ALBERT

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: Several studies have shown that satellite retrievals of solar-induced chlorophyll fluorescence (SIF) provide useful information on terrestrial photosynthesis or gross primary production (GPP). Here, we have incorporated equations coupling SIF to photosynthesis in a land surface model, the National Center for Atmospheric Research Community Land Model version 4 (NCAR CLM4) and have demonstrated its use as a diagnostic tool for evaluating the calculation of photosynthesis, a key process in a land surface model that strongly influences the carbon, water, and energy cycles. By comparing forward simulations of SIF, essentially as a byproduct of photosynthesis, in CLM4 with observations of actual SIF, it is possible to check whether the model is accurately representing photosynthesis and the processes coupled to it. We provide some background on how SIF is coupled to photosynthesis, describe how SIF was incorporated into CLM4, and demonstrate that our simulated relationship between SIF and GPP values are reasonable when compared with satellite (Greenhouse gases Observing SATellite; GOSAT) and in situ flux-tower measurements. CLM4 overestimates SIF in tropical forests, and we show that this error can be corrected by adjusting the maximum carboxylation rate (V max ) specified for tropical forests in CLM4. Our study confirms that SIF has the potential to improve photosynthesis simulation and thereby can play a critical role in improving land surface and carbon cycle models. This article is protected by copyright. All rights reserved.

Description: Climate data created from historic climate observations are integral to most assessments of potential climate change impacts, and frequently comprise the baseline period used to infer species-climate relationships. They are often also central to downscaling coarse resolution climate simulations from General Circulation Models (GCMs) in order to project future climate scenarios at ecologically relevant spatial scales. Uncertainty in these baseline data can be large, particularly where weather observations are sparse and climate dynamics are complex (e.g. over mountainous or coastal regions). Yet, importantly, this uncertainty is almost universally overlooked when assessing potential responses of species to climate change. Here we assessed the importance of historic baseline climate uncertainty for projections of species’ responses to future climate change. We built species distribution models (SDMs) for 895 African bird species of conservation concern, using six different climate baselines. We projected these models to two future periods (2040-2069, 2070-2099), using downscaled climate projections, and calculated species turnover and changes in species-specific climate suitability. We found that the choice of baseline climate data constituted an important source of uncertainty in projections of both species turnover and species-specific climate suitability, often comparable with, or more important than, uncertainty arising from the choice of GCM. Importantly, the relative contribution of these factors to projection uncertainty varied spatially. Moreover, when projecting SDMs to sites of biodiversity importance (Important Bird and Biodiversity Areas), these uncertainties altered site-level impacts, which could affect conservation prioritisation. Our results highlight that projections of species’ responses to climate change are sensitive to uncertainty in the baseline climatology. We recommend that this should be considered routinely in such analyses. This article is protected by copyright. All rights reserved.

Description: Anthropogenic climate change compromises reef growth as a result of increasing temperatures and ocean acidification. Scleractinian corals vary in their sensitivity to these variables, suggesting species composition will influence how reef communities respond to future climate change. Because data are lacking for many species, most studies that model future reef growth rely on uniform scleractinian calcification sensitivities to temperature and ocean acidification. In order to address this knowledge gap, calcification of twelve common and understudied Caribbean coral species was measured for two months under crossed temperatures (27°C, 30.3°C) and CO 2 partial pressures ( p CO 2 ) (400, 900, 1300 μ atm). Mixed effects models of calcification for each species were then used to project community-level scleractinian calcification using Florida Keys reef composition data and IPCC AR5 ensemble climate model data. Three of the four most abundant species, Orbicella faveolata, Montastraea cavernosa, and Porites astreoides , had negative calcification responses to both elevated temperature and p CO 2 . In the business-as-usual CO 2 emissions scenario, reefs with high abundances of these species had projected end-of-century declines in scleractinian calcification of 〉50% relative to present-day rates. Siderastrea siderea , the other most-common species, was insensitive to both temperature and p CO 2 within the levels tested here. Reefs dominated by this species had the most stable end-of-century growth. Under more optimistic scenarios of reduced CO 2 emissions, calcification rates throughout the Florida Keys declined 〈20% by 2100. Under the most extreme emissions scenario, projected declines were highly variable among reefs, ranging 10 to 100%. Without considering bleaching, reef growth will likely decline on most reefs, especially where resistant species like S. siderea are not already dominant. This study demonstrates how species composition influences reef community responses to climate change and how reduced CO 2 emissions can limit future declines in reef calcification. This article is protected by copyright. All rights reserved.

Description: Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15,054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for prediction above-ground biomass. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multi-stemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalisation (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9 to 356 Mg ha −1 ). Losses in efficiency of prediction were 〈 1% if generalised models were used in place of species-specific models. Furthermore, application of generalised multi-species models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand -level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species-specific models is only warranted when gains in accuracy of stand-based predictions are relatively high (e.g. high-value monocultures). This article is protected by copyright. All rights reserved.

Description: Interannual variability in biosphere-atmosphere exchange of CO 2 is driven by a diverse range of biotic and abiotic factors. Replicating this variability thus represents the ‘acid test’ for terrestrial biosphere models. Although such models are commonly used to project responses to both normal and anomalous variability in climate, they are rarely tested explicitly against inter-annual variability in observations. Herein, using standardized data from the North American Carbon Program, we assess the performance of 16 terrestrial biosphere models and 3 remote sensing products against long-term measurements of biosphere-atmosphere CO 2 exchange made with eddy-covariance flux towers at 11 forested sites in North America. Instead of focusing on model-data agreement we take a systematic, variability-oriented approach and show that although the models tend to reproduce the mean magnitude of the observed annual flux variability, they fail to reproduce the timing. Large biases in modeled annual means are evident for all models. Observed interannual variability is found to commonly be on the order of magnitude of the mean fluxes. None of the models consistently reproduce observed interannual variability within measurement uncertainty. Underrepresentation of variability in spring phenology, soil thaw and snowpack melting, and difficulties in reproducing the lagged response to extreme climatic events are identified as systematic errors, common to all models included in this study.

Description: Interannual variability in biosphere-atmosphere exchange of CO 2 is driven by a diverse range of biotic and abiotic factors. Replicating this variability thus represents the ‘acid test’ for terrestrial biosphere models. Although such models are commonly used to project responses to both normal and anomalous variability in climate, they are rarely tested explicitly against inter-annual variability in observations. Here, using standardized data from the North American Carbon Program, we assess the performance of 16 terrestrial biosphere models and 3 remote sensing products against long-term measurements of biosphere-atmosphere CO 2 exchange made with eddy-covariance flux towers at 11 forested sites in North America. Instead of focusing on model-data agreement we take a systematic, variability-oriented, approach and show that although the models tend to reproduce the mean magnitude of the observed annual flux variability, they fail to reproduce the timing. Large biases in modeled annual means are evident for all models. Observed interannual variability is found to commonly be on the order of magnitude of the mean fluxes. None of the models consistently reproduce observed interannual variability within measurement uncertainty. Underrepresentation of variability in spring phenology, soil thaw and snowpack melting, and difficulties in reproducing the lagged response to extreme climatic events are identified as systematic errors, common to all models included in this study.

Description: Abstract As countries advance in greenhouse gas (GHG) accounting for climate change mitigation, consistent estimates of aboveground net biomass change (∆AGB) are needed. Countries with limited forest monitoring capabilities in the tropics and subtropics rely on IPCC 2006 default ∆AGB rates, which are values per ecological zone, per continent. Similarly, research on forest biomass change at large scale also make use of these rates. IPCC 2006 default rates come from a handful of studies, provide no uncertainty indications, and do not distinguish between older secondary forests and old‐growth forests. As part of the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, we incorporate ∆AGB data available from 2006 onwards, comprising 176 chronosequences in secondary forests and 536 permanent plots in old‐growth and managed/logged forests located in 42 countries in Africa, North and South America, and Asia. We generated ∆AGB rate estimates for younger secondary forests (≤20 years), older secondary forests (〉20 years and up to 100 years) and old‐growth forests, and accounted for uncertainties in our estimates. In tropical rainforests, for which data availability was the highest, our ∆AGB rate estimates ranged from 3.4 (Asia) to 7.6 (Africa) Mg ha‐1 yr‐1 in younger secondary forests, from 2.3 (North and South Ameri09ca) to 3.5 (Africa) Mg ha‐1 yr‐1 in older secondary forests, and 0.7 (Asia) to 1.3 (Africa) Mg ha‐1 yr‐1 in old‐growth forests. We provide a rigorous and traceable refinement of the IPCC 2006 default rates in tropical and subtropical ecological zones, and identify which areas require more research on ∆AGB. In this respect, this study should be considered as an important step towards quantifying the role of tropical and subtropical forests as carbon sinks with higher accuracy; our new rates can be used for large‐scale GHG accounting by governmental bodies, non‐governmental organisations and in scientific research. This article is protected by copyright. All rights reserved.

Description: Thermal stress affects organism performance differently depending on the ambient temperature to which they are acclimatized, which varies along latitudinal gradients. This study investigated whether differences in physiological responses to temperature are consistent with regional differences in temperature regimes for the stony coral Oculina patagonica . To resolve this question we experimentally assessed how colonies originating from four different locations characterized by 〉3°C variation in mean maximum annual temperature responded to warming from 20 to 32°C. We assessed plasticity in symbiont identity, density, and photosynthetic properties, together with changes in host tissue biomass. Results show that, without changes in the type of symbiont hosted by coral colonies, O. patagonica has limited capacity to acclimatize to future warming. We found little evidence of variation in overall thermal tolerance, or in thermal optima, in response to spatial variation in ambient temperature. Given that the invader O. patagonica is a relatively new member of the Mediterranean coral fauna our results also suggest that coral populations may need to remain isolated for a long period of time for thermal adaptation to potentially take place. Our study indicates that for O. patagonica , mortality associated with thermal stress manifests primarily through tissue breakdown under moderate but prolonged warming (which does not impair symbiont photosynthesis and, therefore, does not lead to bleaching). Consequently, projected global warming is likely to causes repeat incidents of partial and whole colony mortality and might drive a gradual range contraction of Mediterranean corals. This article is protected by copyright. All rights reserved.