Curso modelado de nicho ecológico, version 1.0

Peterson, A. Townsend; Cobos, Marlon E.; Cuahutle, Martín; Cuervo-Robayo, Ángela P.; Escobar, Luis E.; Fernández, Marc; Jiménez‐García, Daniel; Lira‐Noriega, Andrés; Lobo, Jorge; Machado‐Stredel, Fernando; Martínez‐Meyer, Enrique; Nuñez‐Penichet, Claudia; Nori, Javier; Osorio‐Olvera, Luis; Rodríguez, María Teresa; Rojas-Soto, Octavio R.; Romero-Álvarez, Daniel; Soberón, Jorge; Varela, Sara; Yáñez‐Arenas, Carlos

doi:10.17161/bi.v14i0.8189

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…A buffer for uniformity in occurrence distribution was set to 5 km between points. All genera with more than 20 occurrence data were retained (Asase et al, 2021; Peterson et al, 2019).…”

Section: Methodsmentioning

confidence: 99%

The ecological value of Neotropical forest landscapes through a multicriteria approach employing spatial models

Amador-Cruz,

Figueroa-Rangel,

Jiménez-García

et al. 2024

Progress in Physical Geography: Earth and Environment

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Ecological value (EV) is a term used to characterize the biotic or abiotic elements of a landscape, excluding human influence. Significant criteria for EV estimation can be grouped into two categories: ecological properties (biodiversity and vulnerability) and functional/structural features (fragmentation, connectivity, and resilience). While various methodological frameworks exist for estimating these criteria, few studies integrate all five criteria, and even fewer compare their results with fieldwork data. The objective of this study was to devise a novel spatial modelling tool for EV estimation based on biodiversity, vulnerability, fragmentation, connectivity, and resilience, utilizing data from Neotropical montane forests in west-central Mexico. The model incorporated data on (i) biodiversity and vulnerability estimated through ecological niche models, (ii) fragmentation and connectivity using landscape spatial patterns, and (iii) resilience estimated through the inverse of the vegetation sensitivity index. The results were then compared with fieldwork data. Natural protected areas within the Neotropical montane forests of west-central Mexico exhibited high EVs; however, a substantial portion of these forests lack legal protection. In terms of vegetation types, cloud and semideciduous forests exhibited the highest EV, emphasizing the urgent need for legal protection of these vital ecosystems. The comparison process demonstrated a moderate to high correlation in some criteria between the spatial and fieldwork data, indicating that the spatial model robustly captured the landscape spatial patterns. The spatial modelling tool proposed in this study is not only practical but also reproducible and applicable globally. Its efficacy lies in combining ecological properties with the functional and structural features of the landscape, making it particularly suitable for delineating protected natural areas and contributing to landscape planning efforts.

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“…A buffer for uniformity in occurrence distribution was set to 5 km between points. All genera with more than 20 occurrence data were retained (Asase et al, 2021; Peterson et al, 2019).…”

Section: Methodsmentioning

confidence: 99%

The ecological value of Neotropical forest landscapes through a multicriteria approach employing spatial models

Amador-Cruz,

Figueroa-Rangel,

Jiménez-García

et al. 2024

Progress in Physical Geography: Earth and Environment

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“…This manuscript is an overview of the field of ecological niche modeling for veterinarians and epidemiologists and considers parasites (e.g., tapeworm) and pathogens (e.g., virus) as agents causing disease. The content of this review is a friendly introduction to more specialized literature and study cases described in more detail elsewhere (17,18).…”

Section: Introductionmentioning

confidence: 99%

Ecological Niche Modeling: An Introduction for Veterinarians and Epidemiologists

Escobar

2020

Front. Vet. Sci.

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Most infectious diseases in animals are not distributed randomly. Instead, diseases in livestock and wildlife are predictable in terms of the geography, time, and species affected. Ecological niche modeling approaches have been crucial to the advancement of our understanding of diversity and diseases distributions. This contribution is an introductory overview to the field of distributional ecology, with emphasis on its application for spatial epidemiology. A new, revised modeling framework is proposed for more detailed and replicable models that account for both the biology of the disease to be modeled and the uncertainty of the data available. Considering that most disease systems need at least two organisms interacting (i.e., host and pathogen), biotic interactions lie at the core of the pathogen's ecological niche. As a result, neglecting interacting organisms in pathogen dynamics (e.g., maintenance, reproduction, and transmission) may limit efforts to forecast disease distributions in veterinary epidemiology. Although limitations of ecological niche modeling are noted, it is clear that the application and value of ecological niche modeling to epidemiology will increase in the future. Potential research lines include the examination of the effects of biotic variables on model performance, assessments of protocols for model calibration in disease systems, and new tools and metrics for robust model evaluation. Epidemiologists aiming to employ ecological niche modeling theory and methods to reconstruct and forecast epidemics should familiarize themselves with ecological literature and must consider multidisciplinary collaborations including veterinarians to develop biologically sound, statistically robust analyses. This review attempts to increase the use of tools from ecology in disease mapping.

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“…This novelty and speed of development of the field, combined with intense interest, have led to a series of in-person and online training programs and courses, ranging from broad surveys of all biodiversity informatics (e.g., Peterson and Ingenloff 2015) to courses specifically on ecological niche modeling (e.g., Peterson et al 2019; note, this particular course was in Spanish). However, given the somewhat dated nature of many existing courses and the substantial fees often involved, a significant gap was noted: a free, online course in English spanning the entire suite of theory, protocols, and tools in the ecological niche modeling toolkit.…”

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confidence: 99%

ENM2020: A Free Online Course and Set of Resources on Modeling Species' Niches and Distributions

Peterson

Aiello‐Lammens²,

Amatulli³

et al. 2022

Biodiv. Inf.

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The field of distributional ecology has seen considerable recent attention, particularly surrounding the theory, protocols, and tools for Ecological Niche Modeling (ENM) or Species Distribution Modeling (SDM). Such analyses have grown steadily over the past two decades—including a maturation of relevant theory and key concepts—but methodological consensus has yet to be reached. In response, and following an online course taught in Spanish in 2018, we designed a comprehensive English-language course covering much of the underlying theory and methods currently applied in this broad field. Here, we summarize that course, ENM2020, and provide links by which resources produced for it can be accessed into the future. ENM2020 lasted 43 weeks, with presentations from 52 instructors, who engaged with >2500 participants globally through >14,000 hours of viewing and >90,000 views of instructional video and question-and-answer sessions. Each major topic was introduced by an “Overview” talk, followed by more detailed lectures on subtopics. The hierarchical and modular format of the course permits updates, corrections, or alternative viewpoints, and generally facilitates revision and reuse, including the use of only the Overview lectures for introductory courses. All course materials are free and openly accessible (CC-BY license) to ensure these resources remain available to all interested in distributional ecology.

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Curso modelado de nicho ecológico, version 1.0

Cited by 3 publications

References 5 publications

The ecological value of Neotropical forest landscapes through a multicriteria approach employing spatial models

The ecological value of Neotropical forest landscapes through a multicriteria approach employing spatial models

Ecological Niche Modeling: An Introduction for Veterinarians and Epidemiologists

ENM2020: A Free Online Course and Set of Resources on Modeling Species' Niches and Distributions

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