Evaluating sources of mercury in Canada's Mackenzie River - Una Jermilova; Jane L. Kirk; Ashu Dastoor; Kevin Schaefer; Holger H. Hintelmann (Science of The Total Environment, 2025)

Drug Dissolution in Oral Drug Absorption: Workshop Report - Kimberly Raines; Payal Agarwal; Patrick Augustijns; Alaadin Alayoubi; Lucas Attia; Annette Bauer-Brandl; Martin Brandl; Parnali Chatterjee; Hansong Chen; Yuly Chiang Yu; Carrie Coutant; Ana Luisa Coutinho; et al. (The AAPS Journal, 2023)
The in-person workshop “Drug Dissolution in Oral Drug Absorption” was held on May 23–24, 2023, in Baltimore, MD, USA. The workshop was organized into lectures and breakout sessions. Three common topics that were re-visited by various lecturers were amorphous solid dispersions (ASDs), dissolution/permeation interplay, and in vitro methods to predict in vivo biopharmaceutics performance and risk. Topics that repeatedly surfaced across breakout sessions were the following: (1) meaning and assessment of “dissolved drug,” particularly of poorly water soluble drug in colloidal environments ( e.g. , fed conditions, ASDs); (2) potential limitations of a test that employs sink conditions for a poorly water soluble drug; (3) non-compendial methods ( e.g. , two-stage or multi-stage method, dissolution/permeation methods); (4) non-compendial conditions ( e.g. , apex vessels, non-sink conditions); and (5) potential benefit of having both a quality control method for batch release and a biopredictive/biorelevant method for biowaiver or bridging scenarios. An identified obstacle to non-compendial methods is the uncertainty of global regulatory acceptance of such methods.

Identifying active retrogressive thaw slumps from ArcticDEM - Lingcao Huang; Michael J. Willis; Guiye Li; Trevor C. Lantz; Kevin Schaefer; Elizabeth Wig; Guofeng Cao; Kristy F. Tiampo (ISPRS Journal of Photogrammetry and Remote Sensing, 2023)

Efficacy of Corsi Block Tapping Task training for improving visuospatial skills: a non-randomized two-group study - Sydney Y. Schaefer; Andrew Hooyman; Nicole K. Haikalis; Randy Essikpe; Keith R. Lohse; Kevin Duff; Peiyuan Wang (Experimental Brain Research, 2022)

Beyond ecosystem modeling: A roadmap to community cyberinfrastructure for ecological data‐model integration - Istem Fer; Anthony K. Gardella; Alexey N. Shiklomanov; Eleanor E. Campbell; Elizabeth M. Cowdery; Martin G. De Kauwe; Ankur Desai; Matthew J. Duveneck; Joshua B. Fisher; Katherine D. Haynes; Forrest M. Hoffman; Miriam R. Johnston; et al. (Global Change Biology, 2021)
In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks to informing models with observations have reduced our capacity to fully exploit the growing volume and variety of available data. Here, we take a critical look at the information infrastructure that connects ecosystem modeling and measurement efforts, and propose a roadmap to community cyberinfrastructure development that can reduce the divisions between empirical research and modeling and accelerate the pace of discovery. A new era of data‐model integration requires investment in accessible, scalable, and transparent tools that integrate the expertise of the whole community, including both modelers and empiricists. This roadmap focuses on five key opportunities for community tools: the underlying foundations of community cyberinfrastructure; data ingest; calibration of models to data; model‐data benchmarking; and data assimilation and ecological forecasting. This community‐driven approach is a key to meeting the pressing needs of science and society in the 21st century.

A comparative analysis of genetic hearing loss phenotypes in European/American and Japanese populations - W. Daniel Walls; Hideaki Moteki; Taylor R. Thomas; Shin-ya Nishio; Hidekane Yoshimura; Yoichiro Iwasa; Kathy L. Frees; Carla J. Nishimura; Hela Azaiez; Kevin T. Booth; Robert J. Marini; Diana L. Kolbe; et al. (Human Genetics, 2020)

Global vegetation biomass production efficiency constrained by models and observations - Yue He; Shushi Peng; Yongwen Liu; Xiangyi Li; Kai Wang; Philippe Ciais; M. Altaf Arain; Yuanyuan Fang; Joshua B. Fisher; Daniel Goll; Daniel Hayes; Deborah N. Huntzinger; et al. (Global Change Biology, 2020)
Plants use only a fraction of their photosynthetically derived carbon for biomass production (BP). The biomass production efficiency (BPE), defined as the ratio of BP to photosynthesis, and its variation across and within vegetation types is poorly understood, which hinders our capacity to accurately estimate carbon turnover times and carbon sinks. Here, we present a new global estimation of BPE obtained by combining field measurements from 113 sites with 14 carbon cycle models. Our best estimate of global BPE is 0.41 ± 0.05, excluding cropland. The largest BPE is found in boreal forests (0.48 ± 0.06) and the lowest in tropical forests (0.40 ± 0.04). Carbon cycle models overestimate BPE, although models with carbon–nitrogen interactions tend to be more realistic. Using observation‐based estimates of global photosynthesis, we quantify the global BP of non‐cropland ecosystems of 41 ± 6 Pg C/year. This flux is less than net primary production as it does not contain carbon allocated to symbionts, used for exudates or volatile carbon compound emissions to the atmosphere. Our study reveals a positive bias of 24 ± 11% in the model‐estimated BP (10 of 14 models). When correcting models for this bias while leaving modeled carbon turnover times unchanged, we found that the global ecosystem carbon storage change during the last century is decreased by 67% (or 58 Pg C).

Dynamics of an outburst flood originating from a small and high-altitude glacier in the Arid Andes of Chile - Pablo Iribarren Anacona; Kevin Norton; Andrew Mackintosh; Fernando Escobar; Simon Allen; Bruno Mazzorana; Marius Schaefer (Natural Hazards, 2018)

Investigation of a Worker Death While Agitating Manure in a Non-enclosed Storage - John M. Shutske; Daniel Schaefer; Rebecca Larson; Kevin Erb; Cheryl Skjolaas; Stephanie Leonard; Jeff Nelson; Elizabeth Binversie; Scott Rifleman (Journal of Agromedicine, 2018)

Potential for cometabolic biodegradation of 1,4-dioxane in aquifers with methane or ethane as primary substrates - Paul B. Hatzinger; Rahul Banerjee; Rachael Rezes; Sheryl H. Streger; Kevin McClay; Charles E. Schaefer (Biodegradation, 2017)

Emergent climate and CO 2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America - Christine R. Rollinson; Yao Liu; Ann Raiho; David J. P. Moore; Jason McLachlan; Daniel A. Bishop; Alex Dye; Jaclyn H. Matthes; Amy Hessl; Thomas Hickler; Neil Pederson; Benjamin Poulter; et al. (Global Change Biology, 2017)
Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data‐based evaluations of emergent ecosystem responses to climate and CO 2 at multidecadal and centennial timescales have been rare. We compared the sensitivity of net primary productivity ( NPP ) to temperature, precipitation, and CO 2 in ten ecosystem models with the sensitivities found in tree‐ring reconstructions of NPP and raw ring‐width series at six temperate forest sites. These model‐data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO 2 in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree‐ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm‐growing season temperatures, while tree‐ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO 2 drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO 2 sensitivity. Fire in model simulations reduced model sensitivity to climate and CO 2 , but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multidecadal and multicentennial timescales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the feedbacks with moisture balance and CO 2 in individual models.

Terrestrial biosphere model performance for inter‐annual variability of land‐atmosphere CO 2 exchange - T.F. Keenan; Ian Baker; Alan Barr; Philippe Ciais; Ken Davis; Michael Dietze; Danillo Dragoni; Christopher M Gough; Robert Grant; David Hollinger; Koen Hufkens; Ben Poulter; et al. (Global Change Biology, 2012)
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 N orth A merican 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 N orth A merica. 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.

Terrestrial biosphere models need better representation of vegetation phenology: results from the N orth A merican C arbon P rogram S ite S ynthesis - Andrew D. Richardson; Ryan S. Anderson; M. Altaf Arain; Alan G. Barr; Gil Bohrer; Guangsheng Chen; Jing M. Chen; Philippe Ciais; Kenneth J. Davis; Ankur R. Desai; Michael C. Dietze; Danilo Dragoni; et al. (Global Change Biology, 2012)
Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem‐scale CO 2 exchange, in 14 models participating in the N orth A merican C arbon P rogram S ite S ynthesis. Model predictions were evaluated using long‐term measurements (emphasizing the period 2000–2006) from 10 forested sites within the A meri F lux and F luxnet‐ C anada networks. In deciduous forests, almost all models consistently predicted that the growing season started earlier, and ended later, than was actually observed; biases of 2 weeks or more were typical. For these sites, most models were also unable to explain more than a small fraction of the observed interannual variability in phenological transition dates. Finally, for deciduous forests, misrepresentation of the seasonal cycle resulted in over‐prediction of gross ecosystem photosynthesis by +160 ± 145 g C m −2 yr −1 during the spring transition period and +75 ± 130 g C m −2 yr −1 during the autumn transition period (13% and 8% annual productivity, respectively) compensating for the tendency of most models to under‐predict the magnitude of peak summertime photosynthetic rates. Models did a better job of predicting the seasonality of CO 2 exchange for evergreen forests. These results highlight the need for improved understanding of the environmental controls on vegetation phenology and incorporation of this knowledge into better phenological models. Existing models are unlikely to predict future responses of phenology to climate change accurately and therefore will misrepresent the seasonality and interannual variability of key biosphere–atmosphere feedbacks and interactions in coupled global climate models.

Assimilation exceeds respiration sensitivity to drought: A FLUXNET synthesis - CHRISTOPHER R. SCHWALM; CHRISTOPHER A. WILLIAMS; KEVIN SCHAEFER; ALMUT ARNETH; DAMIEN BONAL; NINA BUCHMANN; JIQUAN CHEN; BEVERLY E. LAW; ANDERS LINDROTH; SEBASTIAAN LUYSSAERT; MARKUS REICHSTEIN; ANDREW D. RICHARDSON (Global Change Biology, 2010)
The intensification of the hydrological cycle, with an observed and modeled increase in drought incidence and severity, underscores the need to quantify drought effects on carbon cycling and the terrestrial sink. FLUXNET, a global network of eddy covariance towers, provides dense data streams of meteorological data, and through flux partitioning and gap filling algorithms, estimates of net ecosystem productivity ( F NEP ), gross ecosystem productivity ( P ), and ecosystem respiration ( R ). We analyzed the functional relationship of these three carbon fluxes relative to evaporative fraction (EF), an index of drought and site water status, using monthly data records from 238 micrometeorological tower sites distributed globally across 11 biomes. The analysis was based on relative anomalies of both EF and carbon fluxes and focused on drought episodes by biome and climatic season. Globally P was ≈50% more sensitive to a drought event than R . Network‐wide drought‐induced decreases in carbon flux averaged −16.6 and −9.3 g C m −2 month −1 for P and R , i.e., drought events induced a net decline in the terrestrial sink. However, in evergreen forests and wetlands drought was coincident with an increase in P or R during parts of the growing season. The most robust relationships between carbon flux and EF occurred during climatic spring for F NEP and in climatic summer for P and R . Upscaling flux sensitivities to a global map showed that spatial patterns for all three carbon fluxes were linked to the distribution of croplands. Agricultural areas exhibited the highest sensitivity whereas the tropical region had minimal sensitivity to drought. Combining gridded flux sensitivities with their uncertainties and the spatial grid of FLUXNET revealed that a more robust quantification of carbon flux response to drought requires additional towers in all biomes of Africa and Asia as well as in the cropland, shrubland, savannah, and wetland biomes globally.

Geographic patterns in fruit colour diversity: do leaves constrain the colour of fleshy fruits? - Kevin C. Burns; Eliana Cazetta; Mauro Galetti; Alfredo Valido; H. Martin Schaefer (Oecologia, 2009)