Synthesizing Remote Sensing and Biophysical Measures to Evaluate Human–wildlife Conflicts: The Case of Wild Boar Crop Raiding in Rural China

Abstract

Crop raiding by wild boars is a growing problem worldwide with potentially damaging consequences for rural dwellers’ cooperation with conservation policies. Still, limited resources inhibit continuous monitoring, and there is uncertainty about the relationship between the biophysical realities of crop raiding and humans’ perceptions and responses. By integrating data from camera traps, remote sensors, and household surveys, this study establishes an empirical model of wild boar population density that can be applied to multiple years to estimate changes in distribution over time. It also correlates historical estimates of boar population distribution with human-reported trends to support the model’s validity and assess local perceptions of crop raiding. Although the model proved useful in coniferous and bamboo forests, it is less useful in mixed broadleaf, evergreen broadleaf, and deciduous forests. Results also show alignment between perceptions of crop raiding and actual boar populations, corroborating farmers’ perceptions which are increasingly dismissed as a less reliable source of information in human–wildlife conflict research. The modeling techniques demonstrated here may provide conservation practitioners with a cost-effective way to maintain up-to-date estimates of the spatial distribution of wild boar and resultant crop raiding.

Editorial for Special Issue “Remote Sensing for Monitoring Wildlife and Habitat in a Changing World”

“…The works included in this Special Issue present some scientific and technological innovations in remote sensing for assessing the spatio-temporal dynamics of wildlife species and their habitats. Although constituting a very small set of studies, they cover a diverse array of geographic settings distributed throughout the world and comprising both terrestrial [6][7][8][9][10][11][12][13][14] and aquatic [9,12,15,16] systems (Figure 1). They also evaluate individual species groups, including corals [15], reptiles [6,9], birds [7,10], mammals [8,11,13,14], or a combination of different species groups [12,16].…”

“…Although constituting a very small set of studies, they cover a diverse array of geographic settings distributed throughout the world and comprising both terrestrial [6][7][8][9][10][11][12][13][14] and aquatic [9,12,15,16] systems (Figure 1). They also evaluate individual species groups, including corals [15], reptiles [6,9], birds [7,10], mammals [8,11,13,14], or a combination of different species groups [12,16]. These studies used diverse analytical Remote Sens.…”

“…terrestrial [6][7][8][9][10][11][12][13][14] and aquatic [9,12,15,16] systems (Figure 1). They also evaluate individual species groups, including corals [15], reptiles [6,9], birds [7,10], mammals [8,11,13,14], or a combination of different species groups [12,16].…”

“…terrestrial [6][7][8][9][10][11][12][13][14] and aquatic [9,12,15,16] systems (Figure 1). They also evaluate individual species groups, including corals [15], reptiles [6,9], birds [7,10], mammals [8,11,13,14], or a combination of different species groups [12,16]. These studies used diverse analytical approaches applied to remotely sensed data acquired by different sensor systems at different scales ranging from high spatial resolution sensors onboard unoccupied aircraft vehicles [16], underwater systems [15], and space-borne vehicles [12], to intermediate spatial resolution multispectral imagery acquired by operational satellite sensor systems such as the Landsat [6][7][8]10,11,14], SPOT [7], and MODIS [8,13] satellite series, together with coarser spatial resolution data acquired by weather satellite systems [9].…”

“…They also evaluate individual species groups, including corals [15], reptiles [6,9], birds [7,10], mammals [8,11,13,14], or a combination of different species groups [12,16]. These studies used diverse analytical approaches applied to remotely sensed data acquired by different sensor systems at different scales ranging from high spatial resolution sensors onboard unoccupied aircraft vehicles [16], underwater systems [15], and space-borne vehicles [12], to intermediate spatial resolution multispectral imagery acquired by operational satellite sensor systems such as the Landsat [6][7][8]10,11,14], SPOT [7], and MODIS [8,13] satellite series, together with coarser spatial resolution data acquired by weather satellite systems [9]. This diverse array of sensors and analytical approaches proved useful for evaluating habitat requirements and distribution [7,8,10,12,16], species distribution and occurrence [11,15], population dynamics [7], human-wildlife conflicts [13,14], the negative impacts of natural [9] and human-driven [8] disturbances on species distribution, and for assessing the potential impacts of climate change [6].…”