Optimizing Presence–Absence Surveys For Detecting Population Trends
(2006) In Journal of Wildlife Management 70(1). p.8-18- Abstract
- Presence–absence surveys are a commonly used method for monitoring broad-scale changes in wildlife distributions. However, the lack of power of these surveys for detecting population trends is problematic for their application in wildlife management. Options for improving power include increasing the sampling effort or arbitrarily relaxing the type I error rate. We present an alternative, whereby targeted sampling of particular habitats in the landscape using information from a habitat model increases power. The advantage of this approach is that it does not require a trade-off with either cost or the Pr{type I error} to achieve greater power. We use a demographic model of koala (Phascolarctos cinereus) population dynamics and simulations... (More)
- Presence–absence surveys are a commonly used method for monitoring broad-scale changes in wildlife distributions. However, the lack of power of these surveys for detecting population trends is problematic for their application in wildlife management. Options for improving power include increasing the sampling effort or arbitrarily relaxing the type I error rate. We present an alternative, whereby targeted sampling of particular habitats in the landscape using information from a habitat model increases power. The advantage of this approach is that it does not require a trade-off with either cost or the Pr{type I error} to achieve greater power. We use a demographic model of koala (Phascolarctos cinereus) population dynamics and simulations of the monitoring process to estimate the power to detect a trend in occupancy for a range of strategies, thereby demonstrating that targeting particular habitat qualities can improve power substantially. If the objective is to detect a decline in occupancy, the optimal strategy is to sample high-quality habitats. Alternatively, if the objective is to detect an increase in occupancy, the optimal strategy is to sample intermediate-quality habitats. The strategies with the highest power remained the same under a range of parameter assumptions, although observation error had a strong influence on the optimal strategy. Our approach specifically applies to monitoring for detecting long-term trends in occupancy or abundance. This is a common and important monitoring objective for wildlife managers, and we provide guidelines for more effectively achieving it. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/165284
- author
- Rhodes, J R ; Tyre, A J ; Jonzén, Niclas LU ; McAlpine, C A and Possingham, H P
- organization
- publishing date
- 2006
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Journal of Wildlife Management
- volume
- 70
- issue
- 1
- pages
- 8 - 18
- publisher
- The Wildlife Society
- external identifiers
-
- scopus:33646489328
- ISSN
- 0022-541X
- DOI
- 10.2193/0022-541X(2006)70[8:OPSFDP]2.0.CO;2
- language
- English
- LU publication?
- yes
- id
- e10b783b-ba9d-4a8f-b3cf-4b52f55def03 (old id 165284)
- date added to LUP
- 2016-04-01 16:53:23
- date last changed
- 2022-04-07 19:27:00
@article{e10b783b-ba9d-4a8f-b3cf-4b52f55def03,
abstract = {{Presence–absence surveys are a commonly used method for monitoring broad-scale changes in wildlife distributions. However, the lack of power of these surveys for detecting population trends is problematic for their application in wildlife management. Options for improving power include increasing the sampling effort or arbitrarily relaxing the type I error rate. We present an alternative, whereby targeted sampling of particular habitats in the landscape using information from a habitat model increases power. The advantage of this approach is that it does not require a trade-off with either cost or the Pr{type I error} to achieve greater power. We use a demographic model of koala (Phascolarctos cinereus) population dynamics and simulations of the monitoring process to estimate the power to detect a trend in occupancy for a range of strategies, thereby demonstrating that targeting particular habitat qualities can improve power substantially. If the objective is to detect a decline in occupancy, the optimal strategy is to sample high-quality habitats. Alternatively, if the objective is to detect an increase in occupancy, the optimal strategy is to sample intermediate-quality habitats. The strategies with the highest power remained the same under a range of parameter assumptions, although observation error had a strong influence on the optimal strategy. Our approach specifically applies to monitoring for detecting long-term trends in occupancy or abundance. This is a common and important monitoring objective for wildlife managers, and we provide guidelines for more effectively achieving it.}},
author = {{Rhodes, J R and Tyre, A J and Jonzén, Niclas and McAlpine, C A and Possingham, H P}},
issn = {{0022-541X}},
language = {{eng}},
number = {{1}},
pages = {{8--18}},
publisher = {{The Wildlife Society}},
series = {{Journal of Wildlife Management}},
title = {{Optimizing Presence–Absence Surveys For Detecting Population Trends}},
url = {{http://dx.doi.org/10.2193/0022-541X(2006)70[8:OPSFDP]2.0.CO;2}},
doi = {{10.2193/0022-541X(2006)70[8:OPSFDP]2.0.CO;2}},
volume = {{70}},
year = {{2006}},
}