Determinants of bird species richness, endemism, and island network roles in Wallacea and the West Indies: is geography sufficient or does current and historical climate matter?

Abstract

Island biogeography has greatly contributed to our understanding of the processes determining species' distributions. Previous research has focused on the effects of island geography (i.e., island area, elevation, and isolation) and current climate as drivers of island species richness and endemism. Here, we evaluate the potential additional effects of historical climate on breeding land bird richness and endemism in Wallacea and the West Indies. Furthermore, on the basis of species distributions, we identify island biogeographical network roles and examine their association with geography, current and historical climate, and bird richness/endemism. We found that island geography, especially island area but also isolation and elevation, largely explained the variation in island species richness and endemism. Current and historical climate only added marginally to our understanding of the distribution of species on islands, and this was idiosyncratic to each archipelago. In the West Indies, endemic richness was slightly reduced on islands with historically unstable climates; weak support for the opposite was found in Wallacea. In both archipelagos, large islands with many endemics and situated far from other large islands had high importance for the linkage within modules, indicating that these islands potentially act as speciation pumps and source islands for surrounding smaller islands within the module and, thus, define the biogeographical modules. Large islands situated far from the mainland and/or with a high number of nonendemics acted as links between modules. Additionally, in Wallacea, but not in the West Indies, climatically unstable islands tended to interlink biogeographical modules. The weak and idiosyncratic effect of historical climate on island richness, endemism, and network roles indicates that historical climate had little effects on extinction-immigration dynamics. This is in contrast to the strong effect of historical climate observed on the mainland, possibly because surrounding oceans buffer against strong climate oscillations and because geography is a strong determinant of island richness, endemism and network roles.

The macroecology of phylogenetically structured hummingbird–plant networks

“…Hence, the relationship between species richness, phylogenetic signal and environmental factors and network structure may differ between mainland and insular communities. For instance, the influence of historical climate change may be weaker on islands than on the mainland (Dalsgaard et al ., , ). As our dataset contains too few island networks ( n = 9) to allow for a separate analysis for insular networks, we explored putative differences in mainland and island networks by analysing a subset of the dataset composed exclusively by networks from the mainland (Mainland; n = 45 networks) and compared these results with those of the entire dataset (Global dataset, which includes both mainland and insular communities; n = 54 networks).…”

Network biogeography of a complex island system: the Aegean Archipelago revisited

“…In this context, network analysis is a promising and powerful tool for understanding island connectivity (Dos Santos et al ., ), as it provides a holistic approach, free of a priori dataset assumptions, which is better than pairwise analyses for assessing interactions within complex datasets (Proulx et al ., ). Network biogeographical analysis based on species distributions is an objective, optimal and emerging method for the identification of biogeographical regions within an archipelago (Carstensen et al ., , ; Dalsgaard et al ., ; Kougioumoutzis et al ., ). Netcarto (Guimerá & Amaral, ) is a module‐detecting algorithm, used among others, in ecological (Olesen et al ., ) and biogeographical studies (Carstensen et al ., , ).…”

A comparison of network and clustering methods to detect biogeographical regions

“…In this approach the network is bipartite, with two sets of nodes; locations and taxa, with the taxa linked to locations in which they are present. The modularity SA method has been used in several studies to delineate biogeographical regions (Carstensen and Olesen 2009, Carstensen et al 2012, 2013a, Thébault 2013, Dalsgaard et al 2014). One commonly used network method is Netcarto.…”

“…clusters of areas and species that are associated with each other (Carstensen et al 2012(Carstensen et al , 2013a) and it has been mainly applied to the bioregionalisation of archipelagos (Carstensen and Olesen 2009, Carstensen et al 2012, Dalsgaard et al 2014, Kougioumoutzis et al 2014. clusters of areas and species that are associated with each other (Carstensen et al 2012(Carstensen et al , 2013a) and it has been mainly applied to the bioregionalisation of archipelagos (Carstensen and Olesen 2009, Carstensen et al 2012, Dalsgaard et al 2014, Kougioumoutzis et al 2014.…”

“…The modularity SA method has proved useful in detecting bioregions (also called biogeographical modules, i.e. clusters of areas and species that are associated with each other (Carstensen et al 2012(Carstensen et al , 2013a) and it has been mainly applied to the bioregionalisation of archipelagos (Carstensen and Olesen 2009, Carstensen et al 2012, Dalsgaard et al 2014, Kougioumoutzis et al 2014. For example, Carstensen et al (2012) have used the modularity SA method to understand the processes driving the assembly of island bird communities in Wallacea (Indonesia) and the West Indies (Caribbean).…”