Space-time species distribution modeling for opportunistic presence-only data: a case study of passerines in a protected area - Archive ouverte HAL
Pré-Publication, Document De Travail (Preprint/Prepublication) Année : 2024

Space-time species distribution modeling for opportunistic presence-only data: a case study of passerines in a protected area

Florian Lasgorceux
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Julien Papaïx
Thomas Opitz

Résumé

In recent decades, Europe has experienced a significant decline in common bird species, particularly farmland species, due to anthropic pressures like agricultural intensification. Protected areas, such as the Écrins National Park in France, play a crucial role in mitigating these impacts. In this study, we utilized an opportunistic presence-only dataset of passerine occurrences to evaluate the impact of protected areas on passerine trends. The data, gathered by skilled rangers from Écrins National Park, were used for spatio-temporal modeling to assess the target-group relative abundance of 76 passerine species across a regular grid, with aggregated occurrences per spatio-temporal cell serving as a proxy for sampling effort. The model demonstrated good calibration for most species, with AUC values from cross-validation scenarios exceeding 0.8 in most cases. The model also effectively distinguished habitat preferences and migratory status. Additionally, we compared trends in target-group relative abundance over 2001–2019 in the Écrins National Park with those across France using the French Breeding Bird Survey (STOC program) for 59 common species. Our analysis revealed that forest specialist species benefited the most from protected areas, farmland species decreased more slowly, and high-elevation specialist species generally decreased. Though, some results should be interpreted with care since our assumption of a homogeneous reporting rate across target-group species may be too strong for some very common species. Our findings illustrate that the extensive spatio-temporal resolution provided by opportunistic presence-only data offers valuable insights into biological phenomena and their trends, while reducing the need for other data sources to determine sampling effort proxies. Similar datasets from various protected areas could serve as powerful tools for assessing the effectiveness of conservation policies.
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Dates et versions

hal-04616332 , version 1 (18-06-2024)
hal-04616332 , version 2 (01-07-2024)

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Florian Lasgorceux, Julien Papaïx, Yoann Bunz, Damien Combrisson, Thomas Opitz. Space-time species distribution modeling for opportunistic presence-only data: a case study of passerines in a protected area. 2024. ⟨hal-04616332v1⟩
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