Balluffi-Fry Juliana, Leroux Shawn J, Wiersma Yolanda F, Heckford Travis R, Rizzuto Matteo, Richmond Isabella C, Vander Wal Eric
Department of Biology Memorial University of Newfoundland St. John's NL Canada.
Present address: Department of Biological Sciences University of Alberta Edmonton AB Canada.
Ecol Evol. 2020 Nov 18;10(24):13847-13859. doi: 10.1002/ece3.6975. eCollection 2020 Dec.
Herbivores consider the variation of forage qualities (nutritional content and digestibility) as well as quantities (biomass) when foraging. Such selection patterns may change based on the scale of foraging, particularly in the case of ungulates that forage at many scales.To test selection for quality and quantity in free-ranging herbivores across scales, however, we must first develop landscape-wide quantitative estimates of both forage quantity and quality. Stoichiometric distribution models (StDMs) bring opportunity to address this because they predict the elemental measures and stoichiometry of resources at landscape extents.Here, we use StDMs to predict elemental measures of understory white birch quality (% nitrogen) and quantity (g carbon/m) across two boreal landscapes. We analyzed global positioning system (GPS) collared moose ( = 14) selection for forage quantity and quality at the landscape, home range, and patch extents using both individual and pooled resource selection analyses. We predicted that as the scale of resource selection decreased from the landscape to the patch, selection for white birch quantity would decrease and selection for quality would increase.Counter to our prediction, pooled-models showed selection for our estimates of quantity and quality to be neutral with low explanatory power and no scalar trends. At the individual-level, however, we found evidence for quality and quantity trade-offs, most notably at the home-range scale where resource selection models explain the largest amount of variation in selection. Furthermore, individuals did not follow the same trade-off tactic, with some preferring forage quantity over quality and vice versa.Such individual trade-offs show that moose may be flexible in attaining a limiting nutrient. Our findings suggest that herbivores may respond to forage elemental compositions and quantities, giving tools like StDMs merit toward animal ecology applications. The integration of StDMs and animal movement data represents a promising avenue for progress in the field of zoogeochemistry.
食草动物在觅食时会考虑草料质量（营养成分和消化率）以及数量（生物量）的变化。这种选择模式可能会根据觅食规模而改变，尤其是有蹄类动物在多个规模上觅食的情况。然而，为了测试自由放养的食草动物在不同规模上对质量和数量的选择，我们必须首先对草料数量和质量进行全景观的定量估计。化学计量分布模型（StDMs）为解决这一问题带来了契机，因为它们可以预测景观范围内资源的元素测量值和化学计量。在这里，我们使用StDMs预测两个北方景观中林下白桦质量（氮含量百分比）和数量（克碳/平方米）的元素测量值。我们使用个体和汇总资源选择分析，分析了佩戴全球定位系统（GPS）项圈的驼鹿（n = 14）在景观、家域和斑块尺度上对草料数量和质量的选择。我们预测，随着资源选择规模从景观尺度减小到斑块尺度，对白桦数量的选择会减少，对质量的选择会增加。与我们的预测相反，汇总模型显示，对我们估计的数量和质量的选择是中性的，解释力低且无尺度趋势。然而，在个体层面，我们发现了质量和数量权衡的证据，最明显的是在家域尺度上，资源选择模型解释了选择中最大量的变异。此外，个体并没有遵循相同的权衡策略，有些个体更喜欢草料数量而非质量，反之亦然。这种个体权衡表明，驼鹿在获取限制性营养物质方面可能具有灵活性。我们的研究结果表明，食草动物可能会对草料元素组成和数量做出反应，这使得像StDMs这样的工具在动物生态学应用方面具有价值。StDMs与动物运动数据的整合代表了动物地球化学领域取得进展的一个有前景的途径。
