Poleward range expansion without a southern contraction in the ground beetle Agonum viridicupreum (Coleoptera, Carabidae)
Author(s) -
Claudia Drees,
Pietro Brandmayr,
Jörn Buse,
Petra Dieker,
Stephan Gurlich,
Jan Christian Habel,
Ingmar Harry,
Werner Härdtle,
Andrea Matern,
Hartmut Meyer,
Roberto Pizzoloto,
Markus Quante,
Katharina Shafer,
Andreas Schuldt,
Ángela Taboada,
Thorsten Aßmann
Publication year - 2011
Publication title -
zookeys
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 43
eISSN - 1313-2989
pISSN - 1313-2970
DOI - 10.3897/zookeys.100.1535
Subject(s) - range (aeronautics) , geography , species distribution , latitude , climate change , ground beetle , physical geography , context (archaeology) , ecology , environmental niche modelling , ecological niche , habitat , biology , archaeology , geodesy , composite material , materials science
We investigated the extent of poleward shifts in the distribution range of Agonum viridicupreum due to climate change in the western Palaearctic. Species' records were obtained from extensive literature sources as well as from collections, and consistent amateur entomologists' recordings. Within the general geographic range of the species, we analyzed in detail two parts of both, the northern and southern distribution range boundaries: (1 and 2) north-western Germany (leading or high-latitude edge), (3) Israel and (4) southern Italy (rear or low-latitude edge). Temporal changes in the occurrence data of the species indicated a northward shift of the leading edge of a minimum of 100 km within the last 50 to 100 years. In contrast, according to the data gathered, the rear edge has not changed during the last decades. Further studies are needed in order to fully understand the underlying mechanisms of the different behaviour of leading and rear range edges of Agonum viridicupreum in the current context of global change. Despite our incomplete understanding, chronosequences of the occurrence of the given species have the potential to optimize climate niche modelling to predict trends in the distribution range in the future.
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