High-biodiversity landscapes around the globe are under immense pressure due to the expansion of human activities. To ensure effective monitoring and management of such landscapes, it is necessary to integrate landscape composition and the associated socio-economic processes in the conservation schemes. Artificial Night-Time Light (ANTL) pollution is a recent but striking environmental alteration due to human interventions. It is a major threat for species and communities which co-evolved with invariant natural light patterns over geological times. In spite of its potential key role in re-shaping natural systems, ANTL is seldom considered in macroecology. Remote sensing provides a unique set of tools to integrate ANTL in macroecological studies. In this work, we used remote sensing data of night-time lights along with Enhanced Vegetation Index (EVI) to study the effects and extent of ANTL in the night-time landscape (nightscape) of two protected areas in Italy. Our results showed that a considerable number of semi-natural vegetated patches suffer from ANTL pollution with varying magnitude. We observed a decline in highly suitable patches for biodiversity while the remaining patches were found concentrated in the innermost part of the parks. By simulating an exponential decrease in ANTL we showed that a moderate reduction in ANTL pollution would result in regaining a substantial amount of highly suitable patches for biodiversity. The decline in homogeneous dark patches in vegetated landscapes has negative impacts on biodiversity as well as on the ecosystem services it provides. Therefore, it is high time that the scientific community and the policy-makers increase their efforts to monitor and mitigate the ecological impacts of ANTL on ecosystems. The integration of light pollution in landscape ecology could combine remote sensing with other aspects of light pollution like indirect propagation and spectral composition.

The integration of Artificial Night-Time Lights in landscape ecology: A remote sensing approach

Pareeth, Sajid;
2015-01-01

Abstract

High-biodiversity landscapes around the globe are under immense pressure due to the expansion of human activities. To ensure effective monitoring and management of such landscapes, it is necessary to integrate landscape composition and the associated socio-economic processes in the conservation schemes. Artificial Night-Time Light (ANTL) pollution is a recent but striking environmental alteration due to human interventions. It is a major threat for species and communities which co-evolved with invariant natural light patterns over geological times. In spite of its potential key role in re-shaping natural systems, ANTL is seldom considered in macroecology. Remote sensing provides a unique set of tools to integrate ANTL in macroecological studies. In this work, we used remote sensing data of night-time lights along with Enhanced Vegetation Index (EVI) to study the effects and extent of ANTL in the night-time landscape (nightscape) of two protected areas in Italy. Our results showed that a considerable number of semi-natural vegetated patches suffer from ANTL pollution with varying magnitude. We observed a decline in highly suitable patches for biodiversity while the remaining patches were found concentrated in the innermost part of the parks. By simulating an exponential decrease in ANTL we showed that a moderate reduction in ANTL pollution would result in regaining a substantial amount of highly suitable patches for biodiversity. The decline in homogeneous dark patches in vegetated landscapes has negative impacts on biodiversity as well as on the ecosystem services it provides. Therefore, it is high time that the scientific community and the policy-makers increase their efforts to monitor and mitigate the ecological impacts of ANTL on ecosystems. The integration of light pollution in landscape ecology could combine remote sensing with other aspects of light pollution like indirect propagation and spectral composition.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/306558
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