Literature DB >> 22594594

Efficient species-level monitoring at the landscape scale.

Barry R Noon1, Larissa L Bailey, Thomas D Sisk, Kevin S McKelvey.   

Abstract

Monitoring the population trends of multiple animal species at a landscape scale is prohibitively expensive. However, advances in survey design, statistical methods, and the ability to estimate species presence on the basis of detection-nondetection data have greatly increased the feasibility of species-level monitoring. For example, recent advances in monitoring make use of detection-nondetection data that are relatively inexpensive to acquire, historical survey data, and new techniques in genetic evaluation. The ability to use indirect measures of presence for some species greatly increases monitoring efficiency and reduces survey costs. After adjusting for false absences, the proportion of sample units in a landscape where a species is detected (occupancy) is a logical state variable to monitor. Occupancy monitoring can be based on real-time observation of a species at a survey site or on evidence that the species was at the survey location sometime in the recent past. Temporal and spatial patterns in occupancy data are related to changes in animal abundance and provide insights into the probability of a species' persistence. However, even with the efficiencies gained when occupancy is the monitored state variable, the task of species-level monitoring remains daunting due to the large number of species. We propose that a small number of species be monitored on the basis of specific management objectives, their functional role in an ecosystem, their sensitivity to environmental changes likely to occur in the area, or their conservation importance. ©2012 Society for Conservation Biology.

Mesh:

Year:  2012        PMID: 22594594     DOI: 10.1111/j.1523-1739.2012.01855.x

Source DB:  PubMed          Journal:  Conserv Biol        ISSN: 0888-8892            Impact factor:   6.560


  16 in total

1.  Long-term trends in the occupancy of ants revealed through use of multi-sourced datasets.

Authors:  Julie K Sheard; Carsten Rahbek; Robert R Dunn; Nathan J Sanders; Nick J B Isaac
Journal:  Biol Lett       Date:  2021-10-20       Impact factor: 3.812

2.  Discrepancies in occupancy and abundance approaches to identifying and protecting habitat for an at-risk species.

Authors:  Reilly R Dibner; Daniel F Doak; Melanie Murphy
Journal:  Ecol Evol       Date:  2017-06-15       Impact factor: 2.912

3.  Large anthropogenic impacts on a charismatic small carnivore: Insights from distribution surveys of red panda Ailurus fulgens in Nepal.

Authors:  Saroj Panthi; Gopal Khanal; Krishna Prasad Acharya; Achyut Aryal; Arjun Srivathsa
Journal:  PLoS One       Date:  2017-07-14       Impact factor: 3.240

4.  Summer Precipitation Predicts Spatial Distributions of Semiaquatic Mammals.

Authors:  Adam A Ahlers; Lisa A Cotner; Patrick J Wolff; Mark A Mitchell; Edward J Heske; Robert L Schooley
Journal:  PLoS One       Date:  2015-08-18       Impact factor: 3.240

5.  Long-term occupancy trends in a data-poor dugong population in the Andaman and Nicobar archipelago.

Authors:  Elrika D'Souza; Vardhan Patankar; Rohan Arthur; Teresa Alcoverro; Nachiket Kelkar
Journal:  PLoS One       Date:  2013-10-15       Impact factor: 3.240

6.  Guidelines for a priori grouping of species in hierarchical community models.

Authors:  Krishna Pacifici; Elise F Zipkin; Jaime A Collazo; Julissa I Irizarry; Amielle Dewan
Journal:  Ecol Evol       Date:  2014-02-22       Impact factor: 2.912

7.  Designing optimized multi-species monitoring networks to detect range shifts driven by climate change: a case study with bats in the North of Portugal.

Authors:  Francisco Amorim; Sílvia B Carvalho; João Honrado; Hugo Rebelo
Journal:  PLoS One       Date:  2014-01-27       Impact factor: 3.240

8.  Recommended survey designs for occupancy modelling using motion-activated cameras: insights from empirical wildlife data.

Authors:  Graeme Shannon; Jesse S Lewis; Brian D Gerber
Journal:  PeerJ       Date:  2014-08-28       Impact factor: 2.984

9.  Simulations inform design of regional occupancy-based monitoring for a sparsely distributed, territorial species.

Authors:  Quresh S Latif; Martha M Ellis; Victoria A Saab; Kim Mellen-McLean
Journal:  Ecol Evol       Date:  2017-12-20       Impact factor: 2.912

10.  A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions.

Authors:  David C Pavlacky; Paul M Lukacs; Jennifer A Blakesley; Robert C Skorkowsky; David S Klute; Beth A Hahn; Victoria J Dreitz; T Luke George; David J Hanni
Journal:  PLoS One       Date:  2017-10-24       Impact factor: 3.240

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