Activity patterns of snow leopards (Panthera uncia) at their kill sites
The snow leopard (Panthera uncia) is an elusive felid, native to the mountains in central Asia. Basic knowledge about the snow leopards’ ecology has long been lacking but is advancing with the help of the GPS-technology. GPS cluster analysis can provide insight in the diet and prey selection of elus...
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| Formato: | H2 |
| Lenguaje: | Inglés sueco |
| Publicado: |
SLU/Dept. of Ecology
2015
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| Materias: |
| _version_ | 1855571296395460608 |
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| author | Nygren, Emma |
| author_browse | Nygren, Emma |
| author_facet | Nygren, Emma |
| author_sort | Nygren, Emma |
| collection | Epsilon Archive for Student Projects |
| description | The snow leopard (Panthera uncia) is an elusive felid, native to the mountains in central Asia. Basic knowledge about the snow leopards’ ecology has long been lacking but is advancing with the help of the GPS-technology. GPS cluster analysis can provide insight in the diet and prey selection of elusive predators, such as the snow leopard. Acceleration data from GPS collars can be used to study animal behavior but the two have never been combined to gain more detailed information of the feeding behavior of large carnivores. In this study reference values for activity loggers were derived by behavioral observations on a captive male snow leopard fitted with a GPS collar. These reference values were used to make interpretations on behaviors of free-ranging snow leopards at their kill sites. In the study a discriminant function analysis was used to (1) test the classification fit of the behaviors from the observed snow leopard with the acceleration data and (2) used the discriminant scores to predict behaviors of GPS-collared snow leopards in the wild using the software R (R 2.12.1 with package MASS). The result showed that behavior explained 83.5% and 94.2% of the variability of the activity data of the observed cat when behaviors where separated into seven and three behavioral categories, respectively. The three behavioral categories were high activity, medium activity and low activity. When predicting behaviors on wild snow leopards at kill sites I found that low activity was the dominating behavior at the kill sites with 85% and 88% for female and male snow leopards, followed by medium activity with 15% and 12%, respectively, and high activity with less than 1% for both sexes. This study suggests that cluster analysis in combination with acceleration data can be a used to get a better understanding of snow leopards behaviors at kill sites. Especially when looking at active and inactive behaviors, however by shortening the time interval for which the activity data is calculated this tool can probably also be used to gain a deeper understanding of the behavior of wild snow leopards. |
| format | H2 |
| id | RepoSLU8109 |
| institution | Swedish University of Agricultural Sciences |
| language | Inglés swe |
| publishDate | 2015 |
| publishDateSort | 2015 |
| publisher | SLU/Dept. of Ecology |
| publisherStr | SLU/Dept. of Ecology |
| record_format | eprints |
| spelling | RepoSLU81092015-07-06T14:29:09Z Activity patterns of snow leopards (Panthera uncia) at their kill sites Nygren, Emma acceleration data behavior GPS-collar Mongolia prey handling The snow leopard (Panthera uncia) is an elusive felid, native to the mountains in central Asia. Basic knowledge about the snow leopards’ ecology has long been lacking but is advancing with the help of the GPS-technology. GPS cluster analysis can provide insight in the diet and prey selection of elusive predators, such as the snow leopard. Acceleration data from GPS collars can be used to study animal behavior but the two have never been combined to gain more detailed information of the feeding behavior of large carnivores. In this study reference values for activity loggers were derived by behavioral observations on a captive male snow leopard fitted with a GPS collar. These reference values were used to make interpretations on behaviors of free-ranging snow leopards at their kill sites. In the study a discriminant function analysis was used to (1) test the classification fit of the behaviors from the observed snow leopard with the acceleration data and (2) used the discriminant scores to predict behaviors of GPS-collared snow leopards in the wild using the software R (R 2.12.1 with package MASS). The result showed that behavior explained 83.5% and 94.2% of the variability of the activity data of the observed cat when behaviors where separated into seven and three behavioral categories, respectively. The three behavioral categories were high activity, medium activity and low activity. When predicting behaviors on wild snow leopards at kill sites I found that low activity was the dominating behavior at the kill sites with 85% and 88% for female and male snow leopards, followed by medium activity with 15% and 12%, respectively, and high activity with less than 1% for both sexes. This study suggests that cluster analysis in combination with acceleration data can be a used to get a better understanding of snow leopards behaviors at kill sites. Especially when looking at active and inactive behaviors, however by shortening the time interval for which the activity data is calculated this tool can probably also be used to gain a deeper understanding of the behavior of wild snow leopards. Högt bland bergen i Centralasien lever snöleoparden (Panthera uncia), ett av världens mest gåtfulla kattdjur. Arten finns i tolv olika länder i Asien och i dagsläget finns mellan 4000-6600 snöleoparder kvar i det vilda. Den är listad som hotad enligt den internationella naturvårdsunionen, IUCN. På grund av att arten lever i så otillgängliga miljöer har grundläggande kunskap om artens ekologi länge saknats. 2008 startade därför organisationerna Snow Leopard Trust, Panthera och Snow Leopard Conservation Fund, en ny långtidsstudie för att öka kunskapen om arten. Tack vare GPS teknologi kan man nu utveckla forskningen hos svårstuderade arter som till exempel snöleoparden. Genom att analysera kluster (ansamling av GPS-positioner som befinner sig inom 100 m från varandra) kan man få en inblick snöleopardens diet och val av bytesdjur. GPS-halsband kan också användas för att studera djurs beteende med hjälp av accelerationsdata, där aktivitet mäts som accelerationen i två axlar (framåt/bakåt och höger/vänster), men accelerationsdata och klusteranalys har aldrig kombinerats för att få fram mer detaljerad information om rovdjurs beteende vid deras kadaver. I denna studie tog jag ta fram referensvärden för accelerationsdata genom att göra beteende- observationer på en snöleopard i fångenskap som försetts men en GPS-halsband. Jag använde sedan dessa referensvärden för att dra slutsatser om hur vilda snöleoparder beter sig vid sina kadaver. I studien använde jag mig av diskriminantfunktionsanalys för att (1) testa hur bra beteenden från den observerade snöleoparden stämde överens med aktivitetsvärdena och (2) använda denna information för att förutsäga beteendet hos märkta snöleoparder vid slagna byten i det vilda. Jag fann att beteendet förklarade 83,5% och 94,2% av variationen i aktivitetsdata för den observerade snöleoparden när beteenden var uppdelade i sju respektive tre separata beteendekategorier. De tre beteendekategorierna var hög aktivitet, medelhög aktivitet och låg aktivitet. När jag använde referensvärdet/ena för att tolka beteenden hos vilda snöleoparder vid deras kadaver fann vi att låg aktivitet var det dominerande beteendet och att beteendet skiljde sig mellan honor och hanar. Denna studie indikerar att klusteranalys i kombination med accelerationsdata kan används för att få en bättre förståelse av snöleopardens beteende vid dess kadaver, speciellt avseende aktiva och inaktiva beteenden. Genom att förkorta tidsintervallet för vilket aktivitetsdata beräknas kan man troligen använda denna teknik för att få en fördjupad förståelse av vilda snöleoparders beteende. SLU/Dept. of Ecology 2015 H2 eng swe https://stud.epsilon.slu.se/8109/ |
| spellingShingle | acceleration data behavior GPS-collar Mongolia prey handling Nygren, Emma Activity patterns of snow leopards (Panthera uncia) at their kill sites |
| title | Activity patterns of snow leopards (Panthera uncia) at their kill sites |
| title_full | Activity patterns of snow leopards (Panthera uncia) at their kill sites |
| title_fullStr | Activity patterns of snow leopards (Panthera uncia) at their kill sites |
| title_full_unstemmed | Activity patterns of snow leopards (Panthera uncia) at their kill sites |
| title_short | Activity patterns of snow leopards (Panthera uncia) at their kill sites |
| title_sort | activity patterns of snow leopards (panthera uncia) at their kill sites |
| topic | acceleration data behavior GPS-collar Mongolia prey handling |