ALBERT

Description: Above-ground tropical tree biomass and carbon storage estimates commonly ignore tree height. We estimate the effect of incorporating height (H) on forest biomass estimates using 37 625 concomitant H and diameter measurements (n = 327 plots) and 1816 harvested trees (n = 21 plots) tropics-wide to answer the following questions: 1. For trees of known biomass (from destructive harvests) which H-model form and geographic scale (plot, region, and continent) most reduces biomass estimate uncertainty? 2. How much does including H relationship estimates derived in (1) reduce uncertainty in biomass estimates across 327 plots spanning four continents? 3. What effect does the inclusion of H in biomass estimates have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of the destructively harvested trees was half (mean 0.06) when including H, compared to excluding H (mean 0.13). The power- and Weibull-H asymptotic model provided the greatest reduction in uncertainty, with the regional Weibull-H model preferred because it reduces uncertainty in smaller-diameter classes that contain the bulk of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows errors are reduced from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0) when including $H$. For all plots, above-ground live biomass was 52.2±17.3 Mg ha−1 lower when including H estimates (13%), with the greatest reductions in estimated biomass in Brazilian Shield forests and relatively no change in the Guyana Shield, central Africa and southeast Asia. We show fundamentally different stand structure across the four forested tropical continents, which affects biomass reductions due to $H$. African forests store a greater portion of total biomass in large-diameter trees and trees are on average larger in diameter. This contrasts to forests on all other continents where smaller-diameter trees contain the greatest fractions of total biomass. After accounting for variation in $H$, total biomass per hectare is greatest in Australia, the Guyana Shield, and Asia and lowest in W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if closed canopy tropical forests span 1668 million km2 and store 285 Pg C, then the overestimate is 35 Pg C if H is ignored, and the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree $H$ is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of pantropical carbon stocks and emissions due to deforestation.

Description: Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (≤40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0). For all plots, aboveground live biomass was −52.2 Mg ha−1 (−82.0 to −20.3 bootstrapped 95% CI), or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to H. After accounting for variation in H, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in east-central Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km2 and store 285 Pg C (estimate including H), then applying our regional relationships implies that carbon storage is overestimated by 35 Pg C (31–39 bootstrapped 95% CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation.

Description: Unconventional sources of data that enhance our understanding of internal interactions between socio-economic and hydrological processes are central to modeling human–water systems. Participatory modeling (PM) departs from conventional modeling tools by informing and conceptualizing human–water systems through stakeholder engagement. However, the implementation of many PM processes remains biased, particularly in regions where marginalized communities are present. Many PM processes are not cognizant of differentiation and diversity within a society and tend to treat communities as homogeneous units with similar capabilities, needs, and interests. This undifferentiation leads to the exclusion of key actors, many of whom are associated with marginalized communities. In this study, a participatory model-building framework (PMBF), aiming to ensure the inclusiveness of marginalized stakeholders – who (1) have low literacy, (2) are comparatively powerless, and/or (3) are associated with a marginalized language – in participatory modeling, is proposed. The adopted approach employs interdisciplinary storylines to inform and conceptualize human–water systems. The suggested method is underpinned by the multi-level perspective (MLP) framework, which was developed by Geels et al. (2002) to conceptualize socio-technical transitions and modified in this study to accommodate the development of interdisciplinary storylines. A case study was conducted in Atitlán Basin, Guatemala, to understand the relationships that govern the lake's cultural eutrophication problem. This research integrated key stakeholders from the Indigenous Mayan community, associated with diverse literacy ranges, and emerging from three different marginalized linguistic backgrounds (Kaqchikel, Tz'utujil, and K'iche'), in the PM activity. The proposed approach facilitated the participation of marginalized stakeholders. Moreover, it (1) helped develop an understanding of mechanisms governing the eutrophication of the lake, (2) initiated a dialogue between Indigenous Peoples and non-Indigenous stakeholders, and (3) extracted potential solutions targeting the system's leverage points. The participatory model-building activity generated three submodules: (1) agriculture, (2) tourism, and (3) environmental awareness. Each submodule contained socioculturally specific mechanisms associated with nutrient discharge to Lake Atitlán. The delineation of such nuanced relationships helps develop well-targeted policies and best management practices (BMPs). Additionally, the suggested process helped decrease the impact of power imbalances in water resources management and empowered community-based decision-making.

Description: We present a laboratory technique to measure tropospheric ozone, following a traditional method developed by Christian Friedrich Schönbein in the 19th century. The aim is to familiarise students with both the scientific method and the concepts of pollution and climate change, taking advantage of the possibilities of a very cheap hands-on approach over other existing theoretical ones. Also, this teaching activity can help the students to understand the differences between objective and subjective analysis. Moreover, they can make effective use of new technologies and photography. We include a description of how to conduct the lesson at two different levels of complexity (advanced and basic) to allow us to adapt it to the capacity of the students. The advanced level includes the production in the lab of paper strips as they were produced in the 19th century, whilst the basic level does not. This practice is suitable for use by both high school and first-year undergraduate students and was presented in high schools during a communication campaign to celebrate the annual Galician Scientist Day. We evaluate the teaching approach used through the results from collected surveys and feedback received from the students and teachers.

Description: In the Aguascalientes valley, middle Mexico, the demand of groundwater from the local aquifer system was suddenly increased after the late 1970s. Since then, several related problems have been occurring or become critical such as land subsidence, ground fissuring, and low-magnitude earthquakes. The most recent data of vertical deformation from PSInSAR, groundwater levels, and earthquakes, has provided critical information regarding the relationship amongst all these processes. In particular, that related to land subsidence, earth fissuring and seismicity. Regarding this, more satellite imagery and data from GPS stations are being revised as a possibility of a more generalized vertical deformation derived with low-magnitude seismicity. A particular seismic event recorded on 6 April 2019 has revealed critical information on the close association between vertical displacements occurred in active faults and low-magnitude seismic events.

Description: Reductions in N2O emissions from nitrification inhibitors (NI) are substantial but remain uncertain because measurements of N2O emissions are highly variable and discontinuous. Mathematical modelling may offer an opportunity to estimate these reductions if the processes causing variability in N2O emissions can be accurately simulated. In this study, the effect of NI was simulated with a simple, time-dependent algorithm to slow NH4+ oxidation in the ecosystem model ecosys. Slower nitrification modelled with NI caused increases in soil NH4+ concentrations and reductions in soil NO3- concentrations and in N2O fluxes that were consistent with those measured following fall and spring applications of slurry over 2 years from 2014 to 2016. The model was then used to estimate direct and indirect effects of NI on seasonal and annual emissions. After spring slurry applications, NI reduced N2O emissions modelled and measured during the drier spring of 2015 (35 % and 45 %) less than during the wetter spring of 2016 (53 % and 72 %). After fall slurry applications, NI reduced modelled N2O emissions by 58 % and 56 % during late fall in 2014 and 2015 and by 8 % and 33 % during subsequent spring thaw in 2015 and 2016. Modelled reductions were consistent with those from meta-analyses of other NI studies. Simulated NI activity declined over time so that reductions in N2O emissions modelled with NI at an annual timescale were relatively smaller than those during emission events. These reductions were accompanied by increases in NH3 emissions and reductions in NO3- losses with NI that caused changes in indirect N2O emissions. With further parameter evaluation, the addition of this algorithm for NI to ecosys may allow emission factors for different NI products to be derived from annual N2O emissions modelled under diverse site, soil, land use and weather.

Description: We analyzed the seismicity of oceanic earthquakes in the Pacific oceanic regime of Mexico. We used data from the earthquake catalogues of the Mexican National Service (SSN) and the International Seismological Centre (ISC) from 1967 to 2017. Events were classified into two different categories: intraplate oceanic (INT) and transform fault zone and mid-ocean ridges (TF-MOR) events, respectively. For each category, we determined statistical characteristics such as magnitude frequency distributions, the aftershocks decay rate, the nonextensivity parameters, and the regional stress field. We obtained b values of 1.17 and 0.82 for the INT and TF-MOR events, respectively. TF-MOR events also exhibit local b-value variations in the range of 0.72–1.30. TF-MOR events follow a tapered Gutenberg–Richter distribution. We also obtained a p value of 0.67 for the 1 May 1997 (Mw=6.9) earthquake. By analyzing the nonextensivity parameters, we obtained similar q values in the range of 1.39–1.60 for both types of earthquakes. On the other hand, the parameter a showed a clear differentiation, being higher for TF-MOR events than for INT events. An important implication is that more energy is released for TF-MOR events than for INT events. Stress orientations are in agreement with geodynamical models for transform fault zone and mid-ocean ridge zones. In the case of intraplate seismicity, stresses are mostly related to a normal fault regime.

Description: With projected increasing intensity of hurricanes and large uncertainty in the path of forest recovery from hurricanes, studies are needed to understand the fundamental response of forests to canopy opening and debris deposition: the response of the abiotic factors underneath the canopy. Through two manipulative experiments and instrumenting prior to Hurricane Maria (2017) in the Luquillo Experimental Forest (LEF) of Puerto Rico, this study found a long recovery time of primary abiotic factors (beneath canopy light, throughfall, and temperature) influenced by the disturbance of canopy opening, as well as complex responses by the secondary abiotic factors (relative humidity, soil moisture, and leaf saturation) influenced by the disturbance of the primary factors. Recovery took 4–5 years for beneath canopy light, while throughfall recovery took 4–9 years and neither had recovered when Hurricane Maria passed 3 years after the second experiment. Air and soil temperature seemingly recovered quickly from each disturbance (

Description: Atmospheric aerosol particles that can nucleate ice are referred to as ice-nucleating particles (INPs). Recent studies have confirmed that aerosol particles emitted by the oceans can act as INPs. This very relevant information can be included in climate and weather models to predict the formation of ice in clouds, given that most of them do not consider oceans as a source of INPs. Very few studies that sample INPs have been carried out in tropical latitudes, and there is a need to evaluate their availability to understand the potential role that marine aerosol may play in the hydrological cycle of tropical regions. This study presents results from the first measurements obtained during a field campaign conducted in the tropical village of Sisal, located on the coast of the Gulf of Mexico of the Yucatan Peninsula in Mexico in January–February 2017, and one of the few data sets currently available at such latitudes (i.e., 21∘ N). Aerosol particles sampled in Sisal are shown to be very efficient INPs in the immersion freezing mode, with onset freezing temperatures in some cases as high as −3 ∘C, similarly to the onset temperature from Pseudomonas syringae. The results show that the INP concentration in Sisal was higher than at other locations sampled with the same type of INP counter. Air masses arriving in Sisal after the passage of cold fronts have surprisingly higher INP concentrations than the campaign average, despite their lower total aerosol concentration. The high concentrations of INPs at warmer ice nucleation temperatures (T〉-15 ∘C) and the supermicron size of the INPs suggest that biological particles may have been a significant contributor to the INP population in Sisal during this study. However, our observations also suggest that at temperatures ranging between −20 and −30 ∘C mineral dust particles are the likely source of the measured INPs.

Description: Observations of multiwavelength Mie–Raman lidar taken during the SHADOW field campaign are used to analyze a smoke–dust episode over West Africa on 24–27 December 2015. For the case considered, the dust layer extended from the ground up to approximately 2000 m while the elevated smoke layer occurred in the 2500–4000 m range. The profiles of lidar measured backscattering, extinction coefficients, and depolarization ratios are compared with the vertical distribution of aerosol parameters provided by the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The MERRA-2 model simulated the correct location of the near-surface dust and elevated smoke layers. The values of modeled and observed aerosol extinction coefficients at both 355 and 532 nm are also rather close. In particular, for the episode reported, the mean value of difference between the measured and modeled extinction coefficients at 355 nm is 0.01 km−1 with SD of 0.042 km−1. The model predicts significant concentration of dust particles inside the elevated smoke layer, which is supported by an increased depolarization ratio of 15 % observed in the center of this layer. The modeled at 355 nm the lidar ratio of 65 sr in the near-surface dust layer is close to the observed value (70 ± 10) sr. At 532 nm, however, the simulated lidar ratio (about 40 sr) is lower than measurements (55 ± 8 sr). The results presented demonstrate that the lidar and model data are complimentary and the synergy of observations and models is a key to improve the aerosols characterization.