Understanding the assembly of ecosystems to estimate the number of species at different spatial scales is a challenging problem. Until now, maximum entropy approaches have lacked the important feature of considering space in an explicit manner. We propose a spatially explicit maximum entropy model suitable to describe spatial patterns such as the species area relationship and the endemic area relationship. Starting from the minimal information extracted from presence/absence data, we compare the behavior of two models considering the occurrence or lack thereof of each species and information on spatial correlations. Our approach uses the information at shorter spatial scales to infer the spatial organization at larger ones. We also hypothesize a possible ecological interpretation of the effective interaction we use to characterize spatial clustering.
From biodiversity modelling to conservation action: a spatial indicator for prioritising tropical forest protection, restoration, and management
INRAE, National Research Institute on Agriculture, Food & the Environment（法国国家农业食品与环境研究院）；CIRAD, Centre for International Cooperation in Agricultural Research for Development（法国国际农业发展研究中心）
Climate-driven statistical models as effective predictors of local dengue incidence in Costa Rica: A Generalized Additive Model and Random Forest approach
Universidad de Costa Rica（哥斯达黎加大学）；Centro de Investigación en Matemática Pura y Aplicada (CIMPA)（纯数学与应用数学研究中心（CIMPA））
Variations of arthropod biodiversity due to human intervention and climatic variations study of a protected and a non-protected area in a tropical forest
Dispersal diversity buffers species vulnerability to local extinction
University of Padova（帕多瓦大学）；National Biodiversity Future Center（国家生物多样性未来中心）；The Abdus Salam International Centre for Theoretical Physics（阿卜杜斯·萨拉姆国际理论物理中心）；University of Lausanne（洛桑大学）；Princeton University（普林斯顿大学）；CMCC Foundation, Euro Mediterranean Center on Climate Change（欧洲地中海气候变化中心基金会）；École Polytechnique Fédérale de Lausanne（洛桑联邦理工学院）
