Evaluating the growth performance of a newly planted forest using multi-temporal UAV imagery - Zhenbang Hao; Christopher J. Post; Elena A. Mikhailova; Shilong Yao; Lili Lin (New Forests, 2026)

Teaching wetlands in a global context: Geospatial learning aligned with Ramsar Convention and United Nations (UN) Sustainable Development Goals - Elena A. Mikhailova; Christopher J. Post; Davis G. Nelson; Hamdi A. Zurqani; Lili Lin; Zhenbang Hao (Wetlands Ecology and Management, 2026)
Teaching wetlands in a global context requires a pedagogical shift from local field observations to planetary systems analysis. This study proposes a teaching approach that integrates wetlands, analytical tools, policy frameworks, and a global purpose, which can be used in Earth science education. Laboratory exercise was developed and tested using wetlands (including a wetland of international importance and a Ramsar site: Congaree National Park) in the state of South Carolina (SC) in the United States of America (USA). Multidisciplinary students (wildlife biology, forestry, environmental and natural resources) engaged in active learning about subject matter definitions (e.g., hydric soils), used various geospatial analytical tools (e.g., Web Soil Survey), learned about Ramsar Convention (RC), and identified ecosystem services provided by wetlands for achieving the United Nations (UN) Sustainable Development Goals (SDGs). Results of two study years (2024 and 2025) were consistent, showing an increase in wetlands knowledge and applied analytical skills. The online quiz, taken by 113 students, had an average score of 9.3 out of 10. Students increased their knowledge of UN SDGs and ranked SDGs 6, 13, 14, and 15 as the most relevant SDGs to wetlands. A newly proposed teaching approach can be adopted worldwide, as most materials and tools are publicly available.

Improved wetlands analytics for achieving the goals of both the Ramsar Convention and the Kunming-Montreal Global Biodiversity Framework for wetlands monitoring - Elena A. Mikhailova; Hamdi A. Zurqani; Lili Lin; Zhenbang Hao; Christopher J. Post; Mark A. Schlautman; Gregory C. Post; George B. Shepherd (Wetlands Ecology and Management, 2026)
Wetlands are an important part of the Ramsar Convention (RC) and Kunming-Montreal Global Biodiversity Framework (KM-GBF), which is a significant agreement committing 196 countries (the United States is not a participant of KM-GBF) to a reduction and halting of the loss of biodiversity by 2030. In comparison to the broadly focused KM-GBF, goals of RC (172 contracting parties) are wetlands-focused such as “wise use” and protection of wetlands, selection of wetlands of “international importance”, and international collaboration. The goal of this study is to explore how improved wetlands analytics can help achieve the goals of both the RC and KM-GBF using the state of North Carolina (NC) in the United States of America (USA) as an example. Several goals and targets of KM-GBF are applicable to wetlands, with only a handful of indicators (e.g., wetland extent trends (WET) index) to monitor them. The WET index is only relevant at the global or continental scale because it relies on a limited database of wetland sites over time. Unfortunately, the WET index does not allow tracking of smaller spatial extents and new methods are needed to understand how wetlands are changing over time. Geospatial analysis results and recommendations are presented for both RC and KM-GBF. Loss of wetlands can result in transboundary damage, harming biodiversity and ecosystem functions and services (ES). A case study of NC showed that almost 49% of the wetland area was lost between 1780 and 1980 in the state. Wetlands loss in NC continued between 2001 and 2021. Future RC and KM-GBF refinements could use sea level rise analysis to evaluate changes in wetlands.

Mapping dynamics of large-scale high-precision pond datasets using a semi-automated method based on deep learning - Zhenbang Hao; Lili Lin; Christopher J. Post; Elena A. Mikhailova; Jeffery Allen (ISPRS Journal of Photogrammetry and Remote Sensing, 2025)

Comparative performance of convolutional neural networks for detecting and mapping a young Casuarina equisetifolia L. forest from unmanned aerial vehicle (UAV) imagery - Zhenbang Hao; Shilong Yao; Christopher J. Post; Elena A. Mikhailova; Lili Lin (New Forests, 2025)

BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series - Maria Dornelas; Laura H. Antão; Amanda E. Bates; Viviana Brambilla; Jonathan M. Chase; Cher F. Y. Chow; Ada Fontrodona‐Eslava; Anne E. Magurran; Inês S. Martins; Faye Moyes; Alban Sagouis; Samuel Adu‐Acheampong; et al. (Global Ecology and Biogeography, 2025)
Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

Thousands of shallow, relict gullies indicate thermo-erosion on the sandy uplands of northern Lower Michigan during the Late Pleistocene - Christopher J. Baish; Alanna Post; Ashton M. Shortridge; Randall J. Schaetzl; Parker Hopkins; Anthony Bowman; Isabella Rabac; Bernard Frantz; Andrew O. Finley (Geomorphology, 2024)

Practical Guide to Measuring Wetland Carbon Pools and Fluxes - Sheel Bansal; Irena F. Creed; Brian A. Tangen; Scott D. Bridgham; Ankur R. Desai; Ken W. Krauss; Scott C. Neubauer; Gregory B. Noe; Donald O. Rosenberry; Carl Trettin; Kimberly P. Wickland; Scott T. Allen; et al. (Wetlands, 2023)
Wetlands cover a small portion of the world, but have disproportionate influence on global carbon (C) sequestration, carbon dioxide and methane emissions, and aquatic C fluxes. However, the underlying biogeochemical processes that affect wetland C pools and fluxes are complex and dynamic, making measurements of wetland C challenging. Over decades of research, many observational, experimental, and analytical approaches have been developed to understand and quantify pools and fluxes of wetland C. Sampling approaches range in their representation of wetland C from short to long timeframes and local to landscape spatial scales. This review summarizes common and cutting-edge methodological approaches for quantifying wetland C pools and fluxes. We first define each of the major C pools and fluxes and provide rationale for their importance to wetland C dynamics. For each approach, we clarify what component of wetland C is measured and its spatial and temporal representativeness and constraints. We describe practical considerations for each approach, such as where and when an approach is typically used, who can conduct the measurements (expertise, training requirements), and how approaches are conducted, including considerations on equipment complexity and costs. Finally, we review key covariates and ancillary measurements that enhance the interpretation of findings and facilitate model development. The protocols that we describe to measure soil, water, vegetation, and gases are also relevant for related disciplines such as ecology. Improved quality and consistency of data collection and reporting across studies will help reduce global uncertainties and develop management strategies to use wetlands as nature-based climate solutions.

Implications of outgroup selection in the phylogenetic inference of hominoids and fossil hominins - Nicholas W. Post; Christopher C. Gilbert; Kelsey D. Pugh; Carrie S. Mongle (Journal of Human Evolution, 2023)

The DynaDeep observatory – a unique approach to study high-energy subterranean estuaries - Gudrun Massmann; Grace Abarike; Kojo Amoako; Felix Auer; Thomas H. Badewien; Cordula Berkenbrink; Michael Ernst Böttcher; Simone Brick; Iris Valeria Medina Cordova; Jairo Cueto; Thorsten Dittmar; Bert Engelen; et al. (Frontiers in Marine Science, 2023)
Subterranean estuaries are connective zones between inland aquifers and the open sea where terrestrial freshwater and circulating seawater mix and undergo major biogeochemical changes. They are biogeochemical reactors that modify groundwater chemistry prior to discharge into the sea. We propose that subterranean estuaries of high-energy beaches are particularly dynamic environments, where the effect of the dynamic boundary conditions propagates tens of meters into the subsurface, leading to strong spatio-temporal variability of geochemical conditions. We hypothesize that they form a unique habitat with an adapted microbial community unlike other typically more stable subsurface environments. So far, however, studies concerning subterranean estuaries of high-energy beaches have been rare and therefore their functioning, and their importance for coastal ecosystems, as well as for carbon, nutrient and trace element cycling, is little understood. We are addressing this knowledge gap within the interdisciplinary research project DynaDeep by studying the combined effect of surface (hydro- and morphodynamics) on subsurface processes (groundwater flow and transport, biogeochemical reactions, microbiology). A unique subterranean estuary observatory was established on the northern beach of the island of Spiekeroog facing the North Sea, serving as an exemplary high-energy research site and model system. It consists of fixed and permanent infrastructure such as a pole with measuring devices, multi-level groundwater wells and an electrode chain. This forms the base for autonomous measurements, regular repeated sampling, interdisciplinary field campaigns and experimental work, all of which are integrated via mathematical modelling to understand and quantify the functioning of the biogeochemical reactor. First results show that the DynaDeep observatory is collecting the intended spatially and temporally resolved morphological, sedimentological and biogeochemical data. Samples and data are further processed ex-situ and combined with experiments and modelling. Ultimately, DynaDeep aims at elucidating the global relevance of these common but overlooked environments.

Comparison of machine learning algorithms to predict dissolved oxygen in an urban stream - Madeleine M. Bolick; Christopher J. Post; Mohannad-Zeyad Naser; Elena A. Mikhailova (Environmental Science and Pollution Research, 2023)

Assessing tree height and density of a young forest using a consumer unmanned aerial vehicle (UAV) - Zhenbang Hao; Lili Lin; Christopher J. Post; Yusen Jiang; Minghui Li; Nibin Wei; Kunyong Yu; Jian Liu (New Forests, 2021)

Alternative Biogeochemical States of River Pools Mediated by Hippo Use and Flow Variability - Christopher L. Dutton; Amanda L. Subalusky; Stephen K. Hamilton; Ella C. Bayer; Laban Njoroge; Emma J. Rosi; David M. Post (Ecosystems, 2021)

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics - Clarissa Alves da Rosa; Bruno R. Ribeiro; Vanesa Bejarano; Fernando Henrique Puertas; Adriana Bocchiglieri; Adriana Loeser dos Santos Barbosa; Adriano Garcia Chiarello; Adriano Pereira Paglia; Adriele Aparecida Pereira; Adryelle Francisca de Souza Moreira; Agnis Cristiane de Souza; Aiesca Pellegrin; et al. (Ecology, 2020)
Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal‐central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus , Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. ( n = 37,782), Sus scrofa ( n = 6,730), and Canis familiaris ( n = 10,084); 17 species were represented by only one record (e.g., S yncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans ). Primates have the highest number of species in the data set ( n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata , and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation‐related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data.

Developing a USLE cover and management factor (C) for forested regions of southern China - Conghui Li; Lili Lin; Zhenbang Hao; Christopher J. Post; Zhanghao Chen; Jian Liu; Kunyong Yu (Frontiers of Earth Science, 2020)

Modeling and monitoring riparian buffer zones using LiDAR data in South Carolina - Emre Akturk; Christopher Post; Elena A. Mikhailova (Environmental Monitoring and Assessment, 2020)

Mapping Urbanization Trends in a Forested Landscape Using Google Earth Engine - Hamdi A. Zurqani; Christopher J. Post; Elena A. Mikhailova; Jeffrey S. Allen (Remote Sensing in Earth Systems Sciences, 2019)

Twenty-three unsolved problems in hydrology (UPH) – a community perspective - Günter Blöschl; Marc F.P. Bierkens; Antonio Chambel; Christophe Cudennec; Georgia Destouni; Aldo Fiori; James W. Kirchner; Jeffrey J. McDonnell; Hubert H.G. Savenije; Murugesu Sivapalan; Christine Stumpp; Elena Toth; et al. (Hydrological Sciences Journal, 2019)

Organic matter and nutrient inputs from large wildlife influence ecosystem function in the Mara River, Africa - Amanda L. Subalusky; Christopher L. Dutton; Laban Njoroge; Emma J. Rosi; David M. Post (Ecology, 2018)
Animals can be important vectors for the movement of resources across ecosystem boundaries. Animals add resources to ecosystems primarily through egestion, excretion, and carcasses, and the stoichiometry and bioavailability of these inputs likely interact with characteristics of the recipient ecosystem to determine their effects on ecosystem function. We studied the influence of hippopotamus excretion/egestion and wildebeest carcasses, and their interactions with discharge, in the Mara River, Kenya. We measured nutrient dissolution and decomposition rates of wildlife inputs, the influence of inputs on nutrient concentrations and nutrient limitation in the river and the influence of inputs on biofilm growth and function in both experimental streams and along a gradient of inputs in the river. We found that hippopotamus excretion/egestion increases ammonium and coarse particulate organic matter in the river, and wildebeest carcasses increase ammonium, soluble reactive phosphorus, and total phosphorus. Concentrations of dissolved carbon and nutrients in the water column increased along a gradient of wildlife inputs and during low discharge, although concentrations of particulate carbon decreased during low discharge due to deposition on the river bottom. Autotrophs were nitrogen limited and heterotrophs were carbon limited and nitrogen and phosphorus colimited upstream of animal inputs but there was no nutrient limitation downstream of inputs. In experimental streams, hippo and wildebeest inputs together increased biofilm gross primary production ( GPP) and respiration ( R ). These results differed in the river, where low concentrations of hippo inputs increased gross primary production ( GPP ) and respiration ( R ) of biofilms, but high concentrations of hippo inputs in conjunction with wildebeest inputs decreased GPP . Our research shows that inputs from large wildlife alleviate nutrient limitation and stimulate ecosystem metabolism in the Mara River and that the extent to which these inputs subsidize the ecosystem is mediated by the quantity and quality of inputs and discharge of the river ecosystem. Thus, animal inputs provide an important ecological subsidy to this river, and animal inputs were likely important in many other rivers prior to the widespread extirpation of large wildlife.

Consensus guidelines for the use and interpretation of angiogenesis assays - Patrycja Nowak-Sliwinska; Kari Alitalo; Elizabeth Allen; Andrey Anisimov; Alfred C. Aplin; Robert Auerbach; Hellmut G. Augustin; David O. Bates; Judy R. van Beijnum; R. Hugh F. Bender; Gabriele Bergers; Andreas Bikfalvi; et al. (Angiogenesis, 2018)

BioTIME: A database of biodiversity time series for the Anthropocene - Maria Dornelas; Laura H. Antão; Faye Moyes; Amanda E. Bates; Anne E. Magurran; Dušan Adam; Asem A. Akhmetzhanova; Ward Appeltans; José Manuel Arcos; Haley Arnold; Narayanan Ayyappan; Gal Badihi; et al. (Global Ecology and Biogeography, 2018)
Motivation The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km 2 (158 cm 2 ) to 100 km 2 (1,000,000,000,000 cm 2 ). Time period and grain BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Software format .csv and .SQL.

Monitoring spatial and temporal variation of dissolved oxygen and water temperature in the Savannah River using a sensor network - Christopher J. Post; Michael P. Cope; Patrick D. Gerard; Nicholas M. Masto; Joshua R. Vine; Roxanne Y. Stiglitz; Jason O. Hallstrom; Jillian C. Newman; Elena A. Mikhailova (Environmental Monitoring and Assessment, 2018)

Executive summary of the 12th HHT international scientific conference - Jillian W. Andrejecsk; Anna E. Hosman; Luisa M. Botella; Claire L. Shovlin; Helen M. Arthur; Sophie Dupuis-Girod; Elisabetta Buscarini; Christopher C. W. Hughes; Franck Lebrin; Christine L. Mummery; Marco C. Post; Johannes J. Mager (Angiogenesis, 2018)

A global database of nitrogen and phosphorus excretion rates of aquatic animals - Michael J. Vanni; Peter B. McIntyre; Dennis Allen; Diane L. Arnott; Jonathan P. Benstead; David J. Berg; Åge Brabrand; Sébastien Brosse; Paul A. Bukaveckas; Adriano Caliman; Krista A. Capps; Luciana S. Carneiro; et al. (Ecology, 2017)
Animals can be important in modulating ecosystem‐level nutrient cycling, although their importance varies greatly among species and ecosystems. Nutrient cycling rates of individual animals represent valuable data for testing the predictions of important frameworks such as the Metabolic Theory of Ecology ( MTE ) and ecological stoichiometry ( ES ). They also represent an important set of functional traits that may reflect both environmental and phylogenetic influences. Over the past two decades, studies of animal‐mediated nutrient cycling have increased dramatically, especially in aquatic ecosystems. Here we present a global compilation of aquatic animal nutrient excretion rates. The dataset includes 10,534 observations from freshwater and marine animals of N and/or P excretion rates. These observations represent 491 species, including most aquatic phyla. Coverage varies greatly among phyla and other taxonomic levels. The dataset includes information on animal body size, ambient temperature, taxonomic affiliations, and animal body N:P. This data set was used to test predictions of MTE and ES , as described in Vanni and McIntyre (2016; Ecology DOI : 10.1002/ecy.1582 ).

Spatio-temporal analysis of flowering using LiDAR topography - Samantha Hart; Elena Mikhailova; Christopher Post; Patrick McMillan; Julia Sharp; William Bridges (Journal of Geographical Sciences, 2017)

A cloud-based spatial-temporal inventory for sustainable urban soil management - Latoisha Y. Green; Elena A. Mikhailova; Christopher J. Post; Christophe C. J. G. Darnault; William C. Bridges; Mark A. Schlautman (Urban Ecosystems, 2016)

Analysis of factors contributing to abandoned residential developments using remote sensing and geographic information systems (GIS) - Christopher Post; Brian Ritter; Emre Akturk; Amy Breedlove; Russell Buchanan; Celestine Che; Jacob Fravel; Lynn Hammett; Thomas Kirby; Elena Mikhailova; Xin Qiao; James Short; et al. (Urban Ecosystems, 2015)

Performance of an empirical bias‐correction of a high‐resolution climate dataset - James C. Bennett; Michael R. Grose; Stuart P. Corney; Christopher J. White; Gregory K. Holz; Jack J. Katzfey; David A. Post; Nathaniel L. Bindoff (International Journal of Climatology, 2014)
We describe the method and performance of a bias‐correction applied to high‐resolution (˜10 km) simulations from a stretched‐grid Regional Climate Model ( RCM ) over Tasmania, Australia. The bias‐correction is a quantile mapping of empirical cumulative frequency distributions. Corrections are applied at a daily time step to five variables: rainfall, potential evaporation (PE), solar radiation, maximum temperature and minimum temperature. Corrections are calculated independently for each season. We show that quantile mapping of empirical distributions can be highly effective in correcting biases in RCM outputs. Cross‐validation shows biases are effectively reduced across the range of cumulative frequency distributions, with few exceptions. The bias‐correction is not as effective at correcting biases for values at or near zero (e.g. in rainfall simulations), although even here the bias‐correction improves biases evident in the uncorrected simulations. In addition, the bias‐correction improves frequency characteristics of variables such as the number of rain days. We use a detrending technique to apply the bias‐correction to 140‐year time series of RCM variables. We show that the bias‐correction effectively preserves long‐term changes (e.g. to the mean and variance) to variables projected by the uncorrected RCM simulations. Correlations between key variables are also largely preserved, thus the bias‐corrected outputs reflect the dynamics of the underlying RCM . However, the bias‐corrected simulations still exhibit some of the deficiencies of the RCM simulations, e.g. the tendency to underestimate the magnitude and duration of large, multi‐day rain events, and the tendency to underestimate the duration of dry spells. The bias‐corrected simulations for six downscaled GCMs for the A2 and B1 emissions scenarios are available to researchers from http://www.tpac.org.au .

An Integrated WebGIS Framework for Volunteered Geographic Information and Social Media in Soil and Water Conservation - Joshua D. Werts; Elena A. Mikhailova; Christopher J. Post; Julia L. Sharp (Environmental Management, 2012)

Relationship between urbanization and bat community structure in national parks of the southeastern U.S. - Susan C. Loeb; Christopher J. Post; Steven T. Hall (Urban Ecosystems, 2009)

Historical land use and soil analysis guiding corridor landscape design - J. Renee Keydoszius; S. Knight Cox; Mary B. Haque; Elena Mikhailova; Christopher J. Post; William C. Stringer; Mark A. Schlautman (Urban Ecosystems, 2007)

Predator disease out‐break modulates top‐down, bottom‐up and climatic effects on herbivore population dynamics - Christopher C. Wilmers; Eric Post; Rolf O. Peterson; John A. Vucetich (Ecology Letters, 2006)
Human‐introduced disease and climatic change are increasingly perturbing natural ecosystems worldwide, but scientists know very little about how they interact to affect ecological dynamics. An outbreak of canine parvovirus (CPV) in the wolf population on Isle Royale allowed us to test the transient effects of an introduced pathogen and global climatic variation on the dynamics of a three‐level food chain. Following the introduction of CPV, wolf numbers plummeted, precipitating a switch from top‐down to bottom‐up regulation of the moose population; consequently, the influence of climate on moose population growth rate doubled. This demonstrates that synergistic interactions between pathogens and climate can lead to shifts in trophic control, and suggests that predators in this system may play an important role in dampening the effects of climate change on the dynamics of their prey.

Predicting the influence of wolf‐provided carrion on scavenger community dynamics under climate change scenarios - CHRISTOPHER C. WILMERS; ERIC POST (Global Change Biology, 2006)
Climate change poses an immediate threat to the persistence and distribution of many species, yet our ability to forecast changes in species composition is hindered by poor understanding of the extent to which higher trophic‐level interactions may buffer or exacerbate the adverse effects of warming. We incorporated species‐specific consumption data from 240 wolf‐killed elk carcasses from Yellowstone National Park into stochastic simulation models to link trends in the El Niño Southern Oscillation (ENSO) to food procurement by a guild of scavengers as a function of gray wolf reintroduction. We find that a shift in ENSO towards the El Niño (warming) phase of the cycle coincident with increasing global temperatures reduces carrion for scavengers, particularly those with strong seasonal patterns in resource use such as grizzly bears. Wolves alleviate these warming‐induced food shortages by rendering control over this crucial resource to biotic rather than abiotic factors. Ecosystems with intact top predators are likely to exhibit stronger biotic regulation and should be more resistant to climate change than ecosystems lacking them.

Fine mapping a gene for pediatric gastroesophageal reflux on human chromosome 13q14 - Fen Ze Hu; Joseph Donfack; Azad Ahmed; Richard Dopico; Sandra Johnson; J. Christopher Post; Garth D. Ehrlich; Robert A. Preston (Human Genetics, 2004)