The strengths and weaknesses of species distribution models in biome delimitation
PW Moonlight, PL Silva de Miranda… - Global Ecology and …, 2020 - Wiley Online Library
Global Ecology and Biogeography, 2020•Wiley Online Library
Aim The 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. Location North‐east Brazil,
including Minas Gerais. Time period Present. Major taxa studied Flowering plants. Methods
Species 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 …
macroecological patterns in a species‐rich, tropical region and provide recommendations
for using SDMs in areas with sparse biotic inventory data. Location North‐east Brazil,
including Minas Gerais. Time period Present. Major taxa studied Flowering plants. Methods
Species 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 …
Aim
The 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.
Location
North‐east Brazil, including Minas Gerais.
Time period
Present.
Major taxa studied
Flowering plants.
Methods
Species 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.
Results
The 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 conclusions
Our 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.
Wiley Online Library以上显示的是最相近的搜索结果。 查看全部搜索结果