Distance sampling of duikers in the rainforest: Dealing with transect avoidance

Abstract

Bushmeat is a major source of protein and income in tropical regions but is often over-harvested. A better monitoring of bushmeat stocks could help achieve sustainability. We used a combination of simulations and transect survey data collected from blue duikers (Philantomba monticola) in the Lomako wildlife reserve, Democratic Republic of the Congo, to investigate the use of transect-based distance sampling to monitor bushmeat stocks. The comparison of dung piles and direct observations of duikers evidenced that animals avoided both the transects in the absence of observers, and the observers themselves. This type of behavioural response appeared common in a literature survey. It causes a negative bias in the estimates of population densities from the standard distance sampling methodology. This negative bias would lead to over-pessimistic predictions of population viability, especially if the behavioural response is more intense in the locations where the animals are hunted. In turn, this would lead to excessively conservative management recommendations. To correct for the effect of the behavioural response of the animals to either the transects or the observers, we recommend recording both the forward and perpendicular distances to the observers (2D distance sampling), not just the perpendicular distance. We also recommend multiple-observer protocols. As a cautionary note, we also demonstrate a scenario where the intensity of the behavioural response is too high to reliably estimate the abundance of the population. As a perspective, we outline the general principles of a local stakeholder-based program combining distance sampling with less intensive types of ecological indicators to monitor wildlife populations.

Estimating forest antelope population densities using distance sampling with camera traps

“…Line transect sampling using direct sightings or signs (including DNA based methods) for estimating density of forest antelopes has severe limitations in terms of reliability, and/or cost and effort (Rovero & Marshall, 2004; Lwanaga, 2006; Waltert et al, 2006; Rovero & Marshall, 2009; Elenga et al, 2020). Despite the high initial set-up costs of camera-trap surveys, there are multiple advantages in terms of reliability of data gathered, long-term cost efficiency, and the large number of species that can be surveyed using a single technique (Amin et al, 2018).…”

Rapid dung removal by beetles suggests higher duiker densities in Central African rainforests

“…When a dung pile was detected, we assigned a unique identifier, measured the diameter covered by pellets, and estimated how many hours ago it had been deposited. Although it was not possible to know the exact time of the defaecation, experienced trackers and researchers can reasonably estimate their age (Viquerat et al, 2013; Elenga et al, 2020). We inspected the appearance of dung piles (shine, moisture) and other factors such as associated presence of urine, time of last rain and exposure to sun.…”

“…Against this background, conflicts have arisen between local people and conservationists (Pyhälä et al, 2016). One of the reasons for these conflicts is the lack of reliable, and the sometimes controversial, information on the abundance of wild animals, including duikers, the major game animals in Central Africa (van Vliet & Nasi, 2008; Elenga et al, 2020). Estimated population densities of game species may differ by 10-fold or more depending on the survey methods used (Koster & Hart, 1988; Wilkie & Finn, 1990; Jost Robinson et al, 2017; Kamgaing et al, 2018).…”

“…In dense tropical forests, wildlife surveys are usually challenging because of poor visibility and the shyness of wild animals (Elenga et al, 2020). Therefore, rather than attempting to quantify numbers directly, indirect survey techniques such as counts of animal signs (e.g.…”

Counting giraffes: A comparison of abundance estimators on the Ongava Game Reserve, Namibia

“…g . linear transects and coverage), and is sometimes difficult to carry out in dense tropical forests of Africa (Duckworth 1998), or when human disturbance induces behavioural responses (see Elenga et al 2020, on duikers). In other words, these two reference methods for estimating animal abundance can rapidly become prohibitively expensive, time consuming and difficult to implement at large spatial scale for wildlife managers (Morellet et al 2007).…”