Environmental and historical imprints on beta diversity: insights from variation in rates of species turnover along gradients.
A common approach for analysing geographical variation in biodiversity involves using linear models to determine the rate at which species similarity declines with geographical or environmental distance and comparing this rate among regions, taxa or communities. Implicit in this approach are weakly justified assumptions that the rate of species turnover remains constant along gradients and that this rate can therefore serve as a means to compare ecological systems. We use generalized dissimilarity modelling, a novel method that accommodates variation in rates of species turnover along gradients and between different gradients, to compare environmental and spatial controls on the floras of two regions with contrasting evolutionary and climatic histories: southwest Australia and northern Europe. We find stronger signals of climate history in the northern European flora and demonstrate that variation in rates of species turnover is persistent across regions, taxa and different gradients. Such variation may represent an important but often overlooked component of biodiversity that complicates comparisons of distance-decay relationships and underscores the importance of using methods that accommodate the curvilinear relationships expected when modelling beta diversity. Determining how rates of species turnover vary along and between gradients is relevant to understanding the sensitivity of ecological systems to environmental change.
Appalachian Laboratory, University of Maryland Centre for Environmental Science, Frostburg, MD 21532, USA. mfitzpatrick@umces.edu
Matthew C
MC
Fitzpatrick
Nathan J
NJ
Sanders
Signe
S
Normand
Jens-Christian
JC
Svenning
Simon
S
Ferrier
Aaron D
AD
Gove
Robert R
RR
Dunn
D044822:Biodiversity; D002980:Climate; D004777:Environment; D005843:Geography; D008954:Models, Biological; D058974:Phylogeography; D011157:Population Dynamics
beta diversity; distance decay; environmental gradients; generalized dissimilarity modelling; history; plant species distributions