1
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Dumandan PKT, Yenni GM, Ernest SKM. Shifts in competitive structures can drive variation in species' phenology. Ecology 2023; 104:e4160. [PMID: 37671433 DOI: 10.1002/ecy.4160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 07/07/2023] [Accepted: 07/29/2023] [Indexed: 09/07/2023]
Abstract
For many species, a well documented response to anthropogenic climate change is a shift in various aspects of its life history, including its timing or phenology. Often, these phenological shifts are associated with changes in abiotic factors used as proxies for resource availability or other suitable conditions. Resource availability, however, can also be impacted by competition, but the impact of competition on phenology is less studied than abiotic drivers. We fit generalized additive models (GAMs) to a long-term experimental dataset on small mammals monitored in the southwestern United States and show that altered competitive landscapes can drive shifts in breeding timing and prevalence, and that, relative to a dominant competitor, other species exhibit less specific responses to environmental factors. These results suggest that plasticity of phenological responses, which is often described in the context of annual variation in abiotic factors, can occur in response to biotic context as well. Variation in phenological responses under different biotic conditions shown here further demonstrates that a more nuanced understanding of shifting biotic interactions is useful to better understand and predict biodiversity patterns in a changing world.
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Affiliation(s)
| | - Glenda M Yenni
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, USA
| | - S K Morgan Ernest
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, USA
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2
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Weinstein BG, Garner L, Saccomanno VR, Steinkraus A, Ortega A, Brush K, Yenni G, McKellar AE, Converse R, Lippitt CD, Wegmann A, Holmes ND, Edney AJ, Hart T, Jessopp MJ, Clarke RH, Marchowski D, Senyondo H, Dotson R, White EP, Frederick P, Ernest SKM. A general deep learning model for bird detection in high-resolution airborne imagery. Ecol Appl 2022; 32:e2694. [PMID: 35708073 DOI: 10.1002/eap.2694] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 02/09/2022] [Accepted: 03/22/2022] [Indexed: 06/15/2023]
Abstract
Advances in artificial intelligence for computer vision hold great promise for increasing the scales at which ecological systems can be studied. The distribution and behavior of individuals is central to ecology, and computer vision using deep neural networks can learn to detect individual objects in imagery. However, developing supervised models for ecological monitoring is challenging because it requires large amounts of human-labeled training data, requires advanced technical expertise and computational infrastructure, and is prone to overfitting. This limits application across space and time. One solution is developing generalized models that can be applied across species and ecosystems. Using over 250,000 annotations from 13 projects from around the world, we develop a general bird detection model that achieves over 65% recall and 50% precision on novel aerial data without any local training despite differences in species, habitat, and imaging methodology. Fine-tuning this model with only 1000 local annotations increases these values to an average of 84% recall and 69% precision by building on the general features learned from other data sources. Retraining from the general model improves local predictions even when moderately large annotation sets are available and makes model training faster and more stable. Our results demonstrate that general models for detecting broad classes of organisms using airborne imagery are achievable. These models can reduce the effort, expertise, and computational resources necessary for automating the detection of individual organisms across large scales, helping to transform the scale of data collection in ecology and the questions that can be addressed.
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Affiliation(s)
- Ben G Weinstein
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, USA
| | - Lindsey Garner
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, USA
| | - Vienna R Saccomanno
- California Oceans Program, The Nature Conservancy, Sacramento, California, USA
| | - Ashley Steinkraus
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, USA
| | - Andrew Ortega
- Geomatics Program, University of Florida, Gainesville, Florida, USA
| | | | - Glenda Yenni
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, USA
| | - Ann E McKellar
- Environment and Climate Change Canada, Saskatoon, Saskatchewan, Canada
| | - Rowan Converse
- Center for the Advancement of Spatial Informatics Research and Education, University of New Mexico, Albuquerque, New Mexico, USA
| | - Christopher D Lippitt
- Center for the Advancement of Spatial Informatics Research and Education, University of New Mexico, Albuquerque, New Mexico, USA
| | - Alex Wegmann
- California Oceans Program, The Nature Conservancy, Sacramento, California, USA
| | - Nick D Holmes
- California Oceans Program, The Nature Conservancy, Sacramento, California, USA
| | - Alice J Edney
- Department of Zoology, University of Oxford, Oxford, UK
| | - Tom Hart
- Department of Zoology, University of Oxford, Oxford, UK
| | - Mark J Jessopp
- School of Biological, Earth and Environmental Sciences, University College Cork, Cork, Ireland
| | - Rohan H Clarke
- School of Biological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Dominik Marchowski
- Ornithological Station, Museum and Institute of Zoology, Polish Academy of Sciences, Gdańsk, Poland
| | - Henry Senyondo
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, USA
| | | | - Ethan P White
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, USA
| | - Peter Frederick
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, USA
| | - S K Morgan Ernest
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, USA
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3
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Diaz RM, Ernest SKM. Maintenance of community function through compensation breaks down over time in a desert rodent community. Ecology 2022; 103:e3709. [PMID: 35362169 PMCID: PMC9287087 DOI: 10.1002/ecy.3709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 01/27/2022] [Accepted: 02/08/2022] [Indexed: 11/08/2022]
Abstract
Understanding the ecological processes that maintain community function in systems experiencing species loss, and how these processes change over time, is key to understanding the relationship between community structure and function and predicting how communities may respond to perturbations in the Anthropocene. Using a 30‐year experiment on desert rodents, we show that the impact of species loss on community‐level energy use has changed repeatedly and dramatically over time, due to (1) the addition of new species to the community, and (2) a reduction in functional redundancy among the same set of species. Although strong compensation, initially driven by the dispersal of functionally redundant species to the local community, occurred in this system from 1997 to 2010, since 2010, compensation has broken down due to decreasing functional overlap within the same set of species. Simultaneously, long‐term changes in sitewide community composition due to niche complementarity have decoupled the dynamics of compensation from the overall impact of species loss on community‐level energy use. Shifting, context‐dependent compensatory dynamics, such as those demonstrated here, highlight the importance of explicitly long‐term, metacommunity, and eco‐evolutionary perspectives on the link between species‐level fluctuations and community function in a changing world.
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Affiliation(s)
- Renata M Diaz
- School of Natural Resources and Environment, University of Florida, Gainesville, FL
| | - S K Morgan Ernest
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL
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4
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Cárdenas PA, Christensen E, Ernest SKM, Lightfoot DC, Schooley RL, Stapp P, Rudgers JA. Declines in rodent abundance and diversity track regional climate variability in North American drylands. Glob Chang Biol 2021; 27:4005-4023. [PMID: 33942467 DOI: 10.1111/gcb.15672] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 04/09/2021] [Indexed: 06/12/2023]
Abstract
Regional long-term monitoring can enhance the detection of biodiversity declines associated with climate change, improving future projections by reducing reliance on space-for-time substitution and increasing scalability. Rodents are diverse and important consumers in drylands, regions defined by the scarcity of water that cover 45% of Earth's land surface and face increasingly drier and more variable climates. We analyzed abundance data for 22 rodent species across grassland, shrubland, ecotone, and woodland ecosystems in the southwestern USA. Two time series (1995-2006 and 2004-2013) coincided with phases of the Pacific Decadal Oscillation (PDO), which influences drought in southwestern North America. Regionally, rodent species diversity declined 20%-35%, with greater losses during the later time period. Abundance also declined regionally, but only during 2004-2013, with losses of 5% of animals captured. During the first time series (wetter climate), plant productivity outranked climate variables as the best regional predictor of rodent abundance for 70% of taxa, whereas during the second period (drier climate), climate best explained variation in abundance for 60% of taxa. Temporal dynamics in diversity and abundance differed spatially among ecosystems, with the largest declines in woodlands and shrublands of central New Mexico and Colorado. Which species were winners or losers under increasing drought and amplified interannual variability in drought depended on ecosystem type and the phase of the PDO. Fewer taxa were significant winners (18%) than losers (30%) under drought, but the identities of winners and losers differed among ecosystems for 70% of taxa. Our results suggest that the sensitivities of rodent species to climate contributed to regional declines in diversity and abundance during 1995-2013. Whether these changes portend future declines in drought-sensitive consumers in the southwestern USA will depend on the climate during the next major PDO cycle.
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Affiliation(s)
- Pablo A Cárdenas
- Department of Biology, University of New Mexico, Albuquerque, NM, USA
| | - Erica Christensen
- Jornada Experimental Range, New Mexico State University, Las Cruces, NM, USA
| | - S K Morgan Ernest
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL, USA
| | - David C Lightfoot
- Museum of Southwestern Biology, University of New Mexico, Albuquerque, NM, USA
| | - Robert L Schooley
- Department of Natural Resources and Environmental Sciences, University of Illinois, Urbana, IL, USA
| | - Paul Stapp
- Department of Biological Science, California State University, Fullerton, CA, USA
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5
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Diaz RM, Ye H, Ernest SKM. Empirical abundance distributions are more uneven than expected given their statistical baseline. Ecol Lett 2021; 24:2025-2039. [PMID: 34142760 DOI: 10.1111/ele.13820] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 02/12/2021] [Accepted: 04/30/2021] [Indexed: 11/30/2022]
Abstract
Exploring and accounting for the emergent properties of ecosystems as complex systems is a promising horizon in the search for general processes to explain common ecological patterns. For example the ubiquitous hollow-curve form of the species abundance distribution is frequently assumed to reflect ecological processes structuring communities, but can also emerge as a statistical phenomenon from the mathematical definition of an abundance distribution. Although the hollow curve may be a statistical artefact, ecological processes may induce subtle deviations between empirical species abundance distributions and their statistically most probable forms. These deviations may reflect biological processes operating on top of mathematical constraints and provide new avenues for advancing ecological theory. Examining ~22,000 communities, we found that empirical SADs are highly uneven and dominated by rare species compared to their statistical baselines. Efforts to detect deviations may be less informative in small communities-those with few species or individuals-because these communities have poorly resolved statistical baselines. The uneven nature of many empirical SADs demonstrates a path forward for leveraging complexity to understand ecological processes governing the distribution of abundance, while the issues posed by small communities illustrate the limitations of using this approach to study ecological patterns in small samples.
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Affiliation(s)
- Renata M Diaz
- School of Natural Resources and Environment, University of Florida, Gainesville, FL, USA
| | - Hao Ye
- Health Science Center Libraries, University of Florida, Gainesville, FL, USA
| | - S K Morgan Ernest
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL, USA
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6
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Abstract
Probabilistic near-term forecasting facilitates evaluation of model predictions against observations and is of pressing need in ecology to inform environmental decision-making and effect societal change. Despite this imperative, many ecologists are unfamiliar with the widely used tools for evaluating probabilistic forecasts developed in other fields. We address this gap by reviewing the literature on probabilistic forecast evaluation from diverse fields including climatology, economics, and epidemiology. We present established practices for selecting evaluation data (end-sample hold out), graphical forecast evaluation (times-series plots with uncertainty, probability integral transform plots), quantitative evaluation using scoring rules (log, quadratic, spherical, and ranked probability scores), and comparing scores across models (skill score, Diebold-Mariano test). We cover common approaches, highlight mathematical concepts to follow, and note decision points to allow application of general principles to specific forecasting endeavors. We illustrate these approaches with an application to a long-term rodent population time series currently used for ecological forecasting and discuss how ecology can continue to learn from and drive the cross-disciplinary field of forecasting science.
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Affiliation(s)
- Juniper L Simonis
- Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, 32611, USA.,DAPPER Stats, 3519 NE 15th Avenue, Suite 467, Portland, Oregon, 97212, USA
| | - Ethan P White
- Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, 32611, USA
| | - S K Morgan Ernest
- Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, 32611, USA
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7
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van Klink R, Bowler DE, Comay O, Driessen MM, Ernest SKM, Gentile A, Gilbert F, Gongalsky KB, Owen J, Pe'er G, Pe'er I, Resh VH, Rochlin I, Schuch S, Swengel AB, Swengel SR, Valone TJ, Vermeulen R, Wepprich T, Wiedmann JL, Chase JM. InsectChange: a global database of temporal changes in insect and arachnid assemblages. Ecology 2021; 102:e03354. [PMID: 33797755 DOI: 10.1002/ecy.3354] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 10/29/2020] [Accepted: 11/24/2020] [Indexed: 11/07/2022]
Abstract
Insects are the most ubiquitous and diverse group of eukaryotic organisms on Earth, forming a crucial link in terrestrial and freshwater food webs. They have recently become the subject of headlines because of observations of dramatic declines in some places. Although there are hundreds of long-term insect monitoring programs, a global database for long-term data on insect assemblages has so far remained unavailable. In order to facilitate synthetic analyses of insect abundance changes, we compiled a database of long-term (≥10 yr) studies of assemblages of insects (many also including arachnids) in the terrestrial and freshwater realms. We searched the scientific literature and public repositories for data on insect and arachnid monitoring using standardized protocols over a time span of 10 yr or longer, with at least two sampling events. We focused on studies that presented or allowed calculation of total community abundance or biomass. We extracted data from tables, figures, and appendices, and, for data sets that provided raw data, we standardized trapping effort over space and time when necessary. For each site, we extracted provenance details (such as country, state, and continent) as well as information on protection status, land use, and climatic details from publicly available GIS sources. In all, the database contains 1,668 plot-level time series sourced from 165 studies with samples collected between 1925 and 2018. Sixteen data sets provided here were previously unpublished. Studies were separated into those collected in the terrestrial realm (103 studies with a total of 1,053 plots) and those collected in the freshwater realm (62 studies with 615 plots). Most studies were from Europe (48%) and North America (29%), with 34% of the plots located in protected areas. The median monitoring time span was 19 yr, with 12 sampling years. The number of individuals was reported in 129 studies, the total biomass was reported in 13 studies, and both abundance and biomass were reported in 23 studies. This data set is published under a CC-BY license, requiring attribution of the data source. Please cite this paper if the data are used in publications, and respect the licenses of the original sources when using (part of) their data as detailed in Metadata S1: Table 1.
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Affiliation(s)
- Roel van Klink
- German Centre for Integrated Biodiversity Research Halle-Jena-Leipzig (iDiv), Puschstrasse 4, Leipzig, 04103, Germany.,Department of Computer Science, Martin Luther University-Halle Wittenberg, Von-Seckendorff-Platz 1, Halle (Saale), 06120, Germany.,WBBS Foundation, Kanaaldijk 36, Loon, 9409TV, The Netherlands
| | - Diana E Bowler
- German Centre for Integrated Biodiversity Research Halle-Jena-Leipzig (iDiv), Puschstrasse 4, Leipzig, 04103, Germany.,Institute of Biodiversity, Friedrich Schiller University Jena, Dornburger Strasse 159, Jena, 07743, Germany.,Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15, Leipzig, 04318, Germany
| | - Orr Comay
- German Centre for Integrated Biodiversity Research Halle-Jena-Leipzig (iDiv), Puschstrasse 4, Leipzig, 04103, Germany.,Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15, Leipzig, 04318, Germany.,School of Zoology and The Steinhardt Museum of Natural History, Tel Aviv University, Haim Lebanon, Tel Aviv, 6997801, Israel
| | - Michael M Driessen
- School of Technology, Environments and Design, University of Tasmania, Private Bag 78, Hobart, Tasmania, 7001, Australia.,Department of Primary Industries, Parks, Water and Environment, Natural Values Science Section, Tasmanian Government, P.O. Box 44, Hobart, Tasmania, 7001, Australia
| | - S K Morgan Ernest
- Department of Wildlife Ecology and Conservation, University of Florida, 110 Newins-Ziegler Hall, Gainesville, Florida, 32611, USA
| | - Alessandro Gentile
- German Centre for Integrated Biodiversity Research Halle-Jena-Leipzig (iDiv), Puschstrasse 4, Leipzig, 04103, Germany
| | - Francis Gilbert
- School of Life Sciences, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Konstantin B Gongalsky
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Leninsky pr. 33, Moscow, 119071, Russia.,M.V. Lomonosov Moscow State University, Leninskie Gory 1, Moscow, 119991, Russia
| | | | - Guy Pe'er
- German Centre for Integrated Biodiversity Research Halle-Jena-Leipzig (iDiv), Puschstrasse 4, Leipzig, 04103, Germany.,Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15, Leipzig, 04318, Germany
| | - Israel Pe'er
- GlueCAD Biodiversity IT, Hantke 39, Haifa, 3460814, Israel
| | - Vincent H Resh
- Department of Environmental Science, Policy & Management, University of California, Berkeley, Berkeley, California, 95720-3114, USA
| | - Ilia Rochlin
- Center for Vector Biology, Rutgers University, 180 Jones Avenue, New Brunswick, New Jersey, 8901, USA
| | - Sebastian Schuch
- Department of Botany, Senckenberg Museum für Naturkunde, Postfach 300154, Görlitz, 02806, Germany
| | | | | | - Thomas J Valone
- Department of Biology, Saint Louis University, 3507 Laclede Avenue, St. Louis, Missouri, 63103, USA
| | | | - Tyson Wepprich
- Department of Botany and Plant Pathology, Oregon State University, 2082 Cordley Hall, Corvallis, Oregon, 97331, USA
| | | | - Jonathan M Chase
- German Centre for Integrated Biodiversity Research Halle-Jena-Leipzig (iDiv), Puschstrasse 4, Leipzig, 04103, Germany.,Department of Computer Science, Martin Luther University-Halle Wittenberg, Von-Seckendorff-Platz 1, Halle (Saale), 06120, Germany
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Abstract
Life-history traits represent organisms' strategies to navigate the fitness trade-offs between survival and reproduction. Eric Charnov developed three dimensionless metrics to quantify fundamental life-history trade-offs. Lifetime reproductive effort (LRE), relative reproductive lifespan (RRL) and relative offspring size (ROS), together with body mass can be used to classify life-history strategies across the four major classes of tetrapods: amphibians, reptiles, mammals and birds. First, we investigate how the metrics have evolved in concert with body mass within tetrapod lineages. In most cases, we find evidence for correlated evolution among body mass and the three dimensionless metrics. Second, we compare life-history strategies across the four classes of tetrapods and find that LRE, RRL and ROS delineate a space in which the major tetrapod classes occupy mostly unique subspaces. These distinct combinations of life-history strategies provide us with a framework to understand the impact of major evolutionary transitions in energetics, physiology and ecology.
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Affiliation(s)
- Cecina Babich Morrow
- Spring Health, New York, NY, USA
- Center for Biodiversity and Conservation, American Museum of Natural History, New York, NY, USA
- Department of Biology, Kenyon College, Gambier, OH, USA
| | - S. K. Morgan Ernest
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL, USA
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9
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Christensen EM, Simpson GL, Ernest SKM. Established rodent community delays recovery of dominant competitor following experimental disturbance. Proc Biol Sci 2019; 286:20192269. [PMID: 31822258 PMCID: PMC6939914 DOI: 10.1098/rspb.2019.2269] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Accepted: 11/13/2019] [Indexed: 12/04/2022] Open
Abstract
Human activities alter processes that control local biodiversity, causing changes in the abundance and identity of species in ecosystems. However, restoring biodiversity to a previous state is rarely as simple as reintroducing lost species or restoring processes to their pre-disturbance state. Theory suggests that established species can impede shifts in species composition via a variety of mechanisms, including direct interference, pre-empting resources or habitat alteration. These mechanisms can create transitory dynamics that delay convergence to an expected end state. We use an experimental manipulation of a desert rodent community to examine differences in recolonization dynamics of a dominant competitor (kangaroo rats of the genus Dipodomys) when patches were already occupied by an existing rodent community relative to when patches were empty. Recovery of kangaroo rat populations was slow on plots with an established community, taking approximately 2 years, in contrast with rapid recovery on empty plots with no established residents (approx. three months). These results demonstrate that the presence of an established alternate community inhibits recolonization by new species, even those that should be dominant in the community. This has important implications for understanding how biodiversity may change in the future, and what processes may slow or prevent this change.
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Affiliation(s)
- Erica M. Christensen
- Department of Wildlife Ecology and Conservation, University of Florida, 110 Newins-Ziegler Hall, Gainesville, FL 32611, USA
- New Mexico State University, Jornada Experimental Range, Wooton Hall, 2995 Knox Street, Las Cruces, NM 88003, USA
| | - Gavin L. Simpson
- Institute of Environmental Change and Society, University of Regina, 3737 Wascana Parkway, Regina, Saskatchewan, CanadaS4S 0A2
- Department of Biology, University of Regina, 3737 Wascana Parkway, Regina, Saskatchewan, CanadaS4S 0A2
| | - S. K. Morgan Ernest
- Department of Wildlife Ecology and Conservation, University of Florida, 110 Newins-Ziegler Hall, Gainesville, FL 32611, USA
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10
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Bledsoe EK, Ernest SKM. Temporal changes in species composition affect a ubiquitous species' use of habitat patches. Ecology 2019; 100:e02869. [PMID: 31454069 PMCID: PMC6899716 DOI: 10.1002/ecy.2869] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 07/30/2019] [Accepted: 08/02/2019] [Indexed: 11/11/2022]
Abstract
Across landscapes, shifts in species composition often co-occur with shifts in structural or abiotic habitat features, making it difficult to disentangle the role of competitors and environment on assessments of patch quality. Using over two decades of rodent community data from a long-term experiment, we show that a small, ubiquitous granivore (Chaetodipus penicillatus) shifted its use of different experimental treatments with the establishment of a novel competitor, C. baileyi. Shifts in residency, probability of movement between patches, and the arrival of new individuals in patches altered which treatment supported the highest abundances of C. penicillatus. Our results suggest that the establishment of a new species worsened the quality of the originally preferred treatment, likely by impacting resource availability. Paradoxically, the presence of the new species also increased C. penicillatus' use of the less preferred treatment, potentially through shifts in the competitive network on those plots.
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Affiliation(s)
- Ellen K. Bledsoe
- School of Natural Resources and EnvironmentUniversity of Florida103 Black HallGainesvilleFlorida32611USA
| | - S. K. Morgan Ernest
- Department of Wildlife Ecology and ConservationUniversity of Florida110 Newins‐Ziegler HallGainesvilleFlorida32611USA
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11
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Affiliation(s)
- S Kathleen Lyons
- University of Nebraska–Lincoln, School of Biological Sciences, St. Lincoln, NE
| | - Felisa A Smith
- University of New Mexico, Department of Biology, Albuquerque, NM
| | - S K Morgan Ernest
- University of Florida, Department of Wildlife Ecology and Conservation, Gainesville, FL
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12
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Abstract
Over the past decade, biology has undergone a data revolution in how researchers collect data and the amount of data being collected. An emerging challenge that has received limited attention in biology is managing, working with, and providing access to data under continual active collection. Regularly updated data present unique challenges in quality assurance and control, data publication, archiving, and reproducibility. We developed a workflow for a long-term ecological study that addresses many of the challenges associated with managing this type of data. We do this by leveraging existing tools to 1) perform quality assurance and control; 2) import, restructure, version, and archive data; 3) rapidly publish new data in ways that ensure appropriate credit to all contributors; and 4) automate most steps in the data pipeline to reduce the time and effort required by researchers. The workflow leverages tools from software development, including version control and continuous integration, to create a modern data management system that automates the pipeline.
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Affiliation(s)
- Glenda M. Yenni
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, United States of America
| | - Erica M. Christensen
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, United States of America
| | - Ellen K. Bledsoe
- School of Natural Resources and the Environment, University of Florida, Gainesville, Florida, United States of America
| | - Sarah R. Supp
- Data Analytics Program, Denison University, Granville, Ohio, United States of America
| | - Renata M. Diaz
- School of Natural Resources and the Environment, University of Florida, Gainesville, Florida, United States of America
| | - Ethan P. White
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, United States of America
- Informatics Institute, University of Florida, Gainesville, Florida, United States of America
| | - S. K. Morgan Ernest
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, United States of America
- Biodiversity Institute, University of Florida, Gainesville, Florida, United States of America
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13
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White EP, Yenni GM, Taylor SD, Christensen EM, Bledsoe EK, Simonis JL, Ernest SKM. Developing an automated iterative near‐term forecasting system for an ecological study. Methods Ecol Evol 2018. [DOI: 10.1111/2041-210x.13104] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Affiliation(s)
- Ethan P. White
- Department of Wildlife Ecology and Conservation University of Florida Gainesville Florida
- Informatics Institute University of Florida Gainesville Florida
- Biodiversity Institute University of Florida Gainesville Florida
| | - Glenda M. Yenni
- Department of Wildlife Ecology and Conservation University of Florida Gainesville Florida
| | - Shawn D. Taylor
- School of Natural Resources and Environment University of Florida Gainesville Florida
| | - Erica M. Christensen
- Department of Wildlife Ecology and Conservation University of Florida Gainesville Florida
| | - Ellen K. Bledsoe
- School of Natural Resources and Environment University of Florida Gainesville Florida
| | - Juniper L. Simonis
- Department of Wildlife Ecology and Conservation University of Florida Gainesville Florida
| | - S. K. Morgan Ernest
- Department of Wildlife Ecology and Conservation University of Florida Gainesville Florida
- Biodiversity Institute University of Florida Gainesville Florida
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14
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Morgan Ernest SK, Yenni GM, Allington G, Christensen EM, Geluso K, Goheen JR, Schutzenhofer MR, Supp SR, Thibault KM, Brown JH, Valone TJ. Long-term monitoring and experimental manipulation of a Chihuahuan desert ecosystem near Portal, Arizona (1977-2013). Ecology 2018; 97:1082. [PMID: 28792597 DOI: 10.1890/15-2115.1] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2015] [Accepted: 12/15/2015] [Indexed: 11/18/2022]
Abstract
Desert ecosystems have long served as model systems in the study of ecological concepts (e.g., competition, resource pulses, top-down/bottom-up dynamics). However, the inherent variability of resource availability in deserts, and hence consumer dynamics, can also make them challenging ecosystems to understand. Study of a Chihuahuan desert ecosystem near Portal, Arizona began in 1977. At this site, 24 experimental plots were established and divided among controls and experimental manipulations. Experimental manipulations over the years include removal of all or some rodent species, all or some ants, seed additions, and various alterations of the annual plant community. This dataset includes data previously available through an older data publication and adds 11 years of data. It also includes additional ant and weather data not previously available. These data have been used in a variety of publications documenting the effects of the experimental manipulations as well as the response of populations and communities to long-term changes in climate and habitat. Sampling is ongoing and additional data will be published in the future.
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Affiliation(s)
- S K Morgan Ernest
- Department of Biology, UMC 5305, Utah State University, Logan, Utah, 84322, USA.,Department of Wildlife Ecology and Conservation, University of Florida, 110 Newins Ziegler Hall, PO Box 110430, Gainesville, Florida, 32611, USA
| | - Glenda M Yenni
- Department of Biology, UMC 5305, Utah State University, Logan, Utah, 84322, USA.,Department of Wildlife Ecology and Conservation, University of Florida, 110 Newins Ziegler Hall, PO Box 110430, Gainesville, Florida, 32611, USA
| | - Ginger Allington
- School of Natural Resources and Environment, University of Michigan, 440 Church St., Ann Arbor, Michigan, 48109, USA
| | - Erica M Christensen
- Department of Biology, UMC 5305, Utah State University, Logan, Utah, 84322, USA.,Department of Wildlife Ecology and Conservation, University of Florida, 110 Newins Ziegler Hall, PO Box 110430, Gainesville, Florida, 32611, USA
| | - Keith Geluso
- Department of Biology, The University of Nebraska at Kearney, 905 West 25th Street, Kearney, Nebraska, 68849, USA
| | - Jacob R Goheen
- Departments of Zoology & Physiology and Botany, University of Wyoming, 1000 E. University Ave, Laramie, Wyoming, 82071, USA
| | | | - Sarah R Supp
- School of Biology & Ecology, University of Maine, Deering Hall 303, Orono, Maine, 04469, USA
| | | | - James H Brown
- Department of Biology, University of New Mexico, 167 Castetter Hall, MSC03 2020, Albuquerque, New Mexico, 87131, USA
| | - Thomas J Valone
- Department of Biology, St. Louis University, 3507 Laclede Ave., St. Louis, Missouri, 63103, USA
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15
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Dornelas M, Antão LH, Moyes F, Bates AE, Magurran AE, Adam D, Akhmetzhanova AA, Appeltans W, Arcos JM, Arnold H, Ayyappan N, Badihi G, Baird AH, Barbosa M, Barreto TE, Bässler C, Bellgrove A, Belmaker J, Benedetti‐Cecchi L, Bett BJ, Bjorkman AD, Błażewicz M, Blowes SA, Bloch CP, Bonebrake TC, Boyd S, Bradford M, Brooks AJ, Brown JH, Bruelheide H, Budy P, Carvalho F, Castañeda‐Moya E, Chen CA, Chamblee JF, Chase TJ, Siegwart Collier L, Collinge SK, Condit R, Cooper EJ, Cornelissen JHC, Cotano U, Kyle Crow S, Damasceno G, Davies CH, Davis RA, Day FP, Degraer S, Doherty TS, Dunn TE, Durigan G, Duffy JE, Edelist D, Edgar GJ, Elahi R, Elmendorf SC, Enemar A, Ernest SKM, Escribano R, Estiarte M, Evans BS, Fan T, Turini Farah F, Loureiro Fernandes L, Farneda FZ, Fidelis A, Fitt R, Fosaa AM, Daher Correa Franco GA, Frank GE, Fraser WR, García H, Cazzolla Gatti R, Givan O, Gorgone‐Barbosa E, Gould WA, Gries C, Grossman GD, Gutierréz JR, Hale S, Harmon ME, Harte J, Haskins G, Henshaw DL, Hermanutz L, Hidalgo P, Higuchi P, Hoey A, Van Hoey G, Hofgaard A, Holeck K, Hollister RD, Holmes R, Hoogenboom M, Hsieh C, Hubbell SP, Huettmann F, Huffard CL, Hurlbert AH, Macedo Ivanauskas N, Janík D, Jandt U, Jażdżewska A, Johannessen T, Johnstone J, Jones J, Jones FAM, Kang J, Kartawijaya T, Keeley EC, Kelt DA, Kinnear R, Klanderud K, Knutsen H, Koenig CC, Kortz AR, Král K, Kuhnz LA, Kuo C, Kushner DJ, Laguionie‐Marchais C, Lancaster LT, Min Lee C, Lefcheck JS, Lévesque E, Lightfoot D, Lloret F, Lloyd JD, López‐Baucells A, Louzao M, Madin JS, Magnússon B, Malamud S, Matthews I, McFarland KP, McGill B, McKnight D, McLarney WO, Meador J, Meserve PL, Metcalfe DJ, Meyer CFJ, Michelsen A, Milchakova N, Moens T, Moland E, Moore J, Mathias Moreira C, Müller J, Murphy G, Myers‐Smith IH, Myster RW, Naumov A, Neat F, Nelson JA, Paul Nelson M, Newton SF, Norden N, Oliver JC, Olsen EM, Onipchenko VG, Pabis K, Pabst RJ, Paquette A, Pardede S, Paterson DM, Pélissier R, Peñuelas J, Pérez‐Matus A, Pizarro O, Pomati F, Post E, Prins HHT, Priscu JC, Provoost P, Prudic KL, Pulliainen E, Ramesh BR, Mendivil Ramos O, Rassweiler A, Rebelo JE, Reed DC, Reich PB, Remillard SM, Richardson AJ, Richardson JP, van Rijn I, Rocha R, Rivera‐Monroy VH, Rixen C, Robinson KP, Ribeiro Rodrigues R, de Cerqueira Rossa‐Feres D, Rudstam L, Ruhl H, Ruz CS, Sampaio EM, Rybicki N, Rypel A, Sal S, Salgado B, Santos FAM, Savassi‐Coutinho AP, Scanga S, Schmidt J, Schooley R, Setiawan F, Shao K, Shaver GR, Sherman S, Sherry TW, Siciński J, Sievers C, da Silva AC, Rodrigues da Silva F, Silveira FL, Slingsby J, Smart T, Snell SJ, Soudzilovskaia NA, Souza GBG, Maluf Souza F, Castro Souza V, Stallings CD, Stanforth R, Stanley EH, Mauro Sterza J, Stevens M, Stuart‐Smith R, Rondon Suarez Y, Supp S, Yoshio Tamashiro J, Tarigan S, Thiede GP, Thorn S, Tolvanen A, Teresa Zugliani Toniato M, Totland Ø, Twilley RR, Vaitkus G, Valdivia N, Vallejo MI, Valone TJ, Van Colen C, Vanaverbeke J, Venturoli F, Verheye HM, Vianna M, Vieira RP, Vrška T, Quang Vu C, Van Vu L, Waide RB, Waldock C, Watts D, Webb S, Wesołowski T, White EP, Widdicombe CE, Wilgers D, Williams R, Williams SB, Williamson M, Willig MR, Willis TJ, Wipf S, Woods KD, Woehler EJ, Zawada K, Zettler ML, Hickler T. BioTIME: A database of biodiversity time series for the Anthropocene. Glob Ecol Biogeogr 2018; 27:760-786. [PMID: 30147447 PMCID: PMC6099392 DOI: 10.1111/geb.12729] [Citation(s) in RCA: 141] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Revised: 11/25/2017] [Accepted: 11/28/2017] [Indexed: 05/08/2023]
Abstract
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 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2). 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.
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Affiliation(s)
- Maria Dornelas
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
| | - Laura H. Antão
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
- Department of Biology and CESAMUniversidade de Aveiro, Campus Universitário de SantiagoAveiroPortugal
| | - Faye Moyes
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
| | - Amanda E. Bates
- National Oceanography Centre, University of Southampton Waterfront CampusSouthamptonUnited Kingdom
- Department of Ocean Sciences, Memorial University of NewfoundlandSt John'sNewfoundland and LabradorCanada
| | - Anne E. Magurran
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
| | - Dušan Adam
- Department of Forest Ecology, Silva Tarouca Research InstituteBrnoCzech Republic
| | | | - Ward Appeltans
- UNESCO, Intergovernmental Oceanographic Commission, IOC Project Office for IODEOostendeBelgium
| | | | - Haley Arnold
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
| | | | - Gal Badihi
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
| | - Andrew H. Baird
- ARC Centre of Excellence for Coral Reef Studies, James Cook UniversityTownsvilleQueenslandAustralia
| | - Miguel Barbosa
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
- Department of Biology and CESAMUniversidade de Aveiro, Campus Universitário de SantiagoAveiroPortugal
| | - Tiago Egydio Barreto
- Laboratório de Ecologia e Restauração Florestal, Fundação Espaço Eco, Piracicaba, São PauloBrazil
| | | | - Alecia Bellgrove
- School of Life and Environmental SciencesCentre for Integrative Ecology, Deakin UniversityWarrnamboolVictoriaAustralia
| | - Jonathan Belmaker
- School of Zoology, George S. Wise Faculty of Life SciencesTel Aviv UniversityTel AvivIsrael
| | | | - Brian J. Bett
- National Oceanography Centre, University of Southampton Waterfront CampusSouthamptonUnited Kingdom
| | - Anne D. Bjorkman
- Section for Ecoinformatics and Biodiversity, Department of BioscienceAarhus UniversityAarhusDenmark
| | - Magdalena Błażewicz
- Laboratory of Polar Biology and Oceanobiology, Faculty of Biology and Environmental ProtectionUniversity of ŁódźŁódźPoland
| | - Shane A. Blowes
- School of Zoology, George S. Wise Faculty of Life SciencesTel Aviv UniversityTel AvivIsrael
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐LeipzigLeipzigGermany
| | - Christopher P. Bloch
- Department of Biological SciencesBridgewater State UniversityBridgewaterMassachusetts
| | | | - Susan Boyd
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
| | - Matt Bradford
- CSIRO Land & WaterEcosciences Precinct, Dutton ParkQueenslandAustralia
| | - Andrew J. Brooks
- Marine Science Institute, University of CaliforniaSanta BarbaraCalifornia
| | - James H. Brown
- Department of BiologyUniversity of New MexicoAlbuquerqueNew Mexico
| | - Helge Bruelheide
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐LeipzigLeipzigGermany
- Institute of Biology/Geobotany and Botanical Garden, Martin‐Luther‐University Halle‐WittenbergHalleGermany
| | - Phaedra Budy
- Department of Watershed Sciences and the Ecology Center, US Geological Survey, UCFWRU and Utah State UniversityLoganUtah
| | - Fernando Carvalho
- Universidade do Extremo Sul Catarinense (PPG‐CA)CriciúmaSanta CatarinaBrazil
| | - Edward Castañeda‐Moya
- Southeast Environmental Research Center (OE 148), Florida International UniversityMiamiFlorida
| | - Chaolun Allen Chen
- Coral Reef Ecology and Evolution LabBiodiversity Research Centre, Academia SinicaTaipeiTaiwan
| | | | - Tory J. Chase
- ARC Centre of Excellence for Coral Reef Studies, James Cook UniversityTownsvilleQueenslandAustralia
- Marine Biology and Aquaculture, College of Science and EngineeringJames Cook UniversityDouglasQueenslandAustralia
| | | | | | - Richard Condit
- Center for Tropical Forest ScienceWashingtonDistrict of Columbia
| | - Elisabeth J. Cooper
- Biosciences Fisheries and EconomicsUiT‐ The Arctic University of NorwayTromsøNorway
| | - J. Hans C. Cornelissen
- Systems Ecology, Department of Ecological Science, Vrije UniversiteitAmsterdamThe Netherlands
| | | | - Shannan Kyle Crow
- The National Institute of Water and Atmospheric ResearchAucklandNew Zealand
| | - Gabriella Damasceno
- Lab of Vegetation Ecology, Instituto de Biociências, Universidade Estadual Paulista (UNESP), Rio ClaroBrazil
| | | | - Robert A. Davis
- School of ScienceEdith Cowan UniversityJoondalupWestern AustraliaAustralia
| | - Frank P. Day
- Department of Biological SciencesOld Dominion UniversityNorfolkVirginia
| | - Steven Degraer
- Royal Belgian Institute of Natural Sciences, Operational Directorate Natural Environment, Marine Ecology and ManagementBrusselsBelgium
- Marine Biology Research Group, Ghent UniversityGentBelgium
| | - Tim S. Doherty
- School of ScienceEdith Cowan UniversityJoondalupWestern AustraliaAustralia
- School of Life and Environmental SciencesCentre for Integrative Ecology (Burwood Campus), Deakin UniversityGeelongVictoriaAustralia
| | | | - Giselda Durigan
- Divisão de Florestas e Estações Experimentais, Floresta Estadual de Assis, Laboratório de Ecologia e Hidrologia Florestal, Instituto FlorestalSão PauloBrazil
| | - J. Emmett Duffy
- Tennenbaum Marine Observatories Network, Smithsonian InstitutionWashington, District of Columbia
| | - Dor Edelist
- National Institute of Oceanography, Tel‐ShikmonaHaifaIsrael
| | - Graham J. Edgar
- Institute for Marine and Antarctic Studies, University of TasmaniaHobartTasmaniaAustralia
| | - Robin Elahi
- Hopkins Marine Station, Stanford University, StanfordCalifornia
| | | | - Anders Enemar
- Department of Biological and Environmental SciencesUniversity of GothenburgGothenburgSweden
| | - S. K. Morgan Ernest
- Department of Wildlife Ecology and ConservationUniversity of FloridaGainesvilleFL
| | - Rubén Escribano
- Instituto Milenio de Oceanografía, Universidad de ConcepciónConcepciónChile
| | - Marc Estiarte
- CSIC, Global Ecology Unit CREAF‐CSIC‐UABBellaterraCataloniaSpain
- CREAF, Universitat Autònoma de BarcelonaCerdanyola del VallèsCataloniaSpain
| | - Brian S. Evans
- Migratory Bird Center, Smithsonian Conservation Biology Institute, National Zoological ParkWashingtonDistrict of Columbia
| | - Tung‐Yung Fan
- National Museum of Marine Biology and AquariumPingtung CountyTaiwan
| | - Fabiano Turini Farah
- Laboratório de Ecologia e Restauração Florestal, Escola Superior de Agricultura “Luiz de Queiroz”, Universidade de São PauloSão PauloBrazil
| | - Luiz Loureiro Fernandes
- Departamento de Oceanografia e Ecologia, Universidade Federal do Espírito Santo, Vitória, Espírito SantoBrazil
| | - Fábio Z. Farneda
- Centre for Ecology, Evolution and Environmental Changes – cE3c, Faculty of SciencesUniversity of LisbonLisbonPortugal
- Biological Dynamics of Forest Fragments Project, National Institute for Amazonian Research and Smithsonian Tropical Research InstituteManausBrazil
- Department of Ecology/PPGEFederal University of Rio de JaneiroRio de JaneiroBrazil
| | - Alessandra Fidelis
- Lab of Vegetation Ecology, Instituto de Biociências, Universidade Estadual Paulista (UNESP), Rio ClaroBrazil
| | - Robert Fitt
- School of Biological SciencesUniversity of AberdeenAberdeenUnited Kingdom
| | - Anna Maria Fosaa
- Botanical Department, Faroese Museum of Natural HistoryTorshavnFaroe Islands
| | | | - Grace E. Frank
- Marine Biology and Aquaculture, College of Science and EngineeringJames Cook UniversityDouglasQueenslandAustralia
| | | | - Hernando García
- Alexander von Humboldt Biological Resources Research InstituteBogotá DCColombia
| | | | - Or Givan
- School of Zoology, George S. Wise Faculty of Life SciencesTel Aviv UniversityTel AvivIsrael
| | - Elizabeth Gorgone‐Barbosa
- Lab of Vegetation Ecology, Instituto de Biociências, Universidade Estadual Paulista (UNESP), Rio ClaroBrazil
| | - William A. Gould
- USDA Forest Service, 65 USDA Forest Service, International Institute of Tropical ForestrySan JuanPuerto Rico
| | - Corinna Gries
- Center for Limnology, University of WisconsinMadisonWisconsin
| | - Gary D. Grossman
- The Warnell School of Forestry and Natural ResourcesUniversity of GeorgiaAthensGeorgia
| | - Julio R. Gutierréz
- Departamento de Biología, Facultad de Ciencias, Universidad de La SerenaLa SerenaChile
- Centro de Estudios Avanzados en Zonas Aridas (CEAZA)La SerenaChile
- Institute of Ecology and Biodiversity (IEB)SantiagoChile
| | - Stephen Hale
- U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Atlantic Ecology DivisionNarragansettRhode Island
| | - Mark E. Harmon
- Department of Forest Ecosystems and SocietyOregon State UniversityCorvallisOregon
| | - John Harte
- The Energy and Resources Group and The Department of Environmental Science, Policy and ManagementUniversity of CaliforniaBerkeleyCalifornia
| | - Gary Haskins
- Cetacean Research & Rescue UnitBanffUnited Kingdom
| | - Donald L. Henshaw
- U.S. Forest Service Pacific Northwest Research LaboratoryCorvallisOregon
| | - Luise Hermanutz
- Memorial University, St John'sNewfoundland and LabradorCanada
| | - Pamela Hidalgo
- Instituto Milenio de Oceanografía, Universidad de ConcepciónConcepciónChile
| | - Pedro Higuchi
- Laboratório de Dendrologia e Fitossociologia, Universidade do Estado de Santa CatarinaFlorianópolisSanta CatarinaBrazil
| | - Andrew Hoey
- ARC Centre of Excellence for Coral Reef Studies, James Cook UniversityTownsvilleQueenslandAustralia
| | - Gert Van Hoey
- Department of Aquatic Environment and Quality, Flanders Research Institute for Agriculture, Fisheries and FoodOostendeBelgium
| | | | - Kristen Holeck
- Department of Natural Resources and Cornell Biological Field StationCornell UniversityIthacaNew York
| | | | | | - Mia Hoogenboom
- ARC Centre of Excellence for Coral Reef Studies, James Cook UniversityTownsvilleQueenslandAustralia
- Marine Biology and Aquaculture, College of Science and EngineeringJames Cook UniversityDouglasQueenslandAustralia
| | - Chih‐hao Hsieh
- Institute of Oceanography, National Taiwan UniversityTaipeiTaiwan
| | | | - Falk Huettmann
- EWHALE lab‐ Biology and Wildlife DepartmentInstitute of Arctic Biology, University of AlaskaFairbanksAlaska
| | | | - Allen H. Hurlbert
- Department of BiologyUniversity of North CarolinaChapel HillNorth Carolina
| | | | - David Janík
- Department of Forest Ecology, Silva Tarouca Research InstituteBrnoCzech Republic
| | - Ute Jandt
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐LeipzigLeipzigGermany
- Institute of Biology/Geobotany and Botanical Garden, Martin‐Luther‐University Halle‐WittenbergHalleGermany
| | - Anna Jażdżewska
- Laboratory of Polar Biology and Oceanobiology, Faculty of Biology and Environmental ProtectionUniversity of ŁódźŁódźPoland
| | | | - Jill Johnstone
- Department of BiologyUniversity of SaskatchewanSaskatoonSaskatchewanCanada
| | - Julia Jones
- College of Earth, Ocean, and Atmospheric Sciences, Oregon State UniversityCorvallisOregon
| | - Faith A. M. Jones
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
| | - Jungwon Kang
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
| | | | | | - Douglas A. Kelt
- Department of WildlifeFish, and Conservation Biology, University of California, DavisDavisCalifornia
| | - Rebecca Kinnear
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
- Shetland Oil Terminal Environmental Advisory Group (SOTEAG)St AndrewsUnited Kingdom
| | - Kari Klanderud
- Faculty of Environmental Sciences and Natural Resource ManagementNorwegian University of Life SciencesÅsNorway
| | - Halvor Knutsen
- Institute of Marine ResearchHisNorway
- Department of Natural Sciences, Faculty of Engineering and Science, Centre for Coastal Research, University of AgderKristiansandNorway
| | | | - Alessandra R. Kortz
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
| | - Kamil Král
- Department of Forest Ecology, Silva Tarouca Research InstituteBrnoCzech Republic
| | - Linda A. Kuhnz
- Monterey Bay Aquarium Research InstituteMoss LandingCalifornia
| | - Chao‐Yang Kuo
- ARC Centre of Excellence for Coral Reef Studies, James Cook UniversityTownsvilleQueenslandAustralia
| | - David J. Kushner
- Channel Islands National Park, U. S. National Park ServiceCalifornia, VenturaCalifornia
| | | | | | - Cheol Min Lee
- Forest and Climate Change Adaptation LaboratoryCenter for Forest and Climate Change, National Institute of Forest ScienceSeoulRepublic of Korea
| | - Jonathan S. Lefcheck
- Department of Biological SciencesVirginia Institute of Marine Science, The College of William & Mary, Gloucester PointVirginia
| | - Esther Lévesque
- Département des sciences de l'environnementUniversité du Québec à Trois‐Rivières and Centre d’études nordiquesQuébecCanada
| | - David Lightfoot
- Department of BiologyMuseum of Southwestern Biology, University of New MexicoAlbuquerqueNew Mexico
| | - Francisco Lloret
- CREAF, Universitat Autònoma de BarcelonaCerdanyola del VallèsCataloniaSpain
| | | | - Adrià López‐Baucells
- Centre for Ecology, Evolution and Environmental Changes – cE3c, Faculty of SciencesUniversity of LisbonLisbonPortugal
- Biological Dynamics of Forest Fragments Project, National Institute for Amazonian Research and Smithsonian Tropical Research InstituteManausBrazil
- Museu de Ciències Naturals de GranollersCatalunyaSpain
| | | | - Joshua S. Madin
- Hawai‘i Institute of Marine Biology, University of Hawai‘i at Mānoa, KaneoheHawai‘iUSA
- Department of Biological SciencesMacquarie UniversitySydneyNew South WalesAustralia
| | | | - Shahar Malamud
- School of Zoology, George S. Wise Faculty of Life SciencesTel Aviv UniversityTel AvivIsrael
| | - Iain Matthews
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
| | | | - Brian McGill
- School of Biology and EcologySustainability Solutions Initiative, University of MaineOronoMaine
| | | | - William O. McLarney
- Stream Biomonitoring Program, Mainspring Conservation TrustFranklinNorth Carolina
| | - Jason Meador
- Stream Biomonitoring Program, Mainspring Conservation TrustFranklinNorth Carolina
| | | | | | - Christoph F. J. Meyer
- Centre for Ecology, Evolution and Environmental Changes – cE3c, Faculty of SciencesUniversity of LisbonLisbonPortugal
- Biological Dynamics of Forest Fragments Project, National Institute for Amazonian Research and Smithsonian Tropical Research InstituteManausBrazil
- Ecosystems and Environment Research Centre (EERC), School of Environment and Life Sciences, University of SalfordSalfordUnited Kingdom
| | - Anders Michelsen
- Terrestrial Ecology Section, Department of Biology, University of CopenhagenCopenhagenDenmark
| | - Nataliya Milchakova
- Laboratory of Phytoresources, Kovalevsky Institute of Marine Biological Research of RAS (IMBR)SevastopolRussia
| | - Tom Moens
- Marine Biology Research Group, Ghent UniversityGentBelgium
| | - Even Moland
- Institute of Marine ResearchHisNorway
- Department of Natural Sciences, Faculty of Engineering and Science, Centre for Coastal Research, University of AgderKristiansandNorway
| | - Jon Moore
- Shetland Oil Terminal Environmental Advisory Group (SOTEAG)St AndrewsUnited Kingdom
- Aquatic Survey & Monitoring Ltd. ASMLDurhamUnited Kingdom
| | | | - Jörg Müller
- Bavarian Forest National ParkGrafenauGermany
- Field Station Fabrikschleichach, University of WürzburgRauhenebrachGermany
| | - Grace Murphy
- Department of BiologyDalhousie UniversityHalifaxNova ScotiaCanada
| | | | | | - Andrew Naumov
- Zoological Institute, Russian Academy SciencesSt PetersburgRussia
| | - Francis Neat
- Marine Scotland, Marine LaboratoryScottish GovernmentEdinburghUnited Kingdom
| | - James A. Nelson
- Department of BiologyUniversity of Louisiana at LafayetteLafayetteLouisiana
| | - Michael Paul Nelson
- Department of Forest Ecosystems and SocietyOregon State UniversityCorvallisOregon
| | | | - Natalia Norden
- Alexander von Humboldt Biological Resources Research InstituteBogotá DCColombia
| | - Jeffrey C. Oliver
- University of Arizona Health Sciences Library, University of ArizonaTucsonArizona
| | - Esben M. Olsen
- Institute of Marine ResearchHisNorway
- Department of Natural Sciences, Faculty of Engineering and Science, Centre for Coastal Research, University of AgderKristiansandNorway
| | | | - Krzysztof Pabis
- Laboratory of Polar Biology and Oceanobiology, Faculty of Biology and Environmental ProtectionUniversity of ŁódźŁódźPoland
| | - Robert J. Pabst
- Department of Forest Ecosystems and SocietyOregon State UniversityCorvallisOregon
| | - Alain Paquette
- Center for Forest Research, Université du Québec à Montréal (UQAM)MontrealQuebecCanada
| | - Sinta Pardede
- Wildlife Conservation Society Indonesia ProgramBogorIndonesia
| | - David M. Paterson
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
- Shetland Oil Terminal Environmental Advisory Group (SOTEAG)St AndrewsUnited Kingdom
| | - Raphaël Pélissier
- UMR AMAP, IRD, CIRAD, CNRS, INRA, Montpellier UniversityMontpellierFrance
| | - Josep Peñuelas
- CSIC, Global Ecology Unit CREAF‐CSIC‐UABBellaterraCataloniaSpain
- CREAF, Universitat Autònoma de BarcelonaCerdanyola del VallèsCataloniaSpain
| | - Alejandro Pérez‐Matus
- Subtidal Ecology Laboratory & Center for Marine Conservation, Estación Costera de Investigaciones MarinasFacultad de Ciencias Biológicas, Pontificia Universidad Católica de ChileSantiagoCasillaChile
| | - Oscar Pizarro
- Australian Centre of Field Robotics, University of SydneySydneyNew South WalesAustralia
| | - Francesco Pomati
- Department of Aquatic EcologyEawag: Swiss Federal Institute of Aquatic Science and TechnologySwitzerland
| | - Eric Post
- Department of WildlifeFish, and Conservation Biology, University of California, DavisDavisCalifornia
| | | | - John C. Priscu
- Department of Land Resources and Environmental SciencesMontana State UniversityBozemanMontana
| | - Pieter Provoost
- UNESCO, Intergovernmental Oceanographic Commission, IOC Project Office for IODEOostendeBelgium
| | | | | | - B. R. Ramesh
- Department of EcologyFrench Institute of PondicherryPuducherryIndia
| | | | - Andrew Rassweiler
- Channel Islands National Park, U. S. National Park ServiceCalifornia, VenturaCalifornia
| | - Jose Eduardo Rebelo
- Ichthyology Laboratory, Fisheries and AquacultureUniversity of AveiroAveiroPortugal
| | - Daniel C. Reed
- Marine Science Institute, University of CaliforniaSanta BarbaraCalifornia
| | - Peter B. Reich
- Department of Forest Resources, University of MinnesotaSt PaulMinnesota
- Hawkesbury Institute for the Environment, Western Sydney UniversityPenrithNew South WalesAustralia
| | - Suzanne M. Remillard
- Department of Forest Ecosystems and SocietyOregon State UniversityCorvallisOregon
| | - Anthony J. Richardson
- CSIRO Oceans and AtmosphereQueensland, BioSciences Precinct (QBP)St Lucia, BrisbaneQldAustralia
- Centre for Applications in Natural Resource Mathematics, The University of QueenslandSt LuciaQueenslandAustralia
| | | | - Itai van Rijn
- School of Zoology, George S. Wise Faculty of Life SciencesTel Aviv UniversityTel AvivIsrael
| | - Ricardo Rocha
- Centre for Ecology, Evolution and Environmental Changes – cE3c, Faculty of SciencesUniversity of LisbonLisbonPortugal
- Biological Dynamics of Forest Fragments Project, National Institute for Amazonian Research and Smithsonian Tropical Research InstituteManausBrazil
- Metapopulation Research Centre, Faculty of Biosciences, University of HelsinkiHelsinkiFinland
| | - Victor H. Rivera‐Monroy
- Department of Oceanography and Coastal Sciences, College of the Coast and EnvironmentLouisiana State UniversityBaton RougeLouisiana
| | - Christian Rixen
- Swiss Federal Institute for Forest, Snow and Landscape ResearchDavos DorfSwitzerland
| | | | - Ricardo Ribeiro Rodrigues
- Laboratório de Ecologia e Restauração Florestal, Escola Superior de Agricultura “Luiz de Queiroz”, Universidade de São PauloSão PauloBrazil
| | - Denise de Cerqueira Rossa‐Feres
- Departamento de Zoologia e Botânica, Universidade Estadual Paulista – UNESPCâmpus São José do Rio Preto, São José do Rio PretoBrazil
| | - Lars Rudstam
- Department of Natural Resources and Cornell Biological Field StationCornell UniversityIthacaNew York
| | - Henry Ruhl
- National Oceanography Centre, University of Southampton Waterfront CampusSouthamptonUnited Kingdom
| | - Catalina S. Ruz
- Subtidal Ecology Laboratory & Center for Marine Conservation, Estación Costera de Investigaciones MarinasFacultad de Ciencias Biológicas, Pontificia Universidad Católica de ChileSantiagoCasillaChile
| | - Erica M. Sampaio
- Biological Dynamics of Forest Fragments Project, National Institute for Amazonian Research and Smithsonian Tropical Research InstituteManausBrazil
- Department of Animal Physiology, Eberhard Karls University TübingenTübingenGermany
| | - Nancy Rybicki
- National Research Program, U.S. Geological SurveyRestonVirginia
| | - Andrew Rypel
- Wisconsin Department of Natural Resources and Center for LimnologyUniversity of Wisconsin‐MadisonMadisonWisconsin
| | - Sofia Sal
- Department of Life SciencesImperial College LondonAscotBerkshireUnited Kingdom
| | - Beatriz Salgado
- Alexander von Humboldt Biological Resources Research InstituteBogotá DCColombia
| | | | - Ana Paula Savassi‐Coutinho
- Departamento de Ciências Biológicas, Escola Superior de Agricultura ‘Luiz de Queiroz’, Universidade de São PauloSão PauloBrazil
| | - Sara Scanga
- Department of BiologyUtica CollegeUticaNew York
| | - Jochen Schmidt
- The National Institute of Water and Atmospheric ResearchAucklandNew Zealand
| | - Robert Schooley
- Wildlife Ecology and Conservation, Department of Natural Resources and Environmental SciencesUniversity of IllinoisChampaignIllinois
| | | | - Kwang‐Tsao Shao
- Biodiversity Research Center, Academia SinicaNankang, TaipeiTaiwan
| | | | | | | | - Jacek Siciński
- Laboratory of Polar Biology and Oceanobiology, Faculty of Biology and Environmental ProtectionUniversity of ŁódźŁódźPoland
| | - Caya Sievers
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
| | - Ana Carolina da Silva
- Laboratório de Dendrologia e Fitossociologia, Universidade do Estado de Santa CatarinaFlorianópolisSanta CatarinaBrazil
| | | | | | - Jasper Slingsby
- Department of Biological Sciences, Centre for Statistics in Ecology, Environment and ConservationUniversity of CapeTownRondeboschSouth Africa
- Fynbos Node, South African Environmental Observation NetworkClaremontSouth Africa
| | - Tracey Smart
- Coastal Finfish Section, South Carolina Department of Natural Resources, Marine Resources Research InstituteCharlestonSouth Carolina
| | - Sara J. Snell
- Department of BiologyUniversity of North CarolinaChapel HillNorth Carolina
| | - Nadejda A. Soudzilovskaia
- Conservation Biology DepartmentInstitute of Environmental Studies, CML, Leiden UniversityLeidenThe Netherlands
| | - Gabriel B. G. Souza
- Laboratório de Biologia e Tecnologia Pesqueira, Universidade Federal do Rio de JaneiroRio de JaneiroBrazil
| | | | - Vinícius Castro Souza
- Laboratório de Ecologia e Restauração Florestal, Escola Superior de Agricultura “Luiz de Queiroz”, Universidade de São PauloSão PauloBrazil
| | | | - Rowan Stanforth
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
| | | | | | - Maarten Stevens
- INBO, Research Institute for Nature and ForestBrusselsBelgium
| | - Rick Stuart‐Smith
- Institute for Marine and Antarctic Studies, University of TasmaniaHobartTasmaniaAustralia
| | - Yzel Rondon Suarez
- Centro de Estudos em Recursos Naturais, Universidade Estadual de Mato Grosso do SulDouradosMato Grosso do SulBrazil
| | - Sarah Supp
- School of Biology and EcologyUniversity of MaineOronoMaine
| | | | | | - Gary P. Thiede
- Department of Watershed Sciences and the Ecology Center, US Geological Survey, UCFWRU and Utah State UniversityLoganUtah
| | - Simon Thorn
- Field Station Fabrikschleichach, University of WürzburgRauhenebrachGermany
| | - Anne Tolvanen
- Natural Resources Institute Finland, University of OuluOuluFinland
| | | | - Ørjan Totland
- Department of BiologyUniversity of BergenBergenNorway
| | - Robert R. Twilley
- Department of Oceanography and Coastal Sciences, College of the Coast and EnvironmentLouisiana State UniversityBaton RougeLouisiana
| | | | - Nelson Valdivia
- Universidad Austral de Chile and Centro FONDAP en Dinámica de Ecosistemas Marinos de Altas Latitudes (IDEAL)ValdiviaChile
| | | | | | - Carl Van Colen
- Marine Biology Research Group, Ghent UniversityGentBelgium
| | - Jan Vanaverbeke
- Royal Belgian Institute of Natural Sciences, Operational Directorate Natural Environment, Marine Ecology and ManagementBrusselsBelgium
| | - Fabio Venturoli
- Escola de Agronomia, Universidade Federal de GoiásGoiâniaBrazil
| | - Hans M. Verheye
- Department of Environmental AffairsOceans and Coastal ResearchCape TownSouth Africa
- Department of Biological SciencesMarine Research InstituteUniversity of Cape TownCape TownSouth Africa
| | - Marcelo Vianna
- Laboratório de Biologia e Tecnologia Pesqueira, Universidade Federal do Rio de JaneiroRio de JaneiroBrazil
| | - Rui P. Vieira
- National Oceanography Centre, University of Southampton Waterfront CampusSouthamptonUnited Kingdom
| | - Tomáš Vrška
- Department of Forest Ecology, Silva Tarouca Research InstituteBrnoCzech Republic
| | - Con Quang Vu
- Institute of Ecology and Biological Resources, VASTHanoiVietnam
| | - Lien Van Vu
- Vietnam National Museum of NatureHanoiVietnam
- Graduate University of Science and Technology, VASTHanoiVietnam
| | - Robert B. Waide
- Department of BiologyUniversity of New MexicoAlbuquerqueNew Mexico
| | - Conor Waldock
- National Oceanography Centre, University of Southampton Waterfront CampusSouthamptonUnited Kingdom
| | - Dave Watts
- CSIRO Oceans and Atmosphere FlagshipHobartTasmaniaAustralia
| | - Sara Webb
- Biology Department, Drew UniversityMadisonNew Jersey
- Environmental Studies Department, Drew UniversityMadisonNew Jersey
| | | | - Ethan P. White
- Department of Wildlife Ecology & ConservationUniversity of FloridaGainesvilleFlorida
- Informatics Institute, University of FloridaGainesvilleFlorida
| | | | - Dustin Wilgers
- Department of Natural SciencesMcPherson CollegeMcPhersonKansas
| | - Richard Williams
- Australian Antarctic Division, Channel HighwayKingstonTasmaniaAustralia
| | - Stefan B. Williams
- Australian Centre of Field Robotics, University of SydneySydneyNew South WalesAustralia
| | | | - Michael R. Willig
- Department of Ecology & Evolutionary Biology, Center for Environmental Sciences & EngineeringUniversity of ConnecticutMansfieldConnecticut
| | - Trevor J. Willis
- Institute of Marine Sciences, School of Biological Sciences, University of PortsmouthPortsmouthUnited Kingdom
| | - Sonja Wipf
- Research Team Mountain Ecosystems, WSL Institute for Snow and Avalanche Research SLFDavosSwitzerland
| | | | - Eric J. Woehler
- Institute for Marine and Antarctic Studies, University of TasmaniaHobartTasmaniaAustralia
| | - Kyle Zawada
- Centre for Biological Diversity and Scottish Oceans Institute, School of Biology, University of St. AndrewsSt AndrewsUnited Kingdom
- Department of Biological SciencesMacquarie UniversitySydneyNew South WalesAustralia
| | - Michael L. Zettler
- Leibniz Institute for Baltic Sea Research Warnemünde, Seestr. 15, D‐18119 RostockGermany
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Christensen EM, Harris DJ, Ernest SKM. Long-term community change through multiple rapid transitions in a desert rodent community. Ecology 2018; 99:1523-1529. [PMID: 29718539 DOI: 10.1002/ecy.2373] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 03/06/2018] [Accepted: 03/29/2018] [Indexed: 11/08/2022]
Abstract
While studies increasingly document long-term change in community composition, whether long-term change occurs gradually or via rapid reorganization events remains unclear. We used Latent Dirichlet Allocation (LDA) and a change-point model to examine the long-term dynamics of a desert rodent community undergoing compositional change over a 38-yr span. Our approach detected three rapid reorganization events, where changes in the relative abundances of dominant and rare species occurred, and a separate period of increased variance in the structure of the community. These events coincided with time periods, possibly related to climate events, where the total abundance of rodents was extremely low. There are a variety of processes that could link low abundance events with a higher probability of rapid ecological transitions, including higher importance of stochastic processes (i.e., competitive interactions or priority effects) and the removal of structuring effects of competitive dominants or incumbent species. Continued study of the dynamics of community change will provide important information not only on the processes structuring communities, but will also provide guidance for forecasting how communities will undergo change in the future.
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Affiliation(s)
- Erica M Christensen
- Department of Wildlife Ecology and Conservation, University of Florida, 110 Newins-Ziegler Hall, Gainesville, Florida, 32611, USA
| | - David J Harris
- Department of Wildlife Ecology and Conservation, University of Florida, 110 Newins-Ziegler Hall, Gainesville, Florida, 32611, USA
| | - S K Morgan Ernest
- Department of Wildlife Ecology and Conservation, University of Florida, 110 Newins-Ziegler Hall, Gainesville, Florida, 32611, USA
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17
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Bannar-Martin KH, Kremer CT, Ernest SKM, Leibold MA, Auge H, Chase J, Declerck SAJ, Eisenhauer N, Harpole S, Hillebrand H, Isbell F, Koffel T, Larsen S, Narwani A, Petermann JS, Roscher C, Cabral JS, Supp SR. Integrating community assembly and biodiversity to better understand ecosystem function: the Community Assembly and the Functioning of Ecosystems (CAFE) approach. Ecol Lett 2017; 21:167-180. [PMID: 29280282 DOI: 10.1111/ele.12895] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2017] [Revised: 08/01/2017] [Accepted: 11/12/2017] [Indexed: 01/18/2023]
Abstract
The research of a generation of ecologists was catalysed by the recognition that the number and identity of species in communities influences the functioning of ecosystems. The relationship between biodiversity and ecosystem functioning (BEF) is most often examined by controlling species richness and randomising community composition. In natural systems, biodiversity changes are often part of a bigger community assembly dynamic. Therefore, focusing on community assembly and the functioning of ecosystems (CAFE), by integrating both species richness and composition through species gains, losses and changes in abundance, will better reveal how community changes affect ecosystem function. We synthesise the BEF and CAFE perspectives using an ecological application of the Price equation, which partitions the contributions of richness and composition to function. Using empirical examples, we show how the CAFE approach reveals important contributions of composition to function. These examples show how changes in species richness and composition driven by environmental perturbations can work in concert or antagonistically to influence ecosystem function. Considering how communities change in an integrative fashion, rather than focusing on one axis of community structure at a time, will improve our ability to anticipate and predict changes in ecosystem function.
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Affiliation(s)
- Katherine H Bannar-Martin
- Quantitative Assessment Methods Section, Pacific Biological Station, Fisheries and Oceans Canada, Nanaimo, BC, Canada
| | - Colin T Kremer
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA
| | - S K Morgan Ernest
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL, USA
| | - Mathew A Leibold
- Department of Integrative Biology, University of Texas at Austin, Austin, TX, USA
| | - Harald Auge
- Department of Community Ecology, UFZ, Helmholtz-Centre for Environmental Research, Leipzig, Germany.,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
| | - Jonathan Chase
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.,Department of Computer Sciences, Martin Luther University, Halle, Germany
| | | | - Nico Eisenhauer
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.,Institute of Biology, Leipzig University, Leipzig, Germany
| | - Stanley Harpole
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.,Department of Physiological Diversity, Helmholtz Center for Environmental Research - UFZ, Leipzig, Germany.,Institute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Helmut Hillebrand
- Institute for Chemistry and Biology of the Marine Environment, Carl-von-Ossietzky University Oldenburg, Oldenburg, Germany.,Helmholtz-Institute for Functional Marine Biodiversity, University of Oldenburg [HIFMB], Oldenburg, Germany
| | - Forest Isbell
- Department of Ecology, Evolution and Behavior, University of Minnesota Twin Cities, Saint Paul, MN, USA
| | | | - Stefano Larsen
- Synthesis Center of the German Centre for Integrative Biodiversity Research, Leipzig, Germany.,University of Trento, Department of Civil, Environmental and Mechanical Engineering, Trento, Italy
| | - Anita Narwani
- Eawag, Aquatic Ecology Department, Dübendorf, Switzerland
| | - Jana S Petermann
- Department of Ecology and Evolution, University of Salzburg, Salzburg, Austria
| | - Christiane Roscher
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.,Department of Physiological Diversity, UFZ, Helmholtz Centre for Environmental Research, Leipzig, Germany
| | - Juliano Sarmento Cabral
- Synthesis Center of the German Centre for Integrative Biodiversity, Ecosystem Modeling, Center for Computational and Theoretical Biology (CCTB), University of Würzburg, Würzburg, Germany
| | - Sarah R Supp
- School of Biology and Ecology, University of Maine, Orono, ME, USA
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18
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Meiners JM, Griswold TL, Harris DJ, Ernest SKM. Bees without Flowers: Before Peak Bloom, Diverse Native Bees Find Insect-Produced Honeydew Sugars. Am Nat 2017; 190:281-291. [PMID: 28731796 DOI: 10.1086/692437] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Bee foragers respond to complex visual, olfactory, and extrasensory cues to optimize searches for floral rewards. Their abilities to detect and distinguish floral colors, shapes, volatiles, and ultraviolet signals and even gauge nectar availability from changes in floral humidity or electric fields are well studied. Bee foraging behaviors in the absence of floral cues, however, are rarely considered. We observed 42 species of wild bees visiting inconspicuous, nonflowering shrubs during early spring in a protected Mediterranean habitat. We determined experimentally that these bees were accessing sugary honeydew secretions from scale insects without the aid of standard cues. While honeydew use is known among some social Hymenoptera, its use across a diverse community of solitary bees is a novel observation. The widespread ability of native bees to locate and use unadvertised, nonfloral sugars suggests unappreciated sensory mechanisms and/or the existence of an interspecific foraging network among solitary bees that may influence how native bees cope with scarcity of floral resources and increasing environmental change.
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Leibold MA, Chase JM, Ernest SKM. Community assembly and the functioning of ecosystems: how metacommunity processes alter ecosystems attributes. Ecology 2017; 98:909-919. [DOI: 10.1002/ecy.1697] [Citation(s) in RCA: 110] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Revised: 11/07/2016] [Accepted: 11/15/2016] [Indexed: 11/07/2022]
Affiliation(s)
- Mathew A. Leibold
- Department of Integrative Biology 2415 Speedway #C0930, University of Texas at Austin Austin Texas 78712 USA
| | - Jonathan M. Chase
- German Centre for Integrative Biodiversity Research (iDiv), Deutscher Platz 5e 04103 Leipzig Germany
- Department of Computer Science Martin Luther University Halle Germany
| | - S. K. Morgan Ernest
- Department of Wildlife Ecology and Conservation 110 Newins‐Ziegler Hall PO Box 110430, University of Florida Gainesville Florida 84322 USA
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20
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Myhrvold NP, Baldridge E, Chan B, Sivam D, Freeman DL, Ernest SKM. An amniote life-history database to perform comparative analyses with birds, mammals, and reptiles. Ecology 2015. [DOI: 10.1890/15-0846r.1] [Citation(s) in RCA: 194] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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21
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Supp SR, Koons DN, Ernest SKM. Using life history trade-offs to understand core-transient structuring of a small mammal community. Ecosphere 2015. [DOI: 10.1890/es15-00239.1] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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23
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Saarinen JJ, Boyer AG, Brown JH, Costa DP, Ernest SKM, Evans AR, Fortelius M, Gittleman JL, Hamilton MJ, Harding LE, Lintulaakso K, Lyons SK, Okie JG, Sibly RM, Stephens PR, Theodor J, Uhen MD, Smith FA. Patterns of maximum body size evolution in Cenozoic land mammals: eco-evolutionary processes and abiotic forcing. Proc Biol Sci 2014; 281:20132049. [PMID: 24741007 DOI: 10.1098/rspb.2013.2049] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
There is accumulating evidence that macroevolutionary patterns of mammal evolution during the Cenozoic follow similar trajectories on different continents. This would suggest that such patterns are strongly determined by global abiotic factors, such as climate, or by basic eco-evolutionary processes such as filling of niches by specialization. The similarity of pattern would be expected to extend to the history of individual clades. Here, we investigate the temporal distribution of maximum size observed within individual orders globally and on separate continents. While the maximum size of individual orders of large land mammals show differences and comprise several families, the times at which orders reach their maximum size over time show strong congruence, peaking in the Middle Eocene, the Oligocene and the Plio-Pleistocene. The Eocene peak occurs when global temperature and land mammal diversity are high and is best explained as a result of niche expansion rather than abiotic forcing. Since the Eocene, there is a significant correlation between maximum size frequency and global temperature proxy. The Oligocene peak is not statistically significant and may in part be due to sampling issues. The peak in the Plio-Pleistocene occurs when global temperature and land mammal diversity are low, it is statistically the most robust one and it is best explained by global cooling. We conclude that the macroevolutionary patterns observed are a result of the interplay between eco-evolutionary processes and abiotic forcing.
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Affiliation(s)
- Juha J Saarinen
- Department of Geosciences and Geography, University of Helsinki, , Helsinki, Finland, Department of Ecology and Evolutionary Biology, University of Tennessee, , Knoxville, TN, USA, Department of Biology, University of New Mexico, , Albuquerque, NM, USA, Department of Anthropology, University of New Mexico, , Albuquerque, NM, USA, Department of Ecology and Evolutionary Biology, University of California, , Santa Cruz, CA, USA, Department of Biology and the Ecology Center, Utah State University, , Logan, UT, USA, School of Biological Sciences, Monash University, , Victoria, Australia, Odum School of Ecology, University of Georgia, , Athens, GA, USA, Santa Fe Institute, , Santa Fe, NM, USA, Department of Paleobiology, Smithsonian Institution, , Washington, DC, USA, School of Earth and Space Exploration, Arizona State University, , Tempe, Arizona, USA, School of Biological Sciences, University of Reading, , Reading, UK, Department of Biological Sciences, University of Calgary, , Calgary, Alberta, Canada, Department of Atmospheric, Oceanic and Earth Sciences, George Mason University, , Fairfax, VA, USA
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24
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Okie JG, Boyer AG, Brown JH, Costa DP, Ernest SKM, Evans AR, Fortelius M, Gittleman JL, Hamilton MJ, Harding LE, Lintulaakso K, Lyons SK, Saarinen JJ, Smith FA, Stephens PR, Theodor J, Uhen MD, Sibly RM. Effects of allometry, productivity and lifestyle on rates and limits of body size evolution. Proc Biol Sci 2013; 280:20131007. [PMID: 23760865 DOI: 10.1098/rspb.2013.1007] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Body size affects nearly all aspects of organismal biology, so it is important to understand the constraints and dynamics of body size evolution. Despite empirical work on the macroevolution and macroecology of minimum and maximum size, there is little general quantitative theory on rates and limits of body size evolution. We present a general theory that integrates individual productivity, the lifestyle component of the slow-fast life-history continuum, and the allometric scaling of generation time to predict a clade's evolutionary rate and asymptotic maximum body size, and the shape of macroevolutionary trajectories during diversifying phases of size evolution. We evaluate this theory using data on the evolution of clade maximum body sizes in mammals during the Cenozoic. As predicted, clade evolutionary rates and asymptotic maximum sizes are larger in more productive clades (e.g. baleen whales), which represent the fast end of the slow-fast lifestyle continuum, and smaller in less productive clades (e.g. primates). The allometric scaling exponent for generation time fundamentally alters the shape of evolutionary trajectories, so allometric effects should be accounted for in models of phenotypic evolution and interpretations of macroevolutionary body size patterns. This work highlights the intimate interplay between the macroecological and macroevolutionary dynamics underlying the generation and maintenance of morphological diversity.
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Affiliation(s)
- Jordan G Okie
- School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA.
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25
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Abstract
Macroecological patterns such as the species-area relationship (SAR), the species-abundance distribution (SAD), and the species-time relationship (STR) exhibit regular behavior across ecosystems and taxa. However, determinants of these patterns remain poorly understood. Emerging theoretical frameworks for macroecology attempt to understand this regularity by ignoring detailed ecological interactions and focusing on the influence of a small number of community-level state variables, such as species richness and total abundance, on these patterns. We present results from a 15-year rodent removal experiment evaluating the response of three different macroecological patterns in two distinct annual plant communities (summer and winter) to two levels of manipulated seed predation. Seed predator manipulations significantly impacted species composition on all treatments in both communities, but did not significantly impact richness, community abundance, or macroecological patterns in most cases. How'ever, winter community abundance and richness responded significantly to the removal of all rodents. Changes in richness and abundance were coupled with significant shifts in macroecological patterns (SADs, SARs, and STRs). Because altering species interactions only impacted macroecological patterns when the state variables of abundance and richness also changed, we suggest that, in this system, local-scale processes primarily act indirectly through these properties to determine macroecological patterns.
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Affiliation(s)
- S R Supp
- Utah State University, Department of Biology, Ecology Center, 5305 Old Main Hill, Logan, Utah 84322-5305, USA.
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26
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Allington GRH, Koons DN, Morgan Ernest SK, Schutzenhofer MR, Valone TJ. Niche opportunities and invasion dynamics in a desert annual community. Ecol Lett 2012; 16:158-66. [DOI: 10.1111/ele.12023] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2012] [Revised: 07/26/2012] [Accepted: 10/02/2012] [Indexed: 11/30/2022]
Affiliation(s)
| | - David N. Koons
- Department of Wildland Resources and the Ecology Center; Utah State University; Logan; UT; 84322; USA
| | - S. K. Morgan Ernest
- Department of Biology and the Ecology Center; Utah State University; Logan; UT; 84322; USA
| | | | - Thomas J. Valone
- Department of Biology; Saint Louis University; St. Louis; MO; 63103; USA
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27
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Abstract
Theory has recognized a combination of niche and neutral processes each contributing, with varying importance, to species coexistence. However, long-term persistence of rare species has been difficult to produce in trait-based models of coexistence that incorporate stochastic dynamics, raising questions about how rare species persist despite such variability. Following recent evidence that rare species may experience significantly different population dynamics than dominant species, we use a plant community model to simulate the effect of disproportionately strong negative frequency dependence on the long-term persistence of the rare species in a simulated community. This strong self-limitation produces long persistence times for the rare competitors, which otherwise succumb quickly to stochastic extinction. The results suggest that the mechanism causing species to be rare in this case is the same mechanism allowing those species to persist.
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Affiliation(s)
- Glenda Yenni
- Department of Biology, Utah State University, Logan, Utah 84322, USA.
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28
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29
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White EP, Ernest SKM, Adler PB, Hurlbert AH, Lyons SK. Integrating spatial and temporal approaches to understanding species richness. Philos Trans R Soc Lond B Biol Sci 2011; 365:3633-43. [PMID: 20980312 DOI: 10.1098/rstb.2010.0280] [Citation(s) in RCA: 71] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Understanding species richness patterns represents one of the most fundamental problems in ecology. Most research in this area has focused on spatial gradients of species richness, with a smaller area of emphasis dedicated to understanding the temporal dynamics of richness. However, few attempts have been made to understand the linkages between the spatial and temporal patterns related to richness. Here, we argue that spatial and temporal richness patterns and the processes that drive them are inherently linked, and that our understanding of richness will be substantially improved by considering them simultaneously. The species-time-area relationship provides a case in point: successful description of the empirical spatio-temporal pattern led to a rapid development and testing of new theories. Other areas of research on species richness could also benefit from an explicitly spatio-temporal approach, and we suggest future directions for understanding the processes common to these two traditionally isolated fields of research.
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Affiliation(s)
- Ethan P White
- Department of Biology, The Ecology Center, Utah State University, Logan, UT, USA.
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30
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Smith FA, Boyer AG, Brown JH, Costa DP, Dayan T, Ernest SKM, Evans AR, Fortelius M, Gittleman JL, Hamilton MJ, Harding LE, Lintulaakso K, Lyons SK, McCain C, Okie JG, Saarinen JJ, Sibly RM, Stephens PR, Theodor J, Uhen MD. The Evolution of Maximum Body Size of Terrestrial Mammals. Science 2010; 330:1216-9. [DOI: 10.1126/science.1194830] [Citation(s) in RCA: 214] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
The extinction of dinosaurs at the Cretaceous/Paleogene (K/Pg) boundary was the seminal event that opened the door for the subsequent diversification of terrestrial mammals. Our compilation of maximum body size at the ordinal level by sub-epoch shows a near-exponential increase after the K/Pg. On each continent, the maximum size of mammals leveled off after 40 million years ago and thereafter remained approximately constant. There was remarkable congruence in the rate, trajectory, and upper limit across continents, orders, and trophic guilds, despite differences in geological and climatic history, turnover of lineages, and ecological variation. Our analysis suggests that although the primary driver for the evolution of giant mammals was diversification to fill ecological niches, environmental temperature and land area may have ultimately constrained the maximum size achieved.
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Thibault KM, Ernest SKM, White EP, Brown JH, Goheen JR. Long-term insights into the influence of precipitation on community dynamics in desert rodents. J Mammal 2010. [DOI: 10.1644/09-mamm-s-142.1] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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Abstract
Major shifts in many ecosystem-level properties of tropical forests have been observed, but the processes driving these changes are poorly understood. The forest on Barro Colorado Island (BCI) exhibited a 20% decrease in the number of trees and a 10% increase in average diameter. Using a metabolism-based zero-sum framework, we show that increases in per capita resource use at BCI, caused by increased tree size and increased temperature, compensated for the observed declines in abundance. This trade-off between abundance and average resource use resulted in no net change in the rate resources are fluxed by the forest. Observed changes in the forest are not consistent with other hypotheses, including changes in overall resource availability and existing self-thinning models. The framework successfully predicts interrelated changes in size, abundance and temperature, indicating its utility for understanding changes in the structure and dynamics of ecosystems.
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Affiliation(s)
- S K Morgan Ernest
- Department of Biology and the Ecology Center, Utah State University, Logan, UT 84322, USA.
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Ernest SKM, Brown JH, Thibault KM, White EP, Goheen JR. Zero sum, the niche, and metacommunities: long-term dynamics of community assembly. Am Nat 2009; 172:E257-69. [PMID: 18947326 DOI: 10.1086/592402] [Citation(s) in RCA: 92] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Recent models of community assembly, structure, and dynamics have incorporated, to varying degrees, three mechanistic processes: resource limitation and interspecific competition, niche requirements of species, and exchanges between a local community and a regional species pool. Synthesizing 30 years of data from an intensively studied desert rodent community, we show that all of these processes, separately and in combination, have influenced the structural organization of this community and affected its dynamical response to both natural environmental changes and experimental perturbations. In addition, our analyses suggest that zero-sum constraints, niche differences, and metacommunity processes are inextricably linked in the ways that they affect the structure and dynamics of this system. Explicit consideration of the interaction of these processes should yield a deeper understanding of the assembly and dynamics of other ecological communities. This synthesis highlights the role that long-term data, especially when coupled with experimental manipulations, can play in assessing the fundamental processes that govern the structure and function of ecological communities.
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Affiliation(s)
- S K Morgan Ernest
- Department of Biology and the Ecology Center, Utah State University, Logan, Utah 84322, USA.
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Lima M, Ernest SKM, Brown JH, Belgrano A, Stenseth NC. Chihuahuan Desert kangaroo rats: nonlinear effects of population dynamics, competition, and rainfall. Ecology 2008; 89:2594-603. [PMID: 18831180 DOI: 10.1890/07-1246.1] [Citation(s) in RCA: 59] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Using long-term data on two kangaroo rats in the Chihuahuan Desert of North America, we fitted logistic models including the exogenous effects of seasonal rainfall patterns. Our aim was to test the effects of intraspecific interactions and seasonal rainfall in explaining and predicting the numerical fluctuations of these two kangaroo rats. We found that logistic models fit both data sets quite well; Dipodomys merriami showed lower maximum per capita growth rates than Dipodomys ordii, and in both cases logistic models were nonlinear. Summer rainfall appears to be the most important exogenous effect for both rodent populations; models including this variable were able to predict independent data better than models including winter rainfall. D. merriami was also negatively affected by another kangaroo rat (Dipodomys spectabilis), consistent with previous experimental evidence. We hypothesized that summer rainfall influences the carrying capacity of the environment by affecting seed availability and the intensity of intraspecific competition.
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Affiliation(s)
- Mauricio Lima
- Center for Advanced Studies in Ecology and Biodiversity, Pontificia Universidad Catdlica de Chile, Casilla 114-D, Santiago CP 6513677, Chile.
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White EP, Ernest SKM, Kerkhoff AJ, Enquist BJ. Relationships between body size and abundance in ecology. Trends Ecol Evol 2007; 22:323-30. [PMID: 17399851 DOI: 10.1016/j.tree.2007.03.007] [Citation(s) in RCA: 368] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2006] [Revised: 02/19/2007] [Accepted: 03/15/2007] [Indexed: 11/29/2022]
Abstract
Body size is perhaps the most fundamental property of an organism and is related to many biological traits, including abundance. The relationship between abundance and body size has been extensively studied in an attempt to quantify the form of the relationship and to understand the processes that generate it. However, progress has been impeded by the under appreciated fact that there are four distinct, but interrelated, relationships between size and abundance that are often confused in the literature. Here, we review and distinguish between these four patterns, and discuss the linkages between them. We argue that a synthetic understanding of size-abundance relationships will result from more detailed analyses of individual patterns and from careful consideration of how and why the patterns are related.
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Affiliation(s)
- Ethan P White
- Department of Biology and the Ecology Center, Utah State University, Logan, UT 84322, USA.
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Houlahan JE, Currie DJ, Cottenie K, Cumming GS, Ernest SKM, Findlay CS, Fuhlendorf SD, Gaedke U, Legendre P, Magnuson JJ, McArdle BH, Muldavin EH, Noble D, Russell R, Stevens RD, Willis TJ, Woiwod IP, Wondzell SM. Compensatory dynamics are rare in natural ecological communities. Proc Natl Acad Sci U S A 2007; 104:3273-7. [PMID: 17360637 PMCID: PMC1805590 DOI: 10.1073/pnas.0603798104] [Citation(s) in RCA: 243] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2006] [Indexed: 11/18/2022] Open
Abstract
In population ecology, there has been a fundamental controversy about the relative importance of competition-driven (density-dependent) population regulation vs. abiotic influences such as temperature and precipitation. The same issue arises at the community level; are population sizes driven primarily by changes in the abundances of cooccurring competitors (i.e., compensatory dynamics), or do most species have a common response to environmental factors? Competitive interactions have had a central place in ecological theory, dating back to Gleason, Volterra, Hutchison and MacArthur, and, more recently, Hubbell's influential unified neutral theory of biodiversity and biogeography. If competitive interactions are important in driving year-to-year fluctuations in abundance, then changes in the abundance of one species should generally be accompanied by compensatory changes in the abundances of others. Thus, one necessary consequence of strong compensatory forces is that, on average, species within communities will covary negatively. Here we use measures of community covariance to assess the prevalence of negative covariance in 41 natural communities comprising different taxa at a range of spatial scales. We found that species in natural communities tended to covary positively rather than negatively, the opposite of what would be expected if compensatory dynamics were important. These findings suggest that abiotic factors such as temperature and precipitation are more important than competitive interactions in driving year-to-year fluctuations in species abundance within communities.
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Affiliation(s)
- J E Houlahan
- Department of Biology, University of New Brunswick, P.O. Box 5050, Saint John, NB, Canada E2L 4L5.
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Abstract
Nee et al. (Reports, 19 August 2005, p. 1236) used a null model to argue that life history invariants are illusions. We show that their results are largely inconsequential for life history theory because the authors confound two definitions of invariance, and rigorous analysis of their null model demonstrates that it does not match observed data.
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Affiliation(s)
- Van M Savage
- Bauer Center for Genomics Research, Harvard University, Cambridge, MA 02138, USA.
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Abstract
The Smith-Fretwell model for optimal offspring size assumes the existence of an inverse proportional relationship (i.e., trade-off) between the number of offspring and the amount of resources invested in an individual offspring; virtually all of the many models derived from theirs make the same trade-off assumption. Over the last 30 years it has become apparent that the predicted proportionality is often not observed when evaluated across species. We develop a general allometric approach to correct for size-related differences in the resources available for reproduction. Using data on mammals, we demonstrate that the predicted inverse proportional relationship between number of offspring and offspring size is closely approached after correcting for allocation, though there is a slight curvature in the relationship. We discuss applications for this approach to other organisms, possible causes for the curvature, and the usefulness of allometries for estimating life-history variables that are difficult to measure.
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Affiliation(s)
- Eric L Charnov
- Department of Biology, University of New Mexico, Albuquerque, New Mexico 87131, USA.
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White EP, Ernest SKM, Thibault KM. Trade-offs in community properties through time in a desert rodent community. Am Nat 2004; 164:670-6. [PMID: 15540156 DOI: 10.1086/424766] [Citation(s) in RCA: 52] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2004] [Accepted: 06/25/2004] [Indexed: 11/03/2022]
Abstract
Resource limitation represents an important constraint on ecological communities, which restricts the total abundance, biomass, and community energy flux a given community can support. However, the exact relationship among these three measures of biological activity remains unclear. Here we use a simple framework that links abundance and biomass with an energetic constraint. Under constant energetic availability, it is expected that changes in abundance and biomass can result from shifts in the distribution of individual masses. We test these predictions using long-term data from a desert rodent community. Total energy use for the community has not changed directionally for 25 years, but species composition has. As a result, the average body size has decreased by almost 50%, and average abundance has doubled. These results lend support to the idea of resource limitation on desert rodent communities and demonstrate that systems are able to maintain community energy flux in the face of environmental change, through changes in composition and structure.
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Affiliation(s)
- Ethan P White
- Department of Biology, University of New Mexico, Albuquerque, New Mexico 87131, USA.
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Smith FA, Brown JH, Haskell JP, Lyons SK, Alroy J, Charnov EL, Dayan T, Enquist BJ, Ernest SKM, Hadly EA, Jones KE, Kaufman DM, Marquet PA, Maurer BA, Niklas KJ, Porter WP, Tiffney B, Willig MR. Similarity of Mammalian Body Size across the Taxonomic Hierarchy and across Space and Time. Am Nat 2004; 163:672-91. [PMID: 15122486 DOI: 10.1086/382898] [Citation(s) in RCA: 147] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2001] [Accepted: 12/16/2003] [Indexed: 11/03/2022]
Abstract
Although it is commonly assumed that closely related animals are similar in body size, the degree of similarity has not been examined across the taxonomic hierarchy. Moreover, little is known about the variation or consistency of body size patterns across geographic space or evolutionary time. Here, we draw from a data set of terrestrial, nonvolant mammals to quantify and compare patterns across the body size spectrum, the taxonomic hierarchy, continental space, and evolutionary time. We employ a variety of statistical techniques including "sib-sib" regression, phylogenetic autocorrelation, and nested ANOVA. We find an extremely high resemblance (heritability) of size among congeneric species for mammals over approximately 18 g; the result is consistent across the size spectrum. However, there is no significant relationship among the body sizes of congeneric species for mammals under approximately 18 g. We suspect that life-history and ecological parameters are so tightly constrained by allometry at diminutive size that animals can only adapt to novel ecological conditions by modifying body size. The overall distributions of size for each continental fauna and for the most diverse orders are quantitatively similar for North America, South America, and Africa, despite virtually no overlap in species composition. Differences in ordinal composition appear to account for quantitative differences between continents. For most mammalian orders, body size is highly conserved, although there is extensive overlap at all levels of the taxonomic hierarchy. The body size distribution for terrestrial mammals apparently was established early in the Tertiary, and it has remained remarkably constant over the past 50 Ma and across the major continents. Lineages have diversified in size to exploit environmental opportunities but only within limits set by allometric, ecological, and evolutionary constraints.
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Affiliation(s)
- Felisa A Smith
- National Center for Ecological Analysis and Synthesis, Working Group on Body Size in Ecology and Paleoecology, Santa Barbara, California 93101-5504, USA.
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Ernest SKM, Enquist BJ, Brown JH, Charnov EL, Gillooly JF, Savage VM, White EP, Smith FA, Hadly EA, Haskell JP, Lyons SK, Maurer BA, Niklas KJ, Tiffney B. Thermodynamic and metabolic effects on the scaling of production and population energy use. Ecol Lett 2003. [DOI: 10.1046/j.1461-0248.2003.00526.x] [Citation(s) in RCA: 194] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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