Anolis coordinate data and Environmental Niche models

Coordinate data for all Greater Antillean Anolis ecomorphs, and their Environmental Niche models computed with MAXENT. Each ENM was computed on the background of the Greater Antilles, so that the ENMs contain both sutability scores for the ecomorph's own island, as also values fitted on each other island

Figure S1 from Dynamics of host populations affected by the emerging fungal pathogen <i>Batrachochytrium salamandrivorans</i>

Emerging infectious diseases cause extirpation of wildlife populations. We use an epidemiological model to explore the effects of a recently emerged disease caused by the salamander-killing chytrid fungus <i>Batrachochytrium salamandrivorans</i> (<i>Bsal</i>) on host populations, and to evaluate which mitigation measures are most likely to succeed. As individuals do not recover from <i>Bsal</i>, we used a model with the states susceptible, latent and infectious, and parametrized the model using data on host and pathogen taken from the literature and expert opinion. The model suggested that disease outbreaks can occur at very low host densities (one female per hectare). This density is far lower than host densities in the wild. Therefore, all naturally occurring populations are at risk. <i>Bsal</i> can lead to the local extirpation of the host population within a few months. Disease outbreaks are likely to fade out quickly. A spatial variant of the model showed that the pathogen could potentially spread rapidly. As disease mitigation during outbreaks is unlikely to be successful, control efforts should focus on preventing disease emergence and transmission between populations. Thus, this emerging wildlife disease is best controlled through prevention rather than subsequent actions

The ESM contains a description of the model that we used for human-mediated dispersal and supplementary figures which show the results of the sensitivity analysis. from Dynamics of host populations affected by the emerging fungal pathogen <i>Batrachochytrium salamandrivorans</i>

Emerging infectious diseases cause extirpation of wildlife populations. We use an epidemiological model to explore the effects of a recently emerged disease caused by the salamander-killing chytrid fungus <i>Batrachochytrium salamandrivorans</i> (<i>Bsal</i>) on host populations, and to evaluate which mitigation measures are most likely to succeed. As individuals do not recover from <i>Bsal</i>, we used a model with the states susceptible, latent infection and infectious, and parametrized the model using data on host and pathogen taken from the literature and expert opinion. The model suggested that disease outbreaks can occur at very low host densities (one female per hectare). This density is far lower than host densities in the wild. Therefore, all naturally occurring populations are at risk. <i>Bsal</i> can lead to the local extirpation of the host population within a few months. Disease outbreaks are likely to fade out quickly. A spatial variant of the model showed that the pathogen could potentially spread rapidly. As disease mitigation during outbreaks is unlikely to be successful, control efforts should focus on preventing disease emergence and transmission between populations. Thus, this emerging wildlife disease is best controlled through prevention rather than subsequent actions

The ESM contains additional information on evaluating mitigation actions, additional information on human-mediated dispersal, and supplementary figures which show the results of the sensitivity analyses, mitigation actions, and human-mediated dispersal. from Dynamics of host populations affected by the emerging fungal pathogen <i>Batrachochytrium salamandrivorans</i>

Emerging infectious diseases cause extirpation of wildlife populations. We use an epidemiological model to explore the effects of a recently emerged disease caused by the salamander-killing chytrid fungus <i>Batrachochytrium salamandrivorans</i> (<i>Bsal</i>) on host populations, and to evaluate which mitigation measures are most likely to succeed. As individuals do not recover from <i>Bsal</i>, we used a model with the states susceptible, latent and infectious, and parametrized the model using data on host and pathogen taken from the literature and expert opinion. The model suggested that disease outbreaks can occur at very low host densities (one female per hectare). This density is far lower than host densities in the wild. Therefore, all naturally occurring populations are at risk. <i>Bsal</i> can lead to the local extirpation of the host population within a few months. Disease outbreaks are likely to fade out quickly. A spatial variant of the model showed that the pathogen could potentially spread rapidly. As disease mitigation during outbreaks is unlikely to be successful, control efforts should focus on preventing disease emergence and transmission between populations. Thus, this emerging wildlife disease is best controlled through prevention rather than subsequent actions

Figure S2 from Dynamics of host populations affected by the emerging fungal pathogen <i>Batrachochytrium salamandrivorans</i>

Emerging infectious diseases cause extirpation of wildlife populations. We use an epidemiological model to explore the effects of a recently emerged disease caused by the salamander-killing chytrid fungus <i>Batrachochytrium salamandrivorans</i> (<i>Bsal</i>) on host populations, and to evaluate which mitigation measures are most likely to succeed. As individuals do not recover from <i>Bsal</i>, we used a model with the states susceptible, latent and infectious, and parametrized the model using data on host and pathogen taken from the literature and expert opinion. The model suggested that disease outbreaks can occur at very low host densities (one female per hectare). This density is far lower than host densities in the wild. Therefore, all naturally occurring populations are at risk. <i>Bsal</i> can lead to the local extirpation of the host population within a few months. Disease outbreaks are likely to fade out quickly. A spatial variant of the model showed that the pathogen could potentially spread rapidly. As disease mitigation during outbreaks is unlikely to be successful, control efforts should focus on preventing disease emergence and transmission between populations. Thus, this emerging wildlife disease is best controlled through prevention rather than subsequent actions

Heading for New Shores: Projecting Marine Distribution Ranges of Selected Larger Foraminifera

<div><p>The distribution of modern symbiont-bearing larger foraminifera is confined to tropical and subtropical shallow water marine habitats and a narrow range of environmental variables (e.g. temperature). Most of today's taxa are restricted to tropical and subtropical regions (between 30°N and 30°S) and their minimum temperature limits are governed by the 14 to 20°C isotherms. However, during times of extensive global warming (e.g., the Eocene and Miocene), larger foraminifera have been found as far north as 50°N (North America and Central Europe) as well as towards 47°S in New Zealand. During the last century, sea surface temperatures have been rising significantly. This trend is expected to continue and climate change scenarios for 2050 suggest a further increase by 1 to 3°C. We applied Species Distribution Models to assess potential distribution range changes of three taxa of larger foraminifera under current and future climate. The studied foraminifera include <i>Archaias angulatus</i>, <i>Calcarina</i> spp., and <i>Amphistegina</i> spp., and represent taxa with regional, superregional and global distribution patterns. Under present environmental conditions, <i>Amphistegina</i> spp. shows the largest potential distribution, apparently due to its temperature tolerance. Both <i>Archaias angulatus</i> and <i>Calcarina</i> spp. display potential distributions that cover currently uninhabited regions. Under climate conditions expected for the year 2050, all taxa should display latitudinal range expansions between 1 to 2.5 degrees both north- and southward. The modeled range projections suggest that some larger foraminifera may colonize biogeographic regions that so far seemed unsuitable. <i>Archaias angulatus</i> and <i>Calcarina</i> spp. also show an increase in habitat suitability within their native occurrence ranges, suggesting that their tolerance for maximum temperatures has yet not been fully exploited and that they benefit from ocean warming. Our findings suggest an increased role of larger foraminifera as carbonate producers and reef framework builders in future oceans.</p></div

Biogeographic distribution of <i>Amphistegina</i> spp. in the Atlantic Ocean.

<p>(A) Actual distribution and major isotherms (triangles: occurrence records used in the modeling process); (B) potential distribution under present climate conditions and corresponding isotherms; (C) potential distribution under future climate conditions.</p

Relationship of spatial distribution and environmental variables.

<p>(A) Occurrence points of <i>Archaias angulatus</i> (green), <i>Amphistegina</i> spp. (red) and <i>Calcarina</i> spp. (blue) are plotted against sea surface temperature values at the respective location; (B) Occurrence points of <i>Archaias angulatus</i> (green), <i>Amphistegina</i> spp. (orange) and <i>Calcarina</i> spp. (blue) are plotted against salinity values at the respective location; (C) Occurrence points of <i>Archaias angulatus</i> (green), <i>Amphistegina</i> spp. (red) and <i>Calcarina</i> spp. (blue) are plotted against nitrate values at the respective location; (D) Occurrence points of <i>Archaias angulatus</i> (green), <i>Amphistegina</i> spp. (red) and <i>Calcarina</i> spp. (blue) are plotted against phosphate values at the respective location; (E) Occurrence points of <i>Archaias angulatus</i> (green), <i>Amphistegina</i> spp. (red) and <i>Calcarina</i> spp. (blue) are plotted against silicate values at the respective location.</p

Biogeographic distribution of <i>Amphistegina</i> spp. in the Indo-Pacific Ocean.

<p>(A) Actual distribution and major isotherms (triangles: occurrence records used in the modeling process); (B) potential distribution under present climate conditions and corresponding isotherms; (C) potential distribution under future climate conditions.</p

Biogeographic distribution of <i>Archaias angulatus</i> in the Atlantic Ocean.

<p>(A) Actual distribution and major isotherms (triangles: occurrence records used in the modeling process); (B) potential distribution under present climate conditions and corresponding isotherms; (C) potential distribution under future climate conditions.</p