TY - JOUR
T1 - Elephants move faster in small fragments of low productivity in Amboseli ecosystems : Kenya
AU - Gara, T.W.
AU - Wang, Tiejun
AU - Skidmore, A.K.
AU - Ngene, S.M.
AU - Dube, T.
AU - Sibanda, M.
PY - 2017/7/21
Y1 - 2017/7/21
N2 - Understanding factors affecting the behaviour and movement patterns of the African elephant is important for wildlife conservation, especially in increasingly human-dominated savanna landscapes. Currently, knowledge on how landscape fragmentation and vegetation productivity affect elephant speed of movement remains poorly understood. In this study, we tested whether landscape fragmentation and vegetation productivity explains elephant speed of movement in the Amboseli ecosystem in Kenya. We used GPS collar data from five elephants to quantify elephant speed of movement for three seasons (wet, dry and transitional). We then used multiple regression to model the relationship between speed of movement and landscape fragmentation, as well as vegetation productivity for each season. Results of this study demonstrate that landscape fragmentation and vegetation productivity predicted elephant speed of movement poorly (R2 < 0.4) when used as solitary covariates. However, a combination of the covariates significantly (p < 0.05) explained variance in elephant speed of movement with improved R2 values of 0.69, 0.45, 0.47 for wet, transition and dry seasons, respectively.
AB - Understanding factors affecting the behaviour and movement patterns of the African elephant is important for wildlife conservation, especially in increasingly human-dominated savanna landscapes. Currently, knowledge on how landscape fragmentation and vegetation productivity affect elephant speed of movement remains poorly understood. In this study, we tested whether landscape fragmentation and vegetation productivity explains elephant speed of movement in the Amboseli ecosystem in Kenya. We used GPS collar data from five elephants to quantify elephant speed of movement for three seasons (wet, dry and transitional). We then used multiple regression to model the relationship between speed of movement and landscape fragmentation, as well as vegetation productivity for each season. Results of this study demonstrate that landscape fragmentation and vegetation productivity predicted elephant speed of movement poorly (R2 < 0.4) when used as solitary covariates. However, a combination of the covariates significantly (p < 0.05) explained variance in elephant speed of movement with improved R2 values of 0.69, 0.45, 0.47 for wet, transition and dry seasons, respectively.
KW - METIS-317266
KW - ITC-ISI-JOURNAL-ARTICLE
KW - 22/4 OA procedure
UR - https://ezproxy2.utwente.nl/login?url=https://webapps.itc.utwente.nl/library/2017/isi/gara_ele.pdf
UR - https://ezproxy2.utwente.nl/login?url=https://doi.org/10.1080/10106049.2016.1206625
U2 - 10.1080/10106049.2016.1206625
DO - 10.1080/10106049.2016.1206625
M3 - Article
SN - 1010-6049
VL - 32
SP - 1243
EP - 1253
JO - Geocarto international
JF - Geocarto international
IS - 11
ER -