Combining Hierarchical Distribution Models With Dispersal Simulations to Predict the Spread of Invasive Plant Species

IF 6.3 1区环境科学与生态学 Q1 ECOLOGY

Global Ecology and Biogeography Pub Date : 2025-03-25 DOI:10.1111/geb.70026

Adrián Lázaro-Lobo, Johannes Wessely, Franz Essl, Dietmar Moser, Borja Jiménez-Alfaro

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引用次数: 0

Abstract

Aim

Predicting the future distribution of invasive species is a current challenge for biodiversity assessment. Species distribution models (SDMs) have long been the state-of-the-art to evaluate suitable areas for new invasions, but they may be limited by truncated niches and the uncertainties of species dispersal. Here, we developed a framework based on hierarchical SDMs and dispersal simulations to predict the future distribution and spread of invasive species at the ecoregion level.

Location

Cantabrian Mixed Forests Ecoregion (SW Europe) with global distribution data.

Time Period

1950–2063.

Major Taxa Studied

Vascular plants.

Methods

We used occurrence data from 102 invasive species to fit SDMs with machine-learning algorithms and to simulate species dispersal. We combined habitat suitability models based on species' global climatic niches together with regional models including local variables (topography, landscape features, human activity, soil properties) in a hierarchical approach. Then, we simulated species dispersal across suitable areas over the next 40 years, considering species dispersal limitations and climate change.

Results

Global climatic niches retained a strong contribution in the hierarchical models, followed by local factors such as human population density, sand content and soil pH. In general, the highest suitability was predicted for warm and humid climates close to the coastline and urbanised areas. The inclusion of dispersal abilities identified different trajectories of geographic spread for individual species, predicting regional hotspots of species invasion. The predictions were more dependent on global suitability and species dispersal rather than climatic warming scenarios.

Main Conclusions

This study provides a comprehensive framework for predicting the regional distribution of invasive species. While hierarchical modelling combines non-truncated global climatic niches with regional drivers of species invasions, the integration of dispersal simulations allows us to anticipate invasibility in new areas. This framework can be useful to assess the current and future distribution of invasive species pools in biogeographical regions.

查看原文本刊更多论文

结合层次分布模型和扩散模拟预测入侵植物物种的扩散

目的预测入侵物种的未来分布是当前生物多样性评估面临的挑战。物种分布模型（SDMs）长期以来一直是评估新入侵适宜区域的最先进方法，但它可能受到生态位截断和物种扩散的不确定性的限制。在此，我们建立了一个基于分层sdm和扩散模拟的框架来预测未来入侵物种在生态区域水平上的分布和传播。欧洲西南部坎塔布里亚混交林生态区域的地理位置与全球分布数据。时间：1950-2063。维管植物的主要分类群。方法利用102种入侵物种的发生数据，用机器学习算法拟合sdm，模拟物种扩散过程。我们将基于物种全球气候生态位的生境适宜性模型与包含局部变量（地形、景观特征、人类活动、土壤性质）的区域模型结合起来，采用分层方法。然后，在考虑物种扩散限制和气候变化的情况下，我们模拟了未来40年物种在合适区域的扩散。结果全球气候生态位对分层模型的影响最大，其次是人口密度、含沙量和土壤ph等局地因素。总体而言，靠近海岸线和城市化地区的温暖湿润气候最适合分层模型。扩散能力的纳入确定了不同物种的地理传播轨迹，预测了物种入侵的区域热点。这些预测更多地依赖于全球适应性和物种扩散，而不是气候变暖的情景。本研究为入侵物种的区域分布预测提供了一个较为全面的框架。虽然分层模型结合了非截断的全球气候生态位和物种入侵的区域驱动因素，但分散模拟的整合使我们能够预测新地区的入侵性。该框架可用于评估生物地理区域入侵物种库的现状和未来分布。

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来源期刊

Global Ecology and Biogeography 环境科学-生态学

CiteScore

12.10

自引率

3.10%

发文量

170

审稿时长

3 months

期刊介绍： Global Ecology and Biogeography (GEB) welcomes papers that investigate broad-scale (in space, time and/or taxonomy), general patterns in the organization of ecological systems and assemblages, and the processes that underlie them. In particular, GEB welcomes studies that use macroecological methods, comparative analyses, meta-analyses, reviews, spatial analyses and modelling to arrive at general, conceptual conclusions. Studies in GEB need not be global in spatial extent, but the conclusions and implications of the study must be relevant to ecologists and biogeographers globally, rather than being limited to local areas, or specific taxa. Similarly, GEB is not limited to spatial studies; we are equally interested in the general patterns of nature through time, among taxa (e.g., body sizes, dispersal abilities), through the course of evolution, etc. Further, GEB welcomes papers that investigate general impacts of human activities on ecological systems in accordance with the above criteria.