Understanding the impacts of temporal variability on estimates of landscape connectivity

被引:4
|
作者
Simpkins, Craig E. [1 ,2 ]
Perry, George L. W. [2 ]
机构
[1] Univ Auckland, Sch Biol Sci, Private Bag 92019, Auckland, New Zealand
[2] Univ Auckland, Sch Environm, Private Bag 92019, Auckland, New Zealand
关键词
Climate change; Land-cover change; Least-cost path; Seasonal; Simulation experiment; Virtual ecology; DYNAMIC LANDSCAPES; METAPOPULATION PERSISTENCE; CIRCUIT-THEORY; GENE FLOW; HABITAT; RESISTANCE; DISPERSAL; CLIMATE; SCALES; CONSERVATION;
D O I
10.1016/j.ecolind.2017.08.008
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Landscape connectivity estimates are widely used to inform species conservation management. However, although many landscapes and species behaviours change over time, such as between seasons, the vast majority of studies view connectivity as static. Calls have therefore been made to use multiple connectivity estimates to adequately capture periodic (e.g., seasonal) temporal changes. These periodic temporal changes are also influenced by stochastic perturbations, such as extreme weather events, and this variability is likely to increase due to ongoing climate change. We aimed to investigate: 1) how variability interacts with periodic landscape changes to alter connectivity estimates, and 2) how these alterations change over longer time-periods. To achieve this we used a virtual ecology approach in which we simulated 100 landscapes. Each simulation ran for 20 seasons with the landscape experiencing regular seasonal changes. Each simulation was then rerun five times with increasing levels of variability super-imposed on the seasonal dynamics. Connectivity for each landscape and every season was calculated using least-cost paths modelling, and the differences between connectivity estimates calculated. We found that the variation in connectivity estimates between seasons increased with temporal variability. Differences in connectivity accumulated over time, meaning that as the variability increased connectivity estimates changed more quickly and by larger amounts. Our study demonstrates that increasing temporal variability will become a challenge for the successful use of static connectivity estimates.
引用
收藏
页码:243 / 248
页数:6
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