Dataset Information

A simulation study of the use of temporal occupancy for identifying core and transient species.

ABSTRACT: Transient species, which do not maintain self-sustaining populations in a system where they are observed, are ubiquitous in nature and their presence often impacts the interpretation of ecological patterns and processes. Identifying transient species from temporal occupancy, the proportion of time a species is observed at a given site over a time series, is subject to classification errors as a result of imperfect detection and source-sink dynamics. We use a simulation-based approach to assess how often errors in detection or classification occur in order to validate the use of temporal occupancy as a metric for inferring whether a species is a core or transient member of a community. We found that low detection increases error in the classification of core species, while high habitat heterogeneity and high detection increase error in classification of transient species. These findings confirm that temporal occupancy is a valid metric for inferring whether a species can maintain a self-sustaining population, but imperfect detection, low abundance, and highly heterogeneous landscapes may yield high misclassification rates.

SUBMITTER: Snell Taylor S

PROVIDER: S-EPMC7584212 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A simulation study of the use of temporal occupancy for identifying core and transient species.

Snell Taylor Sara S Coyle Jessica R JR White Ethan P EP Hurlbert Allen H AH

PloS one 20201023 10

Transient species, which do not maintain self-sustaining populations in a system where they are observed, are ubiquitous in nature and their presence often impacts the interpretation of ecological patterns and processes. Identifying transient species from temporal occupancy, the proportion of time a species is observed at a given site over a time series, is subject to classification errors as a result of imperfect detection and source-sink dynamics. We use a simulation-based approach to assess h ...[more]

PMID: 33095844

Similar Datasets

Project description:Distribution models are increasingly being used to understand how landscape and climatic changes are affecting the processes driving spatial and temporal distributions of plants and animals. However, many modeling efforts ignore the dynamic processes that drive distributional patterns at different scales, which may result in misleading inference about the factors influencing species distributions. Current occupancy models allow estimation of occupancy at different scales and, separately, estimation of immigration and emigration. However, joint estimation of local extinction, colonization, and occupancy within a multi-scale model is currently unpublished. We extended multi-scale models to account for the dynamic processes governing species distributions, while concurrently modeling local-scale availability. We fit the model to data for lark buntings and chestnut-collared longspurs in the Great Plains, USA, collected under the Integrated Monitoring in Bird Conservation Regions program. We investigate how the amount of grassland and shrubland and annual vegetation conditions affect bird occupancy dynamics and local vegetation structure affects fine-scale occupancy. Buntings were prevalent and longspurs rare in our study area, but both species were locally prevalent when present. Buntings colonized sites with preferred habitat configurations, longspurs colonized a wider range of landscape conditions, and site persistence of both was higher at sites with greener vegetation. Turnover rates were high for both species, quantifying the nomadic behavior of the species. Our model allows researchers to jointly investigate temporal dynamics of species distributions and hierarchical habitat use. Our results indicate that grassland birds respond to different covariates at landscape and local scales suggesting different conservation goals at each scale. High turnover rates of these species highlight the need to account for the dynamics of nomadic species, and our model can help inform how to coordinate management efforts to provide appropriate habitat configurations at the landscape scale and provide habitat targets for local managers.

Project description:Abundance-occupancy (A-O) relationships are widely documented for many organismal groups and regions, and have been used to gain an understanding of regional population and community trends. Monitoring changes in abundance and occupancy over time may be what is required to document changes in conservation status and needs for some species, communities, or areas.We hypothesize that if there is a higher proportion of declining species in one group of species compared with another (e.g., migratory species vs. permanent residents), then a consequence of that difference will be vastly different abundance-occupancy relationships. If this difference persists through time, then the resulting A-O relationships between the groups will continue to diverge.For neotropical migrants, short-distance migrants, and permanent resident birds of North America, we assess the numbers of declining species over 1969-2009. We further test for differences in the A-O relationship across these three groups, and in rates of change in abundance and occupancy separately.We find significant differences in numbers of declining species across the migratory groups, a significant decline in the A-O relationship for permanent residents, a significant increase for Neotropical migrants, and a nonsignificant decline for short-distance migrants over the 40 years. Further, abundances are not changing at different rates but occupancies are consistently greater over time for neotropical migrants versus permanent residents, likely driving the changes in A-O relationships observed.In these analyses, we documented changing A-O trends for different groups of species, over a relatively long time period for ecological studies, one of only a few studies to examine A-O relationships over time. Further, we have shown that a temporally unvarying abundance-occupancy relationship is not universal, and we posit that variability in A-O relationships is due to human impacts on habitats, coupled with variation in species' abilities to respond to human impacts.

Dataset Information

A simulation study of the use of temporal occupancy for identifying core and transient species.

Publications

A simulation study of the use of temporal occupancy for identifying core and transient species.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets