Quantifying climate sensitivity and climate-driven change in North American amphibian communities

Miller, David A. W.; Grant, Evan H. Campbell; Muths, Erin; Amburgey, Staci M.; Adams, Michael J.; Joseph, Maxwell B.; Waddle, J. Hardin; Johnson, Pieter T. J.; Ryan, Maureen E.; Schmidt, Benedikt R.; Calhoun, Daniel L.; Davis, Courtney L.; Fisher, Robert N.; Green, David M.; Hossack, Blake R.; Rittenhouse, Tracy A. G.; Walls, Susan C.; Bailey, Larissa L.; Cruickshank, Sam S.; Fellers, Gary M.; Gorman, Thomas A.; Haas, Carola A.; Hughson, Ward; Pilliod, David S.; Price, Steven J.; Ray, Andrew M.; Sadinski, Walter J.; Saenz, Daniel; Barichivich, William J.; Brand, Adrianne B.; Brehme, Cheryl S.; Dagit, Rosi; Delaney, Katy S.; Glorioso, Brad M.; Kats, Lee B.; Kleeman, Patrick M.; Pearl, Christopher A.; Rochester, Carlton J.; Riley, Seth P. D.; Roth, Mark F.; Sigafus, Brent H.

doi:10.1038/s41467-018-06157-6

Cited by 97 publications

(73 citation statements)

References 62 publications

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“…Opportunities for data integration are not limited to traditional static species distribution models, but also could be utilized when distribution dynamics are of interest (Zipkin et al., ). Dynamic models range from simple abundance models that estimate local changes in occurrence or abundance across space and time (Amburgey et al., ; Miller et al, ) to more complex models that incorporate demographic parameters and life‐stage‐specific abundances (Davis, Hooten, Phillips, & Doherty, ; Zipkin et al., ). Changes in the distribution of species through time (expansion, contraction) are influenced by individual population processes governed by survival, reproduction, and movement.…”

Section: Creating a More Flexible And General Framework For Data Intementioning

confidence: 99%

The recent past and promising future for data integration methods to estimate species’ distributions

et al. 2019

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With the advance of methods for estimating species distribution models has come an interest in how to best combine datasets to improve estimates of species distributions. This has spurred the development of data integration methods that simultaneously harness information from multiple datasets while dealing with the specific strengths and weaknesses of each dataset. We outline the general principles that have guided data integration methods and review recent developments in the field. We then outline key areas that allow for a more general framework for integrating data and provide suggestions for improving sampling design and validation for integrated models. Key to recent advances has been using point‐process thinking to combine estimators developed for different data types. Extending this framework to new data types will further improve our inferences, as well as relaxing assumptions about how parameters are jointly estimated. These along with the better use of information regarding sampling effort and spatial autocorrelation will further improve our inferences. Recent developments form a strong foundation for implementation of data integration models. Wider adoption can improve our inferences about species distributions and the dynamic processes that lead to distributional shifts.

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Section: Creating a More Flexible And General Framework For Data Intementioning

confidence: 99%

The recent past and promising future for data integration methods to estimate species’ distributions

et al. 2019

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“…, Parry et al. ), and has been identified in other studies as a component in demography, colonization, and persistence probabilities (Muths , Miller ). Snowpack increases the stability and predictability of thermal conditions under snow (Pauli et al.…”

Section: Discussionmentioning

confidence: 87%

Twenty‐nine years of population dynamics in a small‐bodied montane amphibian

et al. 2018

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Identifying population declines before they reach crisis proportions is imperative given the current global decline in vertebrate fauna and associated challenges and expense of recovery. Understanding life histories and how the environment influences demography are critical aspects of this challenge, as is determining the biological relevance of covariates that are best supported by the data. We used 29 yr of data on chorus frogs at two sites to estimate demographic parameters, examine life history, assess weather‐related covariates, and determine the magnitude of process variation in target parameters. Average estimates of survival probabilities were 0.51 (Standard Error [SE] = 0.04) and 0.43 (SE = 0.04), and average estimates of recruitment probabilities were 0.64 (SE = 0.07) and 0.44 (SE = 0.04). Process variation accounted for ≥76% of the total temporal variation in both parameters at one pond and in survival probability alone at the other, suggesting that the covariates in our top models were explaining predominantly process rather than sampling variation. Estimates of population growth rates indicated a declining population at one pond (i.e., negative population growth rates in 15 of 18 yr), and comparisons with historical estimates suggested declines in survival probability at the other. The amount of deviance explained was low, providing little support for the influence of covariates on target parameters, despite model selection support. Synthesis and applications: This analysis illustrates the value of disentangling components of variance when assessing demographic drivers and highlights the need for adequate demographic information in assigning conservation labels.

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“…, Miller et al. ). Wetlands are often the principal breeding habitat for amphibians and these habitats are dynamic, fluctuating between wet and dry states depending on annual and seasonal meteorological conditions.…”

Section: Introductionmentioning

confidence: 99%

“…In response to demonstrated global (Houlahan et al 2000, Stuart et al 2004) and continental-scale declines (Adams et al 2013), researchers have investigated the influence of several determinants (e.g., disease, drought, and human influences) on global amphibian diversity (Hof et al 2011) and trends in amphibian occurrence in North America (Grant et al 2016, Davis et al 2017, Miller et al 2018. To date, no single stressor has been universally linked to amphibian decline.…”

Section: Introductionmentioning

confidence: 99%

“…There is mounting evidence that climate-related weather characteristics (hereafter referred to as climate drivers) should be explicitly considered when examining amphibian occupancy dynamics (Cayuela et al 2012, Ray et al 2016, Greenberg et al 2017, Miller et al 2018. Wetlands are often the principal breeding habitat for amphibians and these habitats are dynamic, fluctuating between wet and dry states depending on annual and seasonal meteorological conditions.…”

Section: Introductionmentioning

confidence: 99%

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Multistate occupancy modeling improves understanding of amphibian breeding dynamics in the Greater Yellowstone Area

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et al. 2019

Ecological Applications

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Discerning the determinants of species occurrence across landscapes is fundamental to their conservation and management. In spatially and climatologically complex landscapes, explaining the dynamics of occurrence can lead to improved understanding of short‐ vs. long‐term trends and offer novel insight on local vs. regional change. We examined the changes in occupancy for two species of anurans with different life histories over a decade using hundreds of wetland sites in Yellowstone and Grand Teton National Parks. To account for the joint dynamics of wetland drying and amphibian breeding, we adopted a multistate occupancy model as a means to investigate mechanistic relationships of observed occurrence patterns with climatological drivers of wetland hydrologic variability. This approach allowed us to decompose occupancy dynamics into habitat changes caused by wetland drying and amphibian breeding activity, conditional on available water and previous breeding state. Over our 10‐yr time series, we observed considerable variability in climate drivers and the proportion of dry wetlands. Boreal chorus frogs (Pseudacris maculata) were more responsive to changes in wetland inundation status than Columbia spotted frogs (Rana luteiventris), as indicated by higher breeding colonization probabilities under favorable (wet) conditions. Both species had high probabilities of breeding persistence in permanently inundated wetlands with prior breeding. Despite the absence of multi‐year drought in our time series, mechanistic relationships described here offer insights on how future climate variation may result in reduced and/or shifted occurrence patterns for pond‐breeding anurans in the Greater Yellowstone Area. Further, our modeling approach may prove valuable in evaluating determinants of occurrence for other species that are dependent on wetlands or other dynamic habitats.

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Quantifying climate sensitivity and climate-driven change in North American amphibian communities

Cited by 97 publications

References 62 publications

The recent past and promising future for data integration methods to estimate species’ distributions

The recent past and promising future for data integration methods to estimate species’ distributions

Twenty‐nine years of population dynamics in a small‐bodied montane amphibian

Multistate occupancy modeling improves understanding of amphibian breeding dynamics in the Greater Yellowstone Area

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