Area (km²) and proportion of study area (%) taken up by different classes for each LULC map.

<p>LULC class typology differed between the two LULC maps and so not all categories are comparable (e.g. Rubber class is present for the modified-LULC map but absent from the FROM-GLC map).</p><p>Area (km²) and proportion of study area (%) taken up by different classes for each LULC map.</p

Land use land cover maps.

<p>FROM-GLC and modified-LULC maps using the extent of the study area and including a zoomed image at a common location.</p

Brief description of the six ESV measurement approaches used (two LULC maps and three economic valuation approaches).

<p>Brief description of the six ESV measurement approaches used (two LULC maps and three economic valuation approaches).</p

The most and least valuable management zones according to their ecosystem service value per unit area.

<p>Calculated using each LULC map and valuation approach and based on results shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0129748#pone.0129748.g003" target="_blank">Fig 3</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0129748#pone.0129748.s009" target="_blank">S8 Table</a>; NonPA = Non-protected area.</p><p>The most and least valuable management zones according to their ecosystem service value per unit area.</p

Study site location.

<p>Location of study site and fieldwork in southwestern Yunnan province with delineation of different management zones of the protected area and location of social surveys conducted in November 2012 and August 2013 (Located between 23° 4' 46.19" and 23° 23' 49.92" N & 98° 53' 1.67" and 99° 31' 30" E).</p

Total ecosystem service value for whole study area using the six different approaches.

<p>Val1 = Costanza estimates; Val2 = Amended Costanza estimates; Val3 = Amended estimates only for services identified as locally important; All values given in Chinese Yuan per year; Error bars show variation of some ecosystem services that used low and high estimates provided by Costanza et al. (1997) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0129748#pone.0129748.ref001" target="_blank">1</a>]. Those with small error bars and thus low variation in ESV were calculated using only one estimate; Actual values are provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0129748#pone.0129748.s008" target="_blank">S7 Table</a>.</p

Total ecosystem service value for each management zone for all six valuation approaches.

<p>All values given in Chinese Yuan per year; Error bars show variation of some ecosystem services that used low and high estimates provided by Costanza et al. (1997) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0129748#pone.0129748.ref001" target="_blank">1</a>].</p

Face Value: Towards Robust Estimates of Snow Leopard Densities

<div><p>When densities of large carnivores fall below certain thresholds, dramatic ecological effects can follow, leading to oversimplified ecosystems. Understanding the population status of such species remains a major challenge as they occur in low densities and their ranges are wide. This paper describes the use of non-invasive data collection techniques combined with recent spatial capture-recapture methods to estimate the density of snow leopards <i>Panthera uncia</i>. It also investigates the influence of environmental and human activity indicators on their spatial distribution. A total of 60 camera traps were systematically set up during a three-month period over a 480 km² study area in Qilianshan National Nature Reserve, Gansu Province, China. We recorded 76 separate snow leopard captures over 2,906 trap-days, representing an average capture success of 2.62 captures/100 trap-days. We identified a total number of 20 unique individuals from photographs and estimated snow leopard density at 3.31 (SE = 1.01) individuals per 100 km². Results of our simulation exercise indicate that our estimates from the Spatial Capture Recapture models were not optimal to respect to bias and precision (RMSEs for density parameters less or equal to 0.87). Our results underline the critical challenge in achieving sufficient sample sizes of snow leopard captures and recaptures. Possible performance improvements are discussed, principally by optimising effective camera capture and photographic data quality.</p></div

The map of the spatial distribution of snow leopards across the study area.

<p>A pixelated density map produced in SPACECAP showing estimated snow leopard densities per pixel of size 1.96 km².</p

Le Petit Marocain

07 décembre 19461946/12/07 (A34,N9480)-1946/12/07