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At least 523 records · Page 29

Global latitudinal-asymmetric vegetation growth trends and their driving mechanisms: 1982-2009

Using a recent Leaf Area Index (LAI) dataset and the Community Land Model version 4 (CLM4), we investigate percent changes and controlling factors of global vegetation growth for the period 1982 to 2009. Over that 28-year period, both the remote-sensing estimate and model simulation show a significant increasing trend in annual vegetation growth. Latitudinal asymmetry appeared in both products, with small increases in the Southern Hemisphere (SH) and larger increases at high latitudes in the Northern Hemisphere (NH). The south-to-north asymmetric land surface warming was assessed to be the principal driver of this latitudinal asymmetry of LAI trend. Heterogeneous precipitation functioned to decrease this latitudinal LAI gradient, and considerably regulated the local LAI change. CO2 fertilization during the last three decades, was simulated to be the dominant cause for the enhanced vegetation growth. Our study, though limited by observational and modeling uncertainties, adds further insight into vegetation growth trends and environmental correlations. These validation exercises also provide new quantitative and objective metrics for evaluation of land ecosystem process models at multiple spatio-temporal scales.

Mao, Jiafu↗

Above and belowground connections and species interactions: Controls over ecosystem fluxes

The ultimate goal of this work was to quantify soil and volatile organic compound fluxes as a function of tree species and associated mycorrhizal associations in an intact forest, but also to describe the physical and biological factors that control these emissions. The results of this research lay the foundation toward an improved mechanistic understanding of carbon pathways, fluxes, and ecosystem function, ultimately improving the representation of forest ecosystems in Earth System models. To this end, a multidisciplinary approach was necessary to fill a critical gap in our understanding of how soil and root processes may influence whole-ecosystem carbon-based volatile fluxes in the face of a rapidly changing climate. We developed a series of novel sampling protocols and coupled a variety of advanced analytical techniques, resulting in findings relevant across disciplines. Furthermore, we leveraged existing infrastructure, research sites, and datasets to design a low-cost exploratory project that links belowground processes, soil volatile emissions, and total ecosystem carbon budgets. Measurements from soil collars installed across a species/mycorrhizal gradient at the DOE-supported Moran Monroe State Forest Ameriflux tower site suggest that leaf litter is the primary source of belowground and forest floor volatile emissions, but the strength of this source is significantly affected not only by leaf litter type, but the strength of the soil as a sink. Results suggest that the strength of the sink is influenced by tree species-specific associated microbial communities that change throughout the season as a function of temperature, soil moisture, leaf litter inputs, and phenology. The magnitude of the observed volatile fluxes from the forest floor is small relative to total aboveground ecosystem flux, but the contribution of these emissions to volatile-mediated ecological interactions and soil processes (e.g. nitrification) varies substantially across the growing season. This research lays the foundation to answer important questions regarding the impacts of seasonality and forest composition on belowground volatile source-sink dynamics in mediating nutrient cycling and biogeochemistry dynamics—critical components of overall ecosystem functioning. In collaboration with the Environmental Simulations Unit (EUS) at the Helmholtz Zentrum in Munich, Germany (headed by Prof. Dr. Joerg-Peter Schinitzler), we investigated carbon investment in above and belowground plant volatile compounds in response to environmental conditions and mycorrhizal associations. Using the sophisticated phytotron facility and on-line trace gas instruments, we conducted controlled laboratory experiments that showed that biotic stresses, such as herbivore feeding, can alter the magnitude of belowground volatile emissions as well as carbon allocation towards these volatiles. We saw no effect of mycorrhizae on any induced response, suggesting that microbial effects were unrelated to source-sink dynamics driving terpene emissions. Furthermore, the results suggest that even though enzyme activity responsible for root volatile synthesis is up-regulated following herbivory, the sink strength of the soil can significantly impact what is measured at the soil/atmosphere interface and thereby what enters the atmosphere. This is important as scientists may be underestimating the magnitude of belowground volatile emissions and their influence on belowground interactions due to limitations associated with current sampling techniques. These key findings are being integrated with results from a hydroxyl radical reactivity-VOC campaign and a late season litter removal experiment to offer a comprehensive mechanistic understanding of the sources and controls over soil volatile emissions, particularly during times of the year when vegetative aboveground emissions are low (leaf senescence). Ultimately, these coupled field and laboratory experiments offer insights into seasonal dynamics of volatile emissions and the mechanisms that control carbon allocation to these compounds with an eye towards improving carbon budgets, nutrient cycling, and terrestrial ecosystem models.

54 ENVIRONMENTAL SCIENCES↗

Assessment of the impact of increased solar ultraviolet radiation upon marine ecosystems

Data was provided to assess the potential impact upon marine ecosystems if space shuttle operations contribute to a reduction of the stratospheric ozone layer. The potential for irreversible damage to the productivity, structure and/or functioning of a model estuarine ecosystem by increased UV-B radiation was established. The sensitivity of key community components (the primary producers) to increased UV-B radiation was delineated.

Vandyke, H.↗

An Evidence-Based Evaluation of the Cumulative Effects of Tidal Freshwater and Estuarine Ecosystem Restoration on Endangered Juvenile Salmon in the Columbia River: Final Report

The listing of 13 salmon and steelhead stocks in the Columbia River basin (hereafter collectively referred to as “salmon”) under the Endangered Species Act of 1973, as amended, has stimulated tidal wetland restoration in the lower 235 kilometers of the Columbia River and estuary for juvenile salmon habitat functions. The purpose of the research reported herein was to evaluate the effect on listed salmon of the restoration effort currently being conducted under the auspices of the federal Columbia Estuary Ecosystem Restoration Program (CEERP). Linking changes in the quality and landscape pattern of tidal wetlands in the lower Columbia River and estuary (LCRE) to salmon recovery is a complex problem because of the characteristics of the ecosystem, the salmon, the restoration actions, and available sampling technologies. Therefore, we designed an evidence-based approach to develop, synthesize, and evaluate information to determine early-stage (~10 years) outcomes of the CEERP. We developed an ecosystem conceptual model and from that, a primary hypothesis that habitat restoration activities in the LCRE have a cumulative beneficial effect on juvenile salmon. There are two necessary conditions of the hypothesis: • habitat-based indicators of ecosystem controlling factors, processes, and structures show positive effects from restoration actions, and • fish-based indicators of ecosystem processes and functions show positive effects from restoration actions and habitats undergoing restoration. Our evidence-based approach to evaluate the primary hypothesis incorporated seven lines of evidence, most of which are drawn from the LCRE. The lines of evidence are spatial and temporal synergies, cumulative net ecosystem improvement, estuary-wide meta-analysis, offsite benefits to juvenile salmon, landscape condition evaluation, and evidence-based scoring of global literature. The general methods we used to develop information for the lines of evidence included field measurements, data analyses, modeling, meta-analysis, and reanalysis of previously collected data sets. We identified a set of 12 ancillary hypotheses regarding habitat and salmon response. Each ancillary hypothesis states that the response metric will trend toward conditions at relatively undisturbed reference sites. We synthesized the evidence for and against the two necessary conditions by using eleven causal criteria: strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, analogy, complete exposure pathway, and predictive performance. Our final evaluation included cumulative effects assessment because restoration is occurring at multiple sites and the collective effect is important to salmon recovery. We concluded that all five lines of evidence from the LCRE indicated positive habitat-based and fish-based responses to the restoration performed under the CEERP, although tide gate replacements on small sloughs were an exception. Our analyses suggested that hydrologic reconnections restore access for fish to move into a site to find prey produced there. Reconnections also restore the potential for the flux of prey from the site to the main stem river, where our data show that they are consumed by salmon. We infer that LCRE ecosystem restoration supports increased juvenile salmon growth and enhanced fitness (condition), thereby potentially improving survival rates during the early ocean stage.

54 ENVIRONMENTAL SCIENCES↗

Constraining DALECv2 using multiple data streams and ecological constraints: analysis and application

We use a variational method to assimilate multiple data streams into the terrestrial ecosystem carbon cycle model DALECv2 (Data Assimilation Linked Ecosystem Carbon). Ecological and dynamical constraints have recently been introduced to constrain unresolved components of this otherwise ill-posed problem. We recast these constraints as a multivariate Gaussian distribution to incorporate them into the variational framework and we demonstrate their advantage through a linear analysis. By using an adjoint method we study a linear approximation of the inverse problem: firstly we perform a sensitivity analysis of the different outputs under consideration, and secondly we use the concept of resolution matrices to diagnose the nature of the ill-posedness and evaluate regularisation strategies. We then study the non-linear problem with an application to real data. Finally, we propose a modification to the model: introducing a spin-up period provides us with a built-in formulation of some ecological constraints which facilitates the variational approach.

58 GEOSCIENCES↗

Hydrodynamic trait coordination and cost–benefit trade‐offs throughout the isohydric–anisohydric continuum in trees

Abstract Whole‐plant hydraulic performance depends on the integrated function of trait complexes, such as embolism resistance, stomatal closure mechanisms, and root properties. The diversity of such traits produces a wide range of response strategies to both short‐term variation of environmental conditions and long‐term changes to climate and hydrological cycles. This study aims to assess the role of different emergent hydraulic trait combinations in trees' vulnerability to drought using a quantitative modelling framework. This modelling framework may be helpful in studying the influence of plant hydraulic traits independently. It will also be used to assess how different groups of traits interact to form viable hydraulic strategies in response to different environmental conditions. We use the advanced plant hydrodynamic model, finite‐difference ecosystem‐scale tree crown hydrodynamics model version 2, to resolve plant functional traits of roots, stems, and leaves and simulate the transpiration. We define a multidimensional hydraulic “strategy space” by considering a continuum of these traits to test the outcomes of different hypothetical strategies in response to environmental conditions as observed in Northern Michigan, USA. We evaluate the degree to which simulated trees suffer hydraulic failure due to cavitation or carbon deficiency in response to reduced stomatal conductance. Our results demonstrate how the relationship between plant hydraulic strategy and hydraulic safety margin emerges from trait combinations along different tissue levels. Our findings suggest that hydrodynamic models present an exciting new possibility to define and study plant traits and hydrodynamics.

Mirfenderesgi, Golnazalsadat↗

Polar Lakes and Springs as Analogs for Mars

If we accept the fluvial features as evidence of liquid water on Mars we conclude that early in Martian history there was an extensive period during which liquid water was prevalent and stable. The duration of this epoch and the environmental conditions that allowed for water flow are uncertain but because liquid water is the most critical environmental requirement for life on Earth, the observation that there was liquid water on Mars during on early epoch is a strong motivation for considering the possibility of past life. Microbial ecosystems can thrive in polar lakes and springs on Earth, such as those in the Antarctic dry valleys, even when the mean temperatures are well below freezing. Mars need not have ever been above freezing for life to persist. These microbial ecosystems provide specific models for possible past martian ecosystems and can be used in the development of methods to locate and identify analogous Martian fossil forms, if they exist.

McKay, C. P.↗

A Comprehensive Framework for Valuation of Ecosystem Services in the Context of Hydropower

While models to value ecosystem services exist, they suffer from a lack of “portability” in the sense that a single modelling framework developed for one site cannot be imported and applied to another. Additionally, benefit estimations are often fragmented, incomplete, incomparable, and in heterogenous metrics, thus preventing aggregation to arrive at one comprehensive value. In the context of hydropower, the methods, as well as the metrics used to value the associated ecosystem services, vary between stakeholders (e.g., competing water users, agencies, etc.), detracting from the ability to assess the total value of a hydropower project, water management schemes, or comparing value between competing water users. Further, current methods to value water neglect non-market ecosystem services’ values by failing to account for externalities, resulting in misallocation of costs (e.g., obligatory stakeholder payments for water use) and misinterpretation of hydropower benefits. The benefit-cost ratios in hydropower development are often incomplete because non-market benefits are excluded (e.g., benefits, such as fish habitat resiliency and agricultural water reliability, derived from hydropower development). An approach to enable consistent, standardized hydropower benefit-cost analyses does not currently exist. This paper conceptualizes a methodology to standardize ecosystem services valuation in the context of hydropower projects through the integration of the U.S. Environmental Protection Agency’s existing Final Ecosystem Goods and Services Classification System framework and economic valuation techniques, and demonstrates the applicability of this methodology through a limited proof-of-concept application (the New Waddell Plant, a pumped hydroelectric energy storage facility in Phoenix, AZ). The beauty of our proposed framework lies in its ability to be imported and applied to any other pumped storage facility after accounting for site-specific features.

13 HYDRO ENERGY↗

Moisture availability mediates the relationship between terrestrial gross primary production and solar-induced chlorophyll fluorescence: Insights from global-scale variations

Effective use of solar-induced chlorophyll fluorescence (SIF) to estimate and monitor gross primary production (GPP) in terrestrial ecosystems requires a comprehensive understanding and quantification of the relationship between SIF and GPP. To date, this understanding is incomplete and somewhat controversial in the literature. Here we derived the GPP/SIF ratio from multiple data sources as a diagnostic metric to explore its global-scale patterns of spatial variation and potential climatic dependence. We found that the growing season GPP/SIF ratio varied substantially across global land surfaces, with the highest ratios consistently found in boreal regions. Spatial variation in GPP/SIF was strongly modulated by climate variables. The most striking pattern was a consistent decrease in GPP/SIF from cold-and-wet climates to hot-and-dry climates. We propose that the reduction in GPP/SIF with decreasing moisture availability may be related to stomatal responses to aridity. Furthermore, we show that GPP/SIF can be empirically modeled from climate variables using a machine learning (random forest) framework, which can improve the modeling of ecosystem production and quantify its uncertainty in global terrestrial biosphere models. Finally, our results point to the need for targeted field and experimental studies to better understand the patterns observed and to improve the modeling of the relationship between SIF and GPP over broad scales.

59 BASIC BIOLOGICAL SCIENCES↗

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

54 ENVIRONMENTAL SCIENCES↗

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

Laura Duncanson↗

Monthly averages of ED2 model simulations initialized with airborne lidar structure, Jan 1981-Dec 2018, Brazilian Amazon

Deforestation and forest degradation (selective logging, fires, fragmentation) have impacted nearly 40% of the original extent of the Brazilian Amazon, and have markedly impacted forest structure across the region. To date, few studies analysed how shifts in forest structure from degradation influence the forest sensitivity to climate extremes, because of the complex interactions between forest structure and micro-environmental conditions. To address this knowledge gap, we carried out a series of simulations across the Brazilian Amazon using the Ecosystem Demography Model (ED2), using observed forest structure derived from 541 airborne lidar transects (375 ha each) and two scenarios representing forest recovery and expansion of degradation to investigate how shifts in forest structure impact ecosystem function under near-average and extreme climate conditions, as part of the manuscript Longo et al 2025 "Degradation and Deforestation Increase the Sensitivity of the Amazon Forest to Climate Extremes". This dataset provides the output results from the ED2 model simulations for the three simulations at monthly time scales, in NetCDF format. For all simulations, we used bias-corrected hourly reanalyses (WFDE5) for most meteorological drivers, except for precipitation, which was obtained from CHIRPS. The meteorological drivers used in the study span 38 years (Jan 1981–Dec 2018). The output results correspond to the last 38 years of simulation (one full cycle of meteorological drivers), in which ED2 simulations used static stand structure (i.e., the forest structure was held constant). The following files are provided:ED2_emean_Global_R004_BrAmaz_s1c0t0l0f0.nc. This corresponds to the Control simulation. The forest structure was obtained from the airborne lidar.ED2_emean_Global_R005_BrAmaz_s1c0t1l1f0.nc. This corresponds to the Degraded simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that expanded deforestation and selective logging across the Amazon.ED2_emean_Global_R006_BrAmaz_s1c0t1l0f0.nc. This corresponds to the Recovery simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that completely halted deforestation and degradation, allowing degraded forests to recover for 38 years.We also provide file ED2_zones_R004_BrAmaz_s1c0t0l0f0.nc, which classifies each grid cell into zones used in the reference manuscript: 1: Southeast. 2: South. 3: West. 4: Central. 5: Northeast. 6: North. 7: Northwest". Index 0 corresponds to grid cells excluded from sub-region analyses because they were dominated by flooded forests, deforestation, and naturally non-forest vegetation.

54 ENVIRONMENTAL SCIENCES↗

Across‐model spread and shrinking in predicting peatland carbon dynamics under global change

Abstract Large across‐model spread in simulating land carbon (C) dynamics has been ubiquitously demonstrated in model intercomparison projects (MIPs), and became a major impediment in advancing climate change prediction. Thus, it is imperative to identify underlying sources of the spread. Here, we used a novel matrix approach to analytically pin down the sources of across‐model spread in transient peatland C dynamics in response to a factorial combination of two atmospheric CO 2 levels and five temperature levels. We developed a matrix‐based MIP by converting the C cycle module of eight land models (i.e., TEM, CENTURY4, DALEC2, TECO, FBDC, CASA, CLM4.5 and ORCHIDEE) into eight matrix models. While the model average of ecosystem C storage was comparable to the measurement, the simulation differed largely among models, mainly due to inter‐model difference in baseline C residence time. Models generally overestimated net ecosystem production (NEP), with a large spread that was mainly attributed to inter‐model difference in environmental scalar. Based on the sources of spreads identified, we sequentially standardized model parameters to shrink simulated ecosystem C storage and NEP to almost none. Models generally captured the observed negative response of NEP to warming, but differed largely in the magnitude of response, due to differences in baseline C residence time and temperature sensitivity of decomposition. While there was a lack of response of NEP to elevated CO 2 (eCO 2 ) concentrations in the measurements, simulated NEP responded positively to eCO 2 concentrations in most models, due to the positive responses of simulated net primary production. Our study used one case study in Minnesota peatland to demonstrate that the sources of across‐model spreads in simulating transient C dynamics can be precisely traced to model structures and parameters, regardless of their complexity, given the protocol that all the matrix models were driven by the same gross primary production and environmental variables.

Hou, Enqing↗

Phenological variation decreased carbon uptake in European forests during 1999–2013

A number of studies have suggested that the duration of a growing season has significantly lengthened during the past decades, but the connections between phenology variability and the terrestrial carbon cycle are far from clear. In this study, we used a process-based ecosystem simulation model, BIOME-BGC, to investigate spatio-temporal variation in phenology and its impacts on carbon fluxes in European forests during 1999–2013. We found that the start of vegetation growing season advanced on average by 0.22 ± 0.55 d yr -1 and the length of growing season extended on average by 0.42 ± 0.86 d yr -1 for the period 1999–2013. Model simulations indicated that European forests acted as a weak carbon (C) sink with a mean value of 0.27 Tg C yr -1 (1 Tg = 10 12 g) during 1999–2013. Phenological variation lowered the net ecosystem exchange (NEE) by 3.99 Tg C for the same period, and this could be explained by the opposing effect of enhanced heterotrophic respiration directly induced by the extension of growing season. NEE effects were negatively correlated with heterotrophic respiration (R 2 = 0.43), and one Tg increase in the heterotrophic respiration decreased NEE by 2.28 Tg C. The implications for the practical management is that a climate change will result in a significant change of selection pressure, and that phenology is a major aspect of tree functioning that will need adjusting for a future climate.

54 ENVIRONMENTAL SCIENCES↗

Growth and opportunities in networked synthesis through AmeriFlux

Since its inception in 1996 with just 15 sites, the AmeriFlux network has grown to include over 300 sites, representing every major ecosystem type across the Americas. This grassroots coalition of the willing has for the past two decades continuously measured the exchange of carbon, water and energy between ecosystems and the atmosphere. Recent years in particular have seen remarkable growth in both the degree of coordination of activities within the AmeriFlux network, and the number of researchers involved. Through the AmeriFlux Management Project, the network has made public over 1500 site-years of observations. This project now represents over 5000 registered members, a quarter of whom have signed up in the past year, who use the observations for a range of applications, including ecosystem science, modeling, and remote sensing, but also education and outreach.

photosynthesis↗

DayCent data and results for "Robust paths to net greenhouse gas mitigation and negative emissions via advanced biofuels"

DayCent data and results for:J. L. Field, T. L. Richard, E. A. Smithwick, H. Cai, M. S. Laser, D. S. LeBauer, S. P. Long, K. Paustian, Z. Qin, J. J. Sheehan, P. Smith, M. Q. Wang, L. R. Lynd, Robust paths to net greenhouse gas mitigation and negative emissions via advanced biofuels. Proceedings of the National Academy of Sciences (2020). https://doi.org/10.1073/pnas.1920877117 This zip file contains a UNIX-format DayCent model executable, input files, automation code, and associated directory structure necessary to re-produce the DayCent analysis underlying the manuscript. The main script 'autodaycent.py' (written for Python 2.7) opens an interactive command line routine that facilitates:* Calibrating the DayCent pine growth model.* Initializing DayCent for a set of case studies sites.* Executing an ensemble of model runs representing case study site reforestation, grassland restoration, or conversion to switchgrass cultivation. * Results analysis & generation of manuscript Fig. 3. Note that the interactive analysis code requires that all input files to be contained in the directory structure as uploaded, without modification. Executable versions of the DayCent model (https://www.nrel.colostate.edu/projects/daycent/) compatible with other operating systems are available upon request.Please send questions/comments to John.L.Field@gmail.com

Agro-ecosystem function and prediction↗

Assessment of the impact of increased solar ultraviolet radiation upon marine ecosystems

Reduction of the earth's ozone layer, with a resultant increase in transmission of solar ultraviolet radiation in the 290 to 320nm waveband (UV-B), via space shuttle operations through the stratosphere is considered. It is shown that simulated solar ultraviolet radiation can, under experimental conditions, detrimentally affect the marine organisms that form the base of the food web of oceanic and estuarine ecosystems. Whether a small increase in biologically harmful ultraviolet radiation might overwhelm these mechanisms and produce changes that will have damaging consequences to the biosphere is discussed. The potential for irreversible damage to the productivity, structure and/or functioning of a model estuarine ecosystem by increased UV-B radiation and whether these ecosystems are highly stable or amenable to adaptive change is studied. Data are provided to assess the potential impact upon marine ecosystems if space shuttle operations contribute to a reduction of the stratospheric ozone layer and the sensitivity of key community components to increased UV-B radiation is examined.

Worrest, R. C.↗

A framework for predicting impacts on ecosystem services from (sub)organismal responses to chemicals

Protection of ecosystem services is increasingly emphasized as a risk-assessment goal, but there are wide gaps between current ecological risk-assessment endpoints and potential effects on services provided by ecosystems. The authors present a framework that links common ecotoxicological endpoints to chemical impacts on populations and communities and the ecosystem services that they provide. This framework builds on considerable advances in mechanistic effects models designed to span multiple levels of biological organization and account for various types of biological interactions and feedbacks. For illustration, the authors introduce 2 case studies that employ well-developed and validated mechanistic effects models: the inSTREAM individual-based model for fish populations and the AQUATOX ecosystem model. They also show how dynamic energy budget theory can provide a common currency for interpreting organism-level toxicity. Lastly, they suggest that a framework based on mechanistic models that predict impacts on ecosystem services resulting from chemical exposure, combined with economic valuation, can provide a useful approach for informing environmental management.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗