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The Equilibrium Theory of Island Biogeography postulates that larger and closer islands support higher biodiversity through the dynamic balance of colonization and extinction processes. The negative diversity–isolation (i.e. the distance to the mainland) relationship is derived based on the assumption that the mainland is the only source pool for island biotas. However, nearby islands could also act as species sources for focal islands via a source effect. In this study, we move a further step and hypothesize that nearby islands may reduce bird colonizers of the focal island and diminish its biodiversity, resulting in a negative target effect.To test our hypothesis, we assessed the effects of island area and isolation (metrics considering both the mainland and nearby islands) on taxonomic (i.e. species richness), functional and phylogenetic diversity of terrestrial breeding birds on 42 islands in the largest archipelago of China, the Zhoushan Archipelago. Furthermore, we compared the predictive power of the distance to the large island under a set of relative area thresholds and the relative area of nearby islands on species richness under a set of distance thresholds to explore the role of nearby islands as a source and/or target island.We found that island area had a positive effect on species richness, phylogenetic diversity and functional diversity, while the distance to the mainland had a negative effect only on species richness. Species richness on the focal island increased with increasing distance to the nearest larger island, indicating the negative target effect. Furthermore, the negative target effect depended on the area of nearby islands relative to the area of the focal island.Our finding of the negative target effect suggests islands located between the mainland and the focal island can be not only sources or stepping stones, but also colonization targets. This result demonstrates the importance of considering multiple geographical attributes of islands in island biogeographic studies, especially the characteristics related to source and/or target effects. [ABSTRACT FROM AUTHOR]

Although arboreal camera trapping is a growing field, it has rarely been used for monitoring plant‐frugivore interactions in the trees. Frugivore foraging behavior generally occurs in trees, hence arboreal camera trapping can be a potentially useful tool for frugivory research. We developed a camera trap sampling method to monitor plant‐frugivore interactions during mature fruiting periods. We used this method to monitor 318 individuals (camera sites) of 18 fleshy‐fruit plant species on 22 subtropical land‐bridge islands in the Thousand Island Lake, China. We recorded a total of at least 52 frugivorous animals, including a ground‐foraging bird species (Lophura nycthemera) and several mammals with foraging behaviors in the trees. We also recorded 4399 independent interaction events, including 275 unique plant‐bird interactions. We proposed a framework to classify interaction types and performed a sampling completeness test. We found that a sampling strategy that covered approximately a third of the fruit maturation period when most fruits were ripe was sufficient to sample plant‐frugivore interactions. Our results demonstrated that our sampling method with camera transects is reliable to monitor plant‐frugivore interactions in a fragmented landscape. This study helps to lay the methodological foundation for building networks of plant‐frugivore interactions with arboreal camera trapping on large spatial/temporal scales. As a non‐invasive, labor‐saving, and largely unbiased sampling method, the field application of arboreal camera trapping in different regions can advance the technology of biodiversity monitoring and lead to more accurate biodiversity inventories in arboreal environments. [ABSTRACT FROM AUTHOR]

Anthropogenic activities have reshaped biodiversity on islands worldwide. However, it remains unclear how island attributes and land-use change interactively shape multiple facets of island biodiversity through community assembly processes. To answer this, we conducted bird surveys in various land-use types (mainly forest and farmland) using transects on 34 oceanic land-bridge islands in the largest archipelago of China. We found that bird species richness increased with island area and decreased with isolation, regardless of the intensity of land-use change. However, forest-dominated habitats exhibited lower richness than farmland-dominated habitats. Island bird assemblages generally comprised species that share more similar traits or evolutionary histories (i.e. functional and/or phylogenetic clustering) than expected if assemblages were randomly assembled. Contrary to our expectations, we observed that bird assemblages in forest-dominated habitats were more clustered on large and close islands, whereas assemblages in farmland-dominated habitats were more clustered on small islands. These contrasting results indicate that land-use change interacts with island biogeography to alter the community assembly of birds on inhabited islands. Our findings emphasize the importance of incorporating human-modified habitats when examining the community assembly of island biota, and further suggest that agricultural landscapes on large islands may play essential roles in protecting countryside island biodiversity.

Building ecological networks is the fundamental basis of depicting how species in communities interact, but sampling complex interaction networks is extremely labour intensive. Recently, indirect ecological information has been applied to build interaction networks. Here we propose to extend the source of indirect ecological information, and applied regional ecological knowledge to build local interaction networks. Using a high-resolution dataset consisting of 22 locally observed networks with 17 572 seed-dispersal events, we test the reliability of indirectly derived local networks based on regional ecological knowledge (REK) across islands. We found that species richness strongly influenced 'local interaction rewiring' (i.e. the proportion of locally observed interactions among regionally interacting species), and all network properties were biased using REK-based networks. Notably, species richness and local interaction rewiring strongly affected estimations of REK-based network structures. However, locally observed and REK-based networks detected the same trends of how network structure correlates to island area and isolation. These results suggest that we should use REK-based networks cautiously for reflecting actual interaction patterns of local networks, but highlight that REK-based networks have great potential for comparative studies across environmental gradients. The use of indirect regional ecological information may thus advance our understanding of biogeographical patterns of species interactions.