Data from: Potential trajectories of old-growth Neotropical forest functional composition under climate change

Quantifying relationships between plant functional traits and abiotic gradients is valuable for evaluating potential responses of forest communities to climate change. However, the trajectories of change expected to occur in tropical forest functional characteristics as a function of future climate variation are largely unknown. We modeled community level trait values of Costa Rican rain forests as a function of current and future climate, and quantified potential changes in functional composition. We calculated per-plot community weighted mean (CWM) trait values for leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC), leaf nitrogen (N) and phosphorus (P) content, and wood basic specific gravity (WSG), for tree and palm species in 127 0.25 ha plots. We modeled the response of CWM traits to current temperature and precipitation gradients using generalized additive modeling. We then predicted and mapped CWM traits values under current and future climate, and quantified potential changes under a global warming scenario (RCP8.5, year 2050). We calculated the area within the multi trait functional space occupied by forest plots under both current and future climate, and determined potential changes in functional space occupied by forest plots. Overall, precipitation predicted CWM traits better than temperature. Models indicated increases in CWM SLA, N and P, and a decrease in CWM LDMC under climate change. Lowland forest communities converged on a single direction of change towards more acquisitive CWM trait values, indicating a change in forest functional composition resulting from a changed climate. Functional space occupied by forest plots was reduced by 50% under the future climate. Functional composition changes may have further effects on forests ecosystem services. Assessing functional trait spatial-gradients can help bridge the gap between species-based biogeography and biogeochemical approaches to strengthen biodiversity and ecosystem services conservation efforts.量化植物功能性状（plant functional traits）与非生物梯度（abiotic gradients）间的关联，对于评估森林群落（forest communities）应对气候变化（climate change）的潜在响应具有重要价值。然而，热带森林功能特征随未来气候变化的变化轨迹，目前仍不明晰。我们以当前及未来气候为自变量，对哥斯达黎加雨林的群落水平性状值进行建模，并量化功能组成的潜在变化。我们在127个0.25公顷的样地中，针对乔木与棕榈物种，计算了叶面积（Leaf Area, LA）、比叶面积（Specific Leaf Area, SLA）、叶干物质含量（Leaf Dry Matter Content, LDMC）、叶片氮（N）与磷（P）含量，以及木材基本比重（Wood Basic Specific Gravity, WSG）的群落加权均值（Community Weighted Mean, CWM）。我们采用广义相加模型（Generalized Additive Modeling），拟合了群落加权均值性状对当前温度与降水梯度的响应。随后我们预测并绘制了当前及未来气候情景下的群落加权均值性状空间分布，并量化了全球变暖情景（典型浓度路径8.5，Representative Concentration Pathway 8.5, RCP8.5；2050年）下的潜在变化。我们计算了当前与未来气候下，森林样地所占据的多性状功能空间的面积，并确定了森林样地占据的功能空间的潜在变化。总体而言，降水对群落加权均值性状的预测效果优于温度。模型结果显示，在气候变化情景下，群落加权均值比叶面积、叶片氮与磷含量均有所上升，而叶干物质含量则呈下降趋势。低地森林群落呈现出单一的变化方向，即朝向更具资源获取型的群落加权均值性状，表明气候改变引发了森林功能组成的转变。未来气候情景下，森林样地占据的功能空间缩减了50%。功能组成的变化可能会对森林生态系统服务产生进一步影响。评估功能性状的空间梯度，有助于弥合基于物种的生物地理学与生物地球化学研究方法之间的差距，进而强化生物多样性与生态系统服务保护工作。