Improving population estimates of difficult‐to‐observe species: A dung decay model for forest elephants with remotely sensed imagery

Meier, Amelia; Shirley, Matthew H.; Beirne, Christopher; Breuer, Thomas; Lewis, Martin W.; Masseloux, Juliana; Jasperse-Sjolander, Liam; Todd, Angelique; Poulsen, John R.

doi:10.1111/acv.12704

Cited by 5 publications

(5 citation statements)

References 44 publications

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“…Instead, a promising way forward may be to understand predictors of behavioral variation, such as environmental drivers like rainfall, which could be used as a proxy of artifact production behavior where behavioral sampling is not possible. The approach of replacing locally measured metrics of sign discoverability with environmental proxies has been previously suggested as a useful method for accommodating variability in sign decay (Bessone et al ., 2021; Meier et al ., 2021), and therefore may be suitably extended to proxies of behavioral variability. To accomplish this, researchers who depend on metrics of behavior in surveying should aim to increase sampling efforts of that behavior across populations where behavior can be observed, and within those populations across time periods and seasons, to characterize behavioral variation for that species.…”

Section: Discussionmentioning

confidence: 99%

“…The impacts of behavioral variability upon population monitoring have wide reaching consequences across a variety of taxa, as all sign‐based monitoring is largely dependent in some form on behavior of the individuals who leave behind these traces. A wide range of taxa are surveyed using indirect methods like tracks (e.g., ungulates: Reyna‐Hurtado & Tanner, 2007; Licona et al ., 2011), feces/scat (e.g., elephants: Meier et al ., 2021, small carnivores: Espírito‐Santo, Rosalino & Santos‐Reis, 2007; García & Mateos, 2009, deer: Bailey & Putman, 1981; Massei & Genov, 1998; Marques et al ., 2001), and nest or drey counts (e.g., apes: Kouakou et al ., 2009, this study, squirrels: Gurnell et al ., 2004) that are clearly linked to behaviors that can vary. Furthermore, methodologies like hair traps (e.g., mustelids: García & Mateos, 2009), scent stations (e.g., bees: Almeida et al ., 2019), and exuviae (Raebel et al ., 2010) can also be argued to be dependent in some manner on behaviors that vary across scales (e.g., time, individual, social unit, population, and species).…”

Section: Discussionmentioning

confidence: 99%

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Failure to account for behavioral variability significantly compromises accuracy in indirect population monitoring

Wessling

Surbeck

2022

Animal Conservation

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Indirect wildlife population surveying largely depends upon counts of artifacts of behavior (e.g., nests or dung). Likelihood to encounter these artifacts is derived from both artifact production and decay, and variability in production behavior is considered to contribute minimally to inaccuracy in wildlife estimation. Here, we demonstrate how ignoring behavioral variability leads to significant population misestimation, using an example of an endangered ape, the bonobo (Pan paniscus). Until now, a single estimate of nest construction rate has been used to extrapolate bonobo densities, assumed to be broadly representative of bonobo sign production behavior. We estimated nest construction rates across seasons and social groups at the Kokolopori Bonobo Reserve, Democratic Republic of the Congo, and find nest construction rates in bonobos to be highly variable across populations as well as seasonal within populations. Failure to account for this variability led to degradation in the accuracy of bonobo population density estimates, accounting for a likely overestimation of bonobo numbers by 34%, and at worst as high as 80%. With this example, we demonstrate that failure to account for inter-and intrapopulation behavioral variation compromises the ability to estimate both relative and absolute wildlife abundances. We argue that variation in sign production is but one of the several potential ways that behavioral variability can affect conservation monitoring, should be measured across contexts whenever possible, and must be considered in population estimation confidence intervals. With increasing attention to behavioral variability as a potential tool for conservation, conservationists must also account for the impact that behavioral variability can have upon wildlife population estimation. Our results underline the importance of observational research to wildlife monitoring schemes as a critical component of conservation management. We discuss the avenues through which behavioral variability is likely to impact wildlife monitoring accuracy and precision and propose potential approaches for accounting for behavioral variability in wildlife monitoring.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Failure to account for behavioral variability significantly compromises accuracy in indirect population monitoring

Wessling

Surbeck

2022

Animal Conservation

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show abstract

“…Instead, a promising way forward may be to understand predictors of behavioral variation, such as environmental drivers like rainfall, which could be used as a proxy of artefact production behavior where behavioral sampling is not possible. The approach of replacing locally measured metrics of sign discoverability with environmental proxies has been previously suggested as a useful method for accommodating variability in sign decay (Meier et al 2021; Bessone et al 2021), and therefore may be suitably extended to proxies of behavioral variability. To accomplish this, researchers who depend on metrics of behavior in surveying should aim to increase sampling efforts of that behavior across populations where behavior can be observed, and within those populations across time periods and seasons, to characterize behavioral variation for that species.…”

Section: Discussionmentioning

confidence: 99%

“…The impacts of behavioral variability upon population monitoring have wide reaching consequences across a variety of taxa, as all sign-based monitoring is largely dependent in some form on behavior of the individuals who leave behind these traces. A wide range of taxa are surveyed using indirect methods like tracks (e.g., ungulates: Licona et al 2011; Reyna-Hurtado & Tanner 2007), feces/scat (e.g., elephants: Meier et al 2021, small carnivores: Espirito-Santo et al 2007, deer: Bailey & Putnam 1981, Marques et al 2001, Massei & Genov 1998), and nest or drey counts (e.g., apes: Kouakou et al 2009, this study, squirrels: Gurnell et al 2004) that are clearly linked to behaviors that can vary. Furthermore, methodologies like hair traps (e.g., mustelids: Garcia & Mateos 2009), scent stations (e.g., bees: Almeida et al 2019), and exuviae (Raebel et al 2010) can also be argued to be dependent in some manner on behaviors that vary across scales (e.g., time, individual, social unit, population, species).…”

Section: Discussionmentioning

confidence: 99%

Failure to account for behavioral variability significantly compromises accuracy in indirect population monitoring

Wessling

Surbeck

2021

Preprint

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Wildlife population monitoring depends on accurate counts of individual animals or artefacts of behavior (e.g., nests or dung), but also must account for potential biases in the likelihood to encounter these animals or artefacts. In indirect surveying, which depends largely upon artefacts of behavior, likelihood to encounter indirect signs of a species is derived from both artefact production and decay. Although environmental context as well as behavior contribute to artefact abundance, variability in behaviors relevant to artefact abundance is rarely considered in population estimation. Here we demonstrate how ignoring behavioral variability contributes to overestimation of population size of a highly endangered great ape endemic only to the Democratic Republic of the Congo, the bonobo (Pan paniscus). Variability in decay of signs of bonobo presence (i.e., nests) is well documented and linked to environmental determinants. Conversely, a single metric of sign production (i.e., nest construction) is commonly used to estimate bonobo density, assumed to be representative of bonobo nest behavior across all contexts. We estimated nest construction rates from three bonobo groups within the Kokolopori Bonobo Reserve and found that nest construction rates in bonobos to be highly variable across populations as well as seasonal within populations. Failure to account for behavioral variability in nest construction leads to potentially severe degradation in accuracy of bonobo population estimates of abundance, accounting for a likely overestimation of bonobo numbers by 34%, and in the worst cases as high as 80% overestimation. Using bonobo nesting as an example, we demonstrate that failure to account for inter- and intra-population behavioral variation compromises our ability to monitor population change or reliably compare contributors to population decline or persistence. We argue that variation in sign production is but one of several potential ways that behavioral variability can affect conservation monitoring, should be measured across contexts whenever possible, and must be considered in population estimation confidence intervals. With increasing attention to behavioral variability as a potential tool for conservation, conservationists must also account for the impact that behavioral variability across time, space, individuals, and populations can play upon precision and accuracy of wildlife population estimation.

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“…Various sampling techniques: vehicle survey, foot survey through counting method used to estimate the elephant population. The dung count method (Meier et al, 2021) by the belt or strip transect technique was chosen to estimate elephant population size due to its less biased estimates and lower standard error (Bicho et al, 2023). Two types of systematic sampling techniques used: line transects and belt or strips transect techniques used for ecological study.…”

Section: Population Estimate Sampling Designmentioning

confidence: 99%

Ecological studies andThreats on African elephant (Loxodonta africana) in Babile Elephant Sanctuary, Eastern Ethiopia

Geleta,

Mengesha,

Workeneh

2023

IJAGRI

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A study was conducted on the ecological, and threats to African elephants in the Babile Elephant Sanctuary in eastern Ethiopia from March 2019 to December 2021. The research aimed to understand population size, age structure, movement, feeding preference, impact on woody plant species, and threats to elephants. For the study, before carrying out data collection, the habitat of the sanctuary was first divided into riverine, woodland, and bushlands. A total area of 48 km2divided into 16 km2each, was sampled to compare and collect the dung of an elephant. The study used dung counting techniques and woody species assessment to estimate elephant population size, feeding preferences, and the impact of elephants on woody species. The sanctuary had 210 to 250 elephantsor (i.e., 230±20)at a Mean of (χ) =230 and SD=20, with 47% being younger and 2.6% sub-adult. Others were adult (19%), calves (17.2%), and Juveniles (13.4%). According to all (100%) key informants and observations revealed, the elephants’ movement followed the Erer and Gobele valleys. The result also showed that 24(63.15%) of the 38 woody species were selected by elephants as a diet. The Acacia seyel (PI= 3.3033)and Opuntia ficus-indica (PI= 2.0328)were the most frequently browsed tree and shrub species, respectively. Observations revealed elephants uprooted debarked trees and destroyed parts, particularly a small size class.The study found that the high human population and settlers' need for land for cultivation increased conflicts between people and elephants. Despite a remnant elephant population in the sanctuary, the species could be negatively affected by human activities. Therefore, rehabilitating woody plants consumed by elephants,reducing threats and conservingthe remaining elephant populationis crucial.

show abstract

Improving population estimates of difficult‐to‐observe species: A dung decay model for forest elephants with remotely sensed imagery

Cited by 5 publications

References 44 publications

Failure to account for behavioral variability significantly compromises accuracy in indirect population monitoring

Failure to account for behavioral variability significantly compromises accuracy in indirect population monitoring

Failure to account for behavioral variability significantly compromises accuracy in indirect population monitoring

Ecological studies andThreats on African elephant (Loxodonta africana) in Babile Elephant Sanctuary, Eastern Ethiopia

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