Thinking outside the patch: a multi-species comparison of conceptual models from real-world landscapes
Autor: | Giovanni Manghi, António Mira, Sara Santos, Bruno M. C. Silva, Carmo Silva, João E. Rabaça, Pedro A. Salgueiro, Denis Medinas, Sofia Eufrázio |
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Rok vydání: | 2017 |
Předmět: |
0106 biological sciences
Computer science media_common.quotation_subject Ecology (disciplines) Geography Planning and Development Context (language use) Generalist and specialist species Machine learning computer.software_genre 010603 evolutionary biology 01 natural sciences Variegated landscape Habitat quality Nature and Landscape Conservation media_common Continuum model Ecology Conceptualization business.industry 010604 marine biology & hydrobiology Statistical model Spatial heterogeneity Discrete model Conceptual model Mosaic landscapr Artificial intelligence Landscape ecology business computer |
Zdroj: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) Agência para a Sociedade do Conhecimento (UMIC)-FCT-Sociedade da Informação instacron:RCAAP |
ISSN: | 1572-9761 0921-2973 |
DOI: | 10.1007/s10980-017-0603-y |
Popis: | When modeling a species’ distribution, landscapes can alternatively be conceptualized following patch- or gradient-based approaches. However, choosing the most suitable conceptualization is difficult and methods for empirical validation are still lacking. To address the conditions under which a given conceptual model is more suitable, taking into account landscape context and species trait dependency effects. Patch- and gradient-based conceptualizations were built based on two structurally different landscapes: variegated and mosaic. We hypothesize that: (H1) gradient-based models better describe variegated landscapes while patch-based models perform better in mosaic landscapes; and (H2) gradient-based models will fit generalist species better while patch-based models will suit specialists better. We modeled the distribution of eleven bird species in each landscape using each conceptualization. We determined the suitability of each conceptual model to fit statistical models by looking for cross-species responses and deviations from best models. We found no clear support for our hypotheses. Although patch-based models performed better in mosaic landscapes (H1), they also provided useful conceptualizations in variegated landscapes. However, when patches showed high heterogeneity, gradient-based approaches better fit specialist species (H2). The suitability of a given conceptual model depends on the interaction between species habitat specialization, and the intrinsic spatial heterogeneity of the landscape and the ability of each conceptualization to capture it. Gradient-based models provide better information on resource allocation, while patch-based models offer a simplified perspective on landscape attributes. Future research should consider the nature of both species and landscapes in order to avoid bias from inadequate landscape conceptualizations. |
Databáze: | OpenAIRE |
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