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En el instante 23 de junio de 2026, 15:59:57 UTC,
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Modificado el valor del campo
spatial_coverage
a[{'bbox': '{"type": "Polygon", "coordinates": [[[-18.16, 27.64], [4.32, 27.64], [4.32, 43.79], [-18.16, 43.79], [-18.16, 27.64]]]}', 'centroid': '{"type": "Point", "coordinates": [-6.92, 35.715]}', 'text': 'España', 'uri': 'http://datos.gob.es/recurso/sector-publico/territorio/Pais/España'}]
en Spatiotemporal persistence of bat roadkill hotspots in response to dynamics of habitat suitability and activity patterns.
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| 5 | "author": "Medinas, D., Marques, J.T., Costa, P., Santos, S., | 5 | "author": "Medinas, D., Marques, J.T., Costa, P., Santos, S., | ||
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| 81 | "notes": "Wildlife roadkill hotspots are frequently used to identify | 81 | "notes": "Wildlife roadkill hotspots are frequently used to identify | ||
| 82 | priority locations for implementing mitigation measures. However, | 82 | priority locations for implementing mitigation measures. However, | ||
| 83 | understanding the landscape-context and the spatial and temporal | 83 | understanding the landscape-context and the spatial and temporal | ||
| 84 | dynamics of these hotspots is challenging. Here, we investigate the | 84 | dynamics of these hotspots is challenging. Here, we investigate the | ||
| 85 | factors that drive the spatiotemporal variation of bat mortality | 85 | factors that drive the spatiotemporal variation of bat mortality | ||
| 86 | hotspots on roads along three years. We hypothesize that hotspot | 86 | hotspots on roads along three years. We hypothesize that hotspot | ||
| 87 | locations occur where bat activity is higher and that this activity is | 87 | locations occur where bat activity is higher and that this activity is | ||
| 88 | related to vegetation density and productivity, probably because this | 88 | related to vegetation density and productivity, probably because this | ||
| 89 | is associated with food availability. Statistically significant | 89 | is associated with food availability. Statistically significant | ||
| 90 | clusters of bat-vehicle collisions for each year were identified using | 90 | clusters of bat-vehicle collisions for each year were identified using | ||
| 91 | the Kernel Density Estimation (KDE) approach. Additionally, we used a | 91 | the Kernel Density Estimation (KDE) approach. Additionally, we used a | ||
| 92 | spatiotemporal analysis and generalized linear mixed models to | 92 | spatiotemporal analysis and generalized linear mixed models to | ||
| 93 | evaluate the effect of local spatiotemporal variation of environmental | 93 | evaluate the effect of local spatiotemporal variation of environmental | ||
| 94 | indices and bat activity to predict the variation on roadkill hotspot | 94 | indices and bat activity to predict the variation on roadkill hotspot | ||
| 95 | locations and to asses hotspot strength over time. Between 2009 and | 95 | locations and to asses hotspot strength over time. Between 2009 and | ||
| 96 | 2011 we conducted daily surveys of bat casualties along a 51-km-long | 96 | 2011 we conducted daily surveys of bat casualties along a 51-km-long | ||
| 97 | transect that incorporates different types of roads in southern | 97 | transect that incorporates different types of roads in southern | ||
| 98 | Portugal. We found 509 casualties and we identified 86 statistically | 98 | Portugal. We found 509 casualties and we identified 86 statistically | ||
| 99 | significant roadkill hotspots, which comprised 12% of the road network | 99 | significant roadkill hotspots, which comprised 12% of the road network | ||
| 100 | length and contained 61% of the casualties. Hotspots tended to be | 100 | length and contained 61% of the casualties. Hotspots tended to be | ||
| 101 | located in areas with higher accumulation of vegetation productivity | 101 | located in areas with higher accumulation of vegetation productivity | ||
| 102 | along the three-year period, high bat activity and low temperature. | 102 | along the three-year period, high bat activity and low temperature. | ||
| 103 | Furthermore, we found that only 17% of the road network length was | 103 | Furthermore, we found that only 17% of the road network length was | ||
| 104 | consistently classified as hotspots across all years; while 43% of | 104 | consistently classified as hotspots across all years; while 43% of | ||
| 105 | hotspots vanished in consecutive years and 40% of new road segments | 105 | hotspots vanished in consecutive years and 40% of new road segments | ||
| 106 | were classified as hotspots. Thus, non-persistent hotspots were the | 106 | were classified as hotspots. Thus, non-persistent hotspots were the | ||
| 107 | most frequent category. Spatiotemporal changes in hotspot location are | 107 | most frequent category. Spatiotemporal changes in hotspot location are | ||
| 108 | associated with decreasing vegetation production and increasing water | 108 | associated with decreasing vegetation production and increasing water | ||
| 109 | stress on road surroundings. This supports our hypothesis that a | 109 | stress on road surroundings. This supports our hypothesis that a | ||
| 110 | decline on overall vegetation productivity and increase of roadside | 110 | decline on overall vegetation productivity and increase of roadside | ||
| 111 | water deficit, and the presumed lower abundance of prey, have a | 111 | water deficit, and the presumed lower abundance of prey, have a | ||
| 112 | significant effect on the decrease of bat roadkills. To our knowledge, | 112 | significant effect on the decrease of bat roadkills. To our knowledge, | ||
| 113 | this is the first study demonstrating that freely available remote | 113 | this is the first study demonstrating that freely available remote | ||
| 114 | sensing data can be a powerful tool to quantify bat roadkill risk and | 114 | sensing data can be a powerful tool to quantify bat roadkill risk and | ||
| 115 | assess its spatiotemporal dynamics.", | 115 | assess its spatiotemporal dynamics.", | ||
| 116 | "notes_translated": { | 116 | "notes_translated": { | ||
| 117 | "en": "Wildlife\u00a0roadkill\u00a0hotspots are frequently used to | 117 | "en": "Wildlife\u00a0roadkill\u00a0hotspots are frequently used to | ||
| 118 | identify priority locations for implementing\u00a0mitigation measures. | 118 | identify priority locations for implementing\u00a0mitigation measures. | ||
| 119 | However, understanding the landscape-context and the spatial and | 119 | However, understanding the landscape-context and the spatial and | ||
| 120 | temporal dynamics of these hotspots is challenging. Here, we | 120 | temporal dynamics of these hotspots is challenging. Here, we | ||
| 121 | investigate the factors that drive the spatiotemporal variation of bat | 121 | investigate the factors that drive the spatiotemporal variation of bat | ||
| 122 | mortality hotspots on roads along three years. We hypothesize that | 122 | mortality hotspots on roads along three years. We hypothesize that | ||
| 123 | hotspot locations occur where bat activity is higher and that this | 123 | hotspot locations occur where bat activity is higher and that this | ||
| 124 | activity is related to vegetation density and productivity, probably | 124 | activity is related to vegetation density and productivity, probably | ||
| 125 | because this is associated with food availability. Statistically | 125 | because this is associated with food availability. Statistically | ||
| 126 | significant clusters of bat-vehicle collisions for each year were | 126 | significant clusters of bat-vehicle collisions for each year were | ||
| 127 | identified using the Kernel Density Estimation (KDE) approach. | 127 | identified using the Kernel Density Estimation (KDE) approach. | ||
| 128 | Additionally, we used a\u00a0spatiotemporal analysis\u00a0and | 128 | Additionally, we used a\u00a0spatiotemporal analysis\u00a0and | ||
| 129 | generalized linear mixed models to evaluate the effect of local | 129 | generalized linear mixed models to evaluate the effect of local | ||
| 130 | spatiotemporal variation of environmental indices and bat activity to | 130 | spatiotemporal variation of environmental indices and bat activity to | ||
| 131 | predict the variation on\u00a0roadkill\u00a0hotspot locations and to | 131 | predict the variation on\u00a0roadkill\u00a0hotspot locations and to | ||
| 132 | asses hotspot strength over time. Between 2009 and 2011 we conducted | 132 | asses hotspot strength over time. Between 2009 and 2011 we conducted | ||
| 133 | daily surveys of bat casualties along a 51-km-long transect that | 133 | daily surveys of bat casualties along a 51-km-long transect that | ||
| 134 | incorporates different types of roads in southern Portugal. We found | 134 | incorporates different types of roads in southern Portugal. We found | ||
| 135 | 509 casualties and we identified 86 statistically significant roadkill | 135 | 509 casualties and we identified 86 statistically significant roadkill | ||
| 136 | hotspots, which comprised 12% of the\u00a0road network\u00a0length and | 136 | hotspots, which comprised 12% of the\u00a0road network\u00a0length and | ||
| 137 | contained 61% of the casualties. Hotspots tended to be located in | 137 | contained 61% of the casualties. Hotspots tended to be located in | ||
| 138 | areas with higher accumulation of vegetation productivity along the | 138 | areas with higher accumulation of vegetation productivity along the | ||
| 139 | three-year period, high bat activity and low temperature. Furthermore, | 139 | three-year period, high bat activity and low temperature. Furthermore, | ||
| 140 | we found that only 17% of the\u00a0road network\u00a0length was | 140 | we found that only 17% of the\u00a0road network\u00a0length was | ||
| 141 | consistently classified as hotspots across all years; while 43% of | 141 | consistently classified as hotspots across all years; while 43% of | ||
| 142 | hotspots vanished in consecutive years and 40% of new road segments | 142 | hotspots vanished in consecutive years and 40% of new road segments | ||
| 143 | were classified as hotspots. Thus, non-persistent hotspots were the | 143 | were classified as hotspots. Thus, non-persistent hotspots were the | ||
| 144 | most frequent category. Spatiotemporal changes in hotspot location are | 144 | most frequent category. Spatiotemporal changes in hotspot location are | ||
| 145 | associated with decreasing vegetation production and increasing water | 145 | associated with decreasing vegetation production and increasing water | ||
| 146 | stress on road surroundings. This supports our hypothesis that a | 146 | stress on road surroundings. This supports our hypothesis that a | ||
| 147 | decline on overall vegetation productivity and increase | 147 | decline on overall vegetation productivity and increase | ||
| 148 | of\u00a0roadside\u00a0water deficit, and the presumed lower abundance | 148 | of\u00a0roadside\u00a0water deficit, and the presumed lower abundance | ||
| 149 | of prey, have a significant effect on the decrease of bat roadkills. | 149 | of prey, have a significant effect on the decrease of bat roadkills. | ||
| 150 | To our knowledge, this is the first study demonstrating that freely | 150 | To our knowledge, this is the first study demonstrating that freely | ||
| 151 | available\u00a0remote sensing\u00a0data can be a powerful tool to | 151 | available\u00a0remote sensing\u00a0data can be a powerful tool to | ||
| 152 | quantify bat roadkill risk and assess its spatiotemporal dynamics.", | 152 | quantify bat roadkill risk and assess its spatiotemporal dynamics.", | ||
| 153 | "es": "Wildlife roadkill hotspots are frequently used to identify | 153 | "es": "Wildlife roadkill hotspots are frequently used to identify | ||
| 154 | priority locations for implementing mitigation measures. However, | 154 | priority locations for implementing mitigation measures. However, | ||
| 155 | understanding the landscape-context and the spatial and temporal | 155 | understanding the landscape-context and the spatial and temporal | ||
| 156 | dynamics of these hotspots is challenging. Here, we investigate the | 156 | dynamics of these hotspots is challenging. Here, we investigate the | ||
| 157 | factors that drive the spatiotemporal variation of bat mortality | 157 | factors that drive the spatiotemporal variation of bat mortality | ||
| 158 | hotspots on roads along three years. We hypothesize that hotspot | 158 | hotspots on roads along three years. We hypothesize that hotspot | ||
| 159 | locations occur where bat activity is higher and that this activity is | 159 | locations occur where bat activity is higher and that this activity is | ||
| 160 | related to vegetation density and productivity, probably because this | 160 | related to vegetation density and productivity, probably because this | ||
| 161 | is associated with food availability. Statistically significant | 161 | is associated with food availability. Statistically significant | ||
| 162 | clusters of bat-vehicle collisions for each year were identified using | 162 | clusters of bat-vehicle collisions for each year were identified using | ||
| 163 | the Kernel Density Estimation (KDE) approach. Additionally, we used a | 163 | the Kernel Density Estimation (KDE) approach. Additionally, we used a | ||
| 164 | spatiotemporal analysis and generalized linear mixed models to | 164 | spatiotemporal analysis and generalized linear mixed models to | ||
| 165 | evaluate the effect of local spatiotemporal variation of environmental | 165 | evaluate the effect of local spatiotemporal variation of environmental | ||
| 166 | indices and bat activity to predict the variation on roadkill hotspot | 166 | indices and bat activity to predict the variation on roadkill hotspot | ||
| 167 | locations and to asses hotspot strength over time. Between 2009 and | 167 | locations and to asses hotspot strength over time. Between 2009 and | ||
| 168 | 2011 we conducted daily surveys of bat casualties along a 51-km-long | 168 | 2011 we conducted daily surveys of bat casualties along a 51-km-long | ||
| 169 | transect that incorporates different types of roads in southern | 169 | transect that incorporates different types of roads in southern | ||
| 170 | Portugal. We found 509 casualties and we identified 86 statistically | 170 | Portugal. We found 509 casualties and we identified 86 statistically | ||
| 171 | significant roadkill hotspots, which comprised 12% of the road network | 171 | significant roadkill hotspots, which comprised 12% of the road network | ||
| 172 | length and contained 61% of the casualties. Hotspots tended to be | 172 | length and contained 61% of the casualties. Hotspots tended to be | ||
| 173 | located in areas with higher accumulation of vegetation productivity | 173 | located in areas with higher accumulation of vegetation productivity | ||
| 174 | along the three-year period, high bat activity and low temperature. | 174 | along the three-year period, high bat activity and low temperature. | ||
| 175 | Furthermore, we found that only 17% of the road network length was | 175 | Furthermore, we found that only 17% of the road network length was | ||
| 176 | consistently classified as hotspots across all years; while 43% of | 176 | consistently classified as hotspots across all years; while 43% of | ||
| 177 | hotspots vanished in consecutive years and 40% of new road segments | 177 | hotspots vanished in consecutive years and 40% of new road segments | ||
| 178 | were classified as hotspots. Thus, non-persistent hotspots were the | 178 | were classified as hotspots. Thus, non-persistent hotspots were the | ||
| 179 | most frequent category. Spatiotemporal changes in hotspot location are | 179 | most frequent category. Spatiotemporal changes in hotspot location are | ||
| 180 | associated with decreasing vegetation production and increasing water | 180 | associated with decreasing vegetation production and increasing water | ||
| 181 | stress on road surroundings. This supports our hypothesis that a | 181 | stress on road surroundings. This supports our hypothesis that a | ||
| 182 | decline on overall vegetation productivity and increase of roadside | 182 | decline on overall vegetation productivity and increase of roadside | ||
| 183 | water deficit, and the presumed lower abundance of prey, have a | 183 | water deficit, and the presumed lower abundance of prey, have a | ||
| 184 | significant effect on the decrease of bat roadkills. To our knowledge, | 184 | significant effect on the decrease of bat roadkills. To our knowledge, | ||
| 185 | this is the first study demonstrating that freely available remote | 185 | this is the first study demonstrating that freely available remote | ||
| 186 | sensing data can be a powerful tool to quantify bat roadkill risk and | 186 | sensing data can be a powerful tool to quantify bat roadkill risk and | ||
| 187 | assess its spatiotemporal dynamics." | 187 | assess its spatiotemporal dynamics." | ||
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