Search USGSSearch

USGS · 70217043

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

Abstract

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.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Erin L. Muths, R D Scherer, S M Amburgey, PS Corn. 2018-12-04. Twenty-nine years of population dynamics in a small-bodied montane amphibian. https://doi.org/10.1002/ecs2.2522

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Evaluating harvest liberalization strategies on population dynamics of southern latitude temperate-breeding Canada geese

The recovery of the Canada goose ( Branta canadensis ) is one of North America's greatest conservation success stories. Today, continental abundance of temperate-breeding Canada geese (those breeding in southern Canada and lower 48 states in the United States) greatly exceeds historical levels. As a result of increased abundance, human–goose conflicts have also increased, ranging from private and agricultural property damage to human health concerns. Managers have primarily attempted to lower Canada goose populations using hunter harvest via liberalized hunting regulations (increased bag limits and total hunting days). To evaluate the effectiveness of harvest strategies for temperate-breeding Canada geese, managers need a better understanding of how liberalized hunting regulations affect population dynamics. We estimated survival and harvest probabilities, abundance, and recovery distribution of temperate-breeding Canada geese banded in Arkansas, USA, during 2005–2020. We found that adult harvest probabilities declined overall during the study and adult survival probabilities increased. Annual abundances of juvenile geese (≤1 year old) declined during the study, whereas there was no detectable trend in abundance of the adult population over time. Most Canada geese breeding in Arkansas were shot in Arkansas, indicating potential for population dynamics to be influenced largely by state-specific harvest regulations. However, our results suggest that harvest liberalization as a management tool may have limited capacity to further influence population dynamics of Canada geese. Declines in productivity and recruitment likely had a greater influence on the similar observed declines in juvenile and adult abundances, respectively, during our study. More research is needed to better understand the ecological mechanism affecting the population dynamics of Canada geese in both urban and rural environments.

Arkansas

Predicted habitat use for reintroduced grizzly bears in the transboundary North Cascades ecosystem

Grizzly bears ( Ursus arctos ) were once numerous in the North Cascades transboundary region of Washington State (United States) and British Columbia (Canada); however, few remain today. To support ongoing reintroduction evaluations, we used simulations based on movement models developed in the Northern Rocky Mountains to predict habitat use by a small founding group of grizzly bears in the North Cascades during the early stages of reintroduction. These simulations represent movements across a spatially explicit landscape based on individual-specific selection and movement parameters. We first evaluated predictive performance in three nearby populations of grizzly bears in the Squamish-Lillooet, McGillvary Mountains, and North Stein-Nahatlatch regions of the Coast Mountains, British Columbia. After applying an elevation-based calibration, predicted habitat use showed strong agreement with GPS location data from 73 collared bears. Across population–sex subgroups, Spearman rank correlations were ≥0.95, with 69.2%–83.3% of locations occurring within the top five habitat classes (covering 50% of mapped habitat) and 17.1%–36.2% in the top class (representing 10%). Overall, 24.5% and 77.9% of locations fell within the top class and top five classes, respectively. Seasonal validation showed strongest predictive performance from May to late summer or fall. Model predictions for the North Cascades indicate that habitat use during early reintroduction is likely to be concentrated in the central and northern mountainous portions of the ecosystem along the US–Canada border. These maps can guide recovery planning when no local bear data are yet available in the North Cascades transboundary region.

British Columbia, Washington

Holistic understanding of uncertainty for collaborative and proactive global change decision making

Global change is accelerating and pushing the planet's ecosystems beyond the range of historical observations, creating increasing uncertainty in future system conditions. Despite general agreement that proactive environmental action is warranted, environmental decision conversations often end by identifying additional data needed to reduce uncertainty before taking novel action. Given the inherent uncertainty in complex issues such as global change, quantitative data alone are likely insufficient to support proactive environmental action. Holistic understanding of uncertainty includes scientific quantification of uncertainty paired with emotional responses and transcendental grounding to help people work together toward proactive action in uncertain decision contexts. Holistic understanding arises from the four ways in which humans perceive the world, termed the Four Realms: Physical (e.g., how I observe), Mental (e.g., how I think), Emotional (e.g., how I feel), and Transcendental (e.g., how I connect to greater meaning or purpose). Environmental scientists and decision makers are generally trained in Physical and Mental Realm observation and analysis, but not in how to apply Emotional and Transcendental Realm understanding. Emotional and Transcendental processing occurs in scientists and decision makers whether it is acknowledged or not and contributes to different people interpreting the same information in different ways. Thus, when the role of Emotional and Transcendental Realms in an individual's interpretation process is not understood, it can derail conversations and perpetuate the status quo. Explicitly recognizing all Four Realms can bring people together across differences and inspire shared, novel decision making even in increasing uncertainty. To illustrate the benefits of holistic understanding, we share stories from our experiences in environmental decision contexts. Because accessing the Four Realms requires experiential and embodied techniques, while still relying on core scientific tenets of observation and analysis, we also present techniques for readers to learn to feel their own emotional understanding and connect to their own transcendental understanding. Holistic understanding can enhance data-driven decisions by recognizing that human responses to uncertainty inherently include interactions between emotions, thoughts, transcendental connections, and behavior. Ultimately, holistic understanding can help anchor data-driven decisions in intra- and interpersonal connections, inspiring action in the face of uncertainty.

Ecosphere