Population Viability Analysis with Species Occurrence Data from Museum Collections

被引:6
|
作者
Skarpaas, Olav [1 ]
Stabbetorp, Odd E. [1 ]
机构
[1] Norwegian Inst Nat Res NINA, N-0349 Oslo, Norway
关键词
extinction risk; IUCN Red List categories; observation error; occurrence data; population viability analysis; scientific collections; state-space model; ESTIMATING ABUNDANCE; PROCESS NOISE; EXTINCTION; MEANINGFUL; MODELS;
D O I
10.1111/j.1523-1739.2010.01636.x
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
The most comprehensive data on many species come from scientific collections. Thus, we developed a method of population viability analysis (PVA) in which this type of occurrence data can be used. In contrast to classical PVA, our approach accounts for the inherent observation error in occurrence data and allows the estimation of the population parameters needed for viability analysis. We tested the sensitivity of the approach to spatial resolution of the data, length of the time series, sampling effort, and detection probability with simulated data and conducted PVAs for common, rare, and threatened species. We compared the results of these PVAs with results of standard method PVAs in which observation error is ignored. Our method provided realistic estimates of population growth terms and quasi-extinction risk in cases in which the standard method without observation error could not. For low values of any of the sampling variables we tested, precision decreased, and in some cases biased estimates resulted. The results of our PVAs with the example species were consistent with information in the literature on these species. Our approach may facilitate PVA for a wide range of species of conservation concern for which demographic data are lacking but occurrence data are readily available.
引用
收藏
页码:577 / 586
页数:10
相关论文
共 50 条
  • [1] DATA MODELING FOR MUSEUM COLLECTIONS
    Lo Turco, M.
    Calvano, M.
    Giovannini, E. C.
    [J]. 8TH INTERNATIONAL WORKSHOP 3D-ARCH: 3D VIRTUAL RECONSTRUCTION AND VISUALIZATION OF COMPLEX ARCHITECTURES, 2019, 42-2 (W9): : 433 - 440
  • [2] Museum collections, species distributions, and rarefaction
    Solow, Andrew R.
    Roberts, David L.
    [J]. DIVERSITY AND DISTRIBUTIONS, 2006, 12 (04) : 423 - 424
  • [3] Museum collections, scanning, and data access
    Gilissen, Emmanuel
    [J]. JOURNAL OF ANTHROPOLOGICAL SCIENCES, 2009, 87 : 223 - 226
  • [4] Species relative abundances reflected in museum collections
    Ferguson, Ken
    [J]. FRONTIERS IN ECOLOGY AND THE ENVIRONMENT, 2021, 19 (09) : 488 - 488
  • [5] The predictive accuracy of population viability analysis: a test using data from two small mammal species in a fragmented landscape
    Ball, SJ
    Lindenmayer, DB
    Possingham, HP
    [J]. BIODIVERSITY AND CONSERVATION, 2003, 12 (12) : 2393 - 2413
  • [6] The predictive accuracy of population viability analysis: a test using data from two small mammal species in a fragmented landscape
    Stephen J. Ball
    David B. Lindenmayer
    Hugh P. Possingham
    [J]. Biodiversity & Conservation, 2003, 12 : 2393 - 2413
  • [7] Visual Topical Analysis of Museum Collections
    An, Lu
    Zhou, Liqin
    Lin, Xia
    Yu, Chuanming
    [J]. DIGITAL LIBRARIES: PROVIDING QUALITY INFORMATION, 2015, 9469 : 1 - 11
  • [8] Validating population viability analysis for corrupted data sets
    Holmes, EE
    Fagan, WE
    [J]. ECOLOGY, 2002, 83 (09) : 2379 - 2386
  • [9] Population Viability Analysis for Two Species of Imperiled Freshwater Turtles
    Gregory, Kaili M.
    Darst, Cat
    Lantz, Samantha M.
    Powelson, Katherine
    Ashton, Don
    Fisher, Robert
    Halstead, Brian J.
    Hubbs, Brian
    Lovich, Jeffrey E.
    McGowan, Conor P.
    [J]. CHELONIAN CONSERVATION AND BIOLOGY, 2024, 23 (01) : 1 - 12