Conservation efforts worldwide have predominantly focussed on protecting large areas devoid of human influence. Despite the dramatic alterations, some human-dominated landscapes such as agro-ecosystems, continue to harbour a variety of native plant and animal species. Unlike industrial agriculture, coupled human-natural ecosystems support high species richness by providing a mosaic of habitat types. Anthropogenic activities alter natural habitats, with impacts on species that live in these human-modified systems. Often abrupt, anthropogenic changes to the landscape not only alter the availability and distribution of suitable habitats for species, but also the ability of species to predict variations within the landscape.

In some human-modified landscapes, especially agro-ecosystems that depend on both rainfall and irrigation, drivers that influence animal space use can show unexpected spatial and temporal patterns due to anthropogenic activities. I used movement data from a guild of mesocarnivores to determine how home-range size and habitat selection differs across species and seasons in a complex agro-ecosystem in Central India. Based on high-resolution location data from golden jackals (Canis aureus), jungle cats (Felis chaus) and Indian foxes (Vulpes bengalensis) over a period of ~3 years, I found that home-range sizes scaled with body mass as expected, with high intra-species variability. Home-ranges of golden jackals, jungle cats and Indian foxes varied from 3.1 to 23.7 (mean = 12.3 ± 1.6), 1.01 to 26.48 (mean = 5.9 ± 0.9) and 1.16 to 10.71 (mean = 4.3 ± 0.5) km2, respectively. Contrary to expectations, home-range size did not vary significantly with season, suggesting that agricultural activities may dampen typical seasonal variations in resource availability and distribution. Site fidelity in seasonal home-ranges for golden jackals, jungle cats and Indian foxes was high (seasonal overlaps = 0.94 ± 0.01, 0.89 ± 0.02 and 0.81 ± 0.03, respectively). I also found that the habitat specialist Indian fox primarily selected for remnant native grasslands and plantations, whereas the generalist golden jackal and jungle cat selected more human-modified land cover types at both the landscape and home-range scales. As I observed that seasonal scales do not sufficiently capture variations in habitat use by mesocarnivore species in highly dynamic human-dominated landscapes, I conducted a literature review on terrestrial vertebrate species to determine whether survival in agro-ecosystems requires a common set of traits or qualities along multiple axes (diet/habitat/activity). I found that species that are commonly found in agro-ecosystems often utilise multiple vegetation types, are able to shift their activity periods to reduce overlap with human activity, and have a wide dietary breadth. These traits, which are shared across disparate taxonomic groups, not only enable species to maximize resource acquisition, but minimize encounter and conflict with humans. Some species however, show specialisation along one or more of these axes, and therefore require additional ecological conditions. In order to maximise the conservation of biodiversity within these landscapes, it is important to identify conditions that allow continued persistence, even of species that are not hyper-generalists. Maintaining these conditions could be achieved through relevant policy level interventions by encouraging a combination of land sharing and land sparing practices. Researchers studying the drivers of species distribution and behaviour often use “static” land-cover maps as descriptors of habitat, which are most typically characterized at predictably cyclical seasonal scales. Changes that occur over shorter temporal scales are rarely quantified, and there is a lack of understanding of how landscapes change within seasons. I propose a work-flow to identify the temporal scales at which changes in land-cover patterns can be detected within a landscape. I use easily calculated landscape metrics such as patch area (PA), inter-patch distance (ENN) and shape complexity (SHAPE), obtained using high-resolution satellite imagery at different interval periods. In our semi-arid mixed-use study area, I show that changes in landscape structure and in land-cover classes can be detected even at a 15-day time period.

Agricultural fallows showed the highest proportion of change-points, except at 45-day intervals for ENN and at 15- and 60-day intervals for SHAPE. The grassland class was the most stable across metrics and time-scales. Among metrics, SHAPE was the most stable and ENN was the most dynamic, indicating that while patch structure remained relatively stable, patch configuration changed more rapidly. I suggest that when studying animal resource use and movement, particularly in anthropogenically modified systems, matching the temporal resolution of landscape-level data to animal movement data is critical, as broad-scale data may miss key triggers of animal response.

Human-dominated landscapes show high spatio-temporal variability, leading to a dynamically varying availability of both habitat and prey. The resulting animal movement patterns vary between their canonical activity modes, CAMs (e.g., resting vs. foraging). Though understanding habitat selection in human-dominated landscapes is important for both fundamental and applied research, fine-temporal scale dynamics in habitat selection are rarely quantified at biologically meaningful scales. Using high-resolution movement data with fine-scale data on external factors, I used integrated step-selection analysis on each CAM at monthly scales for a habitat generalist (jungle cat, Felis chaus, n = 5) and a habitat specialist (Indian fox, Vulpes bengalensis, n = 7) to understand the influence of specific parameters (LULC, distances to anthropogenic features) on their spatial ecology. Overall, there was a substantial difference in seasonal and monthly results, with no specific trends observed at the monthly scale, indicating high dynamism in resource distribution and habitat use. Both species showed strong habitat specificity during resting, and distances to features were not significant. Foxes were highly selective of native savannah and forest plantations across CAMs. Both species selected areas away from settlements but closer to food sources. In the transit mode, jungle cats mostly selected agriculture, and areas away from settlements and closer to poultry and roads. However, the effects were mostly significant during the transit mode only, and not always significant during the other modes for both species.

Interestingly, parameters that showed significance at the monthly scales also varied in effect size and significance at the monthly scale. As anthropogenic features may act as both barriers or enablers to movement, developing effective management schemes for maintaining landscape connectivity is key for conservation planning of such species. Understanding how human land-use affects large mammal movement is particularly important in developing countries like India, and movement ecology has the potential to help policymakers design effective conservation outcomes by providing fine-scale data on habitat structure and space use by species in the landscape. This study highlights the importance of maintaining natural habitats within production landscapes, especially for habitat specialists which are more constrained in their requirements than generalist species.