Landscape heterogeneity of peasant-managed agricultural matrices

Abstract

In agricultural landscapes, management practices and other environmental and social factors shape complex agroecological matrices. In turn, the structure of such matrices impacts both agricultural activities and biodiversity conservation, for instance, by mediating wildlife migration between agricultural and habitat patches. One way to characterize a matrix, its potential role in biodiversity conservation, and how its descriptors change across different spatial scales, is characterizing heterogeneity metrics and systematically examining how such metrics change with grain size and landscape extent. However, these methods have rarely been applied to tropical, peasant-managed landscapes, even though this type of landscape occupies most of the agricultural surface in or near biodiversity hotspots. We focus on a peasant-managed agricultural landscape in Oaxaca, Mexico, for which we mapped and quantified the land-use classes and evaluated heterogeneity metrics. We also examined the response of heterogeneity metrics to changes in grain and extent scales. This allowed us to further understand the structure and conservation potential of the agroecological matrix in this type of landscape, to broadly compare this landscape with other agricultural landscapes in North America, and to recommend specific landscape metrics for different types of studies involving agricultural matrices. We conclude that this type of agricultural matrix is ideal to pursue joint agricultural and conservation strategies in an integrated landscape.

Human-mediated impacts on biodiversity and the consequences for zoonotic disease spillover

“…Within monocultures, all metrics of landscape diversity are reduced. However, in relation to intact ecosystems, moderate agricultural conversion has various effects on patchtype diversity, decreases patch size and thus variation in patch size, and increases the distance among intact habitat patches [54][55][56] . Fragmenting of habitat into small patches can shift the distribution of reservoir species, causing them to aggregate at high densities near humans and increasing their contactswith humans, previously unencountered mammals, and vectors -thereby increasing potential for transmission 57 .…”

Examining Heterogeneity Structured on a Large Data Volume with Minimal Incompleteness

“…Each experiment will be tailored to the study's specifications, which means that the data generated by these experiments is likely to have a diverse range of characteristics (Bridges, et al, 2020). On the other hand, natural heterogeneity is also established by the underlying data sources, for example, in medical data (Yue, et al, 2020), Labor market data (Kikuchi, Kitao and Mikoshiba, 2020), Landscape data (Urrutia, et al, 2020), business data (George and Kabir, 2012), all these can be attributed to "data pooling" as a well-known cause of heterogeneity in data analysis.…”