Data from: Isolated trees support lower bird taxonomic richness than trees within habitat patches but similar functional diversity

We conducted this study in forests and pastures located in a countryside of Rio de Janeiro state, Brazil (within and adjacent to the Reserva Ecológica de Guapiaçu; 22°24’S, 42°44’W). We carefully selected trees for sampling, controlling possible confounding factors. To control for potential differences in the attractiveness of different tree species to birds, we focused on a single tree species, American muskwood (G. guidonia), which is the dominant isolated tree in the study area (A. D. Azevedo, unpublished data) and common throughout the Atlantic Forest (Cartes, 2003; Lima et al., 2009). We measured and georeferenced 102 G. guidonia trees within the study landscape and selected 20 isolated trees and 10 edge trees based on a careful systematic procedure. First, we selected trees that were at least 200 m apart, to prevent double counting of birds and to maximize the independence of sampling units (trees). Second, we selected trees spanning a broad range of sizes (i.e. circumference at breast height). Third, isolated trees varied in the number of surrounding isolated trees (from all species) and in the amount of surrounding forest cover, thus covering the range of conditions present within our study landscape. Edge trees were located at the edge of a large continuous forest area of ~ 100,000-ha. Thus, the edge trees served as a reference to determine the potential pool of bird species present at the edges of continuous forest that might use the sampled isolated trees. Fruit density of all isolated and edge, i.e., the volume of the canopy with fruits estimated by counting and attributing a score from 0 to 5. We sampled birds from September to December 2016, which corresponded to the period of greatest reproductive activity (Sick, 1997). Based on a pilot study conducted in September 2015 and information in the literature (Fischer and Lindenmayer, 2002a, b; DeMars, Rosenberg & Fontaine, 2010), we determined 20 minutes to be the appropriate period for sampling. During each 20-min sampling event, an observer stood at 5 m from a sampled tree (ideal distance for bird identification) and recorded all birds that landed at the tree. Surveys were conducted between 5:00 and 11:00 a.m. and only during fine weather, with the same amount of effort employed for all trees. All trees were sampled in each of the four months of the study at all survey hours, summing to 11 sampling events of 20 min each (220 min in total for each tree). To quantify functional diversity, we selected bird traits related to habitat requirements (open area, generalist, or forest; Stotz, 1996; del Hoyo et al., 2020), diet (carnivore, frugivore, nectarivore, granivore, insectivore, saprophage, or omnivore; Wilman et al., 2014), foraging strata (terrestrial, understory, midstory, superior, or generalized; Stotz 1996, Wilman et al., 2014) and body mass (small – individuals smaller than the median, i.e. 24.75 g, and large – individuals larger than the median; Dunning, 2007), which are related to both the response of species to environmental change and their effects on ecosystem function (Luck et al., 2012). Therefore, we compiled data for a total of four traits containing 16 categories. The traits classification was based on available information in the literature (e.g. Stotz, 1996; Dunning, 2007; Wilman et al., 2014; del Hoyo et al., 2020).

本研究于巴西里约热内卢州乡村区域的森林与牧场内开展，涵盖瓜皮亚苏生态保护区（Reserva Ecológica de Guapiaçu）及其周边区域，地理坐标为南纬22°24′、西经42°44′。
研究严格筛选采样林木以控制潜在混杂因素。为控制不同树种对鸟类的吸引力差异，本研究仅选取单一树种——美果木（American muskwood，G. guidonia），该树种为研究区域内优势孤立林木（A. D. 阿泽维多，未发表数据），且在大西洋森林（Atlantic Forest）中广泛分布（Cartes, 2003；Lima等, 2009）。我们对研究区域内的102株G. guidonia林木进行了测量与地理坐标标定，并通过严谨的系统流程筛选出20株孤立林木与10株林缘林木：其一，林木间间距至少200米，以避免鸟类重复计数并最大化采样单元（林木）的独立性；其二，选取的林木涵盖广泛的胸高围长范围；其三，孤立林木的周边所有物种的孤立林木数量及周边森林覆盖度各不相同，以此覆盖研究区域内的全部生境条件。林缘林木位于一片约10万公顷的大型连续森林的边缘，可作为参照用以明确可能利用采样孤立林木的连续森林边缘鸟类物种潜在库。所有孤立林木与林缘林木的果实密度通过计数并赋予0至5分的评分，以估算带果冠层体积。
我们于2016年9月至12月开展鸟类采样，该时段对应鸟类繁殖活动最为旺盛的时期（Sick, 1997）。基于2015年9月的预实验结果与文献资料（Fischer与Lindenmayer, 2002a、b；DeMars、Rosenberg与Fontaine, 2010），我们确定20分钟为合适的采样时长。每次20分钟的采样过程中，观测者站在距采样林木5米处（鸟类识别的理想距离），记录所有停落于该林木的鸟类。观测于每日5:00至11:00间开展，且仅在晴朗天气进行，所有林木的采样工作量保持一致。本研究的4个月中，所有林木均在各观测时段完成采样，总计每株林木开展11次20分钟采样（单株总采样时长为220分钟）。
为量化功能多样性，我们选取了与鸟类栖息地需求（开阔生境、广适性或森林生境；Stotz, 1996；del Hoyo等, 2020）、食性（食肉动物、食果动物、食蜜动物、食谷动物、食虫动物、食腐动物或杂食动物；Wilman等, 2014）、觅食层（地面层、下层、中层、上层或广适层；Stotz, 1996；Wilman等, 2014）以及体重（小型——体重低于中位数24.75克，大型——体重高于中位数；Dunning, 2007）相关的性状，上述性状既关联物种对环境变化的响应，也影响其生态系统功能（Luck等, 2012）。综上，我们共整理了涵盖16个类别的4类性状数据，性状分类依据已发表的文献资料（如Stotz, 1996；Dunning, 2007；Wilman等, 2014；del Hoyo等, 2020）。