Management agencies need statistically robust, cost-effective monitoring programs to effectively conserve and manage wildlife. However, this requires pilot studies to assess the monitoring protocol's ability to detect meaningful changes in the state variable of interest. This is more challenging for elusive mammals due to low detection rates and the costs associated with fieldwork. A key knowledge gap concerns how spatio-temporal dynamics in species occupancy and detection rates alter the cost-effectiveness of sampling protocols. To fill this gap we used a dataset spanning 16 years on Canada lynx (Lynx canadensis) track surveys conducted in Maine, USA, and developed optimal monitoring protocols that empirically assess the cost-effectiveness of these protocols under different scenarios. We surveyed 96 townships and detected 949 track intercepts, which were converted to detection histories under a spatially-replicated occupancy design. By combining occupancy modeling and power analyses, we estimated the sampling effort required to detect declines in occupancy from 10 to 50 %. Calculating the monetary cost of these protocols indicated that detecting subtle changes in occupancy (<10 %) is very expensive even within high suitability habitats and may often be unrealistic. However, protocols that detected medium (30 %) to large (50 %) declines required similar budgets and were consistent with the observed shifts in occupancy during our study period (34 %), suggesting that a modest budget increase would pay large dividends in population assessment efficacy. Our results provide important guidance on how to implement robust and cost-effective monitoring programs with snow track surveys - a popular survey method used by many conservation agencies.

Developing cost-effective monitoring protocols for track-surveys: An empirical assessment using a Canada lynx Lynx canadensis dataset spanning 16 years

Alessio Mortelliti
2022-01-01

Abstract

Management agencies need statistically robust, cost-effective monitoring programs to effectively conserve and manage wildlife. However, this requires pilot studies to assess the monitoring protocol's ability to detect meaningful changes in the state variable of interest. This is more challenging for elusive mammals due to low detection rates and the costs associated with fieldwork. A key knowledge gap concerns how spatio-temporal dynamics in species occupancy and detection rates alter the cost-effectiveness of sampling protocols. To fill this gap we used a dataset spanning 16 years on Canada lynx (Lynx canadensis) track surveys conducted in Maine, USA, and developed optimal monitoring protocols that empirically assess the cost-effectiveness of these protocols under different scenarios. We surveyed 96 townships and detected 949 track intercepts, which were converted to detection histories under a spatially-replicated occupancy design. By combining occupancy modeling and power analyses, we estimated the sampling effort required to detect declines in occupancy from 10 to 50 %. Calculating the monetary cost of these protocols indicated that detecting subtle changes in occupancy (<10 %) is very expensive even within high suitability habitats and may often be unrealistic. However, protocols that detected medium (30 %) to large (50 %) declines required similar budgets and were consistent with the observed shifts in occupancy during our study period (34 %), suggesting that a modest budget increase would pay large dividends in population assessment efficacy. Our results provide important guidance on how to implement robust and cost-effective monitoring programs with snow track surveys - a popular survey method used by many conservation agencies.
2022
17-nov-2022
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https://www.sciencedirect.com/science/article/pii/S0006320722003469
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3034099
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