Projecting Mammal Distributions in Response to Future Alternative Landscapes in a Rapidly Transitioning Region

Abstract

Finding balance between the needs of people and wildlife is an essential component of planning sustainable landscapes. Because mammals make up a diverse and ecologically important taxon with varying responses to human disturbance, we used representative mammal species to examine how alternative land-use policies might affect their habitats and distributions in the near future. We used wildlife detections from camera traps at 1591 locations along a large-scale urban to wild gradient in northern Virginia, to create occupancy models which determined land cover relationships and the drivers of contemporary mammal distributions. From the 15 species detected, we classified five representative species into two groups based on their responses to human development; sensitive species (American black bears and bobcats) and synanthropic species (red foxes, domestic cats, and white-tailed deer). We then used the habitat models for the representative species to predict their distributions under four future planning scenarios based on strategic versus reactive planning and high or low human population growth. The distributions of sensitive species did not shrink drastically under any scenario, whereas the distributions of synanthropic species increased in response to anthropogenic development, but the magnitude of the response varied based on the projected rate of human population growth. This is likely because most sensitive species are dependent on large, protected public lands in the region, and the majority of projected habitat losses should occur in non-protected private lands. These findings illustrate the importance of public protected lands in mitigating range loss due to land use changes, and the potential positive impact of strategic planning in further mitigating mammalian diversity loss in private lands. mammal diversity and distribution data [14,15]. Despite the increasing availability of wildlife data, few studies have integrated these data to map the distributions of mammal species in regions undergoing expansive land changes [12,16]. These projected species distribution models can then be used to predict range shifts in response to future landscape scenarios, such as those projected under climate change [17,18]. Contemporary biodiversity data provide valuable snapshots of mammal distributions, but they have not been applied to projections of land cover change to forecast community distributions in the future. These predictions would be informative to stakeholders, as they coordinate and select planning policies to preserve biodiversity and their associated ecosystem services.We projected changes in a suite of habitat-relevant land cover types for a rapidly changing landscape in northern Virginia under four different scenarios that varied in policy to plan development strategically (e.g., urban centralized) or reactively (e.g., sprawling) over the next 50 years, while accounting for differences in the rate of human population growth [19]. Scenario planning is a strategic planning approach whereby alternate storyl...

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].…”