Occupancy in dynamic systems: accounting for multiple scales and false positives using environmental DNA to inform monitoring

Occupancy is an important metric to understand current and future trends in populations that have declined globally. In addition, occupancy can be an efficient tool for conducting landscape-scale and long-term monitoring. A challenge for occupancy monitoring programs is to determine the appropriate spatial scale of analysis and to obtain precise occupancy estimates for elusive species. We used a multi-scale occupancy model to assess occupancy of Columbia spotted frogs in the Great Basin, USA, based on environmental DNA (eDNA) detections. We collected three replicate eDNA samples at 220 sites across the Great Basin. We estimated and modeled ecological factors that described watershed and site occupancy at multiple spatial scales simultaneously while accounting for imperfect detection. Additionally, we conducted visual and dipnet surveys at all sites and used our paired detections to estimate the probability of a false positive detection for our eDNA sampling. We applied the estimated false positive rate to our multi-scale occupancy dataset and assessed changes in model selection. We had higher naïve occupancy estimates for eDNA (0.37) than for traditional survey methods (0.20). We estimated our false positive detection rate per qPCR replicate at 0.023 (95% CI: 0.016-0.033). When the false positive rate was applied to the multi-scale dataset, we did not observe substantial changes in model selection or parameter estimates. Conservation and resource managers have an increasing need to understand species occupancy in highly variable landscapes where the spatial distribution of habitat changes significantly over time due to climate change and human impact. A multi-scale occupancy approach can be used to obtain regional occupancy estimates that can account for spatially dynamic differences in availability over time, especially when assessing potential declines. Additionally, this study demonstrates how eDNA can be used as an effective tool for improved occupancy estimates across broad geographic scales for long-term monitoring.

物种占据率是了解全球衰退种群当前与未来趋势的重要指标。此外，占据率可作为开展景观尺度长期监测的高效工具。物种占据率监测项目面临的一大挑战，是确定合适的分析空间尺度，并为隐秘物种获取精准的占据率估算值。本研究基于环境DNA（environmental DNA, eDNA）检测结果，使用多尺度占据率模型对美国大盆地地区的哥伦比亚斑点蛙占据率进行评估。我们在大盆地全境220个采样点采集了三份平行eDNA样本，同时在多个空间尺度上对描述流域与点位占据率的生态因子进行估算与建模，并纳入了不完全检测的影响。此外，我们在所有采样点开展了目视调查与扫网调查，并利用配对检测结果估算了eDNA采样的假阳性检测概率。我们将估算得到的假阳性率应用于多尺度占据率数据集，并评估了模型选择的变化情况。eDNA的朴素占据率估算值（0.37）高于传统调查方法的估算值（0.20）。我们估算得到每一次实时定量PCR（quantitative Polymerase Chain Reaction, qPCR）重复的假阳性检测率为0.023（95%置信区间：0.016~0.033）。当假阳性率被应用于多尺度数据集时，我们未观察到模型选择或参数估算出现显著变化。自然资源与保育管理者愈发需要了解高度动态景观中的物种占据率——这类景观的栖息地空间分布会因气候变化与人类活动随时间发生显著变化。多尺度占据率分析方法可用于获取区域占据率估算值，该方法能够纳入随时间变化的栖息地可获得性空间动态差异，尤其适用于评估物种潜在衰退情况。此外，本研究证实了eDNA可作为高效工具，在大地理尺度下优化长期监测的占据率估算结果。

搜集汇总

背景与挑战

背景概述

该数据集基于环境DNA（eDNA）技术，研究美国大盆地地区哥伦比亚斑点蛙的物种占据度，采用多尺度占据度模型同时分析流域和站点尺度的生态因素，并量化了eDNA检测的假阳性率。数据集支持了eDNA在广域长期监测中的有效性，为动态景观下的物种保护提供了方法学参考。