Latif Quresh S, Ellis Martha M, Saab Victoria A, Mellen-McLean Kim
Rocky Mountain Research Station U.S. Forest Service Bozeman MT USA.
Montana State University Bozeman MT USA.
Ecol Evol. 2017 Dec 20;8(2):1171-1185. doi: 10.1002/ece3.3725. eCollection 2018 Jan.
Sparsely distributed species attract conservation concern, but insufficient information on population trends challenges conservation and funding prioritization. Occupancy-based monitoring is attractive for these species, but appropriate sampling design and inference depend on particulars of the study system. We employed spatially explicit simulations to identify minimum levels of sampling effort for a regional occupancy monitoring study design, using white-headed woodpeckers (), a sparsely distributed, territorial species threatened by habitat decline and degradation, as a case study. We compared the original design with commonly proposed alternatives with varying targets of inference (i.e., species range, space use, or abundance) and spatial extent of sampling. Sampling effort needed to achieve adequate power to observe a long-term population trend (≥80% chance to observe a 2% yearly decline over 20 years) with the previously used study design consisted of annually monitoring ≥120 transects using a single-survey approach or ≥90 transects surveyed twice per year using a repeat-survey approach. Designs that shifted inference toward finer-resolution trends in abundance and extended the spatial extent of sampling by shortening transects, employing a single-survey approach to monitoring, and incorporating a panel design (33% of units surveyed per year) improved power and reduced error in estimating abundance trends. In contrast, efforts to monitor coarse-scale trends in species range or space use with repeat surveys provided extremely limited statistical power. . Sampling resolutions that approximate home range size, spatially extensive sampling, and designs that target inference of abundance trends rather than range dynamics are probably best suited and most feasible for broad-scale occupancy-based monitoring of sparsely distributed territorial animal species.
分布稀疏的物种引发了保护关注，但有关种群趋势的信息不足给保护工作和资金优先分配带来了挑战。基于占有率的监测对这些物种很有吸引力，但合适的抽样设计和推断取决于研究系统的具体情况。我们采用空间明确的模拟方法，以白头啄木鸟（一种因栖息地减少和退化而受到威胁的分布稀疏的领地性物种）为例，确定区域占有率监测研究设计所需的最小抽样工作量水平。我们将原始设计与针对不同推断目标（即物种分布范围、空间利用或丰度）和抽样空间范围的常见替代方案进行了比较。要通过之前使用的研究设计获得足够的统计效力以观察长期种群趋势（在20年内有≥80%的机会观察到每年2%的下降），所需的抽样工作量包括：使用单次调查方法每年监测≥120个样带，或使用重复调查方法每年对≥90个样带进行两次调查。将推断转向更精细分辨率的丰度趋势，并通过缩短样带、采用单次调查监测方法和纳入面板设计（每年调查33%的单元）来扩大抽样的空间范围，这些设计提高了统计效力，并减少了估计丰度趋势时的误差。相比之下，通过重复调查监测物种分布范围或空间利用的粗尺度趋势的努力提供的统计效力极其有限。接近家域大小的抽样分辨率、空间广泛的抽样以及针对丰度趋势而非分布范围动态进行推断的设计，可能最适合且最可行用于对分布稀疏的领地性动物物种进行基于占有率的广泛监测。
