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En el instante 23 de junio de 2026, 16:06:26 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 Are largescale citizen science data precise enough to determine roadkill patterns?
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| 82 | "notes": "Roads are one of the most transforming linear | 82 | "notes": "Roads are one of the most transforming linear | ||
| 83 | infrastructures in human-dominated landscapes, with animal road-kills | 83 | infrastructures in human-dominated landscapes, with animal road-kills | ||
| 84 | as their most studied impact. Therefore, there is the need to gather | 84 | as their most studied impact. Therefore, there is the need to gather | ||
| 85 | road-kill data and in this sense, citizen science is gaining | 85 | road-kill data and in this sense, citizen science is gaining | ||
| 86 | popularity as an easy and cheap source of data collection that allows | 86 | popularity as an easy and cheap source of data collection that allows | ||
| 87 | large scale studies that may otherwise be unattainable. However, | 87 | large scale studies that may otherwise be unattainable. However, | ||
| 88 | citizen science projects that focus on road-kills tends to be | 88 | citizen science projects that focus on road-kills tends to be | ||
| 89 | geographically localised, therefore, there is a debate about whether | 89 | geographically localised, therefore, there is a debate about whether | ||
| 90 | large-scale data collected by citizen scientists can identify spatial | 90 | large-scale data collected by citizen scientists can identify spatial | ||
| 91 | and temporal road-kill patterns, and thus, be used as a reliable | 91 | and temporal road-kill patterns, and thus, be used as a reliable | ||
| 92 | conservation tool. We aim to assess whether citizen science data | 92 | conservation tool. We aim to assess whether citizen science data | ||
| 93 | contained in the Spanish Atlas of Terrestrial Mammals (henceforth | 93 | contained in the Spanish Atlas of Terrestrial Mammals (henceforth | ||
| 94 | \u201cAtlas\u201d), can be as valuable and accurate as road-kill | 94 | \u201cAtlas\u201d), can be as valuable and accurate as road-kill | ||
| 95 | surveys undertaken by experts in detecting road-kill hotspots and | 95 | surveys undertaken by experts in detecting road-kill hotspots and | ||
| 96 | establishing road-kill rates for different species of carnivores. | 96 | establishing road-kill rates for different species of carnivores. | ||
| 97 | Using Linear Models, we compared species-richness, diversity and | 97 | Using Linear Models, we compared species-richness, diversity and | ||
| 98 | abundance of road-killed carnivores between Atlas data and our own | 98 | abundance of road-killed carnivores between Atlas data and our own | ||
| 99 | road-kill survey database. We also compared (per species) the observed | 99 | road-kill survey database. We also compared (per species) the observed | ||
| 100 | road-kills in our road survey with the expected road-kills based on | 100 | road-kills in our road survey with the expected road-kills based on | ||
| 101 | the species abundance from the Atlas. In our Linear Models we did not | 101 | the species abundance from the Atlas. In our Linear Models we did not | ||
| 102 | find a significant relation between the road-kill data and the Atlas | 102 | find a significant relation between the road-kill data and the Atlas | ||
| 103 | data. This suggests that data from the Atlas are unsuitable to | 103 | data. This suggests that data from the Atlas are unsuitable to | ||
| 104 | determine road-kills patterns in our study area. This could be due to | 104 | determine road-kills patterns in our study area. This could be due to | ||
| 105 | the lack of control over the sampling effort in the Atlas data, and | 105 | the lack of control over the sampling effort in the Atlas data, and | ||
| 106 | the fact that the Atlas has a sampling scope that is not fitted for | 106 | the fact that the Atlas has a sampling scope that is not fitted for | ||
| 107 | road mortality studies. When we compared observed road-kills (per | 107 | road mortality studies. When we compared observed road-kills (per | ||
| 108 | species) with those expected based on Atlas abundance, we found that | 108 | species) with those expected based on Atlas abundance, we found that | ||
| 109 | some species are road-killed more (or less) than expected. This may be | 109 | some species are road-killed more (or less) than expected. This may be | ||
| 110 | due to ecological or behavioural traits that make some species more | 110 | due to ecological or behavioural traits that make some species more | ||
| 111 | (or less) prone to be road-killed. To summarize, our findings suggest | 111 | (or less) prone to be road-killed. To summarize, our findings suggest | ||
| 112 | that occurrence in Atlas data does not mirror road-kill patterns, | 112 | that occurrence in Atlas data does not mirror road-kill patterns, | ||
| 113 | likely due to both several biases in Atlas data and to | 113 | likely due to both several biases in Atlas data and to | ||
| 114 | species-specific responses to roads. Thus, to study road-kill rates | 114 | species-specific responses to roads. Thus, to study road-kill rates | ||
| 115 | and patterns, we suggest the use classical road-kill surveys, unless | 115 | and patterns, we suggest the use classical road-kill surveys, unless | ||
| 116 | correcting approaches to citizen science datasets are applied. This is | 116 | correcting approaches to citizen science datasets are applied. This is | ||
| 117 | especially important when the study aims to determine species\u2019 | 117 | especially important when the study aims to determine species\u2019 | ||
| 118 | specific road-kill patterns.", | 118 | specific road-kill patterns.", | ||
| 119 | "notes_translated": { | 119 | "notes_translated": { | ||
| 120 | "en": "Roads are one of the most transforming linear | 120 | "en": "Roads are one of the most transforming linear | ||
| 121 | infrastructures in human-dominated landscapes, with animal road-kills | 121 | infrastructures in human-dominated landscapes, with animal road-kills | ||
| 122 | as their most studied impact. Therefore, there is the need to gather | 122 | as their most studied impact. Therefore, there is the need to gather | ||
| 123 | road-kill data and in this sense, citizen science is gaining | 123 | road-kill data and in this sense, citizen science is gaining | ||
| 124 | popularity as an easy and cheap source of data collection that allows | 124 | popularity as an easy and cheap source of data collection that allows | ||
| 125 | large scale studies that may otherwise be unattainable. However, | 125 | large scale studies that may otherwise be unattainable. However, | ||
| 126 | citizen science projects that focus on road-kills tends to be | 126 | citizen science projects that focus on road-kills tends to be | ||
| 127 | geographically localised, therefore, there is a debate about whether | 127 | geographically localised, therefore, there is a debate about whether | ||
| 128 | large-scale data collected by citizen scientists can identify spatial | 128 | large-scale data collected by citizen scientists can identify spatial | ||
| 129 | and temporal road-kill patterns, and thus, be used as a reliable | 129 | and temporal road-kill patterns, and thus, be used as a reliable | ||
| 130 | conservation tool. We aim to assess whether citizen science data | 130 | conservation tool. We aim to assess whether citizen science data | ||
| 131 | contained in the Spanish Atlas of Terrestrial Mammals (henceforth | 131 | contained in the Spanish Atlas of Terrestrial Mammals (henceforth | ||
| 132 | \u201cAtlas\u201d), can be as valuable and accurate as road-kill | 132 | \u201cAtlas\u201d), can be as valuable and accurate as road-kill | ||
| 133 | surveys undertaken by experts in detecting road-kill hotspots and | 133 | surveys undertaken by experts in detecting road-kill hotspots and | ||
| 134 | establishing road-kill rates for different species of carnivores. | 134 | establishing road-kill rates for different species of carnivores. | ||
| 135 | Using Linear Models, we compared species-richness, diversity and | 135 | Using Linear Models, we compared species-richness, diversity and | ||
| 136 | abundance of road-killed carnivores between Atlas data and our own | 136 | abundance of road-killed carnivores between Atlas data and our own | ||
| 137 | road-kill survey database. We also compared (per species) the observed | 137 | road-kill survey database. We also compared (per species) the observed | ||
| 138 | road-kills in our road survey with the expected road-kills based on | 138 | road-kills in our road survey with the expected road-kills based on | ||
| 139 | the species abundance from the Atlas. In our Linear Models we did not | 139 | the species abundance from the Atlas. In our Linear Models we did not | ||
| 140 | find a significant relation between the road-kill data and the Atlas | 140 | find a significant relation between the road-kill data and the Atlas | ||
| 141 | data. This suggests that data from the Atlas are unsuitable to | 141 | data. This suggests that data from the Atlas are unsuitable to | ||
| 142 | determine road-kills patterns in our study area. This could be due to | 142 | determine road-kills patterns in our study area. This could be due to | ||
| 143 | the lack of control over the sampling effort in the Atlas data, and | 143 | the lack of control over the sampling effort in the Atlas data, and | ||
| 144 | the fact that the Atlas has a sampling scope that\nis not fitted for | 144 | the fact that the Atlas has a sampling scope that\nis not fitted for | ||
| 145 | road mortality studies. When we compared observed road-kills (per | 145 | road mortality studies. When we compared observed road-kills (per | ||
| 146 | species) with those expected based on Atlas abundance, we found that | 146 | species) with those expected based on Atlas abundance, we found that | ||
| 147 | some species are road-killed more (or less) than expected. This may be | 147 | some species are road-killed more (or less) than expected. This may be | ||
| 148 | due to ecological or behavioural traits that make some species more | 148 | due to ecological or behavioural traits that make some species more | ||
| 149 | (or less) prone to be road-killed. To summarize, our findings suggest | 149 | (or less) prone to be road-killed. To summarize, our findings suggest | ||
| 150 | that occurrence in Atlas data does not mirror road-kill patterns, | 150 | that occurrence in Atlas data does not mirror road-kill patterns, | ||
| 151 | likely due to both several biases in Atlas data and to | 151 | likely due to both several biases in Atlas data and to | ||
| 152 | species-specific responses to roads. Thus, to study road-kill rates | 152 | species-specific responses to roads. Thus, to study road-kill rates | ||
| 153 | and patterns, we suggest the use classical road-kill surveys, unless | 153 | and patterns, we suggest the use classical road-kill surveys, unless | ||
| 154 | correcting approaches to citizen science datasets are applied. This is | 154 | correcting approaches to citizen science datasets are applied. This is | ||
| 155 | especially important when the study aims to determine species\u2019 | 155 | especially important when the study aims to determine species\u2019 | ||
| 156 | specific road-kill patterns.", | 156 | specific road-kill patterns.", | ||
| 157 | "es": "Roads are one of the most transforming linear | 157 | "es": "Roads are one of the most transforming linear | ||
| 158 | infrastructures in human-dominated landscapes, with animal road-kills | 158 | infrastructures in human-dominated landscapes, with animal road-kills | ||
| 159 | as their most studied impact. Therefore, there is the need to gather | 159 | as their most studied impact. Therefore, there is the need to gather | ||
| 160 | road-kill data and in this sense, citizen science is gaining | 160 | road-kill data and in this sense, citizen science is gaining | ||
| 161 | popularity as an easy and cheap source of data collection that allows | 161 | popularity as an easy and cheap source of data collection that allows | ||
| 162 | large scale studies that may otherwise be unattainable. However, | 162 | large scale studies that may otherwise be unattainable. However, | ||
| 163 | citizen science projects that focus on road-kills tends to be | 163 | citizen science projects that focus on road-kills tends to be | ||
| 164 | geographically localised, therefore, there is a debate about whether | 164 | geographically localised, therefore, there is a debate about whether | ||
| 165 | large-scale data collected by citizen scientists can identify spatial | 165 | large-scale data collected by citizen scientists can identify spatial | ||
| 166 | and temporal road-kill patterns, and thus, be used as a reliable | 166 | and temporal road-kill patterns, and thus, be used as a reliable | ||
| 167 | conservation tool. We aim to assess whether citizen science data | 167 | conservation tool. We aim to assess whether citizen science data | ||
| 168 | contained in the Spanish Atlas of Terrestrial Mammals (henceforth | 168 | contained in the Spanish Atlas of Terrestrial Mammals (henceforth | ||
| 169 | \u201cAtlas\u201d), can be as valuable and accurate as road-kill | 169 | \u201cAtlas\u201d), can be as valuable and accurate as road-kill | ||
| 170 | surveys undertaken by experts in detecting road-kill hotspots and | 170 | surveys undertaken by experts in detecting road-kill hotspots and | ||
| 171 | establishing road-kill rates for different species of carnivores. | 171 | establishing road-kill rates for different species of carnivores. | ||
| 172 | Using Linear Models, we compared species-richness, diversity and | 172 | Using Linear Models, we compared species-richness, diversity and | ||
| 173 | abundance of road-killed carnivores between Atlas data and our own | 173 | abundance of road-killed carnivores between Atlas data and our own | ||
| 174 | road-kill survey database. We also compared (per species) the observed | 174 | road-kill survey database. We also compared (per species) the observed | ||
| 175 | road-kills in our road survey with the expected road-kills based on | 175 | road-kills in our road survey with the expected road-kills based on | ||
| 176 | the species abundance from the Atlas. In our Linear Models we did not | 176 | the species abundance from the Atlas. In our Linear Models we did not | ||
| 177 | find a significant relation between the road-kill data and the Atlas | 177 | find a significant relation between the road-kill data and the Atlas | ||
| 178 | data. This suggests that data from the Atlas are unsuitable to | 178 | data. This suggests that data from the Atlas are unsuitable to | ||
| 179 | determine road-kills patterns in our study area. This could be due to | 179 | determine road-kills patterns in our study area. This could be due to | ||
| 180 | the lack of control over the sampling effort in the Atlas data, and | 180 | the lack of control over the sampling effort in the Atlas data, and | ||
| 181 | the fact that the Atlas has a sampling scope that is not fitted for | 181 | the fact that the Atlas has a sampling scope that is not fitted for | ||
| 182 | road mortality studies. When we compared observed road-kills (per | 182 | road mortality studies. When we compared observed road-kills (per | ||
| 183 | species) with those expected based on Atlas abundance, we found that | 183 | species) with those expected based on Atlas abundance, we found that | ||
| 184 | some species are road-killed more (or less) than expected. This may be | 184 | some species are road-killed more (or less) than expected. This may be | ||
| 185 | due to ecological or behavioural traits that make some species more | 185 | due to ecological or behavioural traits that make some species more | ||
| 186 | (or less) prone to be road-killed. To summarize, our findings suggest | 186 | (or less) prone to be road-killed. To summarize, our findings suggest | ||
| 187 | that occurrence in Atlas data does not mirror road-kill patterns, | 187 | that occurrence in Atlas data does not mirror road-kill patterns, | ||
| 188 | likely due to both several biases in Atlas data and to | 188 | likely due to both several biases in Atlas data and to | ||
| 189 | species-specific responses to roads. Thus, to study road-kill rates | 189 | species-specific responses to roads. Thus, to study road-kill rates | ||
| 190 | and patterns, we suggest the use classical road-kill surveys, unless | 190 | and patterns, we suggest the use classical road-kill surveys, unless | ||
| 191 | correcting approaches to citizen science datasets are applied. This is | 191 | correcting approaches to citizen science datasets are applied. This is | ||
| 192 | especially important when the study aims to determine species\u2019 | 192 | especially important when the study aims to determine species\u2019 | ||
| 193 | specific road-kill patterns." | 193 | specific road-kill patterns." | ||
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