嵌套
生态学
物种丰富度
下层林
生物多样性
生态系统
生物
传粉者
授粉
栖息地
森林生态学
地理
花粉
天蓬
作者
E. Jacob Cristóbal‐Pérez,Gilbert Barrantes,Alfredo Cascante‐Marín,Paul Hanson,Beatriz Picado,Nicole Gamboa-Barrantes,Geovanna Rojas-Malavasi,Manuel A. Zumbado,Ruth Madrigal‐Brenes,Silvana Martén‐Rodríguez,Maurício Quesada,Eric J. Fuchs
出处
期刊:PLOS ONE
[Public Library of Science]
日期:2024-01-11
卷期号:19 (1): e0295258-e0295258
被引量:11
标识
DOI:10.1371/journal.pone.0295258
摘要
Many plant species in high montane ecosystems rely on animal pollination for sexual reproduction, however, our understanding of plant-pollinator interactions in tropical montane habitats is still limited. We compared species diversity and composition of blooming plants and floral visitors, and the structure of plant-floral visitor networks between the Montane Forest and Paramo ecosystems in Costa Rica. We also studied the influence of seasonality on species composition and interaction structure. Given the severe climatic conditions experienced by organisms in habitats above treeline, we expected lower plant and insect richness, as well as less specialized and smaller pollination networks in the Paramo than in Montane Forest where climatic conditions are milder and understory plants are better protected. Accordingly, we found that blooming plants and floral visitor species richness was higher in the Montane Forest than in the Paramo, and in both ecosystems species richness of blooming plants and floral visitors was higher in the rainy season than in the dry season. Interaction networks in the Paramo were smaller and more nested, with lower levels of specialization and modularity than those in the Montane Forest, but there were no seasonal differences within either ecosystem. Beta diversity analyses indicate that differences between ecosystems are likely explained by species turnover, whereas within the Montane Forest differences between seasons are more likely explained by the rewiring of interactions. Results indicate that the decrease in species diversity with elevation affects network structure, increasing nestedness and reducing specialization and modularity.
科研通智能强力驱动
Strongly Powered by AbleSci AI