Activity may not reflect the numbers: an assessment of capture rate and population density of dingoes (Canis familiaris) within landscape-scale cell-fencing.

Most human-carnivore conflicts arise from the impact of predation on livestock. In Australian rangelands, considerable resources are allocated to constructing exclusion fences and implementing control measures to manage dingo populations for sustainable livestock enterprise. Assessing the effectiveness of these measures is crucial for justifying the investment. We used a replicated experimental design to examine the effect of landscape-scale dingo-proof exclusion fences (‘cell-fencing’) on activity and population density of dingoes in the Southern Rangelands of Western Australia. We monitored dingo populations for 22-24 months across six study sites nested within a landscape of about 75,000 km2 and defined ‘fence level’ as the number of dingo-proof fences enclosing each study site. We used camera trap capture rate (number of independent capture events per 100 trap nights) as a metric for dingo activity (including the availability of resources as other potential covariates), estimated dingo density using spatially explicit mark-resight models, and tested the relationship between capture rate and estimated density of dingoes for each study site. Significant variation in both metrics was observed between sites and across time. Fence level and prey occurrence significantly influenced dingo activity. The annual mean dingo density estimate across study sites was below 2 dingoes per 100 km2 (i.e., 0.02 dingoes per km2; the maximum value believed to be compatible with small livestock) at only one study site in the first year, but it was higher across all sites during the second year of monitoring. Dingo activity correlated with estimated dingo density at only two sites, suggesting differences in dingo behaviour and detection across the six study sites. This study provides experimental evidence that camera trap capture rate is not a reliable method for assessing variations in the population size of dingoes. These results have implications for monitoring outcomes of dingo control programs across Australia.多数人兽冲突源于食肉动物捕食家畜所引发的影响。在澳大利亚牧场区域，为保障家畜养殖业的可持续发展，当地投入大量资源用于建造防澳洲野犬隔离围栏（dingo-proof exclusion fences），并实施针对澳洲野犬（dingo）种群的管控措施。评估此类措施的成效，对于论证相关投入的合理性至关重要。 本研究采用重复实验设计，在澳大利亚西部南部牧场范围内，探究景观尺度防澳洲野犬隔离围栏对澳洲野犬活动水平与种群密度的影响，其中该类围栏也被称为“单元格围栏”（cell-fencing）。研究团队在总面积约75000平方千米的研究区域内的6个嵌套样地中，对澳洲野犬种群开展了为期22至24个月的监测，并将“围栏层级”定义为环绕每个研究样地的防澳洲野犬围栏数量。 本研究以红外相机陷阱（camera trap）捕获率，即每100个相机夜的独立捕获事件数，作为澳洲野犬活动水平的衡量指标，同时纳入资源可获得性等潜在协变量；采用空间显性重捕模型（spatially explicit mark-resight models）估算澳洲野犬种群密度，并针对每个研究样地检验捕获率与种群密度估算值之间的相关性。 研究发现，两类指标在不同样地及不同时段均存在显著差异。围栏层级与猎物出现频次对澳洲野犬的活动水平存在显著影响。监测第一年，仅在1个研究样地中，所有样地的年均澳洲野犬种群密度估算值低于每100平方千米2只，即每平方千米0.02只，该数值被认为是与小型家畜养殖兼容的最高种群密度；而在监测第二年，所有样地的种群密度均高于该水平。仅在2个研究样地中，澳洲野犬的活动水平与种群密度估算值存在相关性，这表明6个研究样地间的澳洲野犬行为模式与相机检测率存在差异。 本研究通过实验证实，红外相机陷阱捕获率并非评估澳洲野犬种群规模变化的可靠方法。上述研究结果对澳大利亚全境澳洲野犬管控项目的监测工作具有重要参考意义。