Projecting Untruncated Climate Change Effects on Species' Climate Suitability: Insights From an Alpine Country DOI Creative Commons
Antoine Adde, Nathan Külling, Pierre‐Louis Rey

et al.

Global Change Biology, Journal Year: 2024, Volume and Issue: 30(11)

Published: Nov. 1, 2024

ABSTRACT Climate projections for continental Europe indicate drier summers, increased annual precipitation, and less snowy winters, which are expected to cause shifts in species' distributions. Yet, most regions/countries currently lack comprehensive climate‐driven biodiversity across taxonomic groups, challenging effective conservation efforts. To address this gap, our study evaluated the potential effects of climate change on an alpine country Europe, Switzerland. We used a state‐of‐the art species distribution modeling approach occurrence data that covered climatic conditions encountered full ranges help limiting niche truncation. quantified relationship between baseline spatial 7291 from 12 main groups projected future suitability three 30‐year periods two greenhouse gas concentration scenarios (RCP4.5 8.5). Our results indicated important changes suitability, with responses varying by status group. The percentage facing major was higher under RCP8.5 (68%) compared RCP4.5 (66%). By end century, decreases were 3000 1758 RCP4.5. affected molluscs, algae, amphibians, while it birds, vascular plants Spatially, 2070–2099, we overall decrease 39% cells area 10% RCP4.5, projecting increase 50% 73% consistent geographical upward, southward, eastward. found coverage high protected areas increase. models maps provide guidance planning pointing out climate‐suitable biodiversity.

Language: Английский

Emerging horizons in predictive biogeography DOI Creative Commons
Christine N. Meynard, Sydne Record, Núria Galiana

et al.

Ecography, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 10, 2025

The notion that different branches of biological sciences – including ecology, macroecology, and biogeography should adopt a predictive focus rather than merely aiming to describe understand the natural world has gained traction over past decades (Peters 1991, Shrader-Frechette McCoy 1993). This trend been enabled both by technological advancement leading new frameworks, pressing societal demands anticipate mitigate effects global change on biodiversity associated ecosystem services. An early example this is work Sánchez-Cordero et al. (2004) who contributed chapter for conservation applications in seminal volume (Lomolino Heaney 2004). While authors did not explicitly define term biogeography, their discussion emphasized how developments statistical ecology mapping had allowed description species distributions at large spatial scales. Similarly, Thuiller (2006) employed concept restricted context describing use stacked distribution models (SDMs) predicting plant richness South Africa. Dawson (2011) subsequently highlighted SDMs as most widely used method but also called attention importance establishing broader frameworks changes biodiversity, from ecosystems, response climate change. There are other biogeographic patterns context. Most notably, area relationships (SARs), which have important predict extinctions (Drakare 2006) driven anthropogenic habitat fragmentation example. However, widespread SDMs, along with fact they remain choice scales repeatedly (Bellard 2012, Araújo 2019, Zurell 2020, Soley-Guardia 2024). Mapping remains an essential component large-scale planning (Margules 2002). It critical only delineating statuses, trends, management strategies regional scales, interpreting geological, historical, causes consequences (Whittaker 2005). Therefore, modelling will probably biogeography. many studies emphasize need move beyond individual encompass range spatio-temporal issues interface between society, such services, human health agricultural systems. expanded scope inevitably calls wider definition In special issue, we aim broaden application moving confines spotlight cutting edge research across dimensions field. deliberate opposed or reflects our intent include more diverse array approaches statistical, evolutionary, contribute understanding forecasting distribution, abundance, diversity broad and/or temporal includes systems productive (e.g. agroecosystems). We propose subdiscipline uses known ecological evolutionary processes diversity, whether it be species, intra-, inter-specific levels, biotic interactions relationship environment, Over two decades, field experienced exponential growth, increasing availability digital data genetic variability within them, well proliferation spatially explicit environmental layers increasingly fine resolutions. rapid evolution catalysed development syntheses theories, alongside advancements methodologies computational capabilities. As result, undergoing transformation primarily descriptive discipline championed likes Alexander von Humboldt (1769–1859), Augustin Pyramus de Candolle (1778–1841), Alfred Russel Wallace (1823–1913), Philip Lutley Sclater (1829–1913), amongst others, science, capable informing fundamental practical conservation, resource management, beyond. emergence demand (Dietze 2018, Enquist growing challenges decline rising food demands, far-reaching impacts recent pandemics paired ongoing threaten security, public health, made ability these existential priority humanity. time, expanded. Initially, 1990s, its centred largely past, present, future biodiversity. Today, evolved address directly linked societies, production (Enquist relevance positioned underpinning wide fields (Araújo Peterson 2012). These biology 2011, Fordham 2013), agriculture (Meynard 2017, Gerber 2024, Soubeyrand 2024), forestry (Zhang 2022, Rosa fisheries (Cheung 2010, Boavida-Portugal 2018), epidemiology (Aliaga-Samanez Mestre paleobiology (Metcalf 2014, 2022), reflecting versatility addressing contemporary issues. advances all areas biology, computer science translated into vast high-resolution information geographic areas, landscapes, countries, continents, even globally. Technological molecular sequencing, make monitoring, microscopic life, possible (Beng Corlett 2020). DNA recovery efforts can go so far sequence ancient samples, allowing exploration old specimens stored museum collections (Raxworthy Smith 2021), recovering trophic through samples (Pereira 2023). Sequencing, analytical theoretical advances, makes integrate history, rates diversification (Morlon Kergoat 2018) predictions Remote sensing follow land (Cavender-Bares integrating chemical properties phylogenetic functional 2020), microclimate resolutions (Lembrechts 2020) among promising allow fine-grain mechanisms models. Statistical methods computing (Record 2023), technology allows sharing globally, curated occurrence, trait, phylogenetic, any type datasets. just few expanding extent fine-resolution gathered. When combined, applied, greatly advance future. Within bounds, identify least three components framework (Fig. 1): data, must fall domain biogeography; one scenarios establish relevant predictions; formal model theory translates current biodiversity–environment considered. Note often pertain land-use scenarios), scenarios, extinction strategies, behaviour, driving predictions. Importantly, view dynamic static. Advances scenario lead updates models, turn, outputs requirements guide collection refinement creating positive feedback loop 2018). Conceptual summary framework. Every effort ingredients (a) theories models; (b) shows several indicators measures, feeding each ways. Although usually combination occurrence (SDM) predictions), depend sought; very related change, evolution, resilience, extinction, kind changes. Finally, set combining needed, although main desired scope. compared, validated, measured against real patterns. A panoply higher spatial, temporal, taxonomic resolution, facets genetics, phenotypic, functional, phenological) key larger Examples shown (c), no means exhaustive list. Each involve plethora elements. For example, gene expression profiles, intra-specific intra- traits, others 1). Despite significant progress, technologies enabling measurement, characterization continue evolve. considerable potential innovation relating environment factors, imagining enhancing curating papers aimed interdisciplinary integration. compiled revolve around core tool Boom Kissling (2024) tracking complement traditional improving SDM Chronister demonstrate automated acoustic detectors monitor distinguish juvenile adult great horned owls, opening door estimating demographic parameters By incorporating researchers explore life cycle stages factor consider when setting priorities. Goicolea employ hierarchical refine locally calibrated nested regionally constrained ones. approach mitigates common problem truncating calibrating local (Thuiller Mowry account constraints disease vector ticks, case resulting improved estimates. Several featured issue leverage interplay differentiation populations distributions. Naughtin structure SDM-based reconstructions ranges infer, via approximate Bayesian computation (ABC) likely combinations matches structure. argue help rank otherwise indistinguishable using standard validation methods. another application, Mascarenhas Carnaval random forest relates history particularly dispersal characteristics. Their results highlight traits arthropod phylogeography. Hernández linking suitability, modelled deep time intervals, diversity. integration produces interesting regarding stability paleological periods structures, identification endemic regions poorly surveyed Along similar lines, Formoso-Freire relate abundance distributions, investigating long-term informs present-day community stability. modelling. Sharma niche evolution. utility study hummingbirds. Verdon eDNA estimate soil taxa traditionally overlooked monitoring. ambitious incorporates numerous amplicon variants (ASVs), revealing capabilities limitations approaches. discussed authors, dynamics require better estimates enhanced soil-related Another recurring theme incorporation success adapting changing climates hinges Luoto 2007). Poggiato (2025) tackled while González-Trujillo phenomenological structures proposed Mendoza (2019, 2022). hindcast guild latitudes, interactions. Predictive represented issue. Park present simulation demonstrating median flowering dates mean temperatures onset termination periods. offers valuable inferring phenology strong representation, thus helping phenological shifts Siders capitalize comprehensive literature review extract shark devices comparing vertical without depth-weighted information. show depth preference add sharks, components. Adding third dimension marine seems like venue research, recently available thanks accumulation biotelemetry 3-D ocean (Fragkopoulou Lertzman-Lepofsky take advantage databases role explaining correlations taxa. analysis demonstrates co-variations well-documented enhances time. summary, exemplify innovations reshaping monitor, understand, various From population taxonomic, evolving rapidly. Emerging now previously invisible challenging-to-monitor aspects facilitated tools eDNA, detection (sound telemetry), modelling, big exciting direction involves utilizing deep-time inform forecast sequencing opened possibilities examining variation forging compelling connections there gaps publications (Maldonado 2015, Nuñez focused tropical (Mascarenhas Moreover, small subset those illustrated Fig. 1c. plays crucial monitoring scale, features limited scaling contexts. underscore number unexplored advancing could combine text mining, citizen engaging individuals everyday cell phones multi-modal real-time analysis? Such enable declines shifts. Could genomics epigenetics offer deeper insights genotype-to-phenotype relationships, adaptation prioritizing level? Furthermore, facilitate 'macroscope' (Gonzalez bridging gap leaves Global underrepresented datasets? questions scratch surface what achieved push boundaries does represent exhaustively literature, prevalence absence certain biases state none (Lagerholm Raxworthy 2021) environments middens pollen deposits, pre-human baselines, shifts, influenced intervention. lack coherent uncertainties. ensemble become practice 2007, 2019), equivalent identifying reporting Citizen underrepresented, despite prominence artificial intelligence assisted Pl@ntNet (Joly 2016). Links error estimation further applied development. dominance limitations. To static mechanistic Functional though promising, here. empirical elusive (but see Violle Díaz Neyret developed scaled extents scenarios. incorporate regulation, productivity, stability, functions focusing solely species. Dynamic weather remote Near-term identified making timely decisions play retroactive role, lessons learned improve forecasts Lewis Achieving requires fully replicable pipelines near-real-time data. highlights open programming literacy (Mandeville 2021). Open ensure reproducibility democratize easily adapted settings 2015). Additionally, system archiving synthesizing 2023) needed build based experiences. points out, given us toolkit learn about levels organization, datasets detailed equally informative reconciling scientific cultures: values detail specificity, emphasizes experimentation explanations, simplifies discern generalizable Striking right balance challenging yet worthwhile endeavour science. CNM was funded her salary French servant national institution. Christine Meynard: Conceptualization (equal), Validation Writing - original draft (lead), editing (lead). Sydne Record: (supporting), (supporting). Nuria Galiana: Dominique Gravel: Miguel Araújo:

Language: Английский

Citations

0
Combining Hierarchical Distribution Models With Dispersal Simulations to Predict the Spread of Invasive Plant Species DOI
Adrián Lázaro‐Lobo, Johannes Wessely, Franz Essl

et al.

Global Ecology and Biogeography, Journal Year: 2025, Volume and Issue: 34(3)

Published: March 1, 2025

ABSTRACT Aim Predicting the future distribution of invasive species is a current challenge for biodiversity assessment. Species models (SDMs) have long been state‐of‐the‐art to evaluate suitable areas new invasions, but they may be limited by truncated niches and uncertainties dispersal. Here, we developed framework based on hierarchical SDMs dispersal simulations predict spread at ecoregion level. Location Cantabrian Mixed Forests Ecoregion (SW Europe) with global data. Time Period 1950–2063. Major Taxa Studied Vascular plants. Methods We used occurrence data from 102 fit machine‐learning algorithms simulate combined habitat suitability species' climatic together regional including local variables (topography, landscape features, human activity, soil properties) in approach. Then, simulated across over next 40 years, considering limitations climate change. Results Global retained strong contribution models, followed factors such as population density, sand content pH. In general, highest was predicted warm humid climates close coastline urbanised areas. The inclusion abilities identified different trajectories geographic individual species, predicting hotspots invasion. predictions were more dependent rather than warming scenarios. Main Conclusions This study provides comprehensive species. While modelling combines non‐truncated drivers integration allows us anticipate invasibility can useful assess pools biogeographical regions.

Language: Английский

Citations

0
Advancements in ecological niche models for forest adaptation to climate change: a comprehensive review DOI Creative Commons
Wenhuan Xu, Dawei Luo, Kate Peterson

et al.

Biological reviews/Biological reviews of the Cambridge Philosophical Society, Journal Year: 2025, Volume and Issue: unknown

Published: April 3, 2025

ABSTRACT Climate change poses significant challenges to the health and functions of forest ecosystems. Ecological niche models have emerged as crucial tools for understanding impact climate on forests at population, species, ecosystem levels. These also play a pivotal role in developing adaptive conservation management strategies. Recent advancements model development led enhanced prediction accuracy broadened applications models, driven using high‐quality data, improved algorithms, application landscape genomic information. In this review, we start by elucidating concept rationale behind context forestry adaptation change. We then provide an overview occurrence‐based, trait‐based, genomics‐based contributing more comprehensive species responses addition, summarize findings from 338 studies highlight progress made tree including data sources, future scenarios used diverse applications. To assist researchers practitioners, exemplar set accompanying source code tutorial, demonstrating integration population genetics into models. This paper aims concise yet continuous refinements serving valuable resource effectively addressing posed changing climate.

Language: Английский

Citations

0
sabinaNSDM: An R package for spatially nested hierarchical species distribution modelling DOI Creative Commons
Rubén G. Mateo, Jennifer Morales‐Barbero, Alejandra Zarzo‐Arias

et al.

Methods in Ecology and Evolution, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 12, 2024

Abstract Species distribution models have evolved to combine species‐environment interactions across multiple scales. Spatially nested hierarchical (NSDMs) offer a promising avenue by integrating datasets and predictive from broad fine But user‐friendly tool execute these remains an important ongoing challenge. To address this gap, we introduce the sabinaNSDM R package that provides straightforward approach develop NSDMs. This merges global scale models, capturing extensive ecological niches, with regional featuring high‐resolution covariates, form unified modelling framework. toolkit is designed facilitate implementation of NSDMs for ecologists, conservationists researchers aiming produce more reliable species predictions. streamlines data preparation, calibration, integration projection two It automates (if necessary) generation background points, spatial thinning occurrence absence available) data, covariate selection paper outlines workflow functions integrated into package, complemented applied case study involving pool 76 tree species. Consistent previous publications, generated facilitated precise predictions (mean AUC value through independent evaluation higher than 0.88) distributions under current future environmental scenarios.

Language: Английский

Citations

2
Projecting Untruncated Climate Change Effects on Species' Climate Suitability: Insights From an Alpine Country DOI Creative Commons
Antoine Adde, Nathan Külling, Pierre‐Louis Rey

et al.

Global Change Biology, Journal Year: 2024, Volume and Issue: 30(11)

Published: Nov. 1, 2024

ABSTRACT Climate projections for continental Europe indicate drier summers, increased annual precipitation, and less snowy winters, which are expected to cause shifts in species' distributions. Yet, most regions/countries currently lack comprehensive climate‐driven biodiversity across taxonomic groups, challenging effective conservation efforts. To address this gap, our study evaluated the potential effects of climate change on an alpine country Europe, Switzerland. We used a state‐of‐the art species distribution modeling approach occurrence data that covered climatic conditions encountered full ranges help limiting niche truncation. quantified relationship between baseline spatial 7291 from 12 main groups projected future suitability three 30‐year periods two greenhouse gas concentration scenarios (RCP4.5 8.5). Our results indicated important changes suitability, with responses varying by status group. The percentage facing major was higher under RCP8.5 (68%) compared RCP4.5 (66%). By end century, decreases were 3000 1758 RCP4.5. affected molluscs, algae, amphibians, while it birds, vascular plants Spatially, 2070–2099, we overall decrease 39% cells area 10% RCP4.5, projecting increase 50% 73% consistent geographical upward, southward, eastward. found coverage high protected areas increase. models maps provide guidance planning pointing out climate‐suitable biodiversity.

Language: Английский

Citations

0