Abstract
AbstractAimThe aim was to test whether species distribution models (SDMs) can reproduce major macroecological patterns in a species‐rich, tropical region and provide recommendations for using SDMs in areas with sparse biotic inventory data.LocationNorth‐east Brazil, including Minas Gerais.Time periodPresent.Major taxa studiedFlowering plants.MethodsSpecies composition estimates derived from stacked SDMs (s‐SDMs) were compared with data from 1,506 inventories of 933 woody plant species from north‐east Brazil. Both datasets were used in hierarchical clustering analyses to delimit floristic units that correspond to biomes. The ability of s‐SDMs to predict the identity, functional composition and floristic composition of biomes was compared across geographical and environmental space.ResultsThe s‐SDMs and inventory data both resolved four major biomes that largely corresponded in terms of their distribution, floristics and function. The s‐SDMs proved excellent at identifying broad‐scale biomes and their function, but misassigned many individual sites in complex savanna–forest mosaics.Main conclusionsOur results show that s‐SDMs have a unique role to play in describing macroecological patterns in areas lacking inventory data and for poorly known taxa. s‐SDMs accurately predict floristic and functional macroecological patterns but struggle in areas where non‐climatic factors, such as fire or soil, play key roles in governing distributions.
Highlights
Macroecology is the study of large-scale patterns of biological diversity across space and time and the underlying community assembly processes that determine these patterns
Many previous studies have tested the performance of species distribution models (s-species distribution models (SDMs)) in predicting species richness per site (e.g., D’Amen et al, 2015, 2017; Feria & Peterson, 2002), but here we focused on testing the implication of these differences for downstream analyses of floristic composition and functional diversity patterns at large spatial scales
We investigated the utility of s-SDMs in predicting geographical, floristic and functional characteristics of biomes at 1,506 sites across NE Brazil compared with an inventory dataset
Summary
Macroecology is the study of large-scale patterns of biological diversity across space and time and the underlying community assembly processes that determine these patterns. Distribution data for mammals, birds and amphibians are becoming increasingly available (Castro-Insua, Gomez-Rodrıguez, & Baselga, 2016; McKnight et al, 2007; Melo, Rangel, & DinizFilho, 2009), but distribution data for most lineages in the tree of life are still poor (Scheffers, Joppa, Pimm, & Laurance, 2012). A suite of methods has been developed to extrapolate our limited knowledge of species distributions to complete mapping of biodiversity patterns. These methods fall into two categories: stacked species distribution models (s-SDMs) and macroecological models (MEMs). A significant limitation of macroecological models is, that they cannot predict species identity; they are used primarily for exploring macroecological phenomena relying on emergent ecosystem properties, such as species richness. A significant limitation of macroecological models is, that they cannot predict species identity; they are used primarily for exploring macroecological phenomena relying on emergent ecosystem properties, such as species richness. s-SDMs, on the contrary, permit the exploration of diversity patterns whose investigation relies upon species identity
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