Sex‐specific population dynamics and demography of capercaillie (<i>Tetrao urogallus</i> L.) in a patchy environment

Augustine, Ben C.; Kéry, Marc; Marin, Juanita Olano; Mollet, Pierre; Pasinelli, Gilberto; Sutherland, Chris

doi:10.1002/1438-390x.12031

Cited by 20 publications

(15 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Into the Future What if, akin to weather maps, we could forecast the dynamics of wildlife populations across space and time? The OPSCR model can be used to project density and abundance under different conditions and intervention scenarios (35,36) (Fig. 4).…”

Section: Spatial Population Dynamicsmentioning

confidence: 99%

Estimating and forecasting spatial population dynamics of apex predators using transnational genetic monitoring

Bischof

Milleret

Dupont

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

154

View full text Add to dashboard Cite

The ongoing recovery of terrestrial large carnivores in North America and Europe is accompanied by intense controversy. On the one hand, reestablishment of large carnivores entails a recovery of their most important ecological role, predation. On the other hand, societies are struggling to relearn how to live with apex predators that kill livestock, compete for game species, and occasionally injure or kill people. Those responsible for managing these species and mitigating conflict often lack fundamental information due to a long-standing challenge in ecology: How do we draw robust population-level inferences for elusive animals spread over immense areas? Here we showcase the application of an effective tool for spatially explicit tracking and forecasting of wildlife population dynamics at scales that are relevant to management and conservation. We analyzed the world’s largest dataset on carnivores comprising more than 35,000 noninvasively obtained DNA samples from over 6,000 individual brown bears (Ursus arctos), gray wolves (Canis lupus), and wolverines (Gulo gulo). Our analyses took into account that not all individuals are detected and, even if detected, their fates are not always known. We show unequivocal quantitative evidence of large carnivore recovery in northern Europe, juxtaposed with the finding that humans are the single-most important factor driving the dynamics of these apex predators. We present maps and forecasts of the spatiotemporal dynamics of large carnivore populations, transcending national boundaries and management regimes.

show abstract

Section: Spatial Population Dynamicsmentioning

confidence: 99%

Estimating and forecasting spatial population dynamics of apex predators using transnational genetic monitoring

Bischof

Milleret

Dupont

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

154

View full text Add to dashboard Cite

show abstract

“…The effect of interruptions on precision was generally less pronounced when the gap in the time series was framed by several consecutive sampled occasions (11011). Although OPSCR models have already been used to infer abundance in the presence of interruptions (Chandler and Clark 2014, Augustine et al 2019), our study is the first to explore the conditions under which reliable abundance inferences can be obtained when SCR data time series include temporal gaps in sampling.…”

Section: Discussionmentioning

confidence: 99%

Estimating abundance with interruptions in data collection using open population spatial capture–recapture models

et al. 2020

View full text Add to dashboard Cite

The estimation of population size remains one of the primary goals and challenges in ecology and provides a basis for debate and policy in wildlife management. Despite the development of efficient noninvasive sampling methods and robust statistical tools to estimate abundance, the maintenance of field sampling is still subject to economic and logistic constraints. These can result in intentional or unintentional interruptions in sampling and cause gaps in data time series, posing a challenge to abundance estimation, and ultimately conservation and management decisions. We applied an open population spatial capture–recapture (OPSCR) model to simulations and a real‐life case study to test the reliability of abundance inference to interruptions in data collection. Using individual detections occurring over consecutive sampling occasions, OPSCR models allow the estimation of abundance while accounting for lack of demographic and geographic closure between occasions. First, we simulated sampling data with interruptions in field sampling of different lengths and timing and checked the performance of an OPSCR model in deriving abundance for species with slow and intermediate life‐history strategies. Next, we introduced artificial sampling interruptions of various magnitudes and timing to a five‐year noninvasive monitoring data set of wolverines (Gulo gulo) in Norway and quantified the consequences for OPSCR model predictions. Inferences from OPSCR models were reliable even with temporal interruptions in monitoring. Interruption did not cause systematic bias, but increased uncertainty. Interruptions occurring at occasions near the beginning and the end of the sampling period caused higher uncertainty. The loss in precision was more severe for species with a faster life‐history strategy. OPSCR allows monitoring studies to provide contiguous abundance estimates to managers, stakeholders, and policy makers even when data are noncontiguous. OPSCR models do not only help cope with unintentional interruptions during sampling but also offer opportunities for using intentional sampling interruptions during the design of cost‐effective population surveys.

show abstract

Section: Discussionmentioning

confidence: 99%

“…The use of data collected over multiple occasions and propagation of individual information on spatial location and demographic status across time steps should help OPSCR bridge gaps in data collection, allowing inferences about abundance during occasions with sampling interruption. Although OPSCR models have already been used to infer abundance at occasions without individual detections (Chandler and Clark 2014, Augustine et al 2019), there is a lack of knowledge about the quantitative consequences of sampling interruptions under different conditions (i.e. multiple interruptions, different life history characteristics).…”

Section: Introductionmentioning

confidence: 99%

Estimating abundance with interruptions in data collection using open population spatial capture-recapture models

Milleret

Dupont

Chipperfield

et al. 2019

Preprint

View full text Add to dashboard Cite

The estimation of population size remains one of the primary goals and challenges in ecology and provides a basis for debate and policy in wildlife management. Despite the development of efficient non-invasive sampling methods and robust statistical tools to estimate abundance, maintenance of field sampling is still subject to economic and logistic constraints. These can result in intentional or unintentional interruptions in sampling and cause gaps in data time series, posing a challenge to abundance estimation, and ultimately conservation and management decisions. We applied an open population spatial capture-recapture (OPSCR) model to simulations and a real case study to test the reliability of abundance inferences models to interruption in data collection. Using individual detections occurring over consecutive sampling occasions, OPSCR models allow the estimation of abundance from individual detection data while accounting for lack of demographic and geographic closure between occasions. First, we simulated sampling data with interruptions in field sampling of different lengths and timing. We checked the performance of an OPSCR model in deriving abundance for species with slow and intermediate life history strategies. Finally, we introduced artificial sampling interruptions of various magnitudes and timing to a five-year non-invasive monitoring data set of wolverines (Gulo gulo) in Norway and quantified the consequences for OPSCR model predictions. Inferences from OPSCR models were reliable even with temporal interruptions in monitoring. Interruption did not cause any systematic bias, but increased uncertainty. Interruptions occurring at occasions towards the beginning and the end of the sampling caused higher uncertainty. The loss in precision was more severe for species with a faster life history strategy. We provide a reliable framework to estimate abundance even in the presence of sampling interruptions. OPSCR allows monitoring studies to provide contiguous abundance estimates to managers, stakeholders, and policy makers even when data are non-contiguous. OPSCR models do not only help cope with unintentional interruptions during sampling but also offer opportunities for using intentional sampling interruptions during the design of cost-effective population surveys.

show abstract

Sex‐specific population dynamics and demography of capercaillie (Tetrao urogallus L.) in a patchy environment

Cited by 20 publications

References 34 publications

Estimating and forecasting spatial population dynamics of apex predators using transnational genetic monitoring

Estimating and forecasting spatial population dynamics of apex predators using transnational genetic monitoring

Estimating abundance with interruptions in data collection using open population spatial capture–recapture models

Estimating abundance with interruptions in data collection using open population spatial capture-recapture models

Contact Info

Product

Resources

About