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Abstract Effective conservation requires understanding species’ abundance patterns and demographic rates across space and time. Ideally, such knowledge should be available for whole communities because variation in species’ dynamics can elucidate factors leading to biodiversity losses. However, collecting data to simultaneously estimate abundance and demographic rates of communities of species is often prohibitively time intensive and expensive. We developed a multispecies dynamicN‐occupancy model to estimate unbiased, community‐wide relative abundance and demographic rates. In this model, detection–nondetection data (e.g., repeated presence–absence surveys) are used to estimate species‐ and community‐level parameters and the effects of environmental factors. To validate our model, we conducted a simulation study to determine how and when such an approach can be valuable and found that our multispecies model outperformed comparable single‐species models in estimating abundance and demographic rates in many cases. Using data from a network of camera traps across tropical equatorial Africa, we then used our model to evaluate the statuses and trends of a forest‐dwelling antelope community. We estimated relative abundance, rates of recruitment (i.e., reproduction and immigration), and apparent survival probabilities for each species’ local population. The antelope community was fairly stable (although 17% of populations [species–park combinations] declined over the study period). Variation in apparent survival was linked more closely to differences among national parks than to individual species’ life histories. The multispecies dynamicN‐occupancy model requires only detection–nondetection data to evaluate the population dynamics of multiple sympatric species and can thus be a valuable tool for examining the reasons behind recent biodiversity loss.
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Pathways to global-change effects on biodiversity: new opportunities for dynamically forecasting demography and species interactions
In structured populations, persistence under environmental change may be particularly threatened when abiotic factors simultaneously negatively affect survival and reproduction of several life cycle stages, as opposed to a single stage. Such effects can then be exacerbated when species interactions generate reciprocal feedbacks between the demographic rates of the different species. Despite the importance of such demographic feedbacks, forecasts that account for them are limited as individual-based data on interacting species are perceived to be essential for such mechanistic forecasting—but are rarely available. Here, we first review the current shortcomings in assessing demographic feedbacks in population and community dynamics. We then present an overview of advances in statistical tools that provide an opportunity to leverage population-level data on abundances of multiple species to infer stage-specific demography. Lastly, we showcase a state-of-the-art Bayesian method to infer and project stage-specific survival and reproduction for several interacting species in a Mediterranean shrub community. This case study shows that climate change threatens populations most strongly by changing the interaction effects of conspecific and heterospecific neighbours on both juvenile and adult survival. Thus, the repurposing of multi-species abundance data for mechanistic forecasting can substantially improve our understanding of emerging threats on biodiversity.
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- Award ID(s):
- 2247042
- PAR ID:
- 10411163
- Date Published:
- Journal Name:
- Proceedings of the Royal Society B: Biological Sciences
- Volume:
- 290
- Issue:
- 1993
- ISSN:
- 0962-8452
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1098/rspb.2022.1494
