Geology topics

Thierry A. Chambert

Publications and source records attributed to Thierry A. Chambert.

6 recordsLinked to original sources

USGS2017

Heterogeneous responses of temperate-zone amphibian populations to climate change complicates conservation planning

The pervasive and unabated nature of global amphibian declines suggests common demographic responses to a given driver, and quantification of major drivers and responses could inform broad-scale conservation actions. We explored the influence of climate on demographic parameters (i.e., changes in the probabilities of survival and recruitment) using 31 datasets from temperate zone amphibian populations (North America and Europe) with more than a decade of observations each. There was evidence for an influence of climate on population demographic rates, but the direction and magnitude of responses to climate drivers was highly variable among taxa and among populations within taxa. These results reveal that climate drivers interact with variation in life-history traits and population-specific attributes resulting in a diversity of responses. This heterogeneity complicates the identification of conservation ‘rules of thumb’ for these taxa, and supports the notion of local focus as the most effective approach to overcome global-scale conservation challenges.

Scientific Reports↗

USGS2017

A new framework for analysing automated acoustic species detection data: Occupancy estimation and optimization of recordings post-processing

The development and use of automated species-detection technologies, such as acoustic recorders, for monitoring wildlife are rapidly expanding. Automated classification algorithms provide a cost- and time-effective means to process information-rich data, but often at the cost of additional detection errors. Appropriate methods are necessary to analyse such data while dealing with the different types of detection errors. We developed a hierarchical modelling framework for estimating species occupancy from automated species-detection data. We explore design and optimization of data post-processing procedures to account for detection errors and generate accurate estimates. Our proposed method accounts for both imperfect detection and false positive errors and utilizes information about both occurrence and abundance of detections to improve estimation. Using simulations, we show that our method provides much more accurate estimates than models ignoring the abundance of detections. The same findings are reached when we apply the methods to two real datasets on North American frogs surveyed with acoustic recorders. When false positives occur, estimator accuracy can be improved when a subset of detections produced by the classification algorithm is post-validated by a human observer. We use simulations to investigate the relationship between accuracy and effort spent on post-validation, and found that very accurate occupancy estimates can be obtained with as little as 1% of data being validated. Automated monitoring of wildlife provides opportunity and challenges. Our methods for analysing automated species-detection data help to meet key challenges unique to these data and will prove useful for many wildlife monitoring programs.

Methods in Ecology and Evolution↗

USGS2016

Quantitative evidence for the effects of multiple drivers on continental-scale amphibian declines

Since amphibian declines were first proposed as a global phenomenon over a quarter century ago, the conservation community has made little progress in halting or reversing these trends. The early search for a “smoking gun” was replaced with the expectation that declines are caused by multiple drivers. While field observations and experiments have identified factors leading to increased local extinction risk, evidence for effects of these drivers is lacking at large spatial scales. Here, we use observations of 389 time-series of 83 species and complexes from 61 study areas across North America to test the effects of 4 of the major hypothesized drivers of declines. While we find that local amphibian populations are being lost from metapopulations at an average rate of 3.79% per year, these declines are not related to any particular threat at the continental scale; likewise the effect of each stressor is variable at regional scales. This result - that exposure to threats varies spatially, and populations vary in their response - provides little generality in the development of conservation strategies. Greater emphasis on local solutions to this globally shared phenomenon is needed.

Scientific Reports↗

USGS2016

Estimating abundance in the presence of species uncertainty

1.N-mixture models have become a popular method for estimating abundance of free-ranging animals that are not marked or identified individually. These models have been used on count data for single species that can be identified with certainty. However, co-occurring species often look similar during one or more life stages, making it difficult to assign species for all recorded captures. This uncertainty creates problems for estimating species-specific abundance and it can often limit life stages to which we can make inference. 2.We present a new extension of N-mixture models that accounts for species uncertainty. In addition to estimating site-specific abundances and detection probabilities, this model allows estimating probability of correct assignment of species identity. We implement this hierarchical model in a Bayesian framework and provide all code for running the model in BUGS-language programs. 3.We present an application of the model on count data from two sympatric freshwater fishes, the brook stickleback ( Culaea inconstans ) and the ninespine stickleback ( Pungitius pungitius ), ad illustrate implementation of covariate effects (habitat characteristics). In addition, we used a simulation study to validate the model and illustrate potential sample size issues. We also compared, for both real and simulated data, estimates provided by our model to those obtained by a simple N-mixture model when captures of unknown species identification were discarded. In the latter case, abundance estimates appeared highly biased and very imprecise, while our new model provided unbiased estimates with higher precision. 4.This extension of the N-mixture model should be useful for a wide variety of studies and taxa, as species uncertainty is a common issue. It should notably help improve investigation of abundance and vital rate characteristics of organisms’ early life stages, which are sometimes more difficult to identify than adults.

Methods in Ecology and Evolution↗

USGS2016

Distribution of the Sonora Tiger Salamander (Ambystoma mavortium stebbinsi) in Mexico

The Sonoran Tiger Salamander (Ambystoma mavortium stebbinsi Lowe, 1954) was listed as federally endangered in the USA in 1997 (USFWS 1997). In the USA, the distribution of A. mavortium stebbinsi is limited to the San Rafael Valley (approximately 567 km2), between the Sierra San Antonio (called the Patagonia Mountains in Arizona) and Huachuca Mountains, and south of the Canelo Hills, Arizona (Fig. 1). The USA listing was triggered by loss of natural wetland habitats, threats from invasive predators, frequent die-offs from disease, introgression with the introduced Barred Tiger Salamander (A. mavortium mavortium), and small range and number of breeding sites that increases susceptibility to stochastic events (USFWS 1997). Small population sizes and limited gene flow have caused inbreeding, which may further reduce population viability and the potential for recovery (Jones et al. 1988; Storfer et al. 2014).

Sonora↗

USGS2015

Testing hypotheses on distribution shifts and changes in phenology of imperfectly detectable species

With ongoing climate change, many species are expected to shift their spatial and temporal distributions. To document changes in species distribution and phenology, detection/non-detection data have proven very useful. Occupancy models provide a robust way to analyse such data, but inference is usually focused on species spatial distribution, not phenology. We present a multi-season extension of the staggered-entry occupancy model of Kendall et al . (2013, Ecology , 94, 610), which permits inference about the within-season patterns of species arrival and departure at sampling sites. The new model presented here allows investigation of species phenology and spatial distribution across years, as well as site extinction/colonization dynamics. We illustrate the model with two data sets on European migratory passerines and one data set on North American treefrogs. We show how to derive several additional phenological parameters, such as annual mean arrival and departure dates, from estimated arrival and departure probabilities. Given the extent of detection/non-detection data that are available, we believe that this modelling approach will prove very useful to further understand and predict species responses to climate change.

Methods in Ecology and Evolution↗