Keim Jonah L, DeWitt Philip D, Fitzpatrick J Jeremy, Jenni Noemie S
Matrix Solutions Inc. Edmonton AB Canada.
Matrix Solutions Inc.Edmonton AB Canada; Ontario Ministry of Natural Resources & Forestry Science and Research Branch Peterborough ON Canada.
Ecol Evol. 2016 Dec 20;7(2):486-493. doi: 10.1002/ece3.2625. eCollection 2017 Jan.
Quantifying abundance and distribution of plant species can be difficult because data are often inflated with zero values due to rarity or absence from many ecosystems. Terrestrial fruticose lichens ( spp.) occupy a narrow ecological niche and have been linked to the diets of declining caribou and reindeer populations () across their global distribution, and conditions related to their abundance and distribution are not well understood. We attempted to measure effects related to the occupancy and abundance of terrestrial fruticose lichens by sampling and simultaneously modeling two discrete conditions: absence and abundance. We sampled the proportion cover of terrestrial lichens at 438 vegetation plots, including 98 plots having zero lichens. A zero-inflated beta regression model was employed to simultaneously estimate both the absence and the proportion cover of terrestrial fruticose lichens using fine resolution satellite imagery and light detection and ranging (LiDAR) derived covariates. The probability of lichen absence significantly increased with shallower groundwater, taller vegetation, and increased moss cover. Vegetation productivity, moss cover, and seasonal changes in photosynthetic capacity were negatively related to the abundances of terrestrial lichens. Inflated beta regression reliably estimated the abundance of terrestrial lichens ( = .74) which was interpolated on a map at fine resolution across a caribou range to support ecological conservation and reclamation. Results demonstrate that sampling for and simultaneously estimating both occupancy and abundance offer a powerful approach to improve statistical estimation and expand ecological inference in an applied setting. Learnings are broadly applicable to studying species that are rare, occupy narrow niches, or where the response variable is a proportion value containing zero or one, which is typical of vegetation cover data.
量化植物物种的丰度和分布可能很困难，因为由于许多生态系统中物种稀少或不存在，数据往往会被零值夸大。陆生灌丛地衣（物种）占据着狭窄的生态位，并且在其全球分布范围内，它们与数量不断减少的北美驯鹿和驯鹿种群（）的饮食有关，而与它们的丰度和分布相关的条件尚未得到很好的理解。我们试图通过对两种离散情况进行采样并同时建模来测量与陆生灌丛地衣的占据和丰度相关的影响：不存在和存在。我们在438个植被样地中对陆生 lichens 的覆盖比例进行了采样，其中包括98个 lichens 为零的样地。使用零膨胀贝塔回归模型，利用高分辨率卫星图像和光探测与测距（LiDAR）衍生的协变量，同时估计陆生灌丛地衣的不存在情况和覆盖比例。地衣不存在的概率随着地下水变浅、植被变高和苔藓覆盖增加而显著增加。植被生产力、苔藓覆盖和光合能力的季节变化与陆生 lichens 的丰度呈负相关。膨胀贝塔回归可靠地估计了陆生 lichens 的丰度（=0.74），并在北美驯鹿分布范围内的高分辨率地图上进行了插值，以支持生态保护和开垦。结果表明，对占据和丰度进行采样并同时估计，为在实际应用中改进统计估计和扩展生态推断提供了一种有力的方法。这些经验广泛适用于研究稀有物种、占据狭窄生态位的物种，或者响应变量为包含零或一的比例值的情况，这在植被覆盖数据中很常见。
