Dataset Information

Evaluating the impact of distance measures on deforestation simulations in the fluvial landscapes of amazonia.

ABSTRACT: Land use and land cover change (LUCC) models frequently employ different accessibility measures as a proxy for human influence on land change processes. Here, we simulate deforestation in Peruvian Amazonia and evaluate different accessibility measures as LUCC model inputs. We demonstrate how the selection, and different combinations, of accessibility measures impact simulation results. Out of the individual measures, time distance to market center catches the essential aspects of accessibility in our study area. The most accurate simulation is achieved when time distance to market center is used in association with distance to transport network and additional landscape variables. Although traditional Euclidean measures result in clearly lower simulation accuracy when used separately, the combination of two complementary Euclidean measures enhances simulation accuracy significantly. Our results highlight the need for site and context sensitive selection of accessibility variables. More sophisticated accessibility measures can potentially improve LUCC models' spatial accuracy, which often remains low.

SUBMITTER: Salonen M

PROVIDER: S-EPMC4165832 | biostudies-other | 2014 Oct

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Evaluating the impact of distance measures on deforestation simulations in the fluvial landscapes of amazonia.

Salonen Maria M Maeda Eduardo Eiji EE Toivonen Tuuli T

Ambio 20131029 6

Land use and land cover change (LUCC) models frequently employ different accessibility measures as a proxy for human influence on land change processes. Here, we simulate deforestation in Peruvian Amazonia and evaluate different accessibility measures as LUCC model inputs. We demonstrate how the selection, and different combinations, of accessibility measures impact simulation results. Out of the individual measures, time distance to market center catches the essential aspects of accessibility i ...[more]

PMID: 24165869

Similar Datasets

Project description:Attalea palms provide primary habitat to Rhodnius spp., vectors of Trypanosoma cruzi. Flying from palms, these blood-sucking bugs often invade houses and can infect people directly or via food contamination. Chagas disease (CD) risk may therefore increase when Attalea palms thrive near houses. For example, Attalea dominate many deforested landscapes of eastern Amazonia, where acute-CD outbreaks are disturbingly frequent. Despite this possible link between deforestation and CD risk, the population-level responses of Amazonian Attalea and their resident Rhodnius to anthropogenic landscape disturbance remain largely uncharted. We studied adult Attalea palms in old-growth forest (OGF), young secondary forest (YSF), and cattle pasture (CP) in two localities of eastern Amazonia. We recorded 1856 Attalea along 10 transects (153.6 ha), and detected infestation by Rhodnius spp. in 18 of 280 systematically-sampled palms (33 bugs caught). Distance-sampling models suggest that, relative to OGF, adult Attalea density declined by 70-80% in CP and then recovered in YSF. Site-occupancy models estimate a strong positive effect of deforestation on palm-infestation odds (βCP-infestation = 4.82±1.14 SE), with a moderate decline in recovering YSF (βYSF-infestation = 2.66±1.10 SE). Similarly, N-mixture models suggest that, relative to OGF, mean vector density sharply increased in CP palms (βCP-density = 3.20±0.62 SE) and then tapered in YSF (βYSF-density = 1.61±0.76 SE). Together, these results indicate that disturbed landscapes may support between ~2.5 (YSF) and ~5.1 (CP) times more Attalea-dwelling Rhodnius spp. per unit area than OGF. We provide evidence that deforestation may favor palm-dwelling CD vectors in eastern Amazonia. Importantly, our landscape-disturbance effect estimates explicitly take account of (i) imperfect palm and bug detection and (ii) the uncertainties about infestation and vector density arising from sparse bug data. These results suggest that incorporating landscape-disturbance metrics into the spatial stratification of transmission risk could help enhance CD surveillance and prevention in Amazonia.

Dataset Information

Evaluating the impact of distance measures on deforestation simulations in the fluvial landscapes of amazonia.

Publications

Evaluating the impact of distance measures on deforestation simulations in the fluvial landscapes of amazonia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets