Using wildlife indicators to facilitate wildlife monitoring in hunter-self monitoring schemes

Sergio Marrocoli; Martin Reinhardt Nielsen; David Morgan; Tom van Loon; Lars Kulik; Hjalmar Kühl

doi:10.1016/j.ecolind.2019.05.050

Using wildlife indicators to facilitate wildlife monitoring in hunter-self monitoring schemes

Sergio Marrocoli, Martin Reinhardt Nielsen, David Morgan, Tom van Loon, Lars Kulik, Hjalmar Kühl

Section for Global Development

3 Citations (Scopus)

Abstract

Wildlife populations in tropical forests are difficult to monitor. Hunter self-monitoring schemes hold promise, but their accuracy in estimating populations has not been verified and obtaining useful wildlife estimates from generally low-quality data remains a challenge. We tested whether wildlife indicators could be useful for wildlife monitoring in such schemes, because they might eliminate the need to estimate effort in hunter surveys, and reduce records of many species into a single informative indicator. We implemented a hunter self-monitoring scheme in eight villages in the northern Republic of Congo, collecting shotgun, snare, and camera trap records in “zones” within each village’s hunting territory (shotguns = 83 zones, snares = 50 zones, cameras = 21 zones). Using each of these three survey methods, we calculated for each zone three different indicators used in wildlife studies: mean body mass, the mean intrinsic rate of increase (rmax), and a duiker index (small duikers as a percentage of small and medium sized duikers). Survey effort could be estimated for both snares and cameras and was used to estimate species relative abundances (Catch Per Unit Effort, CPUE). Mean body mass was the most effective indicator, followed by the duiker index. Both were correlated between survey methods and changed with increasing hunting pressure regardless of survey method used. They also predicted the total CPUE of animals >15 kg for zones, and often the CPUE of individual species. They also gave the most precise estimates of the three indicators, and snare estimates were more precise than shotgun. In contrast, mean rmax generally performed poorly, and was often not correlated with the other indicators, or with hunting pressure. Our findings suggest that some indicators can produce useful wildlife estimates from hunter self-monitoring schemes, that are also easy to implement and comprehend for hunters and wildlife managers.

Original language	English
Journal	Ecological Indicators
Volume	105
Pages (from-to)	254-263
Number of pages	10
ISSN	1470-160X
DOIs	https://doi.org/10.1016/j.ecolind.2019.05.050
Publication status	Published - Oct 2019

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@article{f0e0eaca8b024c7aac0c56d42fd93f40,

title = "Using wildlife indicators to facilitate wildlife monitoring in hunter-self monitoring schemes",

abstract = "Wildlife populations in tropical forests are difficult to monitor. Hunter self-monitoring schemes hold promise, but their accuracy in estimating populations has not been verified and obtaining useful wildlife estimates from generally low-quality data remains a challenge. We tested whether wildlife indicators could be useful for wildlife monitoring in such schemes, because they might eliminate the need to estimate effort in hunter surveys, and reduce records of many species into a single informative indicator. We implemented a hunter self-monitoring scheme in eight villages in the northern Republic of Congo, collecting shotgun, snare, and camera trap records in “zones” within each village{\textquoteright}s hunting territory (shotguns = 83 zones, snares = 50 zones, cameras = 21 zones). Using each of these three survey methods, we calculated for each zone three different indicators used in wildlife studies: mean body mass, the mean intrinsic rate of increase (rmax), and a duiker index (small duikers as a percentage of small and medium sized duikers). Survey effort could be estimated for both snares and cameras and was used to estimate species relative abundances (Catch Per Unit Effort, CPUE). Mean body mass was the most effective indicator, followed by the duiker index. Both were correlated between survey methods and changed with increasing hunting pressure regardless of survey method used. They also predicted the total CPUE of animals >15 kg for zones, and often the CPUE of individual species. They also gave the most precise estimates of the three indicators, and snare estimates were more precise than shotgun. In contrast, mean rmax generally performed poorly, and was often not correlated with the other indicators, or with hunting pressure. Our findings suggest that some indicators can produce useful wildlife estimates from hunter self-monitoring schemes, that are also easy to implement and comprehend for hunters and wildlife managers.",

author = "Sergio Marrocoli and Nielsen, {Martin Reinhardt} and David Morgan and {van Loon}, Tom and Lars Kulik and Hjalmar K{\"u}hl",

year = "2019",

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doi = "10.1016/j.ecolind.2019.05.050",

language = "English",

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journal = "Ecological Indicators",

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AU - Marrocoli, Sergio

AU - Nielsen, Martin Reinhardt

AU - Morgan, David

AU - van Loon, Tom

AU - Kulik, Lars

AU - Kühl, Hjalmar

PY - 2019/10

Y1 - 2019/10

N2 - Wildlife populations in tropical forests are difficult to monitor. Hunter self-monitoring schemes hold promise, but their accuracy in estimating populations has not been verified and obtaining useful wildlife estimates from generally low-quality data remains a challenge. We tested whether wildlife indicators could be useful for wildlife monitoring in such schemes, because they might eliminate the need to estimate effort in hunter surveys, and reduce records of many species into a single informative indicator. We implemented a hunter self-monitoring scheme in eight villages in the northern Republic of Congo, collecting shotgun, snare, and camera trap records in “zones” within each village’s hunting territory (shotguns = 83 zones, snares = 50 zones, cameras = 21 zones). Using each of these three survey methods, we calculated for each zone three different indicators used in wildlife studies: mean body mass, the mean intrinsic rate of increase (rmax), and a duiker index (small duikers as a percentage of small and medium sized duikers). Survey effort could be estimated for both snares and cameras and was used to estimate species relative abundances (Catch Per Unit Effort, CPUE). Mean body mass was the most effective indicator, followed by the duiker index. Both were correlated between survey methods and changed with increasing hunting pressure regardless of survey method used. They also predicted the total CPUE of animals >15 kg for zones, and often the CPUE of individual species. They also gave the most precise estimates of the three indicators, and snare estimates were more precise than shotgun. In contrast, mean rmax generally performed poorly, and was often not correlated with the other indicators, or with hunting pressure. Our findings suggest that some indicators can produce useful wildlife estimates from hunter self-monitoring schemes, that are also easy to implement and comprehend for hunters and wildlife managers.

AB - Wildlife populations in tropical forests are difficult to monitor. Hunter self-monitoring schemes hold promise, but their accuracy in estimating populations has not been verified and obtaining useful wildlife estimates from generally low-quality data remains a challenge. We tested whether wildlife indicators could be useful for wildlife monitoring in such schemes, because they might eliminate the need to estimate effort in hunter surveys, and reduce records of many species into a single informative indicator. We implemented a hunter self-monitoring scheme in eight villages in the northern Republic of Congo, collecting shotgun, snare, and camera trap records in “zones” within each village’s hunting territory (shotguns = 83 zones, snares = 50 zones, cameras = 21 zones). Using each of these three survey methods, we calculated for each zone three different indicators used in wildlife studies: mean body mass, the mean intrinsic rate of increase (rmax), and a duiker index (small duikers as a percentage of small and medium sized duikers). Survey effort could be estimated for both snares and cameras and was used to estimate species relative abundances (Catch Per Unit Effort, CPUE). Mean body mass was the most effective indicator, followed by the duiker index. Both were correlated between survey methods and changed with increasing hunting pressure regardless of survey method used. They also predicted the total CPUE of animals >15 kg for zones, and often the CPUE of individual species. They also gave the most precise estimates of the three indicators, and snare estimates were more precise than shotgun. In contrast, mean rmax generally performed poorly, and was often not correlated with the other indicators, or with hunting pressure. Our findings suggest that some indicators can produce useful wildlife estimates from hunter self-monitoring schemes, that are also easy to implement and comprehend for hunters and wildlife managers.

U2 - 10.1016/j.ecolind.2019.05.050

DO - 10.1016/j.ecolind.2019.05.050

M3 - Journal article

SN - 1470-160X

VL - 105

SP - 254

EP - 263

JO - Ecological Indicators

JF - Ecological Indicators

ER -

Using wildlife indicators to facilitate wildlife monitoring in hunter-self monitoring schemes

Abstract

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