Details

Autor(en) / Beteiligte

• Buchanan, Graeme M.
• Fishpool, Lincoln D.C.
• Evans, Michael I.
• Butchart, Stuart H.M.

Titel

Comparing field-based monitoring and remote-sensing, using deforestation from logging at Important Bird Areas as a case study

Ist Teil von

• Biological conservation, 2013-11, Vol.167, p.334-338

Ort / Verlag

Kidlington: Elsevier Ltd

Erscheinungsjahr

2013

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• •Simple field based logging impact scores were compared to remote sensing forest loss.•Field based impact scores for sites correlated to remote sensing forest loss.•Forest loss was lower within sites than around sites.•Simple monitoring protocols can be globally consistent. Monitoring sites of biodiversity conservation importance is essential for their conservation. It allows threats to be identified and quantified, priorities to be set, responses to be developed, and facilitates adaptive management. Field-based monitoring protocols need to be simple enough to be widely applied in countries with limited capacity while being sufficiently robust to provide widely reliable data. A simple, globally standardised monitoring protocol is now being implemented at thousands of sites of global avian conservation significance (Important Bird Areas, IBAs) worldwide, but the consistency of the approach across sites, countries and regions remains untested. We tested the match between estimates of the threat to IBAs from logging derived from such monitoring, with standardised deforestation rates derived from remote sensing data for 2000–2005 to determine if the two were consistently related. We found a significant positive correlation between the impact of the threat from logging and the proportion of forest lost (although the gross forest loss did not differ systematically with the two components of the threat impact: scope and severity). The results give us some confidence that the simple field-based protocol being implemented by a diversity of surveyors with varied technical capacity can generate meaningful and consistent monitoring data across the globe.