Carvalho_S_et_al_2015-JAE_DATA_&_RCODE

Input files and r scripts used to derive non-optimized monitoring schemes for the four stratification strategies (No stratification (NS), Protection stratification (PA), Environmental Stratification (ENV), and Environmental and Protection stratification (ENVPA)) and the three target scenarios (T10, T30 and T50); and to evaluate the performance of both optimized and non-optimized networks using the different indicators

Marxan Files

Input files used in the Marxan software to derive optimized monitoring networks for the four stratification methods - No stratification (NS), Protection stratification (PA), Environmental Stratification (ENV), and Environmental and Protection stratification (ENVPA); and the three target scenarios: T10, T30 and T5

Response curves of predicted habitat suitability for <i>Iris boissieri</i> to the most important predictors.

<p>Response curves for predictors with the highest importance in traditional (climate and land-cover)-based (left) and Ecosystem Functional Attribute (EFA)-based (right) ensemble models for <i>Iris boissieri</i> at all combinations of spatial extents and resolutions.</p

Summary table of performance of the best ensemble models based on traditional (climate -CLI- and/or land-cover -LC-) and on satellite-derived Ecosystem Functional Attribute (EFAs), considering those individual models filtered at Area Under the Curve (AUC) ≥0.7.

<p>The AUC_median±IQR (Inter Quartile Range) and the top variables above a threshold of importance contribution (% >0.10) are showed per species, extent, and spatial resolution. See complete names of variables and extents in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0199292#pone.0199292.t003" target="_blank">Table 3</a>.</p

Specific testable hypotheses for comparison of the performance and scale-dependence (in terms of spatial extent and resolution) of ecosystem functional attributes (EFAs) against traditional climate and land-cover datasets in Species Distribution Models (SDMs).

<p>Specific testable hypotheses for comparison of the performance and scale-dependence (in terms of spatial extent and resolution) of ecosystem functional attributes (EFAs) against traditional climate and land-cover datasets in Species Distribution Models (SDMs).</p

Study areas and species occurrence data.

<p>(a) The three nested study areas and occurrence data of target species (<i>Iris boissieri</i> and <i>Taxus baccata</i>) in (b) the Iberian Peninsula at 5km² cell size, (c) the Iberian Northwest at 5km² (empty squares) and 1km² (filled squares), and (d) the Peneda-Gerês National Park at 1km² cell size.</p

Spatial projections of habitat suitability for <i>Taxus baccata</i> derived from Species Distribution Models (SDMs) based on traditional predictors (climate and land-cover) and on satellite-derived ecosystem functional attributes (EFAs).

<p>Overlay maps of current potential presence-absence distributions predicted using an ensemble modelling approach per combination of spatial extent (IP, NW and NP) and resolution (1km and 5km) for <i>Taxus baccata</i>. IP: Iberian Peninsula; NW: Northwest IP; NP: Peneda-Gerês National Park.</p

Spatial projections of habitat suitability for <i>Iris boissieri</i> derived from Species Distribution Models (SDMs) based on traditional predictors (climate and land-cover) and on satellite-derived ecosystem functional attributes (EFAs).

<p>Overlay maps of current potential presence-absence distributions predicted using an ensemble modelling approach per combination of spatial extent (IP, NW and NP) and resolution (1km and 5km) for <i>Iris boissieri</i>. IP: Iberian Peninsula; NW: Northwest IP; NP: Peneda-Gerês National Park.</p

Comparison of spatial projections from traditional (CLI/LC-based) models and from Ecosystem Functional Attribute (EFA-based) models for <i>Iris boissieri</i> at all scale combinations.

<p>The proportion of predicted suitable area is shown in brackets. IP: Iberian Peninsula; NW: Northwest IP; NP: Peneda-Gerês National Park.</p

Multi-scale modelling framework.

<p>General framework to test the scale-dependence of the performance of satellite-derived Ecosystem Functional Attributes (EFAs) as predictors in Species Distribution Models (SDMs).</p