow assessment. The network has no restrictions that would prevent it from being applied to other basins worldwide. This article is protected by copyright. All rights reserved.

Description: The repository concept for geological disposal of spent nuclear fuel in Sweden and Finland is planned to be constructed in sparsely fractured crystalline bedrock and with an engineered bentonite buffer to embed the waste canisters. An important stage in such a deep repository is the post-closure phase following the deposition and the backfilling operations when the initially unsaturated buffer material gets hydrated by the groundwater delivered by the natural bedrock. We use numerical simulations to interpret observations on buffer wetting gathered during an in situ campaign, the Bentonite Rock Interaction Experiment, in which unsaturated bentonite columns were introduced into deposition holes in the floor of a 417 m deep tunnel at the Äspö Hard Rock Laboratory in Sweden. Our objectives are to assess the performance of state-of-the-art flow models in reproducing the buffer wetting process and to investigate to which extent dependable predictions of buffer wetting times and saturation patterns can be made based on information collected prior to buffer insertion. This would be important for preventing insertion into unsuitable bedrock environments. Field data and modeling results indicate the development of a de-saturated zone in the rock and show that in most cases, the presence or absence of fractures and flow heterogeneity are more important factors for correct wetting predictions than the total inflow. For instance, for an equal open-hole inflow value, homogeneous inflow yields much more rapid buffer wetting than cases where fractures are represented explicitly thus creating heterogeneous inflow distributions. This article is protected by copyright. All rights reserved.

Description: Many aquifers that are highly contaminated by arsenic in South and Southeast Asia are in the floodplains of large river networks. Under natural conditions, these aquifers would discharge into nearby rivers; however large-scale groundwater pumping has reversed the flow in some areas so that rivers now recharge aquifers. At a field site near Hanoi Vietnam, we find river water recharging the aquifer becomes high in arsenic, reaching concentrations above 1000 μg/L, within the upper meter of recently (〈 ∼10 yrs ) deposited riverbed sediments as it is drawn into a heavily pumped aquifer along the Red River. Groundwater arsenic concentrations in aquifers adjacent to the river are largely controlled by river geomorphology. High (〉 50 μg/L) aqueous arsenic concentrations are found in aquifer regions adjacent to zones where the river has recently deposited sediment and low arsenic concentrations are found in aquifer regions adjacent to erosional zones. High arsenic concentrations are even found adjacent to a depositional river reach in a Pleistocene aquifer, a type of aquifer sediment which generally hosts low arsenic water. Using geochemical and isotopic data we estimate the in-situ rate of arsenic release from riverbed sediments to be up to 1000 times the rates calculated on inland aquifer sediments in Vietnam. Geochemical data for riverbed porewater conditions indicate that the reduction of reactive, poorly crystalline iron oxides controls arsenic release. We suggest that aquifers in these regions may be susceptible to further arsenic contamination where riverine recharge drawn into aquifers by extensive groundwater pumping flows through recently deposited river sediments before entering the aquifer. This article is protected by copyright. All rights reserved.

Description: Training image-based geostatistical methods are increasingly popular in groundwater hydrology even if existing algorithms present limitations that often make real-world applications difficult. These limitations include a computational cost that can be prohibitive for high-resolution 3D applications, the presence of visual artifacts in the model realizations, and a low variability between model realizations due to the limited pool of patterns available in a finite-size training image. In this paper, we address these issues by proposing an iterative patch-based algorithm which adapts a graph cuts methodology that is widely used in computer graphics. Our adapted graph cuts method optimally cuts patches of pixel values borrowed from the training image and assembles them successively, each time accounting for the information of previously stitched patches. The initial simulation result might display artifacts, which are identified as regions of high cost. These artifacts are reduced by iteratively placing new patches in high-cost regions. In contrast to most patch-based algorithms, the proposed scheme can also efficiently address point conditioning. An advantage of the method is that the cut process results in the creation of new patterns that are not present in the training image, thereby increasing pattern variability. To quantify this effect, a new measure of variability is developed, the merging index, quantifies the pattern variability in the realizations with respect to the training image. A series of sensitivity analyses demonstrates the stability of the proposed graph cuts approach, which produces satisfying simulations for a wide range of parameters values. Applications to 2D and 3D cases are compared to state-of-the-art multiple-point methods. The results show that the proposed approach obtains significant speedups and increases variability between realizations. Connectivity functions applied to 2D models transport simulations in 3D models are used to demonstrate that pattern continuity is preserved. This article is protected by copyright. All rights reserved.

Description: ABSTRACT We investigate the potential of integrating desalination to existing reservoir systems to mitigate supply uncertainty. Desalinated seawater and wastewater are relatively reliable but expensive. Water from natural resources like reservoirs is generally cheaper but climate sensitive. We propose combining the operation of a reservoir, and seawater and wastewater desalination plants for an overall system that is less vulnerable to scarcity and uncertainty, while constraining total cost. The joint system is modeled as a multi-objective optimization problem with the double objectives of minimizing risk and vulnerability, subject to a minimum limit on resilience. The joint model is applied to two cases, one based on the climate and demands of a location in India and the other of a location in California. The results for the Indian case indicate it possible for the joint system to reduce risk and vulnerability to zero given a budget increase of 20-120% under current climate conditions and 30-150% under projected future conditions. For the Californian case, this would require budget increases of 20-80% and 30-140% under current and future conditions respectively. Further, our analysis shows a two-way interaction between the reservoir and desalination plants where the optimal operation of the former is just as much affected by the latter as the latter by the former. This highlights the importance of an integrated management approach. This study contributes to a greater quantitative understanding of desalination as a redundancy measure for adapting water supply infrastructures for a future of greater scarcity and uncertainty. This article is protected by copyright. All rights reserved.

Description: The cosmic-ray neutron method was developed for intermediate-scale soil moisture detection, but may potentially be used for other hydrological applications. The neutron signal of different hydrogen pools is poorly understood and separating them is difficult based on neutron measurements alone. Including neutron transport modeling may accommodate this shortcoming. However, measured and modeled neutrons are not directly comparable. Neither the scale nor energy ranges are equivalent, and the exact neutron energy sensitivity of the detectors is unknown. Here, a methodology to enable comparability of the measured and modeled neutrons is presented. The usual cosmic-ray soil moisture detector measures moderated neutrons by means of a proportional counter surrounded by plastic, making it sensitive to epithermal neutrons. However, that configuration allows for some thermal neutrons to be measured. The thermal contribution can be removed by surrounding the plastic with a layer of cadmium, which absorbs neutrons with energies below 0.5 eV. Likewise, cadmium-shielding of a bare detector allows for estimating the epithermal contribution. First, the cadmium difference method is used to determine the fraction of thermal and epithermal neutrons measured by the bare and plastic-shielded detectors, respectively. The cadmium difference method results in linear correction models for measurements by the two detectors, and has the greatest impact on the neutron intensity measured by the moderated detector at the ground surface. Next, conversion factors are obtained relating measured and modeled neutron intensities. Finally, the methodology is tested by modeling the neutron profiles at an agricultural field site and satisfactory agreement to measurements is found. This article is protected by copyright. All rights reserved.

Description: The sustainability of using irrigation to produce food depends not only on the availability of sufficient water, but also on the soils ‘response’ to irrigation. Stocks of carbon (C) and nitrogen (N) are key components of soil organic matter (SOM), which is important for sustainable agricultural production. While there is some information about the effects of irrigation on soil C stocks in cropping systems, there is a paucity of such studies in pastoral food production systems. For this study, we sampled soils from 34 paired, irrigated and unirrigated pasture sites across New Zealand (NZ) and analysed these for total C and N. On average, irrigated pastures had significantly ( P 〈0.05) less soil carbon (C) and nitrogen (N) than adjacent unirrigated pastures, with differences of 6.99 t C ha −1 and 0.58 t N ha −1 in the uppermost 0.3 m. Differences in C and N tended to occur throughout the soil profile, so the cumulative differences increased with depth, and the proportion of the soil C lost from deeper horizons was large. There were no relationships between differences in soil C and N stocks and the length of time under irrigation. This study suggests SOM will decrease when pastures under a temperate climate are irrigated. On this basis, increasing the area of temperate pasture land under irrigation would result in more CO 2 in the atmosphere, and may directly and indirectly increase N leaching to groundwater. Given the large and increasing area of land being irrigated both in NZ and on a global scale, there is an urgent need to determine whether the results found in this study are also applicable in other regions and under different land management systems (e.g. arable). This article is protected by copyright. All rights reserved.

Description: From 1890 to 2015, anthropogenic carbon dioxide emissions have increased atmospheric CO 2 concentrations from 270 mol mol −1 to 400 mol mol −1 . The effect of increased carbon emissions on plant growth and reproduction has been the subject of study of Free Air CO 2 Enrichment (FACE) experiments. These experiments have found a) an increase in internal CO 2 partial pressure (c i ) alongside acclimation of photosynthetic capacity, b) variable decreases in stomatal conductance, and c) that increases in yield do not increase commensurate with CO 2 concentrations. Our data set, which includes a 115 year long selection of grasses collected in New Mexico since 1892 is consistent with an increased c i as a response to historical CO 2 increase in the atmosphere; with invasive species showing the largest increase. Comparison with Palmer Drought Sensitivity index (PDSI) for New Mexico indicates a moderate correlation with Δ 13 C (r 2 = 0.32, p 〈 0.01) before 1950, with no correlation (r 2 = 0.00, p = 0.91) after 1950. These results indicate that increased c i may have conferred some drought resistance to these grasses through increased availability of CO 2 in the event of reduced stomatal conductance in response to short term water shortage. Comparison with C 3 trees from arid environments ( Pinus longaeva and Pinus edulis in the US Southwest) as well as from wetter environments ( Bromus and Poa grasses in New Mexico) suggest differing responses based on environment; arid environments in New Mexico see increased intrinsic water use efficiency (WUE) in response to historic elevated CO 2 while wetter environments see increased c i . The present study suggests that a) the observed increases in c i in FACE experiments are consistent with historical CO 2 increases and b) the CO 2 increase influences plant sensitivity to water shortage, through either increased WUE or c i in arid and wet environments, respectively. This article is protected by copyright. All rights reserved.

Description: Models predicting ecosystem carbon dioxide (CO 2 ) exchange under future climate change rely on relatively few real-world tests of their assumptions and outputs. Here we demonstrate a rapid and cost-effective method to estimate CO 2 exchange from intact vegetation patches under varying atmospheric CO 2 concentrations . We find that net ecosystem CO 2 uptake (NEE) in a boreal forest rose linearly by 4.7 ± 0.2% of the current ambient rate for every 10 ppm CO 2 increase, with no detectable influence of foliar biomass, season or nitrogen (N) fertilization. The lack of any clear short-term NEE response to fertilization in such an N-limited system is inconsistent with the instantaneous down-regulation of photosynthesis formalized in many global models. Incorporating an alternative mechanism with considerable empirical support – diversion of excess carbon to storage compounds – into an existing earth system model brings the model output into closer agreement with our field measurements. A global simulation incorporating this modified model reduces a long-standing mismatch between the modeled and observed seasonal amplitude of atmospheric CO 2 . Wider application of this chamber approach would provide critical data needed to further improve modeled projections of biosphere-atmosphere CO 2 exchange in a changing climate. This article is protected by copyright. All rights reserved.

Description: Each year, two or three species that had been considered to be extinct are rediscovered. Uncertainty about whether or not a species is extinct is common, because rare and highly threatened species are difficult to detect. Biological traits such as body size and range size are expected to be associated with extinction. However, these traits, together with the intensity of search effort, might influence the probability of detection and extinction differently. This makes statistical analysis of extinction and rediscovery challenging. Here we use a variant of survival analysis known as cure rate modelling to differentiate factors that influence rediscovery from those that influence extinction. We analyse a global dataset of 99 mammals that have been categorised as extinct or possibly extinct. We estimate the probability that each of these mammals is still extant, and thus estimate the proportion of missing (presumed extinct) mammals that are incorrectly assigned extinction. We find that body mass and population density are predictors of extinction, and body mass and search effort predict rediscovery. In mammals, extinction rate increases with body mass and population density, and these traits act synergistically to greatly elevate extinction rate in large species that also occurred in formerly dense populations. However, when they remain extant, larger-bodied missing species are rediscovered sooner than smaller species. Greater search effort increases the probability of rediscovery in larger species of missing mammals, but has a minimal effect on small species, which take longer to be rediscovered, if extant. By separating the effects of species characteristics on extinction and detection, and using models with the assumption that a proportion of missing species will never be rediscovered, our new approach provides estimates of extinction probability in species with few observation records and scant ecological information. This article is protected by copyright. All rights reserved.

Description: Livestock grazing activities potentially alter ecosystem carbon (C) and nitrogen (N) cycles in grassland ecosystems. Despite the fact that numerous individual studies and a few meta-analyses had been conducted, how grazing, especially its intensity, affects belowground C and N cycling in grasslands remains unclear. In this study, we performed a comprehensive meta-analysis of 115 published studies to examine the responses of 19 variables associated with belowground C and N cycling to livestock grazing in global grasslands. Our results showed that, on average, grazing significantly decreased belowground C and N pools in grassland ecosystems, with the largest decreases in microbial biomass C and N (21.62 and 24.40%, respectively). In contrast, belowground fluxes, including soil respiration, soil net N mineralization and soil N nitrification increased by 4.25%, 34.67 and 25.87%, respectively in grazed grasslands compared to ungrazed ones. More importantly, grazing intensity significantly affected the magnitude (even direction) of changes in the majority of the assessed belowground C and N pools and fluxes, and C:N ratio as well as soil moisture. Specifically,light grazing contributed to soil C and N sequestration whereas moderate and heavy grazing significantly increased C and N losses. In addition, soil depth, livestock type and climatic conditions influenced the responses of selected variables to livestock grazing to some degree. Our findings highlight the importance of the effects of grazing intensity on belowground C and N cycling, which may need to be incorporated into regional and global models for predicting effects of human disturbance on global grasslands and assessing the climate- biosphere feedbacks. This article is protected by copyright. All rights reserved.

Description: Salinity intrusion caused by land subsidence resulting from increasing groundwater abstraction, decreasing river sediment loads and increasing sea level because of climate change has caused widespread soil salinization in coastal ecosystems. Soil salinization may greatly alter nitrogen (N) cycling in coastal ecosystems. However, a comprehensive understanding of the effects of soil salinization on ecosystem N pools, cycling processes and fluxes is not available for coastal ecosystems. Therefore, we compiled data from 551 observations from 21 peer-reviewed papers and conducted a meta-analysis of experimental soil salinization effects on 19 variables related to N pools, cycling processes and fluxes in coastal ecosystems. Our results showed that the effects of soil salinization varied across different ecosystem types and salinity levels. Soil salinization increased plant N content (18%), soil NH 4 + (12%) and soil total N (210%), although it decreased soil NO 3 - (2%) and soil microbial biomass N (74%). Increasing soil salinity stimulated soil N 2 O fluxes as well as hydrological NH 4 + and NO 2 - fluxes more than three-fold, although it decreased the hydrological dissolved organic nitrogen (DON) flux (59%). Soil salinization also increased the net N mineralization by 70%, although salinization effects were not observed on the net nitrification, denitrification and dissimilatory nitrate reduction to ammonium in this meta-analysis. Overall, this meta-analysis improves our understanding of the responses of ecosystem N cycling to soil salinization, identifies knowledge gaps and highlights the urgent need for studies on the effects of soil salinization on coastal agro-ecosystem and microbial N immobilization. Additional increases in knowledge are critical for designing sustainable adaptation measures to the predicted intrusion of salinity intrusion so that the productivity of coastal agro-ecosystems can be maintained or improved and the N losses and pollution of the natural environment can be minimized. This article is protected by copyright. All rights reserved.

Description: Can species shift their distributions fast enough to track changes in climate? We used abundance data from the 1950s and the 2000s in Wisconsin to measure shifts in the distribution and abundance of 78 forest-understory plant species over the last half-century and compare these shifts to changes in climate. We estimated temporal shifts in the geographic distribution of each species using vectors to connect abundance-weighted centroids from the 1950s and 2000s. These shifts in distribution reflect colonization, extirpation, and changes in abundance within sites, separately quantified here. We then applied climate analog analyses to compute vectors representing the climate change that each species experienced. Species shifted mostly to the northwest (mean: 49 ± 29 km) primarily reflecting processes of colonization and changes in local abundance. Analog climates for these species shifted even further to the northwest, however, exceeding species’ shifts by an average of 90 ± 40 km. Most species thus failed to match recent rates of climate change. These lags decline in species that have colonized more sites and those with broader site occupancy, larger seed mass, and higher habitat fidelity. Thus, species’ traits appear to affect their responses to climate change, but relationships are weak. As climate change accelerates, these lags will likely increase, potentially threatening the persistence of species lacking the capacity to disperse to new sites or locally adapt. However, species with greater lags have not yet declined more in abundance. The extent of these threats will likely depend on how other drivers of ecological change and interactions among species affect their responses to climate change. This article is protected by copyright. All rights reserved.

Description: Debris flows are a typical hazard on steep slopes after wildfire, but unlike debris flows that mobilize from landslides, most post-wildfire debris flows are generated from water runoff. The majority of existing debris-flow modeling has focused on landslide-triggered debris flows. In this study we explore the potential for using process-based rainfall-runoff models to simulate the timing of water flow and runoff-generated debris flows in recently burned areas. Two different spatially distributed hydrologic models with differing levels of complexity were used: the full shallow water equations and the kinematic wave approximation. Model parameter values were calibrated in two different watersheds, spanning two orders of magnitude in drainage area. These watersheds were affected by the 2009 Station Fire in the San Gabriel Mountains, CA, USA. Input data for the numerical models were constrained by time series of soil moisture, flow stage, and rainfall collected at field sites, as well as high-resolution lidar-derived digital elevation models. The calibrated parameters were used to model a third watershed in the burn area, and the results show a good match with observed timing of flow peaks. The calibrated roughness parameter (Manning's $n$) was generally higher when using the kinematic wave approximation relative to the shallow water equations, and decreased with increasing spatial scale. The calibrated effective watershed hydraulic conductivity was low for both models, even for storms occurring several months after the fire, suggesting that wildfire-induced changes to soil-water infiltration were retained throughout that time. Overall the two model simulations were quite similar suggesting that a kinematic wave model, which is simpler and more computationally efficient, is a suitable approach for predicting flood and debris flow timing in steep, burned watersheds. This article is protected by copyright. All rights reserved.

Description: We analyze the probability distribution of the hazard attenuation factor for a non-carcinogenic reactive compound captured by a well in heterogeneous porous formations. The hazard attenuation factor is defined as the ratio between the hazard index HI at a detection well and at the source. Heterogeneity of the aquifer is represented through the Multi-Indicator Model (a collection of blocks of independent permeability) while flow and transport are solved by the means of the Self-Consistent Approach, that is able to deal with any degree of heterogeneity. Due to formation heterogeneity, HI is a random variable and similar for hazard attenuation index. The latter can be fully characterized by its cumulative distribution function (CDF), which in turn can be related to the statistics of the travel time of solute particles, from the source to the detection well. The approach is applied to the case of a solute which undergoes decay and a well with a screen much smaller than the correlation scale of hydraulic conductivity. The results show that the probability of exceeding a given acceptable threshold of the hazard index is significantly affected by the level of heterogeneity comparable to the one observed for the MADE site, and the distance between the source and the well. This article is protected by copyright. All rights reserved.

Description: Humans are altering global environment at an unprecedented rate through changes in biodiversity, climate, nitrogen cycle, and land-use. In order to address their effects on ecosystem functioning, experiments most frequently explore one driver at a time and control as many confounding factors as possible. Yet, which driver exerts the largest influence on ecosystem functioning and whether their relative importance changes among systems remain unclear. We analyzed experiments in the Patagonian steppe that evaluated the aboveground net primary production (ANPP) response to manipulated gradients of species richness, precipitation, temperature, nitrogen fertilization (N) and grazing intensity. We compared the effect on ANPP relative to ambient conditions considering intensity and direction of manipulations for each driver. The ranking of responses to drivers with comparable manipulation intensity was: biodiversity〉grazing〉precipitation〉N. For a similar intensity of manipulation, the effect of biodiversity loss was 4.0, 3.6, and 1.5, times larger than N deposition, decreased precipitation, and increased grazing intensity. We interpreted our results considering two hypotheses. First, the response of ANPP to changes in precipitation and biodiversity is saturating, so we expected larger effects when the driver was reduced, relative to ambient conditions, than when it was increased. Experimental manipulations that reduced ambient levels had larger effects than those that increased them. Second, the sensitivity of ANPP to each driver is inversely related to the natural variability of the driver. In Patagonia, the ranking of natural variability of drivers is: precipitation〉grazing〉temperature〉biodiversity〉N. So, in general, the ecosystem was most sensitive to drivers that varied the least. Comparable results from Cedar Creek (MN) support both hypotheses and suggest that sensitivity to drivers varies among ecosystem types. Given the importance of understanding ecosystem sensitivity to predict global-change impacts, it is necessary to design new experiments located in regions with contrasting natural variability and that include the full range of drivers. This article is protected by copyright. All rights reserved.

Description: Evapotranspiration, defined as the total flux of water from the land surface to the atmosphere, is a major component of the hydrologic cycle and surface energy balance. Although evapotranspiration is expected to intensify with increasing temperatures, long-term, regional trends in evapotranspiration remain uncertain due to spatially and temporally limited direct measurements. In this study, we utilize an emergent relation between the land surface and atmospheric boundary layer to infer daily evapotranspiration from historical meteorological data collected at 236 weather stations across the U.S. Our results suggest a statistically significant ( α = 0.05) decrease in evapotranspiration of approximately 6% from 1961 to 2014, with a significant ( α = 0.05) sharp decline of 13% from 1998 to 2014. We attribute the decrease in evapotranspiration mostly to declines in surface conductance, but also to offsetting changes in longwave radiation, wind speed, and incoming solar radiation. Using an established stomatal conductance model, we explain the changes in inferred surface conductance as a response to increases in carbon dioxide and, more recently, to an abrupt decrease in atmospheric humidity. This article is protected by copyright. All rights reserved.

Description: Forest ecosystems across western North America will likely see shifts in both tree species dominance and composition over the rest of this century in response to climate change. Our objective in this paper is to identify which ecological regions might expect the greatest changes to occur. We used the process-based growth model 3-PG, to provide estimates of tree species responses to changes in environmental conditions and to evaluate the extent that species are resilient to shifts in climate over the rest of this century. We assessed the vulnerability of 20 tree species in western North America using the Canadian global circulation model under three different emission scenarios. We provided detailed projections of species shifts by including soil maps that account for the spatial variation in soil water availability and soil fertility as well as by utilizing annual climate projections of monthly changes in air temperature, precipitation, solar radiation, vapor pressure deficit and frost at a spatial resolution of 1 km. Projected suitable areas for tree species were compared to their current ranges based on observations at 〉40,000 field survey plots. Tree species were classified as vulnerable if environmental conditions projected in the future appear outside that of their current distribution ≥70% of the time. We added a migration constraint that limits species dispersal to 〈200 m year −1 to provide more realistic projections on species distributions. Based on these combinations of constraints, we predicted the greatest changes in the distribution of dominant tree species to occur within the Northwest Forested Mountains and the highest number of tree species stressed will likely be in the North American Deserts. Projected climatic changes appear especially unfavorable for species in the subalpine zone, where major shifts in composition may lead to the emergence of new forest types. This article is protected by copyright. All rights reserved.

Description: To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity ( GPP ), of photosynthetic capacity ( Pc ), and of other fluxes and pools. Models simulated consistent dry season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry season GPP reductions were driven by an external environmental factor, “soil water stress” and consequently by a constant or decreasing photosynthetic infrastructure ( Pc) , while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc ) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange ( NEE ) and respiration ( Re ) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry season declines in GPP and Re consistent with most DGVMs simulations. While water-limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light harvesting adaptations (e.g. variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. Correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments. This article is protected by copyright. All rights reserved.

Description: Transit times through hydrologic systems vary in time, but the nature of that variability is not well understood. Transit times variability was investigated in a 1 m 3 sloping lysimeter, representing a simplified model of a hillslope receiving periodic rainfall events for 28 days. Tracer tests were conducted using an experimental protocol that allows time-variable transit time distributions (TTDs) to be calculated from data. Observed TTDs varied with the storage state of the system, and the history of inflows and outflows. We propose that the observed time variability of the TTDs can be decomposed into two parts: ‘internal' variability associated with changes in the arrangement of, and partitioning between, flow pathways; and ‘external' variability driven by fluctuations in the flow rate along all flow pathways. These concepts can be defined quantitatively in terms of rank StorAge Selection (rSAS) functions, which is a theory describing lumped transport dynamics. Internal variability is associated with temporal variability in the rSAS function, while external is not. The rSAS function variability was characterized by an ‘inverse storage effect', whereby younger water is released in greater proportion under wetter conditions than drier. We hypothesize that this effect is caused by the rapid mobilization of water in the unsaturated zone by the rising water table. Common approximations used to model transport dynamics that neglect internal variability were unable to reproduce the observed breakthrough curves accurately. This suggests that internal variability can play an important role in hydrologic transport dynamics, with implications for field data interpretation and modeling. This article is protected by copyright. All rights reserved.

Description: In real water distribution networks (WDNs) are present thousands nodes and optimal placement of pressure and flow observations is a relevant issue for different management tasks. The planning of pressure observations in terms of spatial distribution and number is named sampling design and it was faced considering model calibration. Nowadays, the design of system monitoring is a relevant issue for water utilities e.g. in order to manage background leakages, to detect anomalies and bursts, to guarantee service quality, etc. In recent years, the optimal location of flow observations related to design of optimal district metering areas (DMAs) and leakage management purposes has been faced considering optimal network segmentation and the modularity index using a multi-objective strategy. Optimal network segmentation is the basis to identify network modules by means of optimal conceptual cuts, which are the candidate locations of closed gates or flow meters creating the DMAs. Starting from the WDN-oriented modularity index, as a metric for WDN segmentation, this paper proposes a new way to perform the sampling design , i.e. the optimal location of pressure meters , using newly developed sampling-oriented modularity index. The strategy optimizes the pressure monitoring system mainly based on network topology and weights assigned to pipes according to the specific technical tasks. A multi-objective optimization minimizes the cost of pressure meters while maximizing the sampling-oriented modularity index. The methodology is presented and discussed using the Apulian and Exnet networks. This article is protected by copyright. All rights reserved.

Description: In this paper, a methodology is developed to identify consistency of rating curve data based on a quality analysis of model results. This methodology, called Bidirectional Reach (BReach), evaluates results of a rating curve model with randomly sampled parameter sets in each observation. The combination of a parameter set and an observation is classified as non-acceptable if the deviation between the accompanying model result and the measurement exceeds observational uncertainty. Based on this classification, conditions for satisfactory behavior of a model in a sequence of observations are defined. Subsequently, a parameter set is evaluated in a data point by assessing the span for which it behaves satisfactory in the direction of the previous (or following) chronologically sorted observations. This is repeated for all sampled parameter sets and results are aggregated by indicating the endpoint of the largest span, called the maximum left (right) reach. This temporal reach should not be confused with a spatial reach (indicating a part of a river). The same procedure is followed for each data point and for different definitions of satisfactory behavior. Results of this analysis enable the detection of changes in data consistency. The methodology is validated with observed data and various synthetic stage-discharge data sets and proves to be a robust technique to investigate temporal consistency of rating curve data. It provides satisfying results despite of low data availability, errors in the estimated observational uncertainty and a rating curve model that is known to cover only a limited part of the observations. This article is protected by copyright. All rights reserved.

Description: With population growth, increasing water demands and climate change the need to understand the current and future pathways to water security is becoming more pressing. To contribute to addressing this challenge, we examine the link between water stress and society through socio-hydrological modeling. We conceptualize the interactions between an agricultural society with its environment in a stylized way. We apply the model to the case of the ancient Maya, a population that experienced a peak during the Classic Period (AD 600-830) and then declined during the ninth century. The hypothesis that modest drought periods played a major role in the society's collapse is explored. Simulating plausible feedbacks between water and society we show that a modest reduction in rainfall may lead to an 80% population collapse.Population density and crop sensitivity to droughts, however, may play an equally important role. The simulations indicate that construction of reservoirs results in less frequent drought impacts, but if the reservoirs run dry, drought impact may be more severe and the population drop may be larger. Index terms: 1812 Drought (4303) 1834 Human impacts (4323) 4330 Vulnerability. Keywords: socio-hydrology, Ancient Maya, drought, vulnerability. This article is protected by copyright. All rights reserved.

Description: Reliable characterization of hydraulic parameters is important for the understanding of groundwater flow and solute transport. The normal-score ensemble Kalman filter (NS-EnKF) has proven to be an effective inverse method for the characterization of non-Gaussian hydraulic conductivities by assimilating transient piezometric head data, or solute concentration data. Groundwater temperature, an easily captured state variable, has not drawn much attention as an additional state variable useful for the characterization of aquifer parameters. In this work, we jointly estimate non-Gaussian aquifer parameters (hydraulic conductivities and porosities) by assimilating three kinds of state variables (piezometric head, solute concentration, and groundwater temperature) using the NS-EnKF. A synthetic example including seven tests is designed, and used to evaluate the ability to characterize hydraulic conductivity and porosity in a non-Gaussian setting by assimilating different numbers and types of state variables. The results show that characterization of aquifer parameters can be improved by assimilating groundwater temperature data and that the main patters of the non-Gaussian reference fields can be retrieved with more accuracy and higher precision if multiple state variables are assimilated. This article is protected by copyright. All rights reserved.

Description: Predicting the impacts of climate change requires knowledge of the potential to adapt to rising temperatures, which is unknown for most species. Adaptive potential may be especially important in tropical species that have narrow thermal ranges and live close to their thermal optimum. We used the animal model to estimate heritability, genotype by environment interactions and nongenetic maternal components of phenotypic variation in fitness-related traits in the coral reef damselfish, Acanthochromis polyacanthus . Offspring of wild-caught breeding pairs were reared for two generations at current-day and two elevated temperature treatments (+1.5 and +3.0 °C) consistent with climate change projections. Length, weight, body condition and metabolic traits (resting and maximum metabolic rate and net aerobic scope) were measured at four stages of juvenile development. Additive genetic variation was low for length and weight at 0 and 15 days posthatching (dph), but increased significantly at 30 dph. By contrast, nongenetic maternal effects on length, weight and body condition were high at 0 and 15 dph and became weaker at 30 dph. Metabolic traits, including net aerobic scope, exhibited high heritability at 90 dph. Furthermore, significant genotype x environment interactions indicated potential for adaptation of maximum metabolic rate and net aerobic scope at higher temperatures. Net aerobic scope was negatively correlated with weight, indicating that any adaptation of metabolic traits at higher temperatures could be accompanied by a reduction in body size. Finally, estimated breeding values for metabolic traits in F2 offspring were significantly affected by the parental rearing environment. Breeding values at higher temperatures were highest for transgenerationally acclimated fish, suggesting a possible role for epigenetic mechanisms in adaptive responses of metabolic traits. These results indicate a high potential for adaptation of aerobic scope to higher temperatures, which could enable reef fish populations to maintain their performance as ocean temperatures rise.

Description: Urbanization is a global process contributing to the loss and fragmentation of natural habitats. Many studies have focused on the biological response of terrestrial taxa and habitats to urbanization. However, little is known regarding the consequences of urbanization on freshwater habitats, especially small lentic systems. In this study, we examined aquatic macro-invertebrate diversity (family and species level) and variation in community composition between 240 urban and 782 nonurban ponds distributed across the United Kingdom. Contrary to predictions, urban ponds supported similar numbers of invertebrate species and families compared to nonurban ponds. Similar gamma diversity was found between the two groups at both family and species taxonomic levels. The biological communities of urban ponds were markedly different to those of nonurban ponds, and the variability in urban pond community composition was greater than that in nonurban ponds, contrary to previous work showing homogenization of communities in urban areas. Positive spatial autocorrelation was recorded for urban and nonurban ponds at 0–50 km (distance between pond study sites) and negative spatial autocorrelation was observed at 100–150 km and was stronger in urban ponds in both cases. Ponds do not follow the same ecological patterns as terrestrial and lotic habitats (reduced taxonomic richness) in urban environments; in contrast, they support high taxonomic richness and contribute significantly to regional faunal diversity. Individual cities are complex structural mosaics which evolve over long periods of time and are managed in diverse ways. This facilitates the development of a wide range of environmental conditions and habitat niches in urban ponds which can promote greater heterogeneity between pond communities at larger scales. Ponds provide an opportunity for managers and environmental regulators to conserve and enhance freshwater biodiversity in urbanized landscapes whilst also facilitating key ecosystem services including storm water storage and water treatment.

Description: Nitrogen (N) deposition (N DEP ) drives forest carbon (C) sequestration but the size of this effect is still uncertain. In the field, an estimate of these effects can be obtained by applying mineral N fertilizers over the soil or forest canopy. A 15 N label in the fertilizer can be then used to trace the movement of the added N into ecosystem pools and deduce a C effect. However, N recycling via litter decomposition provides most of the nutrition for trees, even under heavy N DEP inputs. If this recycled litter nitrogen is retained in ecosystem pools differently to added mineral N, then estimates of the effects of N DEP on the relative change in C (ΔC/ΔN) based on short term isotope-labelled mineral fertilizer additions should be questioned. We used 15 N labelled litter to track decomposed N in the soil system (litter, soils, microbes, and roots) over 18 months in a Sitka spruce plantation and directly compared the fate of this 15 N to an equivalent amount in simulated N DEP treatments. By the end of the experiment, three times as much 15 N was retained in the O and A soil layers when N was derived from litter decomposition than from mineral N additions (60 % and 20 %, respectively), primarily because of increased recovery in the O layer. Roots expressed slightly more 15 N tracer from litter decomposition than from simulated mineral N DEP (7.5 % and 4.5 %) and compared to soil recovery, expressed proportionally more 15 N in the A layer than the O layer, potentially indicating uptake of organic N from decomposition. These results suggest effects of N DEP on forest ΔC/ΔN may not be apparent from mineral 15 N tracer experiments alone. Given the importance of N recycling, an important but underestimated effect of N DEP is its influence on the rate of N release from litter. This article is protected by copyright. All rights reserved.

Description: A potato crop multi-model assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low- (Chinoli, Bolivia and Gisozi, Burundi) and high- (Jyndevad, Denmark and Washington, United States) input management sites. Two calibration stages were explored, partial (P1), where experimental dry matter data were not provided, and full (P2). The median model ensemble response outperformed any single model in terms of replicating observed yield across all locations. Uncertainty in simulated yield decreased from 38% to 20% between P1 and P2. Model uncertainty increased with inter-annual variability, and predictions for all agronomic variables were significantly different from one model to another (p 〈 0.001). Uncertainty averaged 15% higher for low- versus high- input sites, with larger differences observed for evapotranspiration (ET), nitrogen uptake, and water use efficiency as compared to dry matter. A minimum of five partial, or three full, calibrated models was required for an ensemble approach to keep variability below that of common field variation. Model variation was not influenced by change in carbon dioxide (C), but increased as much as 41 and 23% for yield and ET respectively as temperature (T) or rainfall (W) moved away from historical levels. Increases in T accounted for the highest amount of uncertainty, suggesting that methods and parameters for T sensitivity represent a considerable unknown among models. Using median model ensemble values, yield increased on average 6% per 100-ppm C, declined 4.6% per °C, and declined 2% for every 10% decrease in rainfall (for non-irrigated sites). Differences in predictions due to model representation of light utilization were significant (p 〈 0.01). These are the first reported results quantifying uncertainty for tuber/root crops and suggest modeling assessments of climate change impact on potato may be improved using an ensemble approach. This article is protected by copyright. All rights reserved.

Description: Understanding responses of forests to increasing CO 2 and temperature is an important challenge, but no easy task. Tree rings are increasingly used to study such responses. In a recent study, Van der Sleen et al. (2014) used tree rings from 12 tropical tree species and find that despite increases in intrinsic water use efficiency, no growth stimulation is observed. This challenges the idea that increasing CO 2 would stimulate growth. Unfortunately, tree ring analysis can be plagued by biases, resulting in spurious growth trends. While their study evaluated several biases, it does not account for all. In particular one bias may have seriously affected their results. Several of the species have recruitment patterns, which are not uniform, but clustered around one specific year. This results in spurious negative growth trends if growth rates are calculated in fixed size classes, as “fast-growing” trees reach the sampling diameter earlier compared to slow growers and thus fast growth rates tend to have earlier calendar dates. We assessed the effect of this “non-uniform age bias” on observed growth trends and find that Van der Sleen's conclusions of a lack of growth stimulation do not hold. Growth trends are -at least partially- driven by underlying recruitment or age distributions. Species with more clustered age distributions show more negative growth trends, and simulations to estimate the effect of species’ age distributions show growth trends close to those observed. Re-evaluation of the growth data and correction for the bias results in significant positive growth trends of 1-2% per decade for the full period, and 6-10% since 1950. These observations however, should be taken cautiously as multiple biases affect these trend estimates. In all, our results highlight that tree ring studies of long-term growth trends can be strongly influenced by biases if demographic processes are not carefully accounted for. This article is protected by copyright. All rights reserved.

Description: Rapidly rising temperatures are expected to cause latitudinal and elevational range shifts as species track their optimal climate north and upward. However, a lack of adaptation to environmental conditions other than climate – for example photoperiod, biotic interactions, or edaphic conditions – might limit the success of immigrants in a new location despite hospitable climatic conditions. Here we present one of the first direct experimental tests of the hypothesis that warmer temperatures at northern latitudes will confer a fitness advantage to southern immigrants relative to native populations. As rates of warming in the Arctic are more than double the global average, understanding the impacts of warming in Arctic ecosystems is especially urgent. We established experimentally warmed and non-warmed common garden plots at Alexandra Fiord, Ellesmere Island in the Canadian High Arctic with seeds of two forb species ( Oxyria digyna and Papaver radicatum ) originating from 3-5 populations at different latitudes across the Arctic. We found that plants from the local populations generally had higher survival and obtained a greater maximum size than foreign individuals, regardless of warming treatment. Phenological traits varied with latitude of the source population, such that southern populations demonstrated substantially delayed leaf-out and senescence relative to northern populations. Our results suggest that environmental conditions other than temperature may influence the ability of foreign populations and species to establish at more northerly latitudes as the climate warms, potentially leading to lags in northward range shifts for some species. This article is protected by copyright. All rights reserved.

Description: Quantitative evidence of sudden shifts in ecological structure and function in large shallow lakes is rare, even though they provide essential benefits to society. Such ‘regime shifts’ can be driven by human activities which degrade ecological stability including water level control (WLC) and nutrient loading. Interactions between WLC and nutrient loading on the long-term dynamics of shallow lake ecosystems are, however, often overlooked and largely underestimated, which has hampered the effectiveness of lake management. Here, we focus on a large shallow lake (Lake Chaohu) located in one of the most densely populated areas in China, the lower Yangtze River floodplain, which has undergone both WLC and increasing nutrient loading over the last several decades. We applied a novel methodology that combines consistent evidence from both paleolimnological records and ecosystem modeling to overcome the hurdle of data insufficiency and to unravel the drivers and underlying mechanisms in ecosystem dynamics. We identified the occurrence of two regime shifts: one in 1963, characterized by the abrupt disappearance of submerged vegetation, and another around 1980, with strong algal blooms being observed thereafter. Using model scenarios, we further disentangled the roles of WLC and nutrient loading, showing that the 1963 shift was predominantly triggered by WLC, whereas the shift ca. 1980 was attributed to aggravated nutrient loading. Our analysis also shows interactions between these two stressors. Compared to the dynamics driven by nutrient loading alone, WLC reduced the critical P loading and resulted in earlier disappearance of submerged vegetation and emergence of algal blooms by approximately 26 years and 10 years, respectively. Overall, our study reveals the significant role of hydrological regulation in driving shallow lake ecosystem dynamics, and it highlights the urgency of using multi-objective management criteria that includes ecological sustainability perspectives when implementing hydrological regulation for aquatic ecosystems around the globe. This article is protected by copyright. All rights reserved.

Description: Numerical morphological modelling of braided rivers, using a physics-based approach, is increasingly used as a technique to explore controls on river pattern and, from an applied perspective, to simulate the impact of channel modifications. This paper assesses a depth averaged non-uniform sediment model (Delft3D) to predict the morphodynamics of a 2.5 km long reach of the braided Rees River, New Zealand, during a single high-flow event. Evaluation of model performance primarily focused upon using high-resolution Digital Elevation Models (DEMs) of Difference, derived from a fusion of terrestrial laser scanning and optical empirical bathymetric mapping, to compare observed and predicted patterns of erosion and deposition, and reach scale sediment budgets. For the calibrated model, this was supplemented with planform metrics (e.g. braiding intensity). Extensive sensitivity analysis of model functions and parameters was executed, including consideration of numerical scheme for bedload component calculations, hydraulics, bed composition, bedload transport and bed slope effects, bank erosion and frequency of calculations. Total predicted volumes of erosion and deposition corresponded well to those observed. The difference between predicted and observed volumes of erosion was less than the factor of two that characterises the accuracy of the Gaeuman et al. bedload transport formula. Grain size distributions were best represented using two-phi intervals. For unsteady flows, results were sensitive to the morphological time scale factor. The approach of comparing observed and predicted morphological sediment budgets shows the value of using natural experiment datasets for model testing. Sensitivity results are transferable to guide Delft3D applications to other rivers. This article is protected by copyright. All rights reserved.

Description: Three-dimensional numerical simulations are used to provide insight into the behavior of methane as it migrates from a leaky decommissioned hydrocarbon well into a shallow aquifer. The conceptual model includes gas-phase migration from a leaky well, dissolution into groundwater, advective-dispersive transport and biodegradation of the dissolved methane plume. Gas-phase migration is simulated using the DuMu x multi-phase simulator, while transport and fate of the dissolved phase is simulated using the BIONAPL/3D reactive transport model. Methane behavior is simulated for two conceptual models: first in a shallow confined aquifer containing a decommissioned leaky well based on a monitored field site near Lindbergh, Alberta, Canada, and secondly on a representative unconfined aquifer based loosely on the Borden, Ontario, field site. The simulations show that the Lindbergh site confined aquifer data are generally consistent with a 2-year methane leak of 2 to 20 m 3 /d, assuming anaerobic (sulfate-reducing) methane oxidation and with maximum oxidation rates of 1 × 10 − 5 to 1 × 10 − 3 kg/m 3 /d. Under the highest oxidation rate, dissolved methane decreased from solubility (110 mg/L) to the threshold concentration of 10 mg/L within 5 years. In the unconfined case with the same leakage rate, including both aerobic and anaerobic methane oxidation, the methane plume was less extensive compared to the confined aquifer scenarios. Unconfined aquifers may therefore be less vulnerable to impacts from methane leaks along decommissioned wells. At other potential leakage sites, site-specific data on the natural background geochemistry would be necessary to make reliable predictions on the fate of methane in groundwater. This article is protected by copyright. All rights reserved.

Description: ABSTRACT Two different methods are currently used for measuring interfacial areas between immiscible fluids within 3-D porous media, high-resolution microtomographic imaging and interfacial partitioning tracer tests (IPTT). Both methods were used in this study to measure non-wetting/wetting interfacial areas for a natural sand. The microtomographic imaging was conducted on the same packed columns that were used for the IPTTs. This is in contrast to prior studies comparing the two methods, for which in all cases different samples were used for the two methods. In addition, the columns were imaged before and after the IPTTs to evaluate the potential impacts of the tracer solution on fluid configuration and attendant interfacial area. The interfacial areas measured using IPTT are ∼5 times larger than the microtomographic-measured values, which is consistent with previous work. Analysis of the image data revealed no significant impact of the tracer solution on NAPL configuration or interfacial area. Other potential sources of error were evaluated, and all were demonstrated to be insignificant. The disparity in measured interfacial areas between the two methods is attributed to the limitation of the microtomography method to characterize interfacial area associated with microscopic surface roughness due to resolution constraints. This article is protected by copyright. All rights reserved.

Description: Honami and monami waves are caused by large-scale coherent vortex structures which form in shear layers generated by canopies. In order to reach new insights on the onset of such waves, the instability of these shear layers is studied. Two different approach are used. In the first approach the presence of the canopy is modeled via a drag coefficient, taken to vary along the canopy as by experimental indications. The second approach considers the canopy as a porous medium and different governing equations for the fluid flow are deduced. In this second case the anisotropy of the canopy, composed by rigid cylindrical elements, is accounted for via an apparent permeability tensor. The results obtained with the latter approach approximate better experimental correlations for the synchronous oscillations of the canopy. This article is protected by copyright. All rights reserved.

Description: This paper presents the fundamental theory and laboratory test results on a new device that is deployed in boreholes in fractured rock aquifers to characterize vertical distributions of water and contaminant fluxes, aquifer hydraulic properties, and fracture network properties (e.g., active fracture density and orientation). The device, a fractured rock passive flux meter (FRPFM), consists of an inflatable core assembled with upper and lower packers that isolate the zone of interest from vertical gradients within the borehole. The outer layer of the core consists of an elastic fabric mesh equilibrated with a visible dye which is used to provide visual indications of active fractures and measures of fracture location, orientation, groundwater flux, and the direction of that flux. Beneath the outer layer is a permeable sorbent that is preloaded with known amounts of water soluble tracers which are eluted at rates proportional to groundwater flow. This sorbent also captures target contaminants present in intercepted groundwater. The mass of contaminant sorbed is used to quantify cumulative contaminant flux; whereas, the mass fractions of resident tracers lost are used to provide measures of water flux. In this paper, the FRPFM is bench tested over a range of fracture velocities (2-20 m/day) using a single fracture flow apparatus (fracture aperture = 0.5 mm). Test results show a discoloration in visible dye corresponding to the location of the active fracture. The geometry of the discoloration can be used to discern fracture orientation as well as direction and magnitude of flow in the fracture. Average contaminant fluxes were measured within 16% and water fluxes within 25% of known imposed fluxes. This article is protected by copyright. All rights reserved.

Description: Groundwater quality is a concern in alluvial aquifers that underlie agricultural areas, such as in the San Joaquin Valley of California. Shallow domestic wells (less than 150 m deep) in agricultural areas are often contaminated by nitrate. Agricultural and rural nitrate sources include dairy manure, synthetic fertilizers, and septic waste. Knowledge of the relative proportion that each of these sources contributes to nitrate concentration in individual wells can aid future regulatory and land management decisions. We show that nitrogen and oxygen isotopes of nitrate, boron isotopes, and iodine concentrations are a useful, novel combination of groundwater tracers to differentiate between manure, fertilizers, septic waste, and natural sources of nitrate. Furthermore, in this work, we develop a new Bayesian mixing model in which these isotopic and elemental tracers were used to estimate the probability distribution of the fractional contributions of manure, fertilizers, septic waste, and natural sources to the nitrate concentration found in an individual well. The approach was applied to 56 nitrate-impacted private domestic wells located in the San Joaquin Valley. Model analysis found that some domestic wells were clearly dominated by the manure source and suggests evidence for majority contributions from either the septic or fertilizer source for other wells. But, predictions of fractional contributions for septic and fertilizer sources were often of similar magnitude, perhaps because modeled uncertainty about the fraction of each was large. For validation of the Bayesian model, fractional estimates were compared to surrounding landuse and estimated source contributions were broadly consistent with nearby landuse types. This article is protected by copyright. All rights reserved.

Description: We use a multiphase level set approach to simulate capillary-controlled motions of isolated fluid ganglia surrounded by two other continuous fluids (i.e., double displacements) during three-phase flow on 3-D porous rock geometries. Double displacements and three-phase snap-off mechanisms are closely related. Water snap-off on gas/oil interfaces can initiate double displacements that mobilize isolated oil ganglia in water-wet rock, but it can also terminate ongoing double displacements and trap oil in water. The multiphase level set approach allows for calculating the evolution of disconnected-phase pressure during the motion. In the events of pore filling by double displacement of oil ganglia, and water snap-off on gas/oil interfaces, we find that the local gas/oil capillary pressure drops, while local oil/water capillary pressure increases, by a similar magnitude as observed for the capillary pressure drops during single-pore filling events in dynamic pore-scale experiments of two-phase drainage. We also find that oil ganglia decrease their surface area, and achieve a more compact shape, when the gas/oil interfacial area decreases at the expense of increased oil/water interfacial area during double displacement. By comparison with similar two-phase gas/water simulations, we find that the level of the gas/water capillary pressure curves, including hysteresis loops, are smaller when a mobile, disconnected oil is present, which suggests double displacement of oil is more favorable than direct gas/water displacement. We also present cases in which phase trapping occurred in the three-phase simulations, but not in the corresponding two-phase simulations, supporting the view that more trapping is possible in three-phase flow. This article is protected by copyright. All rights reserved.

Description: Droughts are expected to become more frequent and more intense under climate change. Plant mortality rates and biomass declines in response to drought depend on stomatal and xylem flow regulation. Plants operate on a continuum of xylem and stomatal regulation strategies from very isohydric (strict regulation) to very anisohydric. Co-existing species may display a variety of isohydricity behaviors. As such, it can be difficult to predict how to model the degree of isohydricity at the ecosystem scale by aggregating studies of individual species. This is nonetheless essential for accurate prediction of ecosystem drought resilience. In this study, we define a metric for the degree of isohydricity at the ecosystem scale in analogy with a recent metric introduced at the species-level. Using data from the AMSR-E satellite, this metric is evaluated globally based on diurnal variations in microwave vegetation optical depth (VOD), which is directly related to leaf water potential. Areas with low annual-mean radiation are found to be more anisohydric. Except for evergreen broadleaf forests in the tropics, which are very isohydric, and croplands, which are very anisohydric, land cover type is a poor predictor of ecosystem isohydricity, in accordance with previous species-scale observations. It is therefore also a poor basis for parameterizing water stress response in land-surface models. For taller ecosystems, canopy height is correlated with higher isohydricity (so that rainforests are mostly isohydric). Highly anisohydric areas show either high or low underlying water use efficiency. In seasonally dry locations, most ecosystems display a more isohydric response (increased stomatal regulation) during the dry season. In several seasonally dry tropical forests, this trend is reversed, as dry-season leaf-out appears to coincide with a shift towards more anisohydric strategies. The metric developed in this study allows for detailed investigations of spatial and temporal variations in plant water behavior. This article is protected by copyright. All rights reserved.

Description: Coastal embayments are at risk of impacts by climate change drivers such as ocean warming, sea level rise and alteration in precipitation regimes. The response of the ecosystem to these drivers is highly dependent on their magnitude of change, but also on physical characteristics such as bay morphology and river discharge, which play key roles in water residence time and hence estuarine functioning. These considerations are especially relevant for bivalve aquaculture sites, where the cultured biomass can alter ecosystem dynamics. The combination of climate change, physical and aquaculture drivers can result in synergistic/antagonistic and nonlinear processes. A spatially explicit model was constructed to explore effects of the physical environment (bay geomorphic type, freshwater inputs), climate change drivers (sea level, temperature, precipitation) and aquaculture (bivalve species, stock) on ecosystem functioning. A factorial design led to 336 scenarios (48 hydrodynamic × 7 management). Model outcomes suggest that the physical environment controls estuarine functioning given its influence on primary productivity (bottom-up control dominated by riverine nutrients) and horizontal advection with the open ocean (dominated by bay geomorphic type). The intensity of bivalve aquaculture ultimately determines the bivalve–phytoplankton trophic interaction, which can range from a bottom-up control triggered by ammonia excretion to a top-down control via feeding. Results also suggest that temperature is the strongest climate change driver due to its influence on the metabolism of poikilothermic organisms (e.g. zooplankton and bivalves), which ultimately causes a concomitant increase of top-down pressure on phytoplankton. Given the different thermal tolerance of cultured species, temperature is also critical to sort winners from losers, benefiting Crassostrea virginica over Mytilus edulis under the specific conditions tested in this numerical exercise. In general, it is predicted that bays with large rivers and high exchange with the open ocean will be more resilient under climate change when bivalve aquaculture is present.

Description: We address the problem of stochastic simulation of soil particle-size curves (PSCs) in heterogeneous aquifer systems. Unlike traditional approaches that focus solely on a few selected features of PSCs (e.g., selected quantiles), our approach considers the entire particle size curves and can optionally include conditioning on available data. We rely on our prior work [Menafoglio et al, 2014,2015] to model PSCs as cumulative distribution functions, and interpret their density functions as functional compositions. We thus approximate the latter through an expansion over an appropriate basis of functions. This enables us to (a) effectively deal with the data dimensionality and constraints, and (b) to develop a simulation method for PSCs based upon a suitable and well defined projection procedure. The new theoretical framework allows representing and reproducing the complete information content embedded in PSC data. As a first field application, we demonstrate the quality of unconditional and conditional simulations obtained with our methodology by considering a set of particle-size curves collected within a shallow alluvial aquifer in the Neckar river valley, Germany. This article is protected by copyright. All rights reserved.

Description: The narrow region of soil around roots, the so-called rhizosphere, defers in its hydraulic properties from the bulk soil. The rhizosphere hydraulic properties primarily depend on the drying and wetting rate of mucilage, a polymeric gel exuded by plant roots. Under equilibrium conditions mucilage increases the water holding capacity. Upon drying mucilage turns hydrophobic and makes the rhizosphere temporarily water repellent. There are several models of root water uptake, from analytical models of water flow to a single root to complex numerical models that consider the root architecture. Most of these models, however, do not account for the specific hydraulic properties of the rhizosphere. Here we describe a single-root model that includes the altered hydraulic properties of the rhizosphere due to mucilage exudation. We use the model to reproduce existing experiments reporting unexpected and puzzling hysteresis in the rhizosphere, which could not be explained under the assumption of homogeneous hydraulic properties. In our model the hydraulic properties depend on the concentration of mucilage. This enables a continuous transition from the bulk soil to the root surface. We assumed that: (a) mucilage increases the water holding capacity in equilibrium conditions, (b) hydrophobicity, swelling and shrinking of mucilage cause a non-equilibrium relation between water content and water potential and (c) mucilage reduces the mobility of water molecules in the liquid phase resulting in a lower hydraulic conductivity at a given water content. Our model reproduces well the experiments and suggests that mucilage softens drought stress in plants during severe drying events. This article is protected by copyright. All rights reserved.

Description: Ocean acidification is a global challenge that faces marine organisms in the near future with a predicted rapid drop in pH of up to 0.4 units by the end of this century. Effects of the change in ocean carbon chemistry and pH on the development, growth and fitness of marine animals are well documented. Recent evidence also suggests that a range of chemically mediated behaviours and interactions in marine fish and invertebrates will be affected. Marine animals use chemical cues, for example, to detect predators, for settlement, homing and reproduction. But, while effects of high CO 2 conditions on these behaviours are described across many species, little is known about the underlying mechanisms, particularly in invertebrates. Here, we investigate the direct influence of future oceanic pH conditions on the structure and function of three peptide signalling molecules with an interdisciplinary combination of methods. NMR spectroscopy and quantum chemical calculations were used to assess the direct molecular influence of pH on the peptide cues, and we tested the functionality of the cues in different pH conditions using behavioural bioassays with shore crabs ( Carcinus maenas ) as a model system. We found that peptide signalling cues are susceptible to protonation in future pH conditions, which will alter their overall charge. We also show that structure and electrostatic properties important for receptor binding differ significantly between the peptide forms present today and the protonated signalling peptides likely to be dominating in future oceans. The bioassays suggest an impaired functionality of the signalling peptides at low pH. Physiological changes due to high CO 2 conditions were found to play a less significant role in influencing the investigated behaviour. From our results, we conclude that the change of charge, structure and consequently function of signalling molecules presents one possible mechanism to explain altered behaviour under future oceanic pH conditions.

Description: Interfacial areas between nonwetting-wetting (NW-W) liquids in natural porous media were measured using a modified version of the interfacial partitioning tracer test (IPTT) method that employed simultaneous two-phase flow conditions, which allowed measurement at NW saturations higher than trapped residual saturation. Measurements were conducted over a range of saturations for a well-sorted quartz sand under three wetting scenarios of primary drainage (PD), secondary imbibition (SI), and secondary drainage (SD). Limited sets of experiments were also conducted for a model glass-bead medium and for a soil. The measured interfacial areas were compared to interfacial areas measured using the standard IPTT method for liquid-liquid systems, which employs residual NW saturations. In addition, the theoretical maximum interfacial areas estimated from the measured data are compared to specific solid surface areas measured with the N 2 /BET method and estimated based on geometrical calculations for smooth spheres. Interfacial areas increase linearly with decreasing water saturation over the range of saturations employed. The maximum interfacial areas determined for the glass beads, which have no surface roughness, are 32±4 and 36±5 cm −1 for PD and SI cycles, respectively. The values are similar to the geometric specific solid surface area (31±2 cm −1 ) and the N 2 /BET solid surface area (28±2 cm −1 ). The maximum interfacial areas are 274±38, 235±27, and 581±160 cm −1 for the sand for PD, SI, and SD cycles, respectively, and ∼7625 cm −1 for the soil for PD and SI. The maximum interfacial areas for the sand and soil are significantly larger than the estimated smooth-sphere specific solid surface areas (107±8 cm −1 and 152±8 cm −1 , respectively), but much smaller than the N 2 /BET solid surface area (1387±92 cm −1 and 55224 cm −1 , respectively). The NW-W interfacial areas measured with the two-phase flow method compare well to values measured using the standard IPTT method. This article is protected by copyright. All rights reserved.

Description: Understanding the influence of attached microbial biomass on water flow in variably saturated soils is crucial for many engineered flow systems. So far, the investigation of the effects of microbial biomass has been mainly limited to water-saturated systems. We have assessed the influence of biofilms on the soil hydraulic properties under variably-saturated conditions. A sandy soil was incubated with Pseudomonas Putida and the hydraulic properties of the incubated soil were determined by a combination of methods. Our results show a stronger soil water retention in the inoculated soil as compared to the control. The increase in volumetric water content reaches approximately 0.015 cm 3 cm −3 but is only moderately correlated with the carbon deficit, a proxy for biofilm quantity, and less with the cell viable counts. The presence of biofilm reduced the saturated hydraulic conductivity of the soil by up to one order of magnitude. Under unsaturated conditions, the hydraulic conductivity was only reduced by a factor of four. This means that relative water conductance in biofilm-affected soils is higher compared to the clean soil at low water contents, and that the unsaturated hydraulic conductivity curve of biofilm-affected soil cannot be predicted by simply scaling the saturated hydraulic conductivity. A flexible parameterization of the soil hydraulic functions accounting for capillary and non-capillary flow was needed to adequately describe the observed properties over the entire wetness range. More research is needed to address the exact flow mechanisms in biofilm-affected, unsaturated soil and how they are related to effective system properties. This article is protected by copyright. All rights reserved.

Description: A framework for interpreting transient pumping tests in heterogeneous transmissivity fields is developed to infer the overall geostatistical parameters of the medium without reconstructing the specific heterogeneous structure point wise. The methodology of Radial Coarse Graining is applied to deduce an effective radial description of multi-Gaussian transmissivity. It was used to derive an Effective Well Flow Solution for transient flow conditions including not only the storativity, but also the geometric mean, the variance, and the correlation length of log-transmissivity. This solution is shown to be appropriate to characterize the pumping test drawdown behavior in heterogeneous transmissivity fields making use of ensembles of simulated pumping tests with multiple combinations of statistical parameters. Based on the Effective Well Flow Solution , a method is developed for inferring heterogeneity parameters from transient pumping test drawdown data by inverse estimation. Thereby, the impact of statistical parameters on the drawdown is analyzed, allowing to determine the dependence of reliability of parameter estimates on location and number of measurements. It is shown, that the number of measurements can be reduced compared to steady state pumping tests. Finally, a sampling strategy for single aquifer analysis is developed, which allows to estimate the statistical parameters, in particular variance and correlation length for individual heterogeneous transmissivity fields making use of transient pumping test measurements at multiple locations. This article is protected by copyright. All rights reserved.

Description: Coral reefs are increasingly exposed to elevated temperatures that can cause coral bleaching and high levels of mortality of corals and associated organisms. The temperature threshold for coral bleaching depends on the acclimation and adaptation of corals to the local maximum temperature regime. However, because of larval dispersal, coral populations can receive larvae from corals that are adapted to very different temperature regimes. We combine an offline particle tracking routine with output from a high-resolution physical oceanographic model to investigate whether connectivity of coral larvae between reefs of different thermal regimes could alter the thermal stress threshold (TST) of corals. Our results suggest that larval transport between reefs of widely varying temperatures is likely in the Coral Triangle, and that accounting for this connectivity may be important in bleaching predictions. This has important implications in conservation planning, because connectivity may allow some reefs to have an inherited heat tolerance that is higher or lower than predicted based on local conditions alone. This article is protected by copyright. All rights reserved.

Description: The role of groundwater in sustaining plant transpiration constitutes an important but not well understood aspect of the interactions between groundwater, the land surface, vegetation and the atmosphere. The effect of the hydraulic redistribution (HR) process by plant roots on the interplay between plant transpiration and groundwater dynamics under water-limited climates is investigated by using the Variable Infiltration Capacity Plus (VIC+) land surface model. Numerical experiments, with or without explicitly considering HR, are conducted on soil columns over a range of groundwater table depths (GWTDs) under different vegetative land covers, soil types and precipitation conditions. When HR is not included, this study obtains transpiration – GWTD relationships consistent with those from watershed studies that do not include HR. When HR is included, the transpiration – GWTD relationships are modified. The modification introduced by HR is manifested in the soil moisture of the root zone. The mechanism of HR is explained by detailing the roles of the hydraulically redistributed water, the upward diffusion of soil water and the daytime root uptake. We have found that HR is particularly important in water-limited climates under which plants have high transpiration demand. At the beginning stage of a dry period, HR modulates the severe impacts that climate has on plant transpiration. Only after a prolonged dry period, impacts of HR are lessened when the groundwater table drops below the depth of water uptake by roots and are diminished when plant transpiration is decoupled from groundwater dynamics. This article is protected by copyright. All rights reserved.

Description: Laboratory measurements of the permeability and spectral induced polarization (SIP) response of samples consisting of unconsolidated sands typical of those found in New Zealand aquifers have been made. After correction of measured formation factors to allow for the fact that some were measured at only one fluid conductivity, predictions of permeability from the grain size ( d ) of the samples are found to agree well with measured values of permeability. The Cole-Cole time constant (derived from the SIP measurements) is found, as expected, to depend upon d 2 , but can be affected by the inclusion of smaller grains in the sample. Measurements made on samples comprising of mixtures of grain sizes show that inclusion in a sample of even 10% of smaller grains can significantly reduce both the Cole-Cole time constant ( τ CC ) and the permeability, and support theoretical derivation of how the permeability of a mixture of grain sizes varies with the content of the mixture. Proposed relationships for using τ CC as a predictor for permeability are tested and found to be crucially dependent on the assumed relationship between the dynamic pore radius and grain size. The inclusion of a multiplicative constant to take account of numerical approximations results in good predictions for the permeability of the samples in this study. It seems unlikely, however, that there is a single global expression for predicting permeability from SIP data for all samples. This article is protected by copyright. All rights reserved.

Description: Observations of terrestrial water storage (TWS) from the Gravity Recovery and Climate Experiment (GRACE) satellite mission have a coarse resolution in time (monthly) and space (roughly 150,000 km 2 at mid-latitudes) and vertically integrate all water storage components over land, including soil moisture and groundwater. Data assimilation can be used to horizontally downscale and vertically partition GRACE-TWS observations. This work proposes a variant of existing ensemble-based GRACE-TWS data assimilation schemes. The new algorithm differs in how the analysis increments are computed and applied. Existing schemes correlate the uncertainty in the modeled monthly TWS estimates with errors in the soil moisture profile state variables at a single instant in the month and then apply the increment either at the end of the month or gradually throughout the month. The proposed new scheme first computes increments for each day of the month and then applies the average of those increments at the beginning of the month. The new scheme therefore better reflects sub-monthly variations in TWS errors. The new and existing schemes are investigated here using gridded GRACE-TWS observations. The assimilation results are validated at the monthly time-scale, using in situ measurements of groundwater depth and soil moisture across the US. The new assimilation scheme yields improved (although not in a statistically significant sense) skill metrics for groundwater compared to the open-loop (no assimilation) simulations and compared to the existing assimilation schemes. A smaller impact is seen for surface and root-zone soil moisture, which have a shorter memory and receive smaller increments from TWS assimilation than groundwater. These results motivate future efforts to combine GRACE-TWS observations with observations that are more sensitive to surface soil moisture, such as L-band brightness temperature observations from Soil Moisture Ocean Salinity (SMOS) or Soil Moisture Active Passive (SMAP). Finally, we demonstrate that the scaling parameters that are applied to the GRACE observations prior to assimilation should be consistent with the land surface model that is used within the assimilation system. This article is protected by copyright. All rights reserved.

Description: There are several models in the literature for predicting enteric methane (CH 4 ) emissions. These models were often developed on region or country-specific data and may not be able to predict the emissions successfully in every region. The majority of extant models require dry matter intake of individual animals (DMI), which is not routinely measured. The objectives of this study were to 1) evaluate performance of extant models in predicting enteric CH 4 emissions from dairy cows in North America (NA), Europe (EU), and Australia and New Zealand (AUNZ), and 2) explore the performance using estimated DMI. Forty extant models were challenged on 55, 105, and 52 enteric CH 4 measurements (g/lactating cow/d) from NA, EU, and AUNZ, respectively. The models were ranked using root mean square prediction error as a percentage of the average observed value (RMSPE), and concordance correlation coefficient (CCC). A modified model of Nielsen et al . (2013) using DMI, and dietary digestible neutral detergent fiber and fatty acid contents as predictor variables, ranked highest in NA (RMSPE = 13.1%, and CCC = 0.78). The gross energy intake-based model of Yan et al . (2000) and the updated IPCC Tier 2 model were ranked highest in EU (RMSPE = 11.0%, and CCC = 0.66), and AUNZ (RMSPE = 15.6%, and CCC = 0.75), respectively. DMI of cows in NA and EU were estimated satisfactorily with body weight and fat corrected milk yield data (RMSPE 〈 12.0%, and CCC 〉 0.60). Using estimated DMI, the Nielsen et al . (2013) [RMSPE = 12.7, and CCC = 0.79], and Yan et al . (2000) [RMSPE = 13.7, and CCC = 0.50] models still predicted emissions in respective regions well. Enteric CH 4 emissions from dairy cows can be predicted successfully (i.e., RMSPE 〈 15%), if DMI can be estimated with reasonable accuracy (i.e., RMSPE 〈 10%). This article is protected by copyright. All rights reserved.

Description: Knowledge of sediment dynamics in rivers is of great importance for various practical purposes. Despite its high relevance in riverine environment processes, the monitoring of sediment rates remains a major and challenging task for both suspended and bedload estimation. While the measurement of suspended load is currently an active area of testing with non-intrusive technologies (optical and acoustic), bedload measurement does not mark a similar progress. This paper describes an innovative combination of measurement techniques and analysis protocols that establishes the proof-of-concept for a promising technique, labeled herein Acoustic Mapping Velocimetry (AMV). The technique estimates bedload rates in rivers developing bedforms using a non-intrusive measurements approach. The raw information for AMV is collected with acoustic multi-beam technology that in turn provides maps of the bathymetry over longitudinal swaths. As long as the acoustic maps can be acquired relatively quickly and the repetition rate for the mapping is commensurate with the movement of the bedforms, successive acoustic maps capture the progression of the bedform movement. Two-dimensional velocity maps associated with the bedform migration are obtained by implementing algorithms typically used in particle image velocimetry to acoustic maps converted in gray-level images. Furthermore, use of the obtained acoustic and velocity maps in conjunction with analytical formulations (e.g., Exner equation) enables estimation of multi-directional bedload rates over the whole imaged area. This paper presents a validation study of the AMV technique using a set of laboratory experiments. This article is protected by copyright. All rights reserved.

Description: Microbial communities inhabiting soil aggregates dynamically adjust their activity and composition in response to variations in hydration and other external conditions. These rapid dynamics shape signatures of biogeochemical activity and gas fluxes emitted from soil profiles. Recent mechanistic models of microbial processes in unsaturated aggregate-like pore networks revealed a highly dynamic interplay between oxic and anoxic microsites jointly shaped by hydration conditions and by aerobic and anaerobic microbial community abundance and self-organization. The spatial extent of anoxic niches (hotspots) flicker in time (hot moments) and support substantial anaerobic microbial activity even in aerated soil profiles. We employed an individual-based model for microbial community life in soil aggregate assemblies represented by 3D angular pore networks. Model aggregates of different sizes were subjected to variable water, carbon, and oxygen contents that varied with soil depth as boundary conditions. The study integrates microbial activity within aggregates of different sizes and soil depth to obtain estimates of biogeochemical fluxes from the soil profile. The results quantify impacts of dynamic shifts in microbial community composition on CO 2 and N 2 O production rates in soil profiles in good agreement with experimental data. Aggregate size distribution and the shape of resource profiles in a soil determine how hydration dynamics shape denitrification and carbon utilization rates. Results from the mechanistic model for microbial activity in aggregates of different sizes were used to derive parameters for analytical representation of soil biogeochemical processes across large scales of practical interest for hydrological and climate models. This article is protected by copyright. All rights reserved.

Description: Removal of biologically available nitrogen (N) by the microbially mediated processes denitrification and anaerobic ammonium oxidation (anammox) affects ecosystem N availability. Although few studies have examined temperature responses of denitrification and anammox, previous work suggests that denitrification could become more important than anammox in response to climate warming. To test this hypothesis, we determined whether temperature responses of denitrification and anammox differed in shelf and estuarine sediments from coastal Rhode Island over a seasonal cycle. The influence of temperature and organic C availability was further assessed in a 12-week laboratory microcosm experiment. Temperature responses, as characterized by thermal optima (T opt ) and apparent activation energy (E a ), were determined by measuring potential rates of denitrification and anammox at 31 discrete temperatures ranging from 3 to 59°C. With a few exceptions, T opt and E a of denitrification and anammox did not differ in Rhode Island sediments over the seasonal cycle. In microcosm sediments, E a  was somewhat lower for anammox compared to denitrification across all treatments. However, T opt  did not differ between processes, and neither E a  nor T opt  changed with warming or carbon addition. Thus, the two processes behaved similarly in terms of temperature response, and this response was not influenced by warming. This led us to reject the hypothesis that anammox is more cold-adapted than denitrification in our study system. Overall, our study suggests that temperature responses of both processes can be accurately modeled for temperate regions in the future using a single set of parameters, which are likely not to change over the next century as a result of predicted climate warming. We further conclude that climate warming will not directly alter the partitioning of N flow through anammox and denitrification. This article is protected by copyright. All rights reserved.

Description: Glacierized high-mountainous catchments are often the water towers for downstream region and modeling these remote areas are often the only available tool for the assessment of water resources availability. Nevertheless, data scarcity affects different aspects of hydrological modeling in such mountainous glacierized basins. On the example of poorly gauged glacierized catchment in Central Asia we examined the effects of input discretization, model complexity and calibration strategy on model performance. The study was conducted with the GSM-Socont model driven with climatic input from the corrected High Asia Reanalysis data set of two different discretizations. We analyze the effects of the use of long-term glacier volume loss, snow cover images and interior runoff as an additional calibration data. In glacierized catchments with winter accumulation type, where the transformation of precipitation into runoff is mainly controlled by snow and glacier melt processes, the spatial discretization of precipitation tends to have less impact on simulated runoff than a correct prediction of the integral precipitation volume. Increasing model complexity by using spatially distributed input or semi-distributed parameters values does not increase model performance in the Gunt catchment, as the more complex model tends to be more sensitive to errors in the input data set. In our case, better model performance and quantification of the flow components can be achieved by additional calibration data, rather than by using a more distributed model parameters. However, a semi-distributed model better predicts the spatial patterns of snow accumulation and provides more plausible runoff predictions at the interior sites. This article is protected by copyright. All rights reserved.

Description: The aim of this paper is to describe and evaluate a hybrid spectral- and time-domain approach for the calibration of shot noise models for daily streamflow generation. The calibration approach allows the parameter estimation of a minimum-phase rainfall/streamflow model using two steps. In the predictor step, the power spectral density of a recorded streamflow series is used to calibrate the parameters connected with the model dynamics. During the corrector step, a classic time-domain procedure is used to calibrate the parameters connected with the average output of the model and the parameters that characterize the rainfall stochastic process. The procedure is demonstrated through its application to the daily streamflow time series associated with three Italian watersheds, and its results are then compared with those obtained by means of a time-domain calibration method available in the literature. This article is protected by copyright. All rights reserved.

Description: Predictions of solute transport in subsurface environments are notoriously unreliable due to aquifer heterogeneity and uncertainty about the values of hydraulic parameters. Probabilistic framework, which treats the relevant parameters and solute concentrations as random fields, allows for quantification of this predictive uncertainty. By providing deterministic equations for either probability density function or cumulative distribution function (CDF) of predicted concentrations, the method of distributions enables one to estimate, e.g., the probability of a contaminant's concentration exceeding a safe dose. We derive a deterministic equation for the CDF of solute concentration, which accounts for uncertainty in flow velocity and initial conditions. The coefficients in this equation are expressed in terms of the mean and variance of concentration. The accuracy and robustness of the CDF equations are analyzed by comparing their predictions with those obtained with Monte Carlo simulations and an assumed beta CDF. This article is protected by copyright. All rights reserved.

Description: We present an investigation of the scale dependence of hydraulic parameters in fractured media based on the concept of transfer functions (TF). TF methods provide an inexpensive way to perform aquifer parameter estimation, as they relate the fluctuations of an observation time series (hydraulic head fluctuations) to an input function (aquifer recharge) in frequency domain. Fractured media are specially sensitive to this approach as hydraulic parameters are strongly scale dependent, involving non-stationary statistical distributions. Our study is based on an extensive data set, involving up to 130 measurement points with periodic head measurements that in some cases extend for more than 30 years. For each point, we use a single-porosity and dual-continuum TF formulation to obtain a distribution of transmissivities and storativities in both mobile and immobile domains. Single-porosity TF estimates are compared with data obtained from the interpretation of over 60 hydraulic tests (slug and pumping tests). Results show that the TF is able to estimate the scale dependence of the hydraulic parameters, and it is consistent with the behavior of estimates from traditional hydraulic tests. In addition, the TF approach seems to provide an estimation of the system variance and the extension of the ergodic behavior of the aquifer (estimated in approximately $500$m in the analyzed aquifer). The scale dependence of transmissivity seems to be independent from the adopted formulation (single or dual-continuum), while storativity is more sensitive to the presence of multiple continua. This article is protected by copyright. All rights reserved.

Description: Recursive digital filters (RDFs) are widely used for estimating baseflow from streamflow hydrographs, and various forms of RDFs have been developed based on different physical models. Numerical experiments have been used to objectively evaluate their performance, but they have not been sufficiently comprehensive to assess a wide range of RDFs. This paper extends these studies to understand the limitations of a generalized RDF method as a pathway for future field calibration. Two formalisms are presented to generalize most existing RDFs, allowing systematic tuning of their complexity. The RDFs with variable complexity are evaluated collectively in a synthetic setting, using modelled daily baseflow produced by Li et al . [2014] from a range of synthetic catchments simulated with HydroGeoSphere. Our evaluation reveals that there are optimal RDF complexities in reproducing baseflow simulations, but shows that there is an inherent physical inconsistency within the RDF construction. Even under the idealized setting where true baseflow data are available to calibrate the RDFs, there is persistent disagreement between true and estimated baseflow over catchments with small baseflow components, low saturated hydraulic conductivity of the soil and larger surface runoff. The simplest explanation is that low baseflow ‘signal' in the streamflow data is hard to distinguish, although more complex RDFs can improve upon the simpler Eckhardt filter at these catchments. This article is protected by copyright. All rights reserved.

Description: Quantifying how watershed structure influences the exchanges of water among component parts of a watershed, particularly the connection between uplands, valley bottoms, and in-stream hydrologic exchange remains a challenge. However, this understanding is critical for ascertaining the source areas and temporal contributions of water and associated biogeochemical constituents in streams. We used dilution gauging, mass recovery, and recording discharge stations to characterize streamflow dynamics across 52 reaches, from peak snowmelt to baseflow, in the Tenderfoot Creek Experimental forest, Montana, USA. We found that watershed-contributing area was only a significant predictor of net changes in streamflow at high moisture states and larger spatial scales. However, at the scale of individual stream reaches, the lateral contributing area in conjunction with underlying lithology and vegetation densities were significant predictors of gross hydrologic gains to the stream. Reach lateral contributing areas underlain by more permeable sandstone yielded less water across flow states relative to those with granite gneiss. Additionally, increases in the frequency of steps across each stream reach contributed to greater hydrologic gross losses. Together, gross gains and losses of water along individual reaches resulted in net changes of discharge that cumulatively scale to the observed outlet discharge dynamics. Our results provide a framework for understanding how hillslope topography, geology, vegetation and valley bottom structure contribute to the exchange of water and cumulative increases of stream flow across watersheds of increasing size. This article is protected by copyright. All rights reserved.

Description: Although ephemeral catchments are widespread in arid and semi-arid climates, the relationship of their water balance with climate, geology, topography, and land cover is poorly known. Here we use four years (2011-2014) of rainfall, streamflow, and groundwater level measurements to estimate the water balance components in two adjacent ephemeral catchments in south-eastern Australia, with one catchment planted with young eucalypts and the other dedicated to grazing pasture. To corroborate the interpretation of the observations, the physically-based hydrological model CATHY was calibrated and validated against the data in the two catchments. The estimated water balances showed that despite a significant decline in groundwater level and greater evapotranspiration in the eucalypt catchment (104-119% of rainfall) compared with the pasture catchment (95-104% of rainfall), streamflow consistently accounted for 1-4% of rainfall in both catchments for the entire study period. Streamflow in the two catchments was mostly driven by the rainfall regime, particularly rainfall frequency (i.e. the number of rain days per year), while the downslope orientation of the plantation furrows also promoted runoff. With minimum calibration, the model was able to adequately reproduce the periods of flow in both catchments in all years. Although streamflow and groundwater levels were better reproduced in the pasture than in the plantation, model-computed water balance terms confirmed the estimates from the observations in both catchments. Overall, the interplay of climate, topography, and geology seems to overshadow the effect of land use in the study catchments, indicating that the management ephemeral catchments remains highly challenging. This article is protected by copyright. All rights reserved.

Description: The use of additional types of observational data has often been suggested to alleviate the ill-posedness inherent to parameter estimation of groundwater models and constrain model uncertainty. Disinformation in observational data, caused by errors in either the observations or the chosen model structure may, however, confound the value of adding observational data in model conditioning. This paper uses the global generalized likelihood uncertainty estimation methodology to investigate the value of different observational data types (heads, fluxes, salinity and temperature) in conditioning a groundwater flow and transport model of an extensively monitored field site in the Netherlands. We compared model conditioning using the real observations to a synthetic model experiment, to demonstrate the possible influence of disinformation in observational data in model conditioning. Results showed that the value of different conditioning targets was less evident when conditioning to real measurements than in a measurement error-only synthetic model experiment. While in the synthetic experiment all conditioning targets clearly improved model outcomes, minor improvements or even worsening of model outcomes was observed for the real measurements. This result was caused by errors in both the model structure and the observations, resulting in disinformation in the observational data. The observed impact of disinformation in the observational data reiterates the necessity of thorough data validation and the need for accounting for both model structural and observational errors in model conditioning. It further suggests caution when translating results of synthetic modeling examples to real-world applications. Still, applying diverse conditioning data types was found to be essential to constrain uncertainty, especially in the transport of solutes in the model. This article is protected by copyright. All rights reserved.

Description: The rainfall-runoff response of watersheds is affected by the legacy of past hydroclimatic conditions. We examined how variability in precipitation affected streamflow using 21 years of daily streamflow and precipitation data from five watersheds at the Coweeta Hydrologic Laboratory in southwestern North Carolina, USA. The gauged watersheds contained both coniferous and deciduous vegetation, dominant north and south aspects, and differing precipitation magnitudes. Lag-correlations between precipitation and runoff ratios across a range of temporal resolutions indicated strong influence of past precipitation (i.e. watershed memory). At all time scales, runoff ratios strongly depended on the precipitation of previous time steps. At monthly time scales the influence of past precipitation was detectable for up to seven months. At seasonal time scales the previous season had a greater effect on a season's runoff ratio than the same season's precipitation. At annual time scales the previous year was equally important for a year's runoff ratio than the same year's precipitation. Estimated watershed storage through time and specifically the previous year's storage state was strongly correlated with the residuals of a regression between annual precipitation and annual runoff, partially explaining observed variability in annual runoff in watersheds with deep soils. This effect was less pronounced in the steepest watershed that also contained shallow soils. We suggest that the location of a watershed on a non-linear watershed-scale storage-release curve can explain differences in runoff during growing and dormant season between watersheds with different annual evapotranspiration. This article is protected by copyright. All rights reserved.

Description: Hysteretic processes have been recognized for decades as an important characteristic of soil hydraulic behaviour. Several studies confirmed that wetting and drying periods cannot be described by a simple functional relationship, and that some non-equilibrium of the water retention characteristics has to be taken into account. A large number of models describing the hysteresis of the soil water retention characteristic were successfully tested on soil cores under controlled laboratory conditions. However, its relevance under field conditions under natural forcings has rarely been investigated. In practice, the modeling of field soils usually neglects the hysteretic nature of soil hydraulic properties. In this study, long-term observations of water content and matric potential in lysimeters of the lysimeter network TERENO-SoilCan are presented, clearly demonstrating the hysteretic behavior of field soils. We propose a classification into three categories related to different time scales. Based on synthetic and long term monitoring data, three different models of hysteresis ( Mualem [1984], Parker and Lenhard [1987], Poulovassilis and Kargas [2000]) were applied to data sets showing different degrees of hysteresis. We found no single model to be superior to the others. The model ranking depended on the degree of hysteresis. All models were able to reflect the general structure of hysteresis in most cases but failed to reproduce the detailed trajectories of state variables especially under highly transient conditions. As an important result we found that the temporal dynamics of wetting and drying significantly affects these trajectories which should be accounted for in future model concepts. This article is protected by copyright. All rights reserved.

Description: Forest stand age plays a major role in regulating carbon fluxes in boreal and temperate ecosystems. Young boreal forests represent a relatively small but persistent source of carbon to the atmosphere over 30 years after disturbance, while temperate forests switch from a substantial source over the first 10 years to a notable sink until they reach maturity. Russian forests are the largest contiguous forest belt in the world that accounts for 17% of the global forest cover; however, despite its critical role in controlling global carbon cycle, little is known about spatial patterns of young forest distribution across Russia as a whole, particularly before the year 2000. Here we present a map of young (0-27 years of age) forests, where 12-27 year old forests were modeled from the single-date 500 m satellite record and augmented with the 0-11 year old forest map aggregated from the 30 m resolution contemporary record between 2001 and 2012. The map captures the distribution of forests with the overall accuracy exceeding 85% within three largest bioclimatic vegetation zones (northern, middle and southern taiga), although mapping accuracy for disturbed classes was generally low (the highest of 31% for user's and producer's accuracy for the 12-27 age class and the maximum of 74% for user's and 32% for producer's accuracy for the 0-11 age class). The results show that 75.5 ± 17.6 Mha (roughly 9%) of Russian forests were younger than 30 years of age at the end of 2012. The majority of these 47 ± 4.7 Mha (62%) were distributed across the middle taiga bioclimatic zone. Based on the published estimates of Net Ecosystem Production (NEP) and the produced map of young forests, this study estimates that young Russian forests represent a total sink of carbon at the rate of 1.26 Tg C yr −1 . This article is protected by copyright. All rights reserved.

Description: Sustainable intensification of agriculture is one of the main strategies to provide global food security. However, its implementation raises enormous political, technological, and social challenges. Meeting these challenges will require, among other things, accurate information on the spatial and temporal patterns of agricultural land use and yield. Here, we investigate historical patterns of agricultural land use (1940–2012) and productivity (1990–2012) in Brazil using a new high-resolution (approximately 1 km 2 ) spatially explicit reconstruction. Although Brazilian agriculture has been historically known for its extensification over natural vegetation (Amazon and Cerrado), data from recent years indicate that extensification has slowed down and was replaced by a strong trend of intensification. Our results provide the first comprehensive historical overview of agricultural land use and productivity in Brazil, providing clear insights to guide future territorial planning, sustainable agriculture, policy, and decision-making.

Description: Estimates of global riverine nitrous oxide (N 2 O) emissions contain great uncertainity. We conducted a meta-analysis incorporating 169 observations from published literature to estimate global riverine N 2 O emission rates and emission factors. Riverine N 2 O flux was significantly correlated with NH 4 , NO 3 and DIN (NH 4 +NO 3 ) concentrations, loads and yields. The emission factors EF(a) ( i.e., the ratio of N 2 O emission rate and DIN load) and EF(b) ( i.e., the ratio of N 2 O and DIN concentrations) values were comparable and showed negative correlations with nitrogen concentration, load and yield and water discharge, but positive correlations with the dissolved organic carbon:DIN ratio. After individually evaluating 82 potential regression models based on EF(a) or EF(b) for global, temperate zone, and sub-tropical zone datasets, a power function of DIN yield multiplied by watershed area was determined to provide the best fit between modeled and observed riverine N 2 O emission rates (EF(a): R 2 =0.92 for both global and climatic zone models, n=70; EF(b): R 2 =0.91 for global model and R 2 =0.90 for climatic zone models, n=70). Using recent estimates of DIN loads for 6400 rivers, models estimated global riverine N 2 O emission rates of 29.6–35.3 (mean=32.2) Gg N 2 O-N yr −1 and emission factors of 0.16–0.19% (mean=0.17%). Global riverine N 2 O emission rates are forecasted to increase by 35%, 25%, 18% and 3% in 2050 compared to the 2000s under the Millennium Ecosystem Assessment's Global Orchestration , Order from Strength , Technogarden , and Adapting Mosaic scenarios, respectively. Previous studies may overestimate global riverine N 2 O emission rates (300–2100 Gg N 2 O-N yr −1 ) since they ignore declining emission factor values with increasing nitrogen levels and channel size, as well as neglect differences in emission factors corresponding to different nitrogen forms. Riverine N 2 O emission estimates will be further enhanced through refining emission factor estimates, extending measurements longitudinally along entire river networks, and improving estimates of global riverine nitrogen loads. This article is protected by copyright. All rights reserved.

Description: The Paris Conference of Parties (COP21) agreement renewed momentum for action against climate change, creating the space for solutions for conservation of the ocean addressing two of its largest threats: climate change and ocean acidification (CCOA). Recent arguments that ocean policies disregard a mature conservation research field, and that protected areas cannot address climate change may be over-simplistic at this time when dynamic solutions for the management of changing oceans are needed. We propose a novel approach, based on spatial meta-analysis of climate impact models, to improve the positioning of marine protected areas to limit CCOA impacts. We do this by estimating the vulnerability of ocean ecosystems to CCOA in a spatially-explicit manner, and then co-mapping human activities such as the placement of renewable energy developments and the distribution of marine protected areas. We test this approach in the NE Atlantic considering also how CCOA impacts the base of the food web which supports protected species, an aspect often neglected in conservation studies. We found that, in this case, current regional conservation plans protect areas with low ecosystem-level vulnerability to CCOA, but disregard how species may re-distribute to new, suitable and productive habitats. Under current plans, these areas remain open to commercial extraction and other uses. Here, and worldwide, ocean conservation strategies under CCOA must recognize the long-term importance of these habitat refuges, and studies such as this one are needed to identify them. Protecting these areas creates adaptive, climate-ready and ecosystem-level policy options for conservation, suitable for changing oceans. This article is protected by copyright. All rights reserved.

Description: Understanding the extent to which phylogenetic constraints and adaptive evolutionary forces help define the physiological sensitivity of species is critical for anticipating climate-related impacts in aquatic environments. Yet, whether upper thermal tolerance and plasticity are shaped by common evolutionary and environmental mechanisms remains to be tested. Based on a systematic literature review, we investigated this question in 82 freshwater fish species (27 families) representing 829 experiments for which data existed on upper thermal limits and it was possible to estimate plasticity using upper thermal tolerance reaction norms. Our findings indicated that there are strong phylogenetic signals in both thermal tolerances and acclimation capacity, although it is weaker in the latter. We found that upper thermal tolerances are correlated with the temperatures experienced by species across their range, likely because of spatially autocorrelated processes in which closely related species share similar selection pressures and limited dispersal from ancestral environments. No association with species thermal habitat was found for acclimation capacity. Instead, species with the lowest physiological plasticity also displayed the highest thermal tolerances, reflecting to some extent an evolutionary trade-off between these two traits. Although our study demonstrates that macroecological climatic niche features measured from species distributions are likely to provide a good approximation of freshwater fish sensitivity to climate change, disentangling the mechanisms underlying both acute and chronic heat tolerances may help to refine predictions regarding climate change-related range shifts and extinctions. This article is protected by copyright. All rights reserved.

Description: The earth is in the midst of a biodiversity crisis, and projections indicate continuing and accelerating rates of global changes. Future alterations in communities and ecosystems may be precipitated by changes in the abundance of strongly interacting species, whose disappearance can lead to profound changes in abundance of other species, including an increase in extinction rate for some. Nearshore coastal communities are often dependent on the habitat and food resources provided by foundational plant (e.g., kelp) and animal (e.g., shellfish) species. We quantified changes in the abundance of the blue mussel ( Mytilus edulis ), a foundation species known to influence diversity and productivity of intertidal habitats, over the past 40 years in the Gulf of Maine, USA, one of the fastest warming regions in the global ocean. Using consistent survey methods, we compared contemporary population sizes to historical data from sites spanning 〉400 km. The results of these comparisons showed that blue mussels have declined in the Gulf of Maine by 〉60% (range: 29-100%) at the site level since the earliest benchmarks in the 1970s. At the same time as mussels declined, community composition shifted: at the 4 sites with historical community data, the sessile community became increasingly algal-dominated. Contemporary (2013-14) surveys across 20 sites showed that sessile species richness was positively correlated to mussel abundance in mid to high intertidal zones. These results suggest that declines in a critical foundation species may have already impacted the intertidal community. To inform future conservation efforts, we provide a database of historical and contemporary baselines of mussel population abundance and dynamics in the Gulf of Maine. Our results underscore the importance of anticipating not only changes in diversity but also changes in the abundance and identity of component species, as strong interactors like foundation species have the potential to drive cascading community shifts. This article is protected by copyright. All rights reserved.

Description: The ongoing climate change is expected to modify the atmospheric carbon (C) sink function of peatlands, which store about 450 Gt of carbon accumulated over centuries and millennia (Fenner and Freeman, 2011). Indeed, the simultaneous rise of temperature and decrease of water level favors soil oxygenation, organic matter (OM) decomposition and in turn, the release of large amounts of CO 2 into the atmosphere. Recently, Bragazza et al. (2016) suggested that climate extreme events reduce carbon accumulation in peatlands by up to 30% owing to the decline of Sphagnum productivity and the rise of microbial decomposition of OM. However, investigating the impact of climate extreme events on OM decomposition requires that indirect effects, such as vegetation changes and water physicochemical properties, did not falsify interpretation of the changes in the microbial activities (Delarue et al., 2014; Delarue et al., 2015). This article is protected by copyright. All rights reserved.

Description: Although the impacts of nutrient pollution on coral reefs are well known, surprisingly, no statistical relationships have ever been established between water quality parameters, coral biodiversity and coral cover. Hong Kong provides a unique opportunity to assess this relationship. Here, coastal waters have been monitored monthly since 1986, at 76 stations, providing a highly spatially resolved water quality dataset including 68,903 data points. Moreover, a robust coral species richness ( S ) dataset is available from more than 100 surveyed locations, composed of 3,453 individual colonies’ observations, as well as a coral cover ( CC ) dataset including 85 sites. This wealth of data provides a unique opportunity to test the hypothesis that water quality, and in particular nutrients, drives coral biodiversity. The influence of water quality on S and CC was analyzed using GIS and multiple regression modeling. Eutrophication (as chlorophyll-a concentration; CHLA) was negatively correlated with S and CC , whereas physico-chemical parameters (DO and salinity) had no significant effect. The modeling further illustrated that PSM, DIN and DIP had a negative effect on S and on CC , however, the effect of nutrients was 1.5 to 2-fold greater. The highest S and CC occurred where CHLA 〈 2 μ g.L −1 , DIN 〈 2 μ M and DIP 〈 0.1 μ M. Where these values were exceeded, S and CC were significantly lower and no live corals were observed where CHLA 〉 15 μ g.L −1 , DIN 〉 9 μ M and DIP 〉 0.33 μ M. This study demonstrates the importance of nutrients over other water quality parameters in coral biodiversity loss and highlights the key role of eutrophication in shaping coral reef ecosystems. This work also provides ecological thresholds that may be useful for water quality guidelines and nutrient-mitigation policies. This article is protected by copyright. All rights reserved.

Description: Groundwater deficits occur in several areas of Central Mexico, where water resource assessment is limited by the availability and reliability of field data. In this context, GRACE and InSAR are used to remotely assess groundwater storage loss in one of Mexico's most important watersheds in terms of size and economic activity: the Lerma-Santiago-Pacifico (LSP). In situ data and Land Surface Models are used to subtract soil moisture and surface water storage changes from the total water storage change measured by GRACE satellites. As a result, groundwater mass change time-series are obtained for a 12 years period. ALOS-PALSAR images acquired from 2007 to 2011 were processed using the SBAS-InSAR algorithm to reveal areas subject to ground motion related to groundwater over-exploitation. In the perspective of providing guidance for groundwater management, GRACE and InSAR observations are compared with official water budgets and field observations. InSAR-derived subsidence mapping generally agrees well with official water budgets, and shows that deficits occur mainly in cities and irrigated agricultural areas. GRACE does not entirely detect the significant groundwater losses largely reported by official water budgets, literature and InSAR observations. The difference is interpreted as returns of wastewater to the groundwater flow systems, which limits the watershed scale groundwater depletion but suggests major impacts on groundwater quality. This phenomenon is enhanced by ground fracturing as noticed in the field. Studying the fate of the extracted groundwater is essential when comparing GRACE data with higher resolution observations, and particularly in the perspective of further InSAR/GRACE combination in hydrogeology. This article is protected by copyright. All rights reserved.

Description: Arctic ecosystems are characterized by a wide range of soil moisture conditions and thermal regimes and contribute differently to the net methane (CH 4 ) budget. Yet, it is unclear how climate change will affect the capacity of those systems to act as a net source or sink of CH 4 . Here, we present results of in situ CH 4 flux measurements made during the growing season 2014 on Disko Island (west Greenland) and quantify the contribution of contrasting soil and landscape types to the net CH 4 budget and responses to summer warming. We compared gas flux measurements from a bare soil and a dry heath, at ambient conditions and increased air temperature, using open-top chambers (OTCs). Throughout the growing season, bare soil consumed 0.22 ± 0.03 g CH 4 -C m −2 (8.1 ± 1.2 g CO 2 -eq m −2 ) at ambient conditions, while the dry heath consumed 0.10 ± 0.02 g CH 4 -C m −2 (3.9 ± 0.6 g CO 2 -eq m −2 ). These uptake rates were subsequently scaled to the entire study area of 0.15 km 2 , a landscape also consisting of wetlands with a seasonally integrated methane release of 0.10 ± 0.01 g CH 4 -C m −2 (3.7 ± 1.2 g CO 2 -eq m −2 ). The result was a net landscape sink of 12.71 kg CH 4 -C (0.48 tonne CO 2 -eq) during the growing season. A nonsignificant trend was noticed in seasonal CH 4 uptake rates with experimental warming, corresponding to a 2% reduction at the bare soil, and 33% increase at the dry heath. This was due to the indirect effect of OTCs on soil moisture, which exerted the main control on CH 4 fluxes. Overall, the net landscape sink of CH 4 tended to increase by 20% with OTCs. Bare and dry tundra ecosystems should be considered in the net CH 4 budget of the Arctic due to their potential role in counterbalancing CH 4 emissions from wetlands – not the least when taking the future climatic scenarios of the Arctic into account.

Description: Understandings of contemporary forest cover loss are critical for policy but have come at the expense of long-term, multi-directional analyses of land cover change. This is a critical gap given (i) profound reconfigurations in land use and land control over the past several decades and (ii) evidence of widespread “woodland resurgence” throughout the tropics. In this paper, we argue that recent advancements within the field of land change science provide new opportunities to address this gap. In turn, we suggest that multi-decadal and multi-directional analyses of land cover change can facilitate richer social analyses of land cover change and more relevant conservation policies and practice. Our argument is grounded in a case study from Southeast Sulawesi, Indonesia. Using a novel analytical platform, Google Earth Engine, and open access to high-quality Landsat data, we map land cover change in Southeast Sulawesi, Indonesia from 1972-2014. We find that tree cover loss constitutes the single largest net change over the period 1972-2014 but that gross rates of tree cover gain were three times higher than gross loss rates from 1972-1995 and equivalent to loss rates from 1995-2014. We suggest the smallholder tree crop economy likely produced both forest loss and Imperata grassland restoration in this region. This case points to the need to expand rather than collapse the baselines used to study carbon and biodiversity change in tropical regions. It also demonstrates the possible utility of applying such methods to other regions. This article is protected by copyright. All rights reserved.

Description: Shifts in biodiversity and ecological processes in stream ecosystems in response to rapid climate change will depend on how numerically and functionally dominant aquatic insect species respond to changes in stream temperature and hydrology. Across 253 minimally perturbed streams in 8 ecoregions in the western US, we modeled the distribution of 88 individual insect taxa in relation to existing combinations of maximum summer temperature, mean annual streamflow, and their interaction. We used a heat map approach along with downscaled General Circulation Model (GCM) projections of warming and streamflow change to estimate site-specific extirpation likelihood for each taxon, allowing estimation of whole community change in streams across these ecoregions. Conservative climate change projections indicate a 30-40% loss of taxa in warmer, drier ecoregions and 10-20% loss in cooler, wetter ecoregions where taxa are relatively buffered from projected warming and hydrologic change. Differential vulnerability of taxa with key functional foraging roles in processing basal resources suggests that climate change has the potential to modify stream trophic structure and function (e.g., alter rates of detrital decomposition and algal consumption), particularly in warmer and drier ecoregions. We show that streamflow change is equally as important as warming in projected risk to stream community composition and that the relative threat posed by these two fundamental drivers varies across ecoregions according to projected gradients of temperature and hydrologic change. Results also indicate that direct human modification of streams through actions such as water abstraction are likely to further exacerbate loss of taxa and ecosystem alteration, especially in drying climates. Management actions to mitigate climate change impacts on stream ecosystems or to proactively adapt to them will require regional calibration, due to geographic variation in insect sensitivity and in exposure to projected thermal warming and hydrologic change. This article is protected by copyright. All rights reserved.

Description: De Oliveira Silva et al. (2016) model beef production in the Brazilian Cerrado , and conclude that – if accompanied by tight deforestation control – increasing production could lower emissions by incentivising better pasture management. While their analysis is valuable in identifying the conditions under which increasing meat consumption could be compatible with reducing greenhouse gas emissions, we believe that there is little chance of such conditions occurring in practice. Overall, increasing beef consumption and production is unlikely to be an effective lever for reducing emissions, and is more likely to exacerbate deforestation. This article is protected by copyright. All rights reserved.

Description: Land-use change due to anthropogenic development is pervasive across the globe and commonly associated with negative consequences for biodiversity. While land-use change has been linked to shifts in the behavior and habitat-use patterns of wildlife species, little is known about its influence on animal population dynamics, despite the relevance of such information for conservation. We conducted the first broad-scale investigation correlating temporal patterns of land-use change with the demographic rates of mule deer, an iconic species in the western United States experiencing wide-scale population declines. We employed a unique combination of long-term (1980–2010) data on residential and energy development across western Colorado, in conjunction with congruent data on deer recruitment, to quantify annual changes in land-use and correlate those changes with annual indices of demographic performance. We also examined annual variation in weather conditions, which are well recognized to influence ungulate productivity, and provided a basis for comparing the relative strength of different covariates in their association with deer recruitment. Using linear mixed models, we found that increasing residential and energy development within deer habitat were correlated with declining recruitment rates, particularly within seasonal winter ranges. Residential housing had two times the magnitude of effect of any other factor we investigated, and energy development had an effect size similar to key weather variables known to be important to ungulate dynamics. This analysis is the first to correlate a demographic response in mule deer with residential and energy development at large spatial extents relevant to population performance, suggesting that further increases in these development types on deer ranges are not compatible with the goal of maintaining highly productive deer populations. Our results underscore the significance of expanding residential development on mule deer populations, a factor that has received little research attention in recent years, despite its rapidly increasing footprint across the landscape.

Description: The cumulative effects of climate warming on herbivore vital rates and population dynamics are hard to predict, given that the expected effects differ between seasons. In the Arctic, warmer summers enhance plant growth which should lead to heavier and more fertile individuals in the autumn. Conversely, warm spells in winter with rainfall (rain-on-snow) can cause ‘icing’, restricting access to forage, resulting in starvation, lower survival and fecundity. Since body condition is a ‘barometer’ of energy demands relative to energy intake, we explored the causes and consequences of variation in body mass of wild female Svalbard reindeer ( Rangifer tarandus platyrhynchus ) from 1994-2015, a period of marked climate warming. Late winter (April) body mass explained 88% of the between-year variation in population growth rate, because it strongly influenced reproductive loss, and hence subsequent fecundity (92%), as well as survival (94%) and recruitment (93%). Autumn (October) body mass affected ovulation rates but did not affect fecundity. April body mass showed no long-term trend (Coefficient of variation, CV = 8.8%) but was higher following warm autumn (October) weather, reflecting delays in winter onset, but most strongly, and negatively, related to ‘rain-on-snow’ events. October body mass (CV =2.5%) increased over the study due to higher plant productivity in the increasingly warm summers. Density-dependent mass change suggested competition for resources in both winter and summer but was less pronounced in recent years, despite an increasing population size. While continued climate warming is expected to increase the carrying capacity of the high Arctic tundra, it is also likely to cause more frequent icing-events. Our analyses suggest that these contrasting effects may cause larger seasonal fluctuations in body mass and vital rates. Overall our findings provide an important ‘missing’ mechanistic link in the current understanding of the population biology of a keystone species in a rapidly warming Arctic. This article is protected by copyright. All rights reserved.

Description: Hydrologic responses to earthquakes and their mechanisms have been widely studied. Some responses have been attributed to increases in the vertical permeability. However, basic questions remain: How do increases in the vertical permeability occur? How frequently do they occur? Is there a quantitative measure for detecting the occurrence of aquitard breaching? We try to answer these questions by examining data from a dense network of ∼50 monitoring stations of clustered wells in a sedimentary basin near the epicenter of the 1999 M7.6 Chi-Chi earthquake in western Taiwan. While most stations show evidence that confined aquifers remained confined after the earthquake, about 10% of the stations show evidence of coseismic breaching of aquitards, creating vertical permeability as high as that of aquifers. The water levels in wells without evidence of coseismic breaching of aquitards show tidal responses similar to that of a confined aquifer before and after the earthquake. Those wells with evidence of coseismic breaching of aquitards, on the other hand, show distinctly different post-seismic tidal response. Furthermore, the post-seismic tidal response of different aquifers became strikingly similar, suggesting that the aquifers became hydraulically connected and the connection was maintained many months thereafter. Breaching of aquitards by large earthquakes has significant implications for a number of societal issues such as the safety of water resources, the security of underground waste repositories, and the production of oil and gas. The method demonstrated here may be used for detecting the occurrence of aquitard breaching by large earthquakes in other seismically active areas. This article is protected by copyright. All rights reserved.

Description: Surrogate models are commonly used in Bayesian approaches such as Markov Chain Monte Carlo (MCMC) to avoid repetitive CPU-demanding model evaluations. However, the approximation error of a surrogate may lead to biased estimation of the posterior distribution. This bias can be corrected by constructing a very accurate surrogate or implementing MCMC in a two-stage manner. Since the two-stage MCMC requires extra original model evaluations after surrogate evaluations, the computational cost is still high. If the information of measurement is incorporated, a locally accurate surrogate can be adaptively constructed with low computational cost. Based on this idea, we integrate Gaussian process (GP) and MCMC to adaptively construct locally accurate surrogates for Bayesian experimental design in groundwater contaminant source identification problems. Moreover, the uncertainty estimate of GP approximation error is incorporated in the Bayesian formula to avoid over-confident estimation of the posterior distribution. The proposed approach is tested with a numerical case study. Without sacrificing the estimation accuracy, the new approach achieves about 200 times of speed-up compared to our previous work which implemented MCMC in a two-stage manner. This article is protected by copyright. All rights reserved.

Description: ABSTRACT Interactions among hydraulic conductivity distributions, subsurface topography, and lateral flow are poorly understood. We applied 407 mm of water and a suite of tracers over 51 hours to a 12 by 16.5 m forested hillslope segment to determine interflow thresholds, preferential pathway pore velocities, large-scale conductivities, the time series of event water fractions, and the fate of dissolved nutrients. The 12% hillslope featured loamy sand A and E horizons overlying a sandy clay loam Bt at 1.25 m average depth. Interflow measured from two drains within an interception trench commenced after 131 and 208 mm of irrigation. Cumulative interflow equaled 49% of applied water. Conservative tracer differences between the collection drains indicated differences in flow paths and storages within the plot. Event water fractions rose steadily throughout irrigation, peaking at 50% sixteen hours after irrigation ceased. Data implied that tightly held water exchanged with event water throughout the experiment and a substantial portion of pre-event water was released from the argillic layer. Surface-applied dye tracers bypassed the matrix, with peak concentrations measured shortly after flow commencement, indicating preferential network conductivities of 864 to 2240 mm/h, yet no macropore flow was observed. Near steady-state flow conditions indicated average conductivities of 460 mm/h and 2.5 mm/h for topsoils and the Bt horizon, respectively. Low ammonium and phosphorus concentrations in the interflow suggested rapid uptake or sorption, while higher nitrate concentrations suggested more conservative transport. These results reveal how hydraulic conductivity variation and subsurface topographic complexity explain otherwise paradoxical solute and flow behaviors. This article is protected by copyright. All rights reserved.

Description: The identification of transport parameters by inverse modeling often suffers from equifinality or parameter correlation when models are fitted to measurements of the solute breakthrough in column outflow experiments. This parameter uncertainty can be approached by performing multiple experiments with different sets of boundary conditions, each provoking observations that are uniquely attributable to the respective transport processes. A promising approach to further increase the information potential of the experimental outcome is the closed-flow column design. It is characterized by the recirculation of the column effluent into the solution supply vessel that feeds the inflow, which results in a damped sinusoidal oscillation in the breakthrough curve. In order to reveal the potential application of closed-flow experiments, we present a comprehensive sensitivity analysis using common models for adsorption and degradation. We show that the sensitivity of inverse parameter determination with respect to the apparent dispersion can be controlled by the experimenter. For optimal settings, a decrease in parameter uncertainty as compared to classical experiments by an order of magnitude is achieved. In addition, we show a reduced equifinality between rate-limited interactions and apparent dispersion. Furthermore, we illustrate the expected breakthrough curve for equilibrium and nonequilibrium adsorption, the latter showing strong similarities to the behavior found for completely mixed batch reactor experiments. Finally, breakthrough data from a reactive tracer experiment is evaluated using the proposed framework with excellent agreement of model and experimental results. This article is protected by copyright. All rights reserved.

Description: ABSTRACT In many areas of the world, groups of people have attempted to create urban landscapes that follow the principles of environmental sustainability. To this end, groups have devised alternative models, such as ecovillages, where low-impact handling is used and a way of life different from that of large population centers is adopted. Although these villages exist, their efficiency in the conservation of natural resources has not been effectively evaluated. This study evaluated the practices used by two Brazilian ecovillages to conserve water resources to assess whether this new concept of living is indeed successful in meeting sustainability goals. We selected 25 indicators of water sustainability, and using the Compromise Programming Method, we quantified the distance between those landscapes self-referenced as sustainable and an ideal hypothetical scenario. We also interpreted the communities perceptions using the distance between the current situations and the envisioned scenario. We concluded that both ecovillage are far from technically ideal scenario, but the communities have a strong sense of their limitations in implementing water resources conservation. The communities attributed this fact primarily to deficiencies in the shared management. This article is protected by copyright. All rights reserved.