亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Blakiston’s Fish-owl Bubo blakistoni and logging: Applying resource selection information to endangered species conservation in Russia

濒危物种 栖息地 地理 河岸带 濒危物种 登录中 IUCN红色名录 生态学 觅食 保护区 渔业 栖息地破坏 林业 生物
作者
Jonathan C. Slaght,Sergei G. Surmach
出处
期刊:Bird Conservation International [Cambridge University Press]
卷期号:26 (2): 214-224 被引量:6
标识
DOI:10.1017/s0959270915000076
摘要

Summary Blakiston's Fish-owl Bubo blakistoni is classified as ‘Endangered’ by IUCN; this species is associated with riparian old-growth forests in north-east Asia, a landscape threatened by a variety of impacts (e.g. logging, agricultural development, human settlement). We examined a 20,213 km 2 study area in Primorye, Russia, and assessed the ability of the protected area network to conserve Blakiston's Fish-owls by analysing resource selection of radio-marked individuals. Based on resource selection functions, we predicted that 60–65 Blakiston's fish-owl home ranges could occur within the study area. We found that the protected area network within our study area contained only 19% of optimal Blakiston's fish-owl habitat and contained only eight potential home ranges (five of these within a single protected area—Sikhote-Alin Biosphere Reserve). We also found that 43% of optimal Blakiston's Fish-owl habitat was within current logging leases; lands capable of supporting habitat equivalent to 24 home ranges. The remaining optimal habitat (38%) was on federal land and potentially contained 28–33 Blakiston's Fish-owl home ranges. The current protected area network, by itself, is not sufficient to conserve the species because relatively few home ranges are actually protected. Therefore, outside of protected areas, we recommend protecting specific locations within potential home ranges that likely contain suitable nest and foraging sites, maintaining integrity of riparian areas, modifying road construction methods, and closing old and unused logging roads to reduce anthropogenic disturbance to the owls and the landscape.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
zhangnj发布了新的文献求助10
4秒前
37秒前
zhangnj发布了新的文献求助10
43秒前
43秒前
45秒前
cy0824发布了新的文献求助10
48秒前
Hello应助荷兰香猪采纳,获得10
49秒前
1分钟前
1分钟前
荷兰香猪发布了新的文献求助10
1分钟前
荷兰香猪完成签到,获得积分10
1分钟前
1分钟前
zhangnj完成签到,获得积分10
1分钟前
1分钟前
2分钟前
nowss完成签到,获得积分10
2分钟前
2分钟前
Kao应助普鲁斯特采纳,获得10
2分钟前
3分钟前
3分钟前
3分钟前
CipherSage应助玛琳卡迪马采纳,获得10
3分钟前
搜集达人应助玛琳卡迪马采纳,获得10
3分钟前
Jasper应助玛琳卡迪马采纳,获得10
3分钟前
molihuakai应助玛琳卡迪马采纳,获得10
3分钟前
丘比特应助玛琳卡迪马采纳,获得10
3分钟前
酷波er应助玛琳卡迪马采纳,获得10
3分钟前
情怀应助玛琳卡迪马采纳,获得10
3分钟前
化学把我害惨了完成签到,获得积分10
3分钟前
3分钟前
香蕉觅云应助MeiyanZou采纳,获得10
3分钟前
3分钟前
4分钟前
4分钟前
4分钟前
4分钟前
MeiyanZou发布了新的文献求助10
4分钟前
4分钟前
MeiyanZou完成签到,获得积分10
5分钟前
Kao应助Kevin采纳,获得10
5分钟前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Matrix Methods in Data Mining and Pattern Recognition 510
Social Skills Improvement System-Rating Scales--Chinese Version 500
Dynamische Polarisation von H-1 und B-11 in (CH-3)-3NBH-3 500
CLSI M07 2024 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7247708
求助须知:如何正确求助?哪些是违规求助? 8870700
关于积分的说明 18712113
捐赠科研通 6925926
什么是DOI,文献DOI怎么找? 3197998
关于科研通互助平台的介绍 2373767
邀请新用户注册赠送积分活动 2172861