Linking occupancy surveys with habitat characteristics to estimate abundance and distribution in an endangered cryptic bird

被引:6
作者
Crampton, Lisa H. [1 ,2 ]
Brinck, Kevin W. [3 ]
Pias, Kyle E. [1 ,2 ]
Heindl, Barbara A. P. [1 ,2 ]
Savre, Thomas [2 ]
Diegmann, Julia S. [2 ,4 ]
Paxton, Eben H. [5 ]
机构
[1] Hawaii Div Forestry & Wildlife, Kauai Forest Bird Recovery Project, POB 27, Hanapepe, HI 96716 USA
[2] Univ Hawaii Manoa, Pacific Cooperat Studies Unit, Honolulu, HI 96822 USA
[3] Univ Hawaii, Hawaii Cooperat Studies Unit, Hilo, HI 96720 USA
[4] Diegmann Sci Serv, Ele Ele, HI USA
[5] US Geol Survey, Pacific Isl Ecosyst Res Ctr, Volcano, HI USA
关键词
Endangered species; Hawai'i; Habitat modeling; Occupancy estimates; HIERARCHICAL-MODELS; KAUAI; ECOLOGY; PUAIOHI; HAWAII; ISLAND;
D O I
10.1007/s10531-017-1313-0
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Accurate estimates of the distribution and abundance of endangered species are crucial to determine their status and plan recovery options, but such estimates are often difficult to obtain for species with low detection probabilities or that occur in inaccessible habitats. The Puaiohi (Myadestes palmeri) is a cryptic species endemic to KauaE >> i, Hawai'i, and restricted to high elevation ravines that are largely inaccessible. To improve current population estimates, we developed an approach to model distribution and abundance of Puaiohi across their range by linking occupancy surveys to habitat characteristics, territory density, and landscape attributes. Occupancy per station ranged from 0.17 to 0.82, and was best predicted by the number and vertical extent of cliffs, cliff slope, stream width, and elevation. To link occupancy estimates with abundance, we used territory mapping data to estimate the average number of territories per survey station (0.44 and 0.66 territories per station in low and high occupancy streams, respectively), and the average number of individuals per territory (1.9). We then modeled Puaiohi occupancy as a function of two remote-sensed measures of habitat (stream sinuosity and elevation) to predict occupancy across its entire range. We combined predicted occupancy with estimates of birds per station to produce a global population estimate of 494 (95% CI 414-580) individuals. Our approach is a model for using multiple independent sources of information to accurately track population trends, and we discuss future directions for modeling abundance of this, and other, rare species.
引用
收藏
页码:1525 / 1539
页数:15
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