Biodiversity modeling advances will improve predictions of nature’s contributions to people

Kass, Jamie M.; Fukaya, Keiichi; Thuiller, Wilfried; Mori, Akira S.

doi:10.1016/j.tree.2023.10.011

Cited by 7 publications

(3 citation statements)

References 101 publications

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“…For financial disclosures, companies will assess how their activities rely on ecosystem services and their opportunities for protecting/recovering nature ( TNFD, 2023 ). By incorporating taxon-specific ecosystem services, multifaceted ecosystem services can be preliminarily screened ( Kass et al, 2024 ). For example, based on estimated distributions of bumblebees or insectivorous animals, the functioning of pollination services or pest regulation services might be inferred.…”

Section: Discussionmentioning

confidence: 99%

Boosting biodiversity monitoring using smartphone-driven, rapidly accumulating community-sourced data

Atsumi,

Nishida,

Ushio

et al. 2024

eLife

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Ecosystem services, which derive in part from biological diversity, are a fundamental support for human society. However, human activities are causing harm to biodiversity, ultimately endangering these critical ecosystem services. Halting nature loss and mitigating these impacts necessitates comprehensive biodiversity distribution data, a requirement for implementing the Kunming-Montreal Global Biodiversity Framework. To efficiently collect species observations from the public, we launched the ‘ Biome ’ mobile application in Japan. By employing species identification algorithms and gamification elements, the app has gathered >6M observations since its launch in 2019. However, community-sourced data often exhibit spatial and taxonomic biases. Species distribution models (SDMs) enable infer species distribution while accommodating such bias. We investigated Biome data’s quality and how incorporating the data influences the performance of SDMs. Species identification accuracy exceeds 95% for birds, reptiles, mammals, and amphibians, but seed plants, molluscs, and fishes scored below 90%. The distributions of 132 terrestrial plants and animals across Japan were modeled, and their accuracy was improved by incorporating our data into traditional survey data. For endangered species, traditional survey data required >2,000 records to build accurate models (Boyce index ≥ 0.9), though only ca.300 records were required when the two data sources were blended. The unique data distributions may explain this improvement: Biome data covers urban-natural gradients uniformly, while traditional data is biased towards natural areas. Combining multiple data sources offers insights into species distributions across Japan, aiding protected area designation and ecosystem service assessment. Providing a platform to accumulate community-sourced distribution data and improving data processing protocol will contribute to not only conserving natural ecosystems but also detecting species distribution changes and testing ecological theories.

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Section: Discussionmentioning

confidence: 99%

Boosting biodiversity monitoring using smartphone-driven, rapidly accumulating community-sourced data

Atsumi,

Nishida,

Ushio

et al. 2024

eLife

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“…Second, recent developments have highlighted several perspectives of concomitant conservation prioritization of species diversity and NCPs 60,68,69 . Although biodiversity highly contributes to ecosystem functioning and services 70 , their conservation demands may differ 71,72 .…”

Section: Articlementioning

confidence: 99%

Transnational conservation to anticipate future plant shifts in Europe

Chauvier-Mendes,

Pollock,

Verburg

et al. 2024

Nat Ecol Evol

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To meet the COP15 biodiversity framework in the European Union (EU), one target is to protect 30% of its land by 2030 through a resilient transnational conservation network. The European Alps are a key hub of this network hosting some of the most extensive natural areas and biodiversity hotspots in Europe. Here we assess the robustness of the current European reserve network to safeguard the European Alps’ flora by 2080 using semi-mechanistic simulations. We first highlight that the current network needs strong readjustments as it does not capture biodiversity patterns as well as our conservation simulations. Overall, we predict a strong shift in conservation need through time along latitudes, and from lower to higher elevations as plants migrate upslope and shrink their distribution. While increasing species, trait and evolutionary diversity, migration could also threaten 70% of the resident flora. In the face of global changes, the future European reserve network will need to ensure strong elevation and latitudinal connections to complementarily protect multifaceted biodiversity beyond national borders.

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“…For financial disclosures, companies will assess how their activities rely on ecosystem services and their opportunities for protecting/recovering nature (TNFD, 2023). By incorporating taxon-specific ecosystem services, multifaceted ecosystem services can be preliminarily screened (Kass et al, 2023). For example, based on estimated distributions of bumblebees or insectivorous animals, the functioning of pollination services or pest regulation services might be inferred.…”

Section: Future Directionsmentioning

confidence: 99%

Boosting biodiversity monitoring using smartphone-driven, rapidly accumulating community-sourced data

Atsumi,

Nishida,

Ushio

et al. 2023

Preprint

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Kunming-Montreal Global Biodiversity Framework increased the demand for biodiversity distribution data. To gather species observation from the public, we introduced a mobile application called 'Biome' in Japan. By employing species identification algorithms and gamification elements, Biome has gathered >5M observations since its launch in 2019. However, cloud-sourced data often exhibit spatial and taxonomic biases. Species distribution models (SDMs) enable infer species distribution while accommodating such bias. We investigated Biome data's quality and how incorporating Biome data influences the performance of SDMs. Species identification accuracy of Biome data exceeds 95% for birds, reptiles, mammals, and amphibians, but seed plants, molluscs, and fishes scored below 90%. The distributions of 132 terrestrial plants and animals across Japan were modeled, and their accuracy was improved by incorporating Biome data into traditional survey data. For endangered species, traditional survey data required >2,000 records to build accurate models (Boyce index >0.9), though only ca.300 records were required when Biome was blended. The unique data distributions may explain this improvement: Biome data covers urban-natural gradients uniformly, while traditional data is biased towards natural areas. Combining multiple data sources offers insights into species distributions across Japan, aiding protected area designation and ecosystem service assessment.

show abstract

Biodiversity modeling advances will improve predictions of nature’s contributions to people

Cited by 7 publications

References 101 publications

Boosting biodiversity monitoring using smartphone-driven, rapidly accumulating community-sourced data

Boosting biodiversity monitoring using smartphone-driven, rapidly accumulating community-sourced data

Transnational conservation to anticipate future plant shifts in Europe

Boosting biodiversity monitoring using smartphone-driven, rapidly accumulating community-sourced data

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