Table1_A geographically flexible approach for mapping the Wildland-Urban Interface integrating fire activity data.XLSX

The Wildland-Urban Interface (WUI) is the area where houses and natural vegetation meet or intermingle. WUI areas are exposed to an increased hazard of wildfires and have significantly expanded worldwide in the past few decades. In this study, we developed a new empirical approach for mapping the WUI by generating a WUI index based on the juxtaposition among buildings, vegetation, and the fire history of the study area. We first calculated the percentage coverage of buildings and three different fuel typologies within circular moving windows with radii of 100, 250, and 500 m, and then acquired the fire history data between 2012 and 2021 for Israel and the West Bank (Palestinian Authority) from the VIIRS active fires remote sensing product. We defined the WUI as cells where the combination of vegetation cover and building cover had more VIIRS fire detections than expected by chance. To assess the effects of using broad vs. local scale parameterizations on resulting WUI maps, we repeated this process twice, first using national-scale data, and then separately in four distinct geographic regions. We assessed the congruence in the amounts and patterns of WUI in regions as mapped by information from these two analysis scales. We found that the WUI in Israel and the West Bank ranged from 0.5% to 1.7%, depending on fuel type and moving window radius. The scale of parameterization (national vs. regional) affected the WUI patterns only in one of the regions, whose characteristics differed markedly than the rest of the country. Our new method differs from existing WUI mapping methods as it is empirical and geographically flexible. These two traits allow it to robustly map the WUI in other countries with different settlement, fuel, climate and wildfire characteristics.</p

Image2_A geographically flexible approach for mapping the Wildland-Urban Interface integrating fire activity data.JPEG

The Wildland-Urban Interface (WUI) is the area where houses and natural vegetation meet or intermingle. WUI areas are exposed to an increased hazard of wildfires and have significantly expanded worldwide in the past few decades. In this study, we developed a new empirical approach for mapping the WUI by generating a WUI index based on the juxtaposition among buildings, vegetation, and the fire history of the study area. We first calculated the percentage coverage of buildings and three different fuel typologies within circular moving windows with radii of 100, 250, and 500 m, and then acquired the fire history data between 2012 and 2021 for Israel and the West Bank (Palestinian Authority) from the VIIRS active fires remote sensing product. We defined the WUI as cells where the combination of vegetation cover and building cover had more VIIRS fire detections than expected by chance. To assess the effects of using broad vs. local scale parameterizations on resulting WUI maps, we repeated this process twice, first using national-scale data, and then separately in four distinct geographic regions. We assessed the congruence in the amounts and patterns of WUI in regions as mapped by information from these two analysis scales. We found that the WUI in Israel and the West Bank ranged from 0.5% to 1.7%, depending on fuel type and moving window radius. The scale of parameterization (national vs. regional) affected the WUI patterns only in one of the regions, whose characteristics differed markedly than the rest of the country. Our new method differs from existing WUI mapping methods as it is empirical and geographically flexible. These two traits allow it to robustly map the WUI in other countries with different settlement, fuel, climate and wildfire characteristics.</p

Appendix A. Tables of references for visitation statistics to protected areas in twelve countries; the number of geo-tagged Flickr photos globally when summed for land and sea areas, coastal and non-coastal areas, protected and unprotected areas, as well as for three night-light intensity levels; the three most visited protected areas in 40 selected countries, according to the total number of Flickr photos; the three most popular protected areas in 40 selected countries according to Flickr;...

Tables of references for visitation statistics to protected areas in twelve countries; the number of geo-tagged Flickr photos globally when summed for land and sea areas, coastal and non-coastal areas, protected and unprotected areas, as well as for three night-light intensity levels; the three most visited protected areas in 40 selected countries, according to the total number of Flickr photos; the three most popular protected areas in 40 selected countries according to Flickr; the three most photographed protected areas in 40 selected countries according to Flickr based on the most photographed grid cell within them; the three most popular protected areas shown for 40 selected countries according to Flickr; the three most impacted protected areas in 40 selected countries based on the average of the percentage of lit area and the percentage area with photographers; and the three most impacted protected areas in 40 selected countries based on the average of the percentage of lit area and the percentage area with photographers

Image1_A geographically flexible approach for mapping the Wildland-Urban Interface integrating fire activity data.JPEG

The Wildland-Urban Interface (WUI) is the area where houses and natural vegetation meet or intermingle. WUI areas are exposed to an increased hazard of wildfires and have significantly expanded worldwide in the past few decades. In this study, we developed a new empirical approach for mapping the WUI by generating a WUI index based on the juxtaposition among buildings, vegetation, and the fire history of the study area. We first calculated the percentage coverage of buildings and three different fuel typologies within circular moving windows with radii of 100, 250, and 500 m, and then acquired the fire history data between 2012 and 2021 for Israel and the West Bank (Palestinian Authority) from the VIIRS active fires remote sensing product. We defined the WUI as cells where the combination of vegetation cover and building cover had more VIIRS fire detections than expected by chance. To assess the effects of using broad vs. local scale parameterizations on resulting WUI maps, we repeated this process twice, first using national-scale data, and then separately in four distinct geographic regions. We assessed the congruence in the amounts and patterns of WUI in regions as mapped by information from these two analysis scales. We found that the WUI in Israel and the West Bank ranged from 0.5% to 1.7%, depending on fuel type and moving window radius. The scale of parameterization (national vs. regional) affected the WUI patterns only in one of the regions, whose characteristics differed markedly than the rest of the country. Our new method differs from existing WUI mapping methods as it is empirical and geographically flexible. These two traits allow it to robustly map the WUI in other countries with different settlement, fuel, climate and wildfire characteristics.</p

Species list Levin et al

Information used to define fish species distribution ranges - depth ranges and marine habitat

Proposed framework for regional marine conservation planning.

<p>The 11 stages of conservation planning presented in Pressey and Bottrill (2009) are on the left, and the additional steps we propose for effective conservation planning within complex marine regions, such as the Mediterranean Sea, are added to the right.</p

Main features and considerations for the selection of existing and proposed conservation areas.

<p>The number of times a specific feature was considered in different initiatives is reported. Some proposals incorporated existing initiatives and plans: these are indicated by the light grey boxes and the red arrows. Among the existing conservation areas, SPAMIs, EU CDDA, and existing MPAs were not included because they are aggregations of protected areas based on different criteria.</p

Proposed conservation priority areas in the Mediterranean Sea (see <b>Table</b><b>1B</b> for descriptions).

<p>Proposed conservation priority areas in the Mediterranean Sea (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059038#pone-0059038-t001" target="_blank"><b>Table</b><b>1B</b></a> for descriptions).</p

Existing marine management and conservation areas in the Mediterranean Sea (see <b>Table</b><b>1A</b> for descriptions).

<p>Existing marine management and conservation areas in the Mediterranean Sea (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059038#pone-0059038-t001" target="_blank"><b>Table</b><b>1A</b></a> for descriptions).</p

Correspondence between the different proposed conservation plans. Values above the diagonal (marked by empty cells) are the overall correspondence between pairs of proposals.

<p>Values below the diagonal are the kappa index of agreement (see <i>Methods</i>).</p