Wild bee diversity of the National Park of the Semois Valley (Belgium)

Biodiversity Data Journal, Journal Year: 2025, Volume and Issue: 13

Published: Feb. 12, 2025

Wild bees are essential pollinators, yet their decline due to human activities threatens ecosystem stability. Protecting these pollinators requires a detailed understanding of both diversity and distribution. In Belgium, the recently-established Semois Valley National Park (SVNP) is located in region with limited bee sampling data this study aims identify habitats most suitable bees, especially for threatened species. Over five months, we surveyed 32 sites collected total 1,119 specimens belonging 120 Twenty-two observed species listed as Belgium according last Red List published 2019 country, four them being Critically Endangered. Our findings indicate that mesic grasslands support highest diversity, well number results underscore need conservation efforts aimed at maintaining richness region. Effective biodiversity preservation will require enhanced habitat management strategies tailored species' ecological requirements.

Language: Английский

Synthetic control methods enable stronger causal inference using participatory science data in cities

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: March 21, 2025

As urban populations grow, conserving biodiversity within cities is increasingly vital and of global policy interest. However, environments pose unique challenges for understanding drivers change, as fragmented land ownership makes traditional monitoring randomized experiments logistically difficult. While participatory science platforms like iNaturalist offer a promising data source by providing extensive from areas, inferring causality remains challenging due to confounding factors in observational data. To leverage these advances, we framework that combines records with synthetic control methods, quasi-experimental approach. We demonstrate this approach case study assessing the impact Hurricane Ida (2021) on bee Philadelphia, USA. The estimated 9.4% decline abundance two years post-event. In contrast, three conventional ecological analyses—an interrupted time series regression, before-after comparison, (BACI) design—failed detect decline, naively detecting an increase unaccounted temporal trends. Synthetic methods powerful tool estimating citywide responses climate events interventions, enhancing utility ecology.

Language: Английский

The Field Automatic Insect Recognition‐Device—A Non‐Lethal Semi‐Automatic Malaise Trap for Insect Biodiversity Monitoring: Proof of Concept

Ecology and Evolution, Journal Year: 2024, Volume and Issue: 14(12)

Published: Nov. 28, 2024

ABSTRACT Field monitoring plays a crucial role in understanding insect dynamics within ecosystems. It facilitates pest distribution assessment, control measure evaluation, and prediction of outbreaks. Additionally, it provides important information on bioindicators with which the state biodiversity ecological integrity specific habitats ecosystems can be accurately assessed. However, traditional systems face various difficulties, leading to limited temporal spatial resolution obtained information. Despite recent advancements automatic traps, also called e‐traps, most these focus exclusively studying agricultural pests, rendering them unsuitable for diverse populations. To address this issue, we introduce Automatic Insect Recognition (FAIR)‐Device, novel nonlethal field tool that relies semi‐automatic image capture species identification using artificial intelligence via iNaturalist platform. Our objective was develop an automatic, cost‐effective, nonspecific solution capable providing high‐resolution data assessing diversity. During 26‐day proof‐of‐concept FAIR‐Device recorded 24.8 GB video, identifying 431 individuals from 9 orders, 50 families, 69 genera. While improvements are possible, our device demonstrated its potential as biodiversity. Looking ahead, envision new such e‐traps valuable tools real‐time monitoring, offering unprecedented insights research practices.

Language: Английский