Assessing biological realism of wildlife population estimates in data‐poor systems
Assessing biological realism of wildlife population estimates in data‐poor systems
复制标题
评估数据贫乏系统中野生动物种群估计的生物现实性
DOI：
--
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
L. Rozylowicz
中科院分区：
文献类型：
--
作者：
V. Popescu;K. Artelle;M. Pop;Steluta Manolache;L. Rozylowicz
总结
大型食肉动物的管理往往是有争议的，特别是在狩猎和保护工作发生冲突的司法管辖区。有管制的狩猎是一种常见的管理工具，但相关决定通常是在缺乏可靠的种群数据的情况下作出的，而且是由生物因素以外的因素驱动的。
我们使用欧洲大型食肉动物（棕熊熊，狼和欧亚猞猁猞猁）管理，以评估生物的可接受性报告的人口估计用于狩猎决策。我们使用罗马尼亚作为测试案例，因为该地区不仅数据贫乏，而且公共和私人游戏经理都是狩猎活动收入的受益者。我们评估了以下内容：（i）2005年至2012年期间根据报告的丰度计算的人口增长率与根据欧洲和北美人口经验得出的公布的增长率相比如何;（ii）通过测试报告的估计值是否在生物学上合理的轨迹范围内，生物学上的不现实是否随着时间的推移而加剧;以及（iii）生物学上不切实际的估计与经济激励（狩猎量）之间的关系。
对美国arctos产生了很高的收入，估计的年人口增长率往往高于最高公布的增长率（报告的增长率高达1.5，文献中为1.136）。在32%的情况下，报告的估计值大于最大模拟种群，差异与狩猎呈正相关（rs = 0.576）。
C.人口增长率狼疮超过最大公布的增长率（1·35）的频率较低，报告的估计值在生物学上合理的估计值范围内（91%的病例），狩猎和生物学上不切实际的估计值之间存在弱相关性（rs = 0·182）。
L.从报告的估计中得出的猞猁种群增长率低于最低模拟种群（60%的情况），狩猎和生物学上不切实际的估计之间的相关性很弱（rs = 0.164）。
合成与应用。我们的研究表明，将管理机构使用的人口估计值与通过严格的同行评审研究获得的人口统计数据进行比较，是评估数据贫乏系统中野生动物数据的生物可验证性的一种有用方法，特别是当管理决策可能受到非科学激励的影响时。
Summary
Large carnivore management is often contentious, particularly in jurisdictions where hunting and conservation efforts collide. Regulated hunting is a common management tool, yet relevant decisions are commonly taken in the absence of reliable population data and are driven by factors other than biological considerations.
We used European large carnivore (brown bear Ursus arctos, wolf Canis lupus and Eurasian lynx Lynx lynx) management to evaluate the biological plausibility of reported population estimates used in hunting decisions. We used Romania as a test case as this region is not only data-poor, but the public and private game managers are beneficiaries of revenue from hunting activities. We assessed the following: (i) how population growth rates calculated from reported abundances between 2005 and 2012 compared to published growth rates empirically derived from European and North American populations; (ii) whether biological unrealism compounded through time by testing whether reported estimates fell within the bounds of biologically plausible trajectories; and (iii) the relationship between the occurrence of biologically unrealistic estimates and financial incentives (amount of hunting).
For U. arctos, which generates high revenue, estimated annual population growth rates were frequently greater than maximum published growth rates (up to 1·5 for reported versus 1·136 in the literature). Reported estimates were greater than maximum simulated populations in 32% of cases, and the difference was positively correlated with hunting (rs = 0·576).
Population growth rates for C. lupus overshot the maximum published growth rate (1·35) less frequently, reported estimates were within the bounds of biologically plausible estimates (91% of cases), and there was a weak correlation between hunting and biologically unrealistic estimates (rs = 0·182).
L. lynx population growth rates derived from reported estimates were lower than minimum simulated populations (60% of cases), and there was a weak correlation between hunting and biologically unrealistic estimates (rs = 0·164).
Synthesis and applications. Our study suggests that comparing population estimates used by management agencies to demographic data obtained through rigorous peer-reviewed studies is a useful approach for evaluating the biological plausibility of wildlife data in data-poor systems, especially when management decisions might be influenced by non-scientific incentives.