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En el instante 23 de junio de 2026, 16:04:32 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 A comparison of Eurasian red squirrel distribution in different fragmented landscapes.
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| 79 | "notes": "1. The occurrence of species vulnerable to habitat | 79 | "notes": "1. The occurrence of species vulnerable to habitat | ||
| 80 | fragmentation is likely to depend on the size and separation of the | 80 | fragmentation is likely to depend on the size and separation of the | ||
| 81 | fragments. However, the shape of the function that relates occurrence | 81 | fragments. However, the shape of the function that relates occurrence | ||
| 82 | to these landscape parameters may be affected by other factors that | 82 | to these landscape parameters may be affected by other factors that | ||
| 83 | are less easily measured, in which case relationships with size and | 83 | are less easily measured, in which case relationships with size and | ||
| 84 | separation in one area may predict occurrence elsewhere only poorly. | 84 | separation in one area may predict occurrence elsewhere only poorly. | ||
| 85 | 2. We explored how well the distribution of red squirrels Sciurus | 85 | 2. We explored how well the distribution of red squirrels Sciurus | ||
| 86 | vulgaris in fragmented woodlands was predicted by simple logistic | 86 | vulgaris in fragmented woodlands was predicted by simple logistic | ||
| 87 | regression models empirically derived in other fragmented landscapes. | 87 | regression models empirically derived in other fragmented landscapes. | ||
| 88 | 3. Comparisons between predictions lead us to identify thresholds in | 88 | 3. Comparisons between predictions lead us to identify thresholds in | ||
| 89 | fragment size (> 10 ha) and distance to a source (< 600 m) where the | 89 | fragment size (> 10 ha) and distance to a source (< 600 m) where the | ||
| 90 | probability of squirrel occupancy was at least 0.9 in all landscapes. | 90 | probability of squirrel occupancy was at least 0.9 in all landscapes. | ||
| 91 | These values may reflect squirrel minimum habitat requirements for | 91 | These values may reflect squirrel minimum habitat requirements for | ||
| 92 | home range and dispersal in the worst study area. 4. For fragments < | 92 | home range and dispersal in the worst study area. 4. For fragments < | ||
| 93 | 10 ha (outside shared thresholds), models developed in a landscape | 93 | 10 ha (outside shared thresholds), models developed in a landscape | ||
| 94 | could predict squirrel occupancy elsewhere only in 17% of cases, as | 94 | could predict squirrel occupancy elsewhere only in 17% of cases, as | ||
| 95 | other factors such as demography or habitat quality might become | 95 | other factors such as demography or habitat quality might become | ||
| 96 | relevant in very small and isolated fragments. 5. The predictive | 96 | relevant in very small and isolated fragments. 5. The predictive | ||
| 97 | ability for small fragments also improved when the range of fragment | 97 | ability for small fragments also improved when the range of fragment | ||
| 98 | sizes in the area of observation fell within the range of sizes in the | 98 | sizes in the area of observation fell within the range of sizes in the | ||
| 99 | area where the model was developed. 6. Some models gave correct | 99 | area where the model was developed. 6. Some models gave correct | ||
| 100 | between-year predictions of squirrel distribution in the same | 100 | between-year predictions of squirrel distribution in the same | ||
| 101 | landscape despite noticeable changes in regional squirrel population | 101 | landscape despite noticeable changes in regional squirrel population | ||
| 102 | density. 7. When size and distance thresholds were met, we found that | 102 | density. 7. When size and distance thresholds were met, we found that | ||
| 103 | models could be used successfully elsewhere. In addition, threshold | 103 | models could be used successfully elsewhere. In addition, threshold | ||
| 104 | values indicate how large forest fragments should be and how they | 104 | values indicate how large forest fragments should be and how they | ||
| 105 | should be arranged to favour squirrel occurrence in a landscape.\n | 105 | should be arranged to favour squirrel occurrence in a landscape.\n | ||
| 106 | Palabras clave: Computer model, Habitat fragmentation, Population, | 106 | Palabras clave: Computer model, Habitat fragmentation, Population, | ||
| 107 | Squirrel", | 107 | Squirrel", | ||
| 108 | "notes_translated": { | 108 | "notes_translated": { | ||
| 109 | "en": "1. The occurrence of species vulnerable to habitat | 109 | "en": "1. The occurrence of species vulnerable to habitat | ||
| 110 | fragmentation is likely to depend on the size and separation of the | 110 | fragmentation is likely to depend on the size and separation of the | ||
| 111 | fragments. However, the shape of the function that relates occurrence | 111 | fragments. However, the shape of the function that relates occurrence | ||
| 112 | to these landscape parameters may be affected by other factors that | 112 | to these landscape parameters may be affected by other factors that | ||
| 113 | are less easily measured, in which case relationships with size and | 113 | are less easily measured, in which case relationships with size and | ||
| 114 | separation in one area may predict occurrence elsewhere only poorly. | 114 | separation in one area may predict occurrence elsewhere only poorly. | ||
| 115 | 2. We explored how well the distribution of red squirrels Sciurus | 115 | 2. We explored how well the distribution of red squirrels Sciurus | ||
| 116 | vulgaris in fragmented woodlands was predicted by simple logistic | 116 | vulgaris in fragmented woodlands was predicted by simple logistic | ||
| 117 | regression models empirically derived in other fragmented landscapes. | 117 | regression models empirically derived in other fragmented landscapes. | ||
| 118 | 3. Comparisons between predictions lead us to identify thresholds in | 118 | 3. Comparisons between predictions lead us to identify thresholds in | ||
| 119 | fragment size (> 10 ha) and distance to a source (< 600 m) where the | 119 | fragment size (> 10 ha) and distance to a source (< 600 m) where the | ||
| 120 | probability of squirrel occupancy was at least 0.9 in all landscapes. | 120 | probability of squirrel occupancy was at least 0.9 in all landscapes. | ||
| 121 | These values may reflect squirrel minimum habitat requirements for | 121 | These values may reflect squirrel minimum habitat requirements for | ||
| 122 | home range and dispersal in the worst study area. 4. For fragments < | 122 | home range and dispersal in the worst study area. 4. For fragments < | ||
| 123 | 10 ha (outside shared thresholds), models developed in a landscape | 123 | 10 ha (outside shared thresholds), models developed in a landscape | ||
| 124 | could predict squirrel occupancy elsewhere only in 17% of cases, as | 124 | could predict squirrel occupancy elsewhere only in 17% of cases, as | ||
| 125 | other factors such as demography or habitat quality might become | 125 | other factors such as demography or habitat quality might become | ||
| 126 | relevant in very small and isolated fragments. 5. The predictive | 126 | relevant in very small and isolated fragments. 5. The predictive | ||
| 127 | ability for small fragments also improved when the range of fragment | 127 | ability for small fragments also improved when the range of fragment | ||
| 128 | sizes in the area of observation fell within the range of sizes in the | 128 | sizes in the area of observation fell within the range of sizes in the | ||
| 129 | area where the model was developed. 6. Some models gave correct | 129 | area where the model was developed. 6. Some models gave correct | ||
| 130 | between-year predictions of squirrel distribution in the same | 130 | between-year predictions of squirrel distribution in the same | ||
| 131 | landscape despite noticeable changes in regional squirrel population | 131 | landscape despite noticeable changes in regional squirrel population | ||
| 132 | density. 7. When size and distance thresholds were met, we found that | 132 | density. 7. When size and distance thresholds were met, we found that | ||
| 133 | models could be used successfully elsewhere. In addition, threshold | 133 | models could be used successfully elsewhere. In addition, threshold | ||
| 134 | values indicate how large forest fragments should be and how they | 134 | values indicate how large forest fragments should be and how they | ||
| 135 | should be arranged to favour squirrel occurrence in a landscape.", | 135 | should be arranged to favour squirrel occurrence in a landscape.", | ||
| 136 | "es": "1. The occurrence of species vulnerable to habitat | 136 | "es": "1. The occurrence of species vulnerable to habitat | ||
| 137 | fragmentation is likely to depend on the size and separation of the | 137 | fragmentation is likely to depend on the size and separation of the | ||
| 138 | fragments. However, the shape of the function that relates occurrence | 138 | fragments. However, the shape of the function that relates occurrence | ||
| 139 | to these landscape parameters may be affected by other factors that | 139 | to these landscape parameters may be affected by other factors that | ||
| 140 | are less easily measured, in which case relationships with size and | 140 | are less easily measured, in which case relationships with size and | ||
| 141 | separation in one area may predict occurrence elsewhere only poorly. | 141 | separation in one area may predict occurrence elsewhere only poorly. | ||
| 142 | 2. We explored how well the distribution of red squirrels Sciurus | 142 | 2. We explored how well the distribution of red squirrels Sciurus | ||
| 143 | vulgaris in fragmented woodlands was predicted by simple logistic | 143 | vulgaris in fragmented woodlands was predicted by simple logistic | ||
| 144 | regression models empirically derived in other fragmented landscapes. | 144 | regression models empirically derived in other fragmented landscapes. | ||
| 145 | 3. Comparisons between predictions lead us to identify thresholds in | 145 | 3. Comparisons between predictions lead us to identify thresholds in | ||
| 146 | fragment size (> 10 ha) and distance to a source (< 600 m) where the | 146 | fragment size (> 10 ha) and distance to a source (< 600 m) where the | ||
| 147 | probability of squirrel occupancy was at least 0.9 in all landscapes. | 147 | probability of squirrel occupancy was at least 0.9 in all landscapes. | ||
| 148 | These values may reflect squirrel minimum habitat requirements for | 148 | These values may reflect squirrel minimum habitat requirements for | ||
| 149 | home range and dispersal in the worst study area. 4. For fragments < | 149 | home range and dispersal in the worst study area. 4. For fragments < | ||
| 150 | 10 ha (outside shared thresholds), models developed in a landscape | 150 | 10 ha (outside shared thresholds), models developed in a landscape | ||
| 151 | could predict squirrel occupancy elsewhere only in 17% of cases, as | 151 | could predict squirrel occupancy elsewhere only in 17% of cases, as | ||
| 152 | other factors such as demography or habitat quality might become | 152 | other factors such as demography or habitat quality might become | ||
| 153 | relevant in very small and isolated fragments. 5. The predictive | 153 | relevant in very small and isolated fragments. 5. The predictive | ||
| 154 | ability for small fragments also improved when the range of fragment | 154 | ability for small fragments also improved when the range of fragment | ||
| 155 | sizes in the area of observation fell within the range of sizes in the | 155 | sizes in the area of observation fell within the range of sizes in the | ||
| 156 | area where the model was developed. 6. Some models gave correct | 156 | area where the model was developed. 6. Some models gave correct | ||
| 157 | between-year predictions of squirrel distribution in the same | 157 | between-year predictions of squirrel distribution in the same | ||
| 158 | landscape despite noticeable changes in regional squirrel population | 158 | landscape despite noticeable changes in regional squirrel population | ||
| 159 | density. 7. When size and distance thresholds were met, we found that | 159 | density. 7. When size and distance thresholds were met, we found that | ||
| 160 | models could be used successfully elsewhere. In addition, threshold | 160 | models could be used successfully elsewhere. In addition, threshold | ||
| 161 | values indicate how large forest fragments should be and how they | 161 | values indicate how large forest fragments should be and how they | ||
| 162 | should be arranged to favour squirrel occurrence in a landscape.\n | 162 | should be arranged to favour squirrel occurrence in a landscape.\n | ||
| 163 | Palabras clave: Computer model, Habitat fragmentation, Population, | 163 | Palabras clave: Computer model, Habitat fragmentation, Population, | ||
| 164 | Squirrel" | 164 | Squirrel" | ||
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