Diversity of European habitat types is correlated with geography more than climate and human pressure

Cervellini, Marco; Musciano, Michele Di; Zannini, Piero; Fattorini, Simone; Jíménez-Alfaro, Borja; Agrillo, Emiliano; Attorre, Fabio; Angelini, Pierangela; Beierkuhnlein, Carl; Casella, Laura; Field, Richard; Fischer, Jan‐Christopher; Genovesi, Piero; Hoffmann, Samuel; Irl, Severin D. H.; Nascimbene, Juri; Rocchini, Duccio; Steinbauer, Manuel J.; Vetaas, Ole R.; Chiarucci, Alessandro

doi:10.1002/ece3.8409

Cited by 21 publications

(6 citation statements)

References 155 publications

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“…), temperate and optimal climate for mammals, plenty of habitat diversity, prey abundance 3 , 28 – 33 Europe Portugal, Spain, United Kingdom, Ireland, France, Belgium, Netherlands, Germany, Denmark, Switzerland, Liechtenstein, Luxembourg, Austria, Italy, Slovenia, Poland, Sweden, Norway, Finland, Slovakia, Czechia, Hungary, Croatia, Romania, Serbia, Moldova, Ukraine, Bosnia and Herzegovina, Albania, Montenegro, Bulgaria, North Macedonia, Greece, Latvia, Lithuania, Estonia, Belarus Close to Anthropocene (parks, bird feeders, etc. ), temperate and optimal climate for mammals, plenty of habitat diversity, prey abundance 3 , 28 , 31 , 32 , 34 Central America Mexico, Guatemala, Belize, Honduras, El Salvador, Nicaragua, Costa Rica, Cuba, Haiti, Dominican Republic, Puerto Rico, several island states Pristine tropical habitats, extraordinary habitat diversity, a high number of different possible ecological niches, and prey abundance 35 – 38 Northwestern Africa Morocco, North Algeria, Tunisia High human impact (benefits of living close to the Anthropocene), ideal for arid-loving species (predominately ground squirrels) 39 , 40 Western Asia Georgia, Armenia, Azerbaijan, Iran, Pakistan, Afghanistan, Turkmenistan, Tajikistan, Kyrgyzstan, Kazakhstan, Western Russia, Northern India, Nepal, Bhutan High habitat diversity with significant altitude changes. Hotspots are often observed close to areas with high human impact 7 , 40 , 41 Most eastern Asia South Korea, Japan, Taiwan Close to Anthropocene (parks, bird feeders, etc.…”

Section: Resultsmentioning

confidence: 99%

“…Hotspots are often observed close to areas with high human impact 7 , 40 , 41 Most eastern Asia South Korea, Japan, Taiwan Close to Anthropocene (parks, bird feeders, etc. ), temperate and optimal climate for mammals, plenty of habitat diversity, prey abundance 3 , 28 , 31 , 32 , 34 Southeast Asia Vietnam, Thailand, Laos, Cambodia, Sri Lanka, Indonesia, Brunei, Malaysia, Philippines Pristine tropical habitats, extraordinary habitat diversity, a high number of different possible ecological niches, and prey abundance 42 – 48 Tropical Africa Ethiopia, Western Kenya, Uganda, Rwanda, Burundi, Tanzania, Congo, DRC, Equatorial Guinea, Cameroon, South Sudan, Southwestern CAR, Nigeria, Benin, Togo, Burkina Faso, Ghana, Ivory Coast, Liberia, Sierra Leone, Guinea Pristine tropical habitats, extraordinary habitat diversity, a high number of different possible ecological niches, and prey abundance 49 – 52 …”

Section: Resultsmentioning

confidence: 99%

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With super SDMs (machine learning, open access big data, and the cloud) towards more holistic global squirrel hotspots and coldspots

Steiner,

Huettmann,

Bryans

et al. 2024

Sci Rep

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Species-habitat associations are correlative, can be quantified, and used for powerful inference. Nowadays, Species Distribution Models (SDMs) play a big role, e.g. using Machine Learning and AI algorithms, but their best-available technical opportunities remain still not used for their potential e.g. in the policy sector. Here we present Super SDMs that invoke ML, OA Big Data, and the Cloud with a workflow for the best-possible inference for the 300 + global squirrel species. Such global Big Data models are especially important for the many marginalized squirrel species and the high number of endangered and data-deficient species in the world, specifically in tropical regions. While our work shows common issues with SDMs and the maxent algorithm (‘Shallow Learning'), here we present a multi-species Big Data SDM template for subsequent ensemble models and generic progress to tackle global species hotspot and coldspot assessments for a more inclusive and holistic inference.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

With super SDMs (machine learning, open access big data, and the cloud) towards more holistic global squirrel hotspots and coldspots

Steiner,

Huettmann,

Bryans

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Then, we ran as many GBM models as the combinations, increasing the n.trees value from 10,000 to 20,000 but keeping the train.fraction = 0.8 and the cv.folds = 10 fixed. We finally chose the set of parameters resulting in the lowest root mean square error (RMSE) ( Friedman, 2001 ; Greenwell, Boehmke & Cunningham, 2019 ; Cervellini et al, 2021 ). To investigate possible spatial autocorrelation in predictions from the optimized GBM model, which could have resulted for instance from sampling bias affecting N. lasiopterus occurrence data ( Roberts et al, 2017 ), we fitted an additional set of 10 GBM models, using the tuned set of parameters.…”

Section: Methodsmentioning

confidence: 99%

Assessing future shifts in habitat suitability and connectivity to old-growth forests to support the conservation of the endangered giant noctule

Iannella¹,

Masciulli²,

Cerasoli³

et al. 2022

PeerJ

Self Cite

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Background Suitable climate and availability of habitats for roosting, foraging, and dispersing are critical for the long-term persistence of bat species. The giant noctule (Nyctalus lasiopterus) represents one of the lesser-known European bats, especially regarding the environmental factors which shape its distribution. Methodology We integrated climate-based ecological niche models with information about topography and rivers’ network to model weighted suitability for N. lasiopterus in the western Palearctic. The weighted suitability map was then used to estimate connectivity among the distinct occurrence localities of N. lasiopterus, as well as from these latter towards European old-growth forests, under current conditions and different combinations of future timeframes (2030, 2050, 2070) and shared socioeconomic pathways (SSPs 3.70 and 5.85). Results Current weighted suitability is highest in Andalusia, northern Iberia, southwestern France, peninsular Italy, coastal Balkans and Anatolia, with dispersed suitable patches elsewhere. A north-eastward shift of weighted suitability emerges in the considered future scenarios, especially under SSP 5.85. The major current ecological corridors for N. lasiopterus are predicted within a ‘belt’ connecting northern Spain and southwestern France, as well as in the Italian Alps. However, following changes in weighted suitability, connectivity would increase in central-eastern Europe in the future. The bioclimatic niche of the western N. lasiopterus populations does not overlap with those of the central and eastern ones, and it only overlaps with climatic conditions characterizing old-growth forests in western Europe. Conclusions The outcomes of our analyses would help in designing specific conservation measures for the distinct groups of giant noctule populations, favoring the possibility of range expansion and movement towards forested habitats.

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“…We explain variation in GME in these countries in relation to two fundamental national characteristics: per capita gross domestic product (GDP) and area. One could also expect greater GME in southern Europe in recognition of greater habitat diversity, species endemicity and biodiversity hotspots than in the north 31 , 32 .…”

Section: Mainmentioning

confidence: 99%

Monitoring of species’ genetic diversity in Europe varies greatly and overlooks potential climate change impacts

Pearman,

Broennimann,

Aavik

et al. 2024

Nat Ecol Evol

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Genetic monitoring of populations currently attracts interest in the context of the Convention on Biological Diversity but needs long-term planning and investments. However, genetic diversity has been largely neglected in biodiversity monitoring, and when addressed, it is treated separately, detached from other conservation issues, such as habitat alteration due to climate change. We report an accounting of efforts to monitor population genetic diversity in Europe (genetic monitoring effort, GME), the evaluation of which can help guide future capacity building and collaboration towards areas most in need of expanded monitoring. Overlaying GME with areas where the ranges of selected species of conservation interest approach current and future climate niche limits helps identify whether GME coincides with anticipated climate change effects on biodiversity. Our analysis suggests that country area, financial resources and conservation policy influence GME, high values of which only partially match species’ joint patterns of limits to suitable climatic conditions. Populations at trailing climatic niche margins probably hold genetic diversity that is important for adaptation to changing climate. Our results illuminate the need in Europe for expanded investment in genetic monitoring across climate gradients occupied by focal species, a need arguably greatest in southeastern European countries. This need could be met in part by expanding the European Union’s Birds and Habitats Directives to fully address the conservation and monitoring of genetic diversity.

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Diversity of European habitat types is correlated with geography more than climate and human pressure

Abstract: This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 21 publications

References 155 publications

With super SDMs (machine learning, open access big data, and the cloud) towards more holistic global squirrel hotspots and coldspots

With super SDMs (machine learning, open access big data, and the cloud) towards more holistic global squirrel hotspots and coldspots

Assessing future shifts in habitat suitability and connectivity to old-growth forests to support the conservation of the endangered giant noctule

Monitoring of species’ genetic diversity in Europe varies greatly and overlooks potential climate change impacts

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