Premium
Patterns of density, diversity, and the distribution of migratory strategies in the Russian boreal forest avifauna
Author(s) -
Greenberg Russell,
Kozlenko Anna,
Etterson Matthew,
Dietsch Thomas
Publication year - 2008
Publication title -
journal of biogeography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.7
H-Index - 158
eISSN - 1365-2699
pISSN - 0305-0270
DOI - 10.1111/j.1365-2699.2008.01954.x
Subject(s) - boreal , taiga , species richness , geography , ecology , abundance (ecology) , physical geography , latitude , correlogram , akaike information criterion , longitude , spatial analysis , habitat , biology , forestry , statistics , remote sensing , mathematics , geodesy
Aim Comparisons of the biotas in the Palaearctic and Nearctic have focused on limited portions of the two regions. The purpose of this study was to assess the geographic pattern in the abundance, species richness, and importance of different migration patterns of the boreal forest avifauna of Eurasia from Europe to East Asia as well as their relationship to climate and forest productivity. We further examine data from two widely separated sites in the New World to see how these conform to the patterns found in the Eurasian system. Location Boreal forest sites in Russia and Canada. Methods Point counts were conducted in two to four boreal forest habitats at each of 14 sites in the Russian boreal forest from near to the Finnish border to the Far East, as well as at two sites in boreal Canada. We examined the abundance and species richness of all birds, and specific migratory classes, against four gradients (climate, primary productivity, latitude, and longitude). We tested for spatial autocorrelation in both dependent and independent variables using Moran’s I to develop spatial correlograms. For each migratory class we used maximum likelihood to fit models, first assuming uncorrelated residuals and then assuming spatially autocorrelated residuals. For models assuming unstructured residuals we again generated correlograms on model residuals to determine whether model fitting removed spatial autocorrelation. Models were compared using Akaike’s information criterion, adjusted for small sample size. Results Overall abundance was highest at the eastern and western extremes of the survey region and lowest at the continent centre, whereas the abundance of tropical and short‐distance migrants displayed an east–west gradient, with tropical migrants increasing in abundance in the east (and south), and short‐distance migrants in the west. Although overall species richness showed no geographic pattern, richness within migratory classes showed patterns weaker than, but similar to, their abundance patterns described above. Overall abundance was correlated with climate variables that relate to continentality. The abundances of birds within different migration strategies were correlated with a second climatic gradient – increasing precipitation from west to east. Models using descriptors of location generally had greater explanatory value for the abundance and species‐richness response variables than did those based on climate data and the normalized difference vegetation index (NDVI). Main conclusions The distribution patterns for migrant types were related to both climatic and locational variables, and thus the patterns could be explained by either climatic regime or the accessibility of winter habitats, both historically and currently. Non‐boreal wintering habitat is more accessible from both the western and eastern ends than from the centre of the boreal forest belt, but the tropics are most accessible from the eastern end of the Palaearctic boreal zone, in terms of distance and the absence of geographical barriers. Based on comparisons with Canadian sites, we recommend that future comparative studies between Palaearctic and Nearctic faunas be focused more on Siberia and the Russian Far East, as well as on central and western Canada.