FN Archimer Export Format
PT J
TI Spatial patterns in the contribution of biotic and abiotic factors to the population dynamics of three freshwater fish species
BT 
AF Chevalier, Mathieu
   Tedesco, Pablo
   Grenouillet, Gael
AS 1:1;2:2;3:2;
FF 1:PDG-ODE-DYNECO-LEBCO;2:;3:;
C1 Centre de Bretagne, DYNECO, Laboratoire d’Ecologie Benthique Côtière (LEBCO), IFREMER, Plouzané, France
   Laboratoire Évolution & Diversité Biologique (EDB), CNRS, Université de Toulouse, Toulouse, France
C2 IFREMER, FRANCE
   CNRS, FRANCE
SI BREST
SE PDG-ODE-DYNECO-LEBCO
IN WOS Ifremer UPR
   DOAJ
   copubli-france
IF 2.7
TC 1
UR https://archimer.ifremer.fr/doc/00753/86474/91837.pdf
   https://archimer.ifremer.fr/doc/00753/86474/91838.docx
   https://archimer.ifremer.fr/doc/00753/86474/91839.bug
   https://archimer.ifremer.fr/doc/00753/86474/91840.txt
   https://archimer.ifremer.fr/doc/00753/86474/91841.rdata
   https://archimer.ifremer.fr/doc/00753/86474/91842.rdata
   https://archimer.ifremer.fr/doc/00753/86474/91843.rdata
LA English
DT Article
DE ;Water temperature;Density-dependence;Spatial variation;Size classes;Population dynamics;Length-frequency histograms;Abundant-center hypothesis;Range shifts
AB Background Population dynamics are driven by a number of biotic (e.g., density-dependence) and abiotic (e.g., climate) factors whose contribution can greatly vary across study systems (i.e., populations). Yet, the extent to which the contribution of these factors varies across populations and between species and whether spatial patterns can be identified has received little attention. Methods Here, we used a long-term (1982–2011), broad scale (182 sites distributed across metropolitan France) dataset to study spatial patterns in the population’s dynamics of three freshwater fish species presenting contrasted life-histories and patterns of elevation range shifts in recent decades. We used a hierarchical Bayesian approach together with an elasticity analysis to estimate the relative contribution of a set of biotic (e.g., strength of density dependence, recruitment rate) and abiotic (mean and variability of water temperature) factors affecting the site-specific dynamic of two different size classes (0+ and >0+ individuals) for the three species. We then tested whether the local contribution of each factor presented evidence for biogeographical patterns by confronting two non-mutually exclusive hypotheses: the “range-shift” hypothesis that predicts a gradient along elevation or latitude and the “abundant-center” hypothesis that predicts a gradient from the center to the edge of the species’ distributional range. Results Despite contrasted life-histories, the three species displayed similar large-scale patterns in population dynamics with a much stronger contribution of biotic factors over abiotic ones. Yet, the contribution of the different factors strongly varied within distributional ranges and followed distinct spatial patterns. Indeed, while abiotic factors mostly varied along elevation, biotic factors—which disproportionately contributed to population dynamics—varied along both elevation and latitude. Conclusions Overall while our results provide stronger support for the range-shift hypothesis, they also highlight the dual effect of distinct factors on spatial patterns in population dynamics and can explain the overall difficulty to find general evidence for geographic gradients in natural populations. We propose that considering the separate contribution of the factors affecting population dynamics could help better understand the drivers of abundance-distribution patterns. 
PY 2022
PD FEB
SO PeerJ
SN 2167-8359
PU PeerJ
VL 10
UT 000763778900001
DI 10.7717/peerj.12857
ID 86474
ER

EF