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En el instante 25 de junio de 2026, 12:31:13 UTC,
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Modificado el valor del campo
modified
a2026-06-25
en Using remote-sensing to map suitable road verges for a rare small mammal, the Cabrera vole (Microtus cabrerae). -
Modificado el valor del campo
modified
del recurso Acceso al recurso a2026-06-25
(anteriormente2026-06-23
) en Using remote-sensing to map suitable road verges for a rare small mammal, the Cabrera vole (Microtus cabrerae).
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| 71 | "miteco_data_population": { | 85 | "miteco_data_population": { | ||
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| 74 | "miteco_data_territory": { | 88 | "miteco_data_territory": { | ||
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| 81 | "name": "af46ab7f-4167-5ea7-a934-b8173980d535", | 95 | "name": "af46ab7f-4167-5ea7-a934-b8173980d535", | ||
| 82 | "notes": "The Cabrera vole (Microtus cabrerae) is a rare Iberian | 96 | "notes": "The Cabrera vole (Microtus cabrerae) is a rare Iberian | ||
| 83 | endemism, classified as \u201cNear-threatened\u201d by IUCN, and | 97 | endemism, classified as \u201cNear-threatened\u201d by IUCN, and | ||
| 84 | \u201cVulnerable\u201d in Portugal and Spain. The species has a | 98 | \u201cVulnerable\u201d in Portugal and Spain. The species has a | ||
| 85 | restricted range and a fragmented distribution, occurring mostly in | 99 | restricted range and a fragmented distribution, occurring mostly in | ||
| 86 | patches of tall and dense wet grasslands in a structured | 100 | patches of tall and dense wet grasslands in a structured | ||
| 87 | meta-population system. Spatial and temporal variation on | 101 | meta-population system. Spatial and temporal variation on | ||
| 88 | species\u2019 resource availability poses difficulties when it is | 102 | species\u2019 resource availability poses difficulties when it is | ||
| 89 | necessary to define which specific areas are most important to | 103 | necessary to define which specific areas are most important to | ||
| 90 | protect. On this issue, species distribution models (SDMs) are often | 104 | protect. On this issue, species distribution models (SDMs) are often | ||
| 91 | used to obtain detailed geographical distribution of species, which | 105 | used to obtain detailed geographical distribution of species, which | ||
| 92 | are then used to define effective conservation and monitoring actions. | 106 | are then used to define effective conservation and monitoring actions. | ||
| 93 | However, SDMs applications on Cabrera vole, and other rare species, at | 107 | However, SDMs applications on Cabrera vole, and other rare species, at | ||
| 94 | a local or regional scale are still challenging, likely due to their | 108 | a local or regional scale are still challenging, likely due to their | ||
| 95 | low detectability, narrow distribution, and short-term occupancy of | 109 | low detectability, narrow distribution, and short-term occupancy of | ||
| 96 | suitable patches. In addition, most available digital environmental | 110 | suitable patches. In addition, most available digital environmental | ||
| 97 | information may not reflect spatial and temporal ecological conditions | 111 | information may not reflect spatial and temporal ecological conditions | ||
| 98 | required for the Cabrera vole occurrence. Nowadays, remote-sensing | 112 | required for the Cabrera vole occurrence. Nowadays, remote-sensing | ||
| 99 | provides information on landscape structure and associated biophysical | 113 | provides information on landscape structure and associated biophysical | ||
| 100 | products at areas on able time frequency and at an unreleased fine | 114 | products at areas on able time frequency and at an unreleased fine | ||
| 101 | spatial resolution, which might be a solution to increase the accuracy | 115 | spatial resolution, which might be a solution to increase the accuracy | ||
| 102 | of models, as availability of resources and its variation through time | 116 | of models, as availability of resources and its variation through time | ||
| 103 | is better described. Our aim was to investigate the usefulness of ESA | 117 | is better described. Our aim was to investigate the usefulness of ESA | ||
| 104 | Sentinel-2 products for the prediction of suitable habitat patches for | 118 | Sentinel-2 products for the prediction of suitable habitat patches for | ||
| 105 | the Cabrera vole in a Mediterranean agro-silvopastoral system. We | 119 | the Cabrera vole in a Mediterranean agro-silvopastoral system. We | ||
| 106 | aimed to 1) identify which Sentinel-2 derived predictors are best | 120 | aimed to 1) identify which Sentinel-2 derived predictors are best | ||
| 107 | surrogates for occupied habitat patches; and 2) quantify its | 121 | surrogates for occupied habitat patches; and 2) quantify its | ||
| 108 | importance when compared with other classic/static predictors. The | 122 | importance when compared with other classic/static predictors. The | ||
| 109 | study was conducted in the Alentejo region, Southern Portugal, in | 123 | study was conducted in the Alentejo region, Southern Portugal, in | ||
| 110 | which herbaceous patches were surveyed in Spring 2017 and Autumn 2018, | 124 | which herbaceous patches were surveyed in Spring 2017 and Autumn 2018, | ||
| 111 | through presence signs and then classified into presence/absence. | 125 | through presence signs and then classified into presence/absence. | ||
| 112 | Dataset was filtered to retain true absences by excluding patches | 126 | Dataset was filtered to retain true absences by excluding patches | ||
| 113 | classified as absences with potential habitat. Thereafter, we | 127 | classified as absences with potential habitat. Thereafter, we | ||
| 114 | calculated 85 predictors from Sentinel-2 images as well as from other | 128 | calculated 85 predictors from Sentinel-2 images as well as from other | ||
| 115 | sources (Topographical information and Landscape element proximity). | 129 | sources (Topographical information and Landscape element proximity). | ||
| 116 | Specifically, each satellite image was composed of 10 multispectral | 130 | Specifically, each satellite image was composed of 10 multispectral | ||
| 117 | bands, combined to describe spectral, biophysical and structural | 131 | bands, combined to describe spectral, biophysical and structural | ||
| 118 | landscape properties for each of the two seasons. To identify | 132 | landscape properties for each of the two seasons. To identify | ||
| 119 | predictors to retain, their ecological importance was quantified by | 133 | predictors to retain, their ecological importance was quantified by | ||
| 120 | utilizing Cabrera vole presence/absence data as response variable | 134 | utilizing Cabrera vole presence/absence data as response variable | ||
| 121 | through a Random forest model accounting for multi-predictor | 135 | through a Random forest model accounting for multi-predictor | ||
| 122 | relationships. A total of 11 uncorrelated predictors were identified | 136 | relationships. A total of 11 uncorrelated predictors were identified | ||
| 123 | as important, namely a distance-based measure, road proximity (~27% | 137 | as important, namely a distance-based measure, road proximity (~27% | ||
| 124 | importance), while from remote-sensing data were NDI45 | 138 | importance), while from remote-sensing data were NDI45 | ||
| 125 | \u201cSpring\u201d, SWIR \u201cAutumn\u201d, RAO\u2019s Q | 139 | \u201cSpring\u201d, SWIR \u201cAutumn\u201d, RAO\u2019s Q | ||
| 126 | \u201cSpring\u201d, NDRE1 \u201cAutumn\u201d, Green | 140 | \u201cSpring\u201d, NDRE1 \u201cAutumn\u201d, Green | ||
| 127 | \u201cAutumn\u201d, BI2 \u201cSpring\u201d, GLMC_Cor | 141 | \u201cAutumn\u201d, BI2 \u201cSpring\u201d, GLMC_Cor | ||
| 128 | \u201cSpring\u201d, RAO\u2019s Q \u201cAutumn\u201d, Blue | 142 | \u201cSpring\u201d, RAO\u2019s Q \u201cAutumn\u201d, Blue | ||
| 129 | \u201cSpring\u201d, GLMC_Con \u201cAutumn\u201d, together contributing | 143 | \u201cSpring\u201d, GLMC_Con \u201cAutumn\u201d, together contributing | ||
| 130 | with ~73% of importance. Cabrera vole presence is more likely in areas | 144 | with ~73% of importance. Cabrera vole presence is more likely in areas | ||
| 131 | close to roads, and associated to remote-sensing indices translating | 145 | close to roads, and associated to remote-sensing indices translating | ||
| 132 | vegetation with intermediate chlorophyll contents and water retention, | 146 | vegetation with intermediate chlorophyll contents and water retention, | ||
| 133 | and more local scale vegetation heterogeneity. Road verges can act as | 147 | and more local scale vegetation heterogeneity. Road verges can act as | ||
| 134 | relatively stable refuges in Mediterranean landscapes, especially when | 148 | relatively stable refuges in Mediterranean landscapes, especially when | ||
| 135 | the surrounding matrix becomes environmentally prohibitive, such as | 149 | the surrounding matrix becomes environmentally prohibitive, such as | ||
| 136 | when under intensive agriculture or livestock farming practices. Our | 150 | when under intensive agriculture or livestock farming practices. Our | ||
| 137 | approach is useful for identifying undiscovered suitable areas, and | 151 | approach is useful for identifying undiscovered suitable areas, and | ||
| 138 | for planning the placement of mitigation/conservation measures along | 152 | for planning the placement of mitigation/conservation measures along | ||
| 139 | the road verges as well under other priority areas.", | 153 | the road verges as well under other priority areas.", | ||
| 140 | "notes_translated": { | 154 | "notes_translated": { | ||
| 141 | "en": "The Cabrera vole (Microtus cabrerae) is a rare Iberian | 155 | "en": "The Cabrera vole (Microtus cabrerae) is a rare Iberian | ||
| 142 | endemism, classified as \u201cNear-threatened\u201d by IUCN, and | 156 | endemism, classified as \u201cNear-threatened\u201d by IUCN, and | ||
| 143 | \u201cVulnerable\u201d in Portugal and Spain. The species has a | 157 | \u201cVulnerable\u201d in Portugal and Spain. The species has a | ||
| 144 | restricted range and a fragmented distribution, occurring mostly in | 158 | restricted range and a fragmented distribution, occurring mostly in | ||
| 145 | patches of tall and dense wet grasslands in a structured | 159 | patches of tall and dense wet grasslands in a structured | ||
| 146 | meta-population system. Spatial and temporal variation on | 160 | meta-population system. Spatial and temporal variation on | ||
| 147 | species\u2019 resource availability poses difficulties when it is | 161 | species\u2019 resource availability poses difficulties when it is | ||
| 148 | necessary to define which specific areas are most important to | 162 | necessary to define which specific areas are most important to | ||
| 149 | protect. On this issue, species distribution models (SDMs) are often | 163 | protect. On this issue, species distribution models (SDMs) are often | ||
| 150 | used to obtain detailed geographical distribution of species, which | 164 | used to obtain detailed geographical distribution of species, which | ||
| 151 | are then used to define effective conservation and monitoring actions. | 165 | are then used to define effective conservation and monitoring actions. | ||
| 152 | However, SDMs applications on Cabrera vole, and other rare species, at | 166 | However, SDMs applications on Cabrera vole, and other rare species, at | ||
| 153 | a local or regional scale are still challenging, likely due to their | 167 | a local or regional scale are still challenging, likely due to their | ||
| 154 | low detectability, narrow distribution, and short-term occupancy of | 168 | low detectability, narrow distribution, and short-term occupancy of | ||
| 155 | suitable patches. In addition, most available digital environmental | 169 | suitable patches. In addition, most available digital environmental | ||
| 156 | information may not reflect spatial and temporal ecological conditions | 170 | information may not reflect spatial and temporal ecological conditions | ||
| 157 | required for the Cabrera vole occurrence. Nowadays, remote-sensing | 171 | required for the Cabrera vole occurrence. Nowadays, remote-sensing | ||
| 158 | provides information on landscape structure and associated biophysical | 172 | provides information on landscape structure and associated biophysical | ||
| 159 | products at areas on able time frequency and at an unreleased fine | 173 | products at areas on able time frequency and at an unreleased fine | ||
| 160 | spatial resolution, which might be a solution to increase the accuracy | 174 | spatial resolution, which might be a solution to increase the accuracy | ||
| 161 | of models, as availability of resources and its variation through time | 175 | of models, as availability of resources and its variation through time | ||
| 162 | is better described. Our aim was to investigate the usefulness of ESA | 176 | is better described. Our aim was to investigate the usefulness of ESA | ||
| 163 | Sentinel-2 products for the prediction of suitable habitat patches for | 177 | Sentinel-2 products for the prediction of suitable habitat patches for | ||
| 164 | the Cabrera vole in a Mediterranean agro-silvopastoral system. We | 178 | the Cabrera vole in a Mediterranean agro-silvopastoral system. We | ||
| 165 | aimed to 1) identify which Sentinel-2 derived predictors are best | 179 | aimed to 1) identify which Sentinel-2 derived predictors are best | ||
| 166 | surrogates for occupied habitat patches; and 2) quantify its | 180 | surrogates for occupied habitat patches; and 2) quantify its | ||
| 167 | importance when compared with other classic/static predictors. The | 181 | importance when compared with other classic/static predictors. The | ||
| 168 | study was conducted in the Alentejo region, Southern Portugal, in | 182 | study was conducted in the Alentejo region, Southern Portugal, in | ||
| 169 | which herbaceous patches were surveyed in Spring 2017 and Autumn 2018, | 183 | which herbaceous patches were surveyed in Spring 2017 and Autumn 2018, | ||
| 170 | through presence signs and then classified into presence/absence. | 184 | through presence signs and then classified into presence/absence. | ||
| 171 | Dataset was filtered to retain true absences by excluding patches | 185 | Dataset was filtered to retain true absences by excluding patches | ||
| 172 | classified as absences with potential habitat. Thereafter, we | 186 | classified as absences with potential habitat. Thereafter, we | ||
| 173 | calculated 85 predictors from Sentinel-2 images as well as from other | 187 | calculated 85 predictors from Sentinel-2 images as well as from other | ||
| 174 | sources (Topographical information and Landscape element proximity). | 188 | sources (Topographical information and Landscape element proximity). | ||
| 175 | Specifically, each satellite image was composed of 10 multispectral | 189 | Specifically, each satellite image was composed of 10 multispectral | ||
| 176 | bands, combined to describe spectral, biophysical and structural | 190 | bands, combined to describe spectral, biophysical and structural | ||
| 177 | landscape properties for each of the two seasons. To identify | 191 | landscape properties for each of the two seasons. To identify | ||
| 178 | predictors to retain, their ecological importance was quantified by | 192 | predictors to retain, their ecological importance was quantified by | ||
| 179 | utilizing Cabrera vole presence/absence data as response variable | 193 | utilizing Cabrera vole presence/absence data as response variable | ||
| 180 | through a Random forest model accounting for multi-predictor | 194 | through a Random forest model accounting for multi-predictor | ||
| 181 | relationships. A total of 11 uncorrelated predictors were identified | 195 | relationships. A total of 11 uncorrelated predictors were identified | ||
| 182 | as important, namely a distance-based measure, road proximity (~27% | 196 | as important, namely a distance-based measure, road proximity (~27% | ||
| 183 | importance), while from remote-sensing data were NDI45 | 197 | importance), while from remote-sensing data were NDI45 | ||
| 184 | \u201cSpring\u201d, SWIR \u201cAutumn\u201d, RAO\u2019s Q | 198 | \u201cSpring\u201d, SWIR \u201cAutumn\u201d, RAO\u2019s Q | ||
| 185 | \u201cSpring\u201d, NDRE1 \u201cAutumn\u201d, Green | 199 | \u201cSpring\u201d, NDRE1 \u201cAutumn\u201d, Green | ||
| 186 | \u201cAutumn\u201d, BI2 \u201cSpring\u201d, GLMC_Cor | 200 | \u201cAutumn\u201d, BI2 \u201cSpring\u201d, GLMC_Cor | ||
| 187 | \u201cSpring\u201d, RAO\u2019s Q \u201cAutumn\u201d, Blue | 201 | \u201cSpring\u201d, RAO\u2019s Q \u201cAutumn\u201d, Blue | ||
| 188 | \u201cSpring\u201d, GLMC_Con \u201cAutumn\u201d, together contributing | 202 | \u201cSpring\u201d, GLMC_Con \u201cAutumn\u201d, together contributing | ||
| 189 | with ~73% of importance. Cabrera vole presence is more likely in areas | 203 | with ~73% of importance. Cabrera vole presence is more likely in areas | ||
| 190 | close to roads, and associated to remote-sensing indices translating | 204 | close to roads, and associated to remote-sensing indices translating | ||
| 191 | vegetation with intermediate chlorophyll contents and water retention, | 205 | vegetation with intermediate chlorophyll contents and water retention, | ||
| 192 | and more local scale vegetation heterogeneity. Road verges can act as | 206 | and more local scale vegetation heterogeneity. Road verges can act as | ||
| 193 | relatively stable refuges in Mediterranean landscapes, especially when | 207 | relatively stable refuges in Mediterranean landscapes, especially when | ||
| 194 | the surrounding matrix becomes environmentally prohibitive, such as | 208 | the surrounding matrix becomes environmentally prohibitive, such as | ||
| 195 | when under intensive agriculture or livestock farming practices. Our | 209 | when under intensive agriculture or livestock farming practices. Our | ||
| 196 | approach is useful for identifying undiscovered suitable areas, and | 210 | approach is useful for identifying undiscovered suitable areas, and | ||
| 197 | for planning the placement of mitigation/conservation measures along | 211 | for planning the placement of mitigation/conservation measures along | ||
| 198 | the road verges as well under other priority areas.", | 212 | the road verges as well under other priority areas.", | ||
| 199 | "es": "The Cabrera vole (Microtus cabrerae) is a rare Iberian | 213 | "es": "The Cabrera vole (Microtus cabrerae) is a rare Iberian | ||
| 200 | endemism, classified as \u201cNear-threatened\u201d by IUCN, and | 214 | endemism, classified as \u201cNear-threatened\u201d by IUCN, and | ||
| 201 | \u201cVulnerable\u201d in Portugal and Spain. The species has a | 215 | \u201cVulnerable\u201d in Portugal and Spain. The species has a | ||
| 202 | restricted range and a fragmented distribution, occurring mostly in | 216 | restricted range and a fragmented distribution, occurring mostly in | ||
| 203 | patches of tall and dense wet grasslands in a structured | 217 | patches of tall and dense wet grasslands in a structured | ||
| 204 | meta-population system. Spatial and temporal variation on | 218 | meta-population system. Spatial and temporal variation on | ||
| 205 | species\u2019 resource availability poses difficulties when it is | 219 | species\u2019 resource availability poses difficulties when it is | ||
| 206 | necessary to define which specific areas are most important to | 220 | necessary to define which specific areas are most important to | ||
| 207 | protect. On this issue, species distribution models (SDMs) are often | 221 | protect. On this issue, species distribution models (SDMs) are often | ||
| 208 | used to obtain detailed geographical distribution of species, which | 222 | used to obtain detailed geographical distribution of species, which | ||
| 209 | are then used to define effective conservation and monitoring actions. | 223 | are then used to define effective conservation and monitoring actions. | ||
| 210 | However, SDMs applications on Cabrera vole, and other rare species, at | 224 | However, SDMs applications on Cabrera vole, and other rare species, at | ||
| 211 | a local or regional scale are still challenging, likely due to their | 225 | a local or regional scale are still challenging, likely due to their | ||
| 212 | low detectability, narrow distribution, and short-term occupancy of | 226 | low detectability, narrow distribution, and short-term occupancy of | ||
| 213 | suitable patches. In addition, most available digital environmental | 227 | suitable patches. In addition, most available digital environmental | ||
| 214 | information may not reflect spatial and temporal ecological conditions | 228 | information may not reflect spatial and temporal ecological conditions | ||
| 215 | required for the Cabrera vole occurrence. Nowadays, remote-sensing | 229 | required for the Cabrera vole occurrence. Nowadays, remote-sensing | ||
| 216 | provides information on landscape structure and associated biophysical | 230 | provides information on landscape structure and associated biophysical | ||
| 217 | products at areas on able time frequency and at an unreleased fine | 231 | products at areas on able time frequency and at an unreleased fine | ||
| 218 | spatial resolution, which might be a solution to increase the accuracy | 232 | spatial resolution, which might be a solution to increase the accuracy | ||
| 219 | of models, as availability of resources and its variation through time | 233 | of models, as availability of resources and its variation through time | ||
| 220 | is better described. Our aim was to investigate the usefulness of ESA | 234 | is better described. Our aim was to investigate the usefulness of ESA | ||
| 221 | Sentinel-2 products for the prediction of suitable habitat patches for | 235 | Sentinel-2 products for the prediction of suitable habitat patches for | ||
| 222 | the Cabrera vole in a Mediterranean agro-silvopastoral system. We | 236 | the Cabrera vole in a Mediterranean agro-silvopastoral system. We | ||
| 223 | aimed to 1) identify which Sentinel-2 derived predictors are best | 237 | aimed to 1) identify which Sentinel-2 derived predictors are best | ||
| 224 | surrogates for occupied habitat patches; and 2) quantify its | 238 | surrogates for occupied habitat patches; and 2) quantify its | ||
| 225 | importance when compared with other classic/static predictors. The | 239 | importance when compared with other classic/static predictors. The | ||
| 226 | study was conducted in the Alentejo region, Southern Portugal, in | 240 | study was conducted in the Alentejo region, Southern Portugal, in | ||
| 227 | which herbaceous patches were surveyed in Spring 2017 and Autumn 2018, | 241 | which herbaceous patches were surveyed in Spring 2017 and Autumn 2018, | ||
| 228 | through presence signs and then classified into presence/absence. | 242 | through presence signs and then classified into presence/absence. | ||
| 229 | Dataset was filtered to retain true absences by excluding patches | 243 | Dataset was filtered to retain true absences by excluding patches | ||
| 230 | classified as absences with potential habitat. Thereafter, we | 244 | classified as absences with potential habitat. Thereafter, we | ||
| 231 | calculated 85 predictors from Sentinel-2 images as well as from other | 245 | calculated 85 predictors from Sentinel-2 images as well as from other | ||
| 232 | sources (Topographical information and Landscape element proximity). | 246 | sources (Topographical information and Landscape element proximity). | ||
| 233 | Specifically, each satellite image was composed of 10 multispectral | 247 | Specifically, each satellite image was composed of 10 multispectral | ||
| 234 | bands, combined to describe spectral, biophysical and structural | 248 | bands, combined to describe spectral, biophysical and structural | ||
| 235 | landscape properties for each of the two seasons. To identify | 249 | landscape properties for each of the two seasons. To identify | ||
| 236 | predictors to retain, their ecological importance was quantified by | 250 | predictors to retain, their ecological importance was quantified by | ||
| 237 | utilizing Cabrera vole presence/absence data as response variable | 251 | utilizing Cabrera vole presence/absence data as response variable | ||
| 238 | through a Random forest model accounting for multi-predictor | 252 | through a Random forest model accounting for multi-predictor | ||
| 239 | relationships. A total of 11 uncorrelated predictors were identified | 253 | relationships. A total of 11 uncorrelated predictors were identified | ||
| 240 | as important, namely a distance-based measure, road proximity (~27% | 254 | as important, namely a distance-based measure, road proximity (~27% | ||
| 241 | importance), while from remote-sensing data were NDI45 | 255 | importance), while from remote-sensing data were NDI45 | ||
| 242 | \u201cSpring\u201d, SWIR \u201cAutumn\u201d, RAO\u2019s Q | 256 | \u201cSpring\u201d, SWIR \u201cAutumn\u201d, RAO\u2019s Q | ||
| 243 | \u201cSpring\u201d, NDRE1 \u201cAutumn\u201d, Green | 257 | \u201cSpring\u201d, NDRE1 \u201cAutumn\u201d, Green | ||
| 244 | \u201cAutumn\u201d, BI2 \u201cSpring\u201d, GLMC_Cor | 258 | \u201cAutumn\u201d, BI2 \u201cSpring\u201d, GLMC_Cor | ||
| 245 | \u201cSpring\u201d, RAO\u2019s Q \u201cAutumn\u201d, Blue | 259 | \u201cSpring\u201d, RAO\u2019s Q \u201cAutumn\u201d, Blue | ||
| 246 | \u201cSpring\u201d, GLMC_Con \u201cAutumn\u201d, together contributing | 260 | \u201cSpring\u201d, GLMC_Con \u201cAutumn\u201d, together contributing | ||
| 247 | with ~73% of importance. Cabrera vole presence is more likely in areas | 261 | with ~73% of importance. Cabrera vole presence is more likely in areas | ||
| 248 | close to roads, and associated to remote-sensing indices translating | 262 | close to roads, and associated to remote-sensing indices translating | ||
| 249 | vegetation with intermediate chlorophyll contents and water retention, | 263 | vegetation with intermediate chlorophyll contents and water retention, | ||
| 250 | and more local scale vegetation heterogeneity. Road verges can act as | 264 | and more local scale vegetation heterogeneity. Road verges can act as | ||
| 251 | relatively stable refuges in Mediterranean landscapes, especially when | 265 | relatively stable refuges in Mediterranean landscapes, especially when | ||
| 252 | the surrounding matrix becomes environmentally prohibitive, such as | 266 | the surrounding matrix becomes environmentally prohibitive, such as | ||
| 253 | when under intensive agriculture or livestock farming practices. Our | 267 | when under intensive agriculture or livestock farming practices. Our | ||
| 254 | approach is useful for identifying undiscovered suitable areas, and | 268 | approach is useful for identifying undiscovered suitable areas, and | ||
| 255 | for planning the placement of mitigation/conservation measures along | 269 | for planning the placement of mitigation/conservation measures along | ||
| 256 | the road verges as well under other priority areas." | 270 | the road verges as well under other priority areas." | ||
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| 401 | "title": "Using remote-sensing to map suitable road verges for a | 415 | "title": "Using remote-sensing to map suitable road verges for a | ||
| 402 | rare small mammal, the Cabrera vole (Microtus cabrerae).", | 416 | rare small mammal, the Cabrera vole (Microtus cabrerae).", | ||
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