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| 4 | "alternate_identifier": "DOI: 10.3897/natureconservation.47.72781", | 4 | "alternate_identifier": "DOI: 10.3897/natureconservation.47.72781", | ||
| 5 | "author": "Ferreira, E. M., Valerio, F., Medinas, D., Fernandes, N., | 5 | "author": "Ferreira, E. M., Valerio, F., Medinas, D., Fernandes, N., | ||
| 6 | Craveiro, J., Costa, P., Silva, J.P., Carrapato, C., Mira, A. y | 6 | Craveiro, J., Costa, P., Silva, J.P., Carrapato, C., Mira, A. y | ||
| 7 | Santos, S.M.", | 7 | Santos, S.M.", | ||
| 8 | "author_name": "Ferreira, E. M., Valerio, F., Medinas, D., | 8 | "author_name": "Ferreira, E. M., Valerio, F., Medinas, D., | ||
| 9 | Fernandes, N., Craveiro, J., Costa, P., Silva, J.P., Carrapato, C., | 9 | Fernandes, N., Craveiro, J., Costa, P., Silva, J.P., Carrapato, C., | ||
| 10 | Mira, A. y Santos, S.M.", | 10 | Mira, A. y Santos, S.M.", | ||
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| 34 | "contact_url": "https://organismo.example.org/", | 34 | "contact_url": "https://organismo.example.org/", | ||
| 35 | "created": "2025-05-23", | 35 | "created": "2025-05-23", | ||
| 36 | "creator": [ | 36 | "creator": [ | ||
| 37 | { | 37 | { | ||
| 38 | "name": "Ferreira, E. M., Valerio, F., Medinas, D., Fernandes, | 38 | "name": "Ferreira, E. M., Valerio, F., Medinas, D., Fernandes, | ||
| 39 | N., Craveiro, J., Costa, P., Silva, J.P., Carrapato, C., Mira, A. y | 39 | N., Craveiro, J., Costa, P., Silva, J.P., Carrapato, C., Mira, A. y | ||
| 40 | Santos, S.M." | 40 | Santos, S.M." | ||
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| 44 | "dataset_scope": "non_spatial_dataset", | 44 | "dataset_scope": "non_spatial_dataset", | ||
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| 56 | "license_id": "cc-by", | 56 | "license_id": "cc-by", | ||
| 57 | "license_title": "Creative Commons Attribution", | 57 | "license_title": "Creative Commons Attribution", | ||
| 58 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 58 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
| 59 | "lineage_process_steps": [], | 59 | "lineage_process_steps": [], | ||
| 60 | "lineage_source": [ | 60 | "lineage_source": [ | ||
| 61 | "Nature Conservation. Vol. 47", | 61 | "Nature Conservation. Vol. 47", | ||
| 62 | "pags. 155-175" | 62 | "pags. 155-175" | ||
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| 64 | "maintainer": "", | 64 | "maintainer": "", | ||
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| 66 | "metadata_created": "2026-06-23T14:47:21.875832", | 66 | "metadata_created": "2026-06-23T14:47:21.875832", | ||
| n | 67 | "metadata_modified": "2026-06-23T15:49:20.305492", | n | 67 | "metadata_modified": "2026-06-23T15:55:32.179562", |
| 68 | "metadata_profile": [ | 68 | "metadata_profile": [ | ||
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| 71 | "miteco_data_population": { | 71 | "miteco_data_population": { | ||
| 72 | "es": "" | 72 | "es": "" | ||
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| 74 | "miteco_data_territory": { | 74 | "miteco_data_territory": { | ||
| 75 | "es": "" | 75 | "es": "" | ||
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| 77 | "miteco_dataset_type": | 77 | "miteco_dataset_type": | ||
| 78 | //publications.europa.eu/resource/authority/dataset-type/STATISTICAL", | 78 | //publications.europa.eu/resource/authority/dataset-type/STATISTICAL", | ||
| 79 | "miteco_geo_level": "1", | 79 | "miteco_geo_level": "1", | ||
| 80 | "modified": "2026-06-23", | 80 | "modified": "2026-06-23", | ||
| 81 | "name": "f9fa4e48-1eb2-5493-a387-f31fb7b6dfc7", | 81 | "name": "f9fa4e48-1eb2-5493-a387-f31fb7b6dfc7", | ||
| 82 | "notes": "Anthropogenic infrastructures and land-use changes are | 82 | "notes": "Anthropogenic infrastructures and land-use changes are | ||
| 83 | major threats to animal movements across heterogeneous landscapes. | 83 | major threats to animal movements across heterogeneous landscapes. | ||
| 84 | Yet, the behavioural consequences of such constraints remain poorly | 84 | Yet, the behavioural consequences of such constraints remain poorly | ||
| 85 | understood. We investigated the relationship between the behaviour of | 85 | understood. We investigated the relationship between the behaviour of | ||
| 86 | the Common genet (Genetta genetta) and road proximity, within a | 86 | the Common genet (Genetta genetta) and road proximity, within a | ||
| 87 | dominant mixed forest-agricultural landscape in southern Portugal, | 87 | dominant mixed forest-agricultural landscape in southern Portugal, | ||
| 88 | fragmented by roads. Specifically, we aimed to: (i) identify and | 88 | fragmented by roads. Specifically, we aimed to: (i) identify and | ||
| 89 | characterise the behavioural states displayed by genets and related | 89 | characterise the behavioural states displayed by genets and related | ||
| 90 | movement patterns; and (ii) understand how behavioural states are | 90 | movement patterns; and (ii) understand how behavioural states are | ||
| 91 | influenced by proximity to main paved roads and landscape features. We | 91 | influenced by proximity to main paved roads and landscape features. We | ||
| 92 | used a multivariate Hidden Markov Model (HMM) to characterise the | 92 | used a multivariate Hidden Markov Model (HMM) to characterise the | ||
| 93 | fine-scale movements (10-min fixes GPS) of seven genets tracked during | 93 | fine-scale movements (10-min fixes GPS) of seven genets tracked during | ||
| 94 | 187 nights (mean 27 days per individual) during the period | 94 | 187 nights (mean 27 days per individual) during the period | ||
| 95 | 2016\u20132019, using distance to major paved roads and landscape | 95 | 2016\u20132019, using distance to major paved roads and landscape | ||
| 96 | features as predictors. Our findings indicated that genet\u2019s | 96 | features as predictors. Our findings indicated that genet\u2019s | ||
| 97 | movement patterns were composed of three basic behavioural states, | 97 | movement patterns were composed of three basic behavioural states, | ||
| 98 | classified as \u201cresting\u201d (short step-lengths [mean = 10.6 m] | 98 | classified as \u201cresting\u201d (short step-lengths [mean = 10.6 m] | ||
| 99 | and highly tortuous), \u201cforaging\u201d (intermediate step-lengths | 99 | and highly tortuous), \u201cforaging\u201d (intermediate step-lengths | ||
| 100 | [mean = 46.1 m] and with a wide range in turning angle) and | 100 | [mean = 46.1 m] and with a wide range in turning angle) and | ||
| 101 | \u201ctravelling\u201d (longer step-lengths [mean = 113.7 m] and | 101 | \u201ctravelling\u201d (longer step-lengths [mean = 113.7 m] and | ||
| 102 | mainly linear movements). Within the genet\u2019s main activity-period | 102 | mainly linear movements). Within the genet\u2019s main activity-period | ||
| 103 | (17.00 h-08.00 h), the movement model predicts that genets spend 36.7% | 103 | (17.00 h-08.00 h), the movement model predicts that genets spend 36.7% | ||
| 104 | of their time travelling, 35.4% foraging and 28.0% resting. The | 104 | of their time travelling, 35.4% foraging and 28.0% resting. The | ||
| 105 | probability of genets displaying the travelling state was highest in | 105 | probability of genets displaying the travelling state was highest in | ||
| 106 | areas far away from roads (> 500 m), whereas foraging and resting | 106 | areas far away from roads (> 500 m), whereas foraging and resting | ||
| 107 | states were more likely in areas relatively close to roads (up to 500 | 107 | states were more likely in areas relatively close to roads (up to 500 | ||
| 108 | m). Landscape features also had a pronounced effect on behaviour state | 108 | m). Landscape features also had a pronounced effect on behaviour state | ||
| 109 | occurrence. More specifically, travelling was most likely to occur in | 109 | occurrence. More specifically, travelling was most likely to occur in | ||
| 110 | areas with lower forest edge density and close to riparian habitats, | 110 | areas with lower forest edge density and close to riparian habitats, | ||
| 111 | while foraging was more likely to occur in areas with higher forest | 111 | while foraging was more likely to occur in areas with higher forest | ||
| 112 | edge density and far away from riparian habitats. The results suggest | 112 | edge density and far away from riparian habitats. The results suggest | ||
| 113 | that, although roads represent a behavioural barrier to the movement | 113 | that, although roads represent a behavioural barrier to the movement | ||
| 114 | of genets, they also take advantage of road proximity as foraging | 114 | of genets, they also take advantage of road proximity as foraging | ||
| 115 | areas. Our study demonstrates that the HMM approach is useful for | 115 | areas. Our study demonstrates that the HMM approach is useful for | ||
| 116 | disentangling movement behaviour and understanding how animals respond | 116 | disentangling movement behaviour and understanding how animals respond | ||
| 117 | to roadsides and fragmented habitats. We emphasise that road-engaged | 117 | to roadsides and fragmented habitats. We emphasise that road-engaged | ||
| 118 | stakeholders need to consider movement behaviour of genets when | 118 | stakeholders need to consider movement behaviour of genets when | ||
| 119 | targeting management practices to maximise road permeability for | 119 | targeting management practices to maximise road permeability for | ||
| 120 | wildlife.", | 120 | wildlife.", | ||
| 121 | "notes_translated": { | 121 | "notes_translated": { | ||
| 122 | "en": "Anthropogenic infrastructures and land-use changes are | 122 | "en": "Anthropogenic infrastructures and land-use changes are | ||
| 123 | major threats to animal movements across heterogeneous landscapes. | 123 | major threats to animal movements across heterogeneous landscapes. | ||
| 124 | Yet, the behavioural consequences of such constraints remain poorly | 124 | Yet, the behavioural consequences of such constraints remain poorly | ||
| 125 | understood. We investigated the relationship between the behaviour of | 125 | understood. We investigated the relationship between the behaviour of | ||
| 126 | the Common genet (Genetta\u00a0genetta) and road proximity, within a | 126 | the Common genet (Genetta\u00a0genetta) and road proximity, within a | ||
| 127 | dominant mixed forest-agricultural landscape in southern Portugal, | 127 | dominant mixed forest-agricultural landscape in southern Portugal, | ||
| 128 | fragmented by roads. Specifically, we aimed to: (i) identify and | 128 | fragmented by roads. Specifically, we aimed to: (i) identify and | ||
| 129 | characterise the behavioural states displayed by genets and related | 129 | characterise the behavioural states displayed by genets and related | ||
| 130 | movement patterns; and (ii) understand how behavioural states are | 130 | movement patterns; and (ii) understand how behavioural states are | ||
| 131 | influenced by proximity to main paved roads and landscape features. We | 131 | influenced by proximity to main paved roads and landscape features. We | ||
| 132 | used a multivariate Hidden Markov Model (HMM) to characterise the | 132 | used a multivariate Hidden Markov Model (HMM) to characterise the | ||
| 133 | fine-scale movements (10-min fixes GPS) of seven genets tracked during | 133 | fine-scale movements (10-min fixes GPS) of seven genets tracked during | ||
| 134 | 187 nights (mean 27 days per individual) during the period | 134 | 187 nights (mean 27 days per individual) during the period | ||
| 135 | 2016\u20132019, using distance to major paved roads and landscape | 135 | 2016\u20132019, using distance to major paved roads and landscape | ||
| 136 | features as predictors. Our findings indicated that genet\u2019s | 136 | features as predictors. Our findings indicated that genet\u2019s | ||
| 137 | movement patterns were composed of three basic behavioural states, | 137 | movement patterns were composed of three basic behavioural states, | ||
| 138 | classified as \u201cresting\u201d (short step-lengths [mean = 10.6 m] | 138 | classified as \u201cresting\u201d (short step-lengths [mean = 10.6 m] | ||
| 139 | and highly tortuous), \u201cforaging\u201d (intermediate step-lengths | 139 | and highly tortuous), \u201cforaging\u201d (intermediate step-lengths | ||
| 140 | [mean = 46.1 m] and with a wide range in turning angle) and | 140 | [mean = 46.1 m] and with a wide range in turning angle) and | ||
| 141 | \u201ctravelling\u201d (longer step-lengths [mean = 113.7 m] and | 141 | \u201ctravelling\u201d (longer step-lengths [mean = 113.7 m] and | ||
| 142 | mainly linear movements). Within the genet\u2019s main activity-period | 142 | mainly linear movements). Within the genet\u2019s main activity-period | ||
| 143 | (17.00 h-08.00 h), the movement model predicts that genets spend 36.7% | 143 | (17.00 h-08.00 h), the movement model predicts that genets spend 36.7% | ||
| 144 | of their time travelling, 35.4% foraging and 28.0% resting. The | 144 | of their time travelling, 35.4% foraging and 28.0% resting. The | ||
| 145 | probability of genets displaying the travelling state was highest in | 145 | probability of genets displaying the travelling state was highest in | ||
| 146 | areas far away from roads (> 500 m), whereas foraging and resting | 146 | areas far away from roads (> 500 m), whereas foraging and resting | ||
| 147 | states were more likely in areas relatively close to roads (up to 500 | 147 | states were more likely in areas relatively close to roads (up to 500 | ||
| 148 | m). Landscape features also had a pronounced effect on behaviour state | 148 | m). Landscape features also had a pronounced effect on behaviour state | ||
| 149 | occurrence. More specifically, travelling was most likely to occur in | 149 | occurrence. More specifically, travelling was most likely to occur in | ||
| 150 | areas with lower forest edge density and close to riparian habitats, | 150 | areas with lower forest edge density and close to riparian habitats, | ||
| 151 | while foraging was more likely to occur in areas with higher forest | 151 | while foraging was more likely to occur in areas with higher forest | ||
| 152 | edge density and far away from riparian habitats. The results suggest | 152 | edge density and far away from riparian habitats. The results suggest | ||
| 153 | that, although roads represent a behavioural barrier to the movement | 153 | that, although roads represent a behavioural barrier to the movement | ||
| 154 | of genets, they also take advantage of road proximity as foraging | 154 | of genets, they also take advantage of road proximity as foraging | ||
| 155 | areas. Our study demonstrates that the\u00a0HMM\u00a0approach is | 155 | areas. Our study demonstrates that the\u00a0HMM\u00a0approach is | ||
| 156 | useful for disentangling movement behaviour and understanding how | 156 | useful for disentangling movement behaviour and understanding how | ||
| 157 | animals respond to roadsides and fragmented habitats. We emphasise | 157 | animals respond to roadsides and fragmented habitats. We emphasise | ||
| 158 | that road-engaged stakeholders need to consider movement behaviour of | 158 | that road-engaged stakeholders need to consider movement behaviour of | ||
| 159 | genets when targeting management practices to maximise road | 159 | genets when targeting management practices to maximise road | ||
| 160 | permeability for wildlife.", | 160 | permeability for wildlife.", | ||
| 161 | "es": "Anthropogenic infrastructures and land-use changes are | 161 | "es": "Anthropogenic infrastructures and land-use changes are | ||
| 162 | major threats to animal movements across heterogeneous landscapes. | 162 | major threats to animal movements across heterogeneous landscapes. | ||
| 163 | Yet, the behavioural consequences of such constraints remain poorly | 163 | Yet, the behavioural consequences of such constraints remain poorly | ||
| 164 | understood. We investigated the relationship between the behaviour of | 164 | understood. We investigated the relationship between the behaviour of | ||
| 165 | the Common genet (Genetta genetta) and road proximity, within a | 165 | the Common genet (Genetta genetta) and road proximity, within a | ||
| 166 | dominant mixed forest-agricultural landscape in southern Portugal, | 166 | dominant mixed forest-agricultural landscape in southern Portugal, | ||
| 167 | fragmented by roads. Specifically, we aimed to: (i) identify and | 167 | fragmented by roads. Specifically, we aimed to: (i) identify and | ||
| 168 | characterise the behavioural states displayed by genets and related | 168 | characterise the behavioural states displayed by genets and related | ||
| 169 | movement patterns; and (ii) understand how behavioural states are | 169 | movement patterns; and (ii) understand how behavioural states are | ||
| 170 | influenced by proximity to main paved roads and landscape features. We | 170 | influenced by proximity to main paved roads and landscape features. We | ||
| 171 | used a multivariate Hidden Markov Model (HMM) to characterise the | 171 | used a multivariate Hidden Markov Model (HMM) to characterise the | ||
| 172 | fine-scale movements (10-min fixes GPS) of seven genets tracked during | 172 | fine-scale movements (10-min fixes GPS) of seven genets tracked during | ||
| 173 | 187 nights (mean 27 days per individual) during the period | 173 | 187 nights (mean 27 days per individual) during the period | ||
| 174 | 2016\u20132019, using distance to major paved roads and landscape | 174 | 2016\u20132019, using distance to major paved roads and landscape | ||
| 175 | features as predictors. Our findings indicated that genet\u2019s | 175 | features as predictors. Our findings indicated that genet\u2019s | ||
| 176 | movement patterns were composed of three basic behavioural states, | 176 | movement patterns were composed of three basic behavioural states, | ||
| 177 | classified as \u201cresting\u201d (short step-lengths [mean = 10.6 m] | 177 | classified as \u201cresting\u201d (short step-lengths [mean = 10.6 m] | ||
| 178 | and highly tortuous), \u201cforaging\u201d (intermediate step-lengths | 178 | and highly tortuous), \u201cforaging\u201d (intermediate step-lengths | ||
| 179 | [mean = 46.1 m] and with a wide range in turning angle) and | 179 | [mean = 46.1 m] and with a wide range in turning angle) and | ||
| 180 | \u201ctravelling\u201d (longer step-lengths [mean = 113.7 m] and | 180 | \u201ctravelling\u201d (longer step-lengths [mean = 113.7 m] and | ||
| 181 | mainly linear movements). Within the genet\u2019s main activity-period | 181 | mainly linear movements). Within the genet\u2019s main activity-period | ||
| 182 | (17.00 h-08.00 h), the movement model predicts that genets spend 36.7% | 182 | (17.00 h-08.00 h), the movement model predicts that genets spend 36.7% | ||
| 183 | of their time travelling, 35.4% foraging and 28.0% resting. The | 183 | of their time travelling, 35.4% foraging and 28.0% resting. The | ||
| 184 | probability of genets displaying the travelling state was highest in | 184 | probability of genets displaying the travelling state was highest in | ||
| 185 | areas far away from roads (> 500 m), whereas foraging and resting | 185 | areas far away from roads (> 500 m), whereas foraging and resting | ||
| 186 | states were more likely in areas relatively close to roads (up to 500 | 186 | states were more likely in areas relatively close to roads (up to 500 | ||
| 187 | m). Landscape features also had a pronounced effect on behaviour state | 187 | m). Landscape features also had a pronounced effect on behaviour state | ||
| 188 | occurrence. More specifically, travelling was most likely to occur in | 188 | occurrence. More specifically, travelling was most likely to occur in | ||
| 189 | areas with lower forest edge density and close to riparian habitats, | 189 | areas with lower forest edge density and close to riparian habitats, | ||
| 190 | while foraging was more likely to occur in areas with higher forest | 190 | while foraging was more likely to occur in areas with higher forest | ||
| 191 | edge density and far away from riparian habitats. The results suggest | 191 | edge density and far away from riparian habitats. The results suggest | ||
| 192 | that, although roads represent a behavioural barrier to the movement | 192 | that, although roads represent a behavioural barrier to the movement | ||
| 193 | of genets, they also take advantage of road proximity as foraging | 193 | of genets, they also take advantage of road proximity as foraging | ||
| 194 | areas. Our study demonstrates that the HMM approach is useful for | 194 | areas. Our study demonstrates that the HMM approach is useful for | ||
| 195 | disentangling movement behaviour and understanding how animals respond | 195 | disentangling movement behaviour and understanding how animals respond | ||
| 196 | to roadsides and fragmented habitats. We emphasise that road-engaged | 196 | to roadsides and fragmented habitats. We emphasise that road-engaged | ||
| 197 | stakeholders need to consider movement behaviour of genets when | 197 | stakeholders need to consider movement behaviour of genets when | ||
| 198 | targeting management practices to maximise road permeability for | 198 | targeting management practices to maximise road permeability for | ||
| 199 | wildlife." | 199 | wildlife." | ||
| 200 | }, | 200 | }, | ||
| 201 | "num_resources": 1, | 201 | "num_resources": 1, | ||
| 202 | "num_tags": 2, | 202 | "num_tags": 2, | ||
| 203 | "organization": { | 203 | "organization": { | ||
| 204 | "approval_status": "approved", | 204 | "approval_status": "approved", | ||
| 205 | "created": "2026-06-23T14:36:08.942021", | 205 | "created": "2026-06-23T14:36:08.942021", | ||
| 206 | "description": "", | 206 | "description": "", | ||
| 207 | "id": "bca483f7-26e2-4ed8-99e8-65f5b3c7a26e", | 207 | "id": "bca483f7-26e2-4ed8-99e8-65f5b3c7a26e", | ||
| 208 | "image_url": "", | 208 | "image_url": "", | ||
| 209 | "is_organization": true, | 209 | "is_organization": true, | ||
| 210 | "name": "iepnb", | 210 | "name": "iepnb", | ||
| 211 | "state": "active", | 211 | "state": "active", | ||
| 212 | "title": "", | 212 | "title": "", | ||
| 213 | "type": "organization" | 213 | "type": "organization" | ||
| 214 | }, | 214 | }, | ||
| 215 | "owner_org": "bca483f7-26e2-4ed8-99e8-65f5b3c7a26e", | 215 | "owner_org": "bca483f7-26e2-4ed8-99e8-65f5b3c7a26e", | ||
| 216 | "private": false, | 216 | "private": false, | ||
| 217 | "provenance": { | 217 | "provenance": { | ||
| 218 | "en": "", | 218 | "en": "", | ||
| 219 | "es": "" | 219 | "es": "" | ||
| 220 | }, | 220 | }, | ||
| 221 | "publisher": [ | 221 | "publisher": [ | ||
| 222 | { | 222 | { | ||
| 223 | "email": "buzon-bdatos@miteco.es", | 223 | "email": "buzon-bdatos@miteco.es", | ||
| 224 | "name": "\u00c1rea de Banco de Datos de la Naturaleza. | 224 | "name": "\u00c1rea de Banco de Datos de la Naturaleza. | ||
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