Human Footprint maps

7-zip file including the Human Footprint maps for 1993 and 2009, individual pressures, and validation data. A full data description is included as a word file in the download

Percentage difference of biomass estimates of those produced by three non-expert teams (N = 41) and those produced by experts (N = 41).

<p>Team A and Team B had 14 participants, and Team C had 13 participants. The line across the middle of each box represents the median; the boxes show the interquartile range for around the median for half the data at the top and the other half at the bottom; the whiskers represent the 10^th to the 90^th percentile, and the outliers are demonstrated by the empty circles.</p

The size distribution of A) all trees, B) trees missed and C) extra trees in non-experts’ surveys.

<p>The dotted lines represent cutoff DBH sizes for subplots (5.0cm, 20.0cm, and 50.0cm) for the three subplots (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0130529#pone.0130529.g002" target="_blank">Fig 2</a>).</p

A) The relationship between expert and non-experts pairs of DBH (N = 1364) and B) the relationship between pairs of height measurements by expert and non-experts (N = 1281).

<p>A) The dotted red line represents a 1:1 relationship, the area between blue lines represents the 95% confidence interval, and the regression equation is from a GLM. B) The dotted red line represents a 1:1 relationship, and the regression equation is from a GLM.</p

Schematic description of how errors (μ) propagate from the tree level to the landscape level in field biomass inventories.

<p>Schematic description of how errors (μ) propagate from the tree level to the landscape level in field biomass inventories.</p

Difference in experts’ and non-experts’ biomass estimates due to measurement discrepancies at the A) site level and B) landscape level.

<p>Negative values represent smaller values of non-experts compared to experts.</p

Species loss that would be averted by protecting a single parcel of land with known species richness (<i>S</i>_<i>0</i>, on the x-axis).

<p>Results are shown for three different levels of leakage. Protecting parcels with relatively low species richness can result in a net loss of species richness. This figure is based on a landscape with <b><i>P</i> = 225</b> parcels, with average species richness <b><i>m</i> = 80</b>, and a background threat rate of <b><i>q</i> = 0.2</b>.</p

Wilderness_maps_R.1

We present the most up-to-date temporally inter-comparable maps of global terrestrial wilderness areas and the Last of the Wild. These are in .shp format, and were created in ArcGIS

The parameter estimates, probable range of values, and the critical value at which the optimal strategy changes.

<p>The optimal strategy using the estimated values was protection. The critical value at which reintroduction resulted in more wild orangutans than protection was calculated by keeping all the other parameters constant at the estimated values, and then varying one parameter to find when the optimal strategy changed. Values were calculated by simulation (although the formula <i>t_H≈2C_P/d e C_R</i> can also be used as an approximation to the critical point). The protection cost has three underlying parameters that were varied; the initial setup cost, the cost per hectare, and the discount rate. For clarity, we have summarized these into variation in the overall protection cost. Hunting was assumed to result in a loss of 0.485% p.a., population growth was 0.75% p.a., and a budget of $5M p.a. was used.</p>a<p>when the efficiency is <1, we assumed that the orangutan growth rate was <i>e₁</i> * 0.75%.</p

Sensitivity analysis.

<p>Each figure shows the probability of protection being the best strategy, when holding one parameter fixed whilst varying all the others. The x-axis gives the fixed value of the parameter in question, all other parameters were randomly chosen from their range. The y-axis is the probability of protection being the optimal strategy, averaged over 50,000 random selections. When every parameter was allowed to vary randomly, the probability of protection was 0.93. The parameters are for conservation forest (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0102174#pone-0102174-t002" target="_blank">Table 2</a>), with hunting and population growth included.</p