Landscape heterogeneity can partially offset negative effects of habitat loss on mammalian biodiversity in agroecosystems

Intensive, large-scale agriculture promotes the conversion of natural habitats and diversified crops into monocultures, decreasing both native vegetation cover and landscape heterogeneity, leading to landscape simplification. Yet, a key knowledge gap persists on the relative impacts of the loss of native vegetation and landscape heterogeneity on biodiversity. Addressing this gap is pressing to support policies that conciliate agricultural production and biodiversity conservation and to move forward some scientific controversies, as the “land sharing versus land sparing” and “habitat loss versus fragmentation” debates.Through a hierarchical sampling design that maximized variation, while minimizing correlation, between landscape heterogeneity and native vegetation cover, we recorded the occurrence of medium and large-bodied mammals in native vegetation and agricultural areas of 55 landscapes in a global conservation hotspot and a key commodity production area – the Brazilian savanna, Cer..., , , # Dataset of the article Landscape heterogeneity can partially offset negative effects of habitat loss on mammalian biodiversity in agroecosystems

[https://doi.org/10.5061/dryad.f7m0cfz38](https://doi.org/10.5061/dryad.f7m0cfz38)

Mammal's species detection in 55 landscapes in the Cerrado Biome in Brazil.

## Description of the data and file structure

The dataset has 55 lines, and each sampled landscape (200 ha) is in one line.
The columns represent each mammal's species detection (0 or 1) and the native and invasive species richness (number of native or invasive species detected per landscape).
The scientific names of the species are indicated in the column names.
Three species are invasive: Sus scrofa, Canis lupus familiaris, and Lepus europaeus.
The data was collected using camera traps and transects (3 camera stations and 9 transects per landscape).

## Code/Software

Analyzes were performed in R environment with 'MuMIn' package (Barton, 2022) and 'psych' package (Revelle, 2022).