Spatial and temporal dimensions of landscape fragmentation across the Brazilian Amazon

The Brazilian Amazon in the past decades has been suffering severe landscape alteration, mainly due to anthropogenic activities, such as road building and land clearing for agriculture. Using a high-resolution time series of land cover maps (classified as mature forest, non-forest, secondary forest) spanning from 1984 through 2011, and four uncorrelated fragmentation metrics (edge density, clumpiness index, area-weighted mean patch size and shape index), we examined the temporal and spatial dynamics of forest fragmentation in three study areas across the Brazilian Amazon (Manaus, Santarém and Machadinho d’Oeste), inside and outside conservation units. Moreover, we compared the impacts on the landscape of: (1) different land uses (e.g. cattle ranching, crop production), (2) occupation processes (spontaneous vs. planned settlements) and (3) implementation of conservation units. By 2010/2011, municipalities located along the Arc of Deforestation had more than 55% of the remaining mature forest strictly confined to conservation units. Further, the planned settlement showed a higher rate of forest loss, a more persistent increase in deforested areas and a higher relative incidence of deforestation inside conservation units. Distinct agricultural activities did not lead to significantly different landscape structures; the accessibility of the municipality showed greater influence in the degree of degradation of the landscapes. Even with a high proportion of the landscapes covered by conservation units, which showed a strong inhibitory effect on forest fragmentation, we show that dynamic agriculturally driven economic activities, in municipalities with extensive road development, led to more regularly shaped, heavily fragmented landscapes, with higher densities of forest edge

On parametric fragmentation measures

In the landscape ecological literature, a number of measures have been proposed for quantifying landscape fragmentation based on distinct objectives and motivations. However, none seems to be generally preferred. The main reason for this disagreement is that, from a statistical viewpoint, by mapping fragmentation into a single scalar, information is necessarily lost and no ideal function is able to uniquely characterize all aspects of landscape fragmentation. A more complete summarization of fragmentation is possible if, instead of one single index, a parametric index family is applied whose members have varying sensitivities to the presence of large and small landscape patches. While traditional indices supply point descriptions of fragmentation, according to a parametric fragmentation family Ha, there is a continuum of possible fragmentation measures that differ in their sensitivity to the presence of large and small patches as a function of the scaling parameter a. Therefore, changing a allows for vector description of fragmentation. The purpose of this paper is to introduce a parametric generalization of Shannon’s entropy to summarize landscape fragmentation. A small set of artificial landscapes is used to clarify our proposal

Radial Basis Function Neural Network with Localized Stochastic-Sensitive Autoencoder for Home-Based Activity Recognition

info:eu-repo/semantics/publishe