Reconstruction of brown bear population dynamics in Slovenia in the period 1998-2019: a new approach combining genetics and long-term mortality data
Reliable data and methods for assessing changes in wildlife population size over time are necessary for management and conservation. For most species, assessing abundance is an expensive and labor-intensive task that is not affordable on a frequent basis. We present a novel approach to reco...
Guardado en:
Autores principales: | , |
---|---|
Formato: | article |
Lenguaje: | DE EN ES FR SL |
Publicado: |
Slovenian Forestry Institute
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/17ecd3b98f5946eba2d679e1ad77e022 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
id |
oai:doaj.org-article:17ecd3b98f5946eba2d679e1ad77e022 |
---|---|
record_format |
dspace |
spelling |
oai:doaj.org-article:17ecd3b98f5946eba2d679e1ad77e0222021-11-15T12:40:55ZReconstruction of brown bear population dynamics in Slovenia in the period 1998-2019: a new approach combining genetics and long-term mortality data2335-31122335-395310.20315/ASetL.124.3https://doaj.org/article/17ecd3b98f5946eba2d679e1ad77e0222021-01-01T00:00:00Zhttp://dirros.openscience.si/IzpisGradiva.php?id=13799https://doaj.org/toc/2335-3112https://doaj.org/toc/2335-3953 Reliable data and methods for assessing changes in wildlife population size over time are necessary for management and conservation. For most species, assessing abundance is an expensive and labor-intensive task that is not affordable on a frequent basis. We present a novel approach to reconstructing brown bear population dynamics in Slovenia in the period 1998-2019, based on the combination of two CMR non-invasive genetic estimates (in 2007 and 2015) and long-term mortality records, to show how the latter can help the study of population dynamics in combination with point-in-time estimates. The spring (i.e. including newborn cubs) population size estimate was 383 (CI: 336-432) bears in 1998 and 971 (CI: 825-1161) bears in 2019. In this period, the average annual population growth rate was 4.5 %. The predicted population size differed by just 7 % from the non-invasive genetic size estimate after eight years, suggesting that the method is reliable. It can predict the evolution of the population size under different management scenarios and provide information on key parameters, e.g. background mortality and the sex- and age-structure of the population. Our approach can be used for several other wildlife species, but it requires reliable mortality data over time.Klemen JerinaAndrés OrdizSlovenian Forestry InstitutearticleForestrySD1-669.5Environmental sciencesGE1-350DEENESFRSLActa Silvae et Ligni, Vol 124, Pp 29-40 (2021) |
institution |
DOAJ |
collection |
DOAJ |
language |
DE EN ES FR SL |
topic |
Forestry SD1-669.5 Environmental sciences GE1-350 |
spellingShingle |
Forestry SD1-669.5 Environmental sciences GE1-350 Klemen Jerina Andrés Ordiz Reconstruction of brown bear population dynamics in Slovenia in the period 1998-2019: a new approach combining genetics and long-term mortality data |
description |
Reliable data and methods for assessing changes in wildlife population size over time are necessary for management and conservation. For most species, assessing abundance is an expensive and labor-intensive task that is not affordable on a frequent basis. We present a novel approach to reconstructing brown bear population dynamics in Slovenia in the period 1998-2019, based on the combination of two CMR non-invasive genetic estimates (in 2007 and 2015) and long-term mortality records, to show how the latter can help the study of population dynamics in combination with point-in-time estimates. The spring (i.e. including newborn cubs) population size estimate was 383 (CI: 336-432) bears in 1998 and 971 (CI: 825-1161) bears in 2019. In this period, the average annual population growth rate was 4.5 %. The predicted population size differed by just 7 % from the non-invasive genetic size estimate after eight years, suggesting that the method is reliable. It can predict the evolution of the population size under different management scenarios and provide information on key parameters, e.g. background mortality and the sex- and age-structure of the population. Our approach can be used for several other wildlife species, but it requires reliable mortality data over time. |
format |
article |
author |
Klemen Jerina Andrés Ordiz |
author_facet |
Klemen Jerina Andrés Ordiz |
author_sort |
Klemen Jerina |
title |
Reconstruction of brown bear population dynamics in Slovenia in the period 1998-2019: a new approach combining genetics and long-term mortality data |
title_short |
Reconstruction of brown bear population dynamics in Slovenia in the period 1998-2019: a new approach combining genetics and long-term mortality data |
title_full |
Reconstruction of brown bear population dynamics in Slovenia in the period 1998-2019: a new approach combining genetics and long-term mortality data |
title_fullStr |
Reconstruction of brown bear population dynamics in Slovenia in the period 1998-2019: a new approach combining genetics and long-term mortality data |
title_full_unstemmed |
Reconstruction of brown bear population dynamics in Slovenia in the period 1998-2019: a new approach combining genetics and long-term mortality data |
title_sort |
reconstruction of brown bear population dynamics in slovenia in the period 1998-2019: a new approach combining genetics and long-term mortality data |
publisher |
Slovenian Forestry Institute |
publishDate |
2021 |
url |
https://doaj.org/article/17ecd3b98f5946eba2d679e1ad77e022 |
work_keys_str_mv |
AT klemenjerina reconstructionofbrownbearpopulationdynamicsinsloveniaintheperiod19982019anewapproachcombininggeneticsandlongtermmortalitydata AT andresordiz reconstructionofbrownbearpopulationdynamicsinsloveniaintheperiod19982019anewapproachcombininggeneticsandlongtermmortalitydata |
_version_ |
1718428416406978560 |