Spatial population dynamics of small mammals: some methodological and practical issues
Small mammals have been widely used to further our understanding of spatial and temporal population dynamical patterns, because their dynamics exhibit large variations, both in time (multi-annual cycles vs. seasonal variation only) and space (regional synchrony, travelling waves). Small mammals have...
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ftdoajarticles:oai:doaj.org/article:32ffdb7c06d94c2a8516ea44323a63a0 2023-05-15T17:39:23+02:00 Spatial population dynamics of small mammals: some methodological and practical issues Yoccoz, N. G. Ims, R. A. 2004-06-01T00:00:00Z https://doaj.org/article/32ffdb7c06d94c2a8516ea44323a63a0 EN ES eng spa Museu de Ciències Naturals de Barcelona http://abc.museucienciesjournals.cat/files/ABC-27-1-pp-427-435.pdf https://doaj.org/toc/1578-665X 1578-665X https://doaj.org/article/32ffdb7c06d94c2a8516ea44323a63a0 Animal Biodiversity and Conservation, Vol 27, Iss 1, Pp 427-435 (2004) Spatial autocorrelation Measurement error Voles Norway Zoology QL1-991 article 2004 ftdoajarticles 2022-12-31T01:12:00Z Small mammals have been widely used to further our understanding of spatial and temporal population dynamical patterns, because their dynamics exhibit large variations, both in time (multi-annual cycles vs. seasonal variation only) and space (regional synchrony, travelling waves). Small mammals have therefore been the focus of a large number of empirical and statistical (analysis of time-series) studies, mostly based on trapping indices. These studies did not take into account sampling variability associated with the use of counts or estimates of population size. In this paper, we use our field study focusing on population dynamics and demography of small mammals in North Norway at three spatial scales (0.1, 10 and 100 km) to illustrate some methodological and practical issues. We first investigate the empirical patterns of spatial population dynamics, focusing on correlation among time-series of population abundance at increasing spatial scales. We then assess using simulated data the bias of estimates of spatial correlation induced by using either population indices such as the number of individuals captured (i.e., raw counts) or estimates of population size derived from statistical modeling of capture-recapture data. The problems encountered are similar to those described when assessing density-dependence in time-series -a special case of the consequence of measurement error for estimates of regression coefficients- but are to our knowledge ignored in the ecological literature. We suggest some empirical solutions as well as more rigorous approaches. Article in Journal/Newspaper North Norway Directory of Open Access Journals: DOAJ Articles Norway |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English Spanish |
topic |
Spatial autocorrelation Measurement error Voles Norway Zoology QL1-991 |
spellingShingle |
Spatial autocorrelation Measurement error Voles Norway Zoology QL1-991 Yoccoz, N. G. Ims, R. A. Spatial population dynamics of small mammals: some methodological and practical issues |
topic_facet |
Spatial autocorrelation Measurement error Voles Norway Zoology QL1-991 |
description |
Small mammals have been widely used to further our understanding of spatial and temporal population dynamical patterns, because their dynamics exhibit large variations, both in time (multi-annual cycles vs. seasonal variation only) and space (regional synchrony, travelling waves). Small mammals have therefore been the focus of a large number of empirical and statistical (analysis of time-series) studies, mostly based on trapping indices. These studies did not take into account sampling variability associated with the use of counts or estimates of population size. In this paper, we use our field study focusing on population dynamics and demography of small mammals in North Norway at three spatial scales (0.1, 10 and 100 km) to illustrate some methodological and practical issues. We first investigate the empirical patterns of spatial population dynamics, focusing on correlation among time-series of population abundance at increasing spatial scales. We then assess using simulated data the bias of estimates of spatial correlation induced by using either population indices such as the number of individuals captured (i.e., raw counts) or estimates of population size derived from statistical modeling of capture-recapture data. The problems encountered are similar to those described when assessing density-dependence in time-series -a special case of the consequence of measurement error for estimates of regression coefficients- but are to our knowledge ignored in the ecological literature. We suggest some empirical solutions as well as more rigorous approaches. |
format |
Article in Journal/Newspaper |
author |
Yoccoz, N. G. Ims, R. A. |
author_facet |
Yoccoz, N. G. Ims, R. A. |
author_sort |
Yoccoz, N. G. |
title |
Spatial population dynamics of small mammals: some methodological and practical issues |
title_short |
Spatial population dynamics of small mammals: some methodological and practical issues |
title_full |
Spatial population dynamics of small mammals: some methodological and practical issues |
title_fullStr |
Spatial population dynamics of small mammals: some methodological and practical issues |
title_full_unstemmed |
Spatial population dynamics of small mammals: some methodological and practical issues |
title_sort |
spatial population dynamics of small mammals: some methodological and practical issues |
publisher |
Museu de Ciències Naturals de Barcelona |
publishDate |
2004 |
url |
https://doaj.org/article/32ffdb7c06d94c2a8516ea44323a63a0 |
geographic |
Norway |
geographic_facet |
Norway |
genre |
North Norway |
genre_facet |
North Norway |
op_source |
Animal Biodiversity and Conservation, Vol 27, Iss 1, Pp 427-435 (2004) |
op_relation |
http://abc.museucienciesjournals.cat/files/ABC-27-1-pp-427-435.pdf https://doaj.org/toc/1578-665X 1578-665X https://doaj.org/article/32ffdb7c06d94c2a8516ea44323a63a0 |
_version_ |
1766140143459106816 |