Norden Natalia, Angarita Héctor A, Bongers Frans, Martínez-Ramos Miguel, Granzow-de la Cerda Iñigo, van Breugel Michiel, Lebrija-Trejos Edwin, Meave Jorge A, Vandermeer John, Williamson G Bruce, Finegan Bryan, Mesquita Rita, Chazdon Robin L
Fundación Cedrela, Bogotá 111311, Colombia; Departamento de Ecología y Territorio, Pontificia Universidad Javeriana, Bogotá 110231, Colombia;
Departamento de Ecología y Territorio, Pontificia Universidad Javeriana, Bogotá 110231, Colombia;
Proc Natl Acad Sci U S A. 2015 Jun 30;112(26):8013-8. doi: 10.1073/pnas.1500403112. Epub 2015 Jun 15.
Although forest succession has traditionally been approached as a deterministic process, successional trajectories of vegetation change vary widely, even among nearby stands with similar environmental conditions and disturbance histories. Here, we provide the first attempt, to our knowledge, to quantify predictability and uncertainty during succession based on the most extensive long-term datasets ever assembled for Neotropical forests. We develop a novel approach that integrates deterministic and stochastic components into different candidate models describing the dynamical interactions among three widely used and interrelated forest attributes--stem density, basal area, and species density. Within each of the seven study sites, successional trajectories were highly idiosyncratic, even when controlling for prior land use, environment, and initial conditions in these attributes. Plot factors were far more important than stand age in explaining successional trajectories. For each site, the best-fit model was able to capture the complete set of time series in certain attributes only when both the deterministic and stochastic components were set to similar magnitudes. Surprisingly, predictability of stem density, basal area, and species density did not show consistent trends across attributes, study sites, or land use history, and was independent of plot size and time series length. The model developed here represents the best approach, to date, for characterizing autogenic successional dynamics and demonstrates the low predictability of successional trajectories. These high levels of uncertainty suggest that the impacts of allogenic factors on rates of change during tropical forest succession are far more pervasive than previously thought, challenging the way ecologists view and investigate forest regeneration.
尽管传统上森林演替被视为一个确定性过程,但植被变化的演替轨迹差异很大,即使在环境条件和干扰历史相似的邻近林分中也是如此。在此,据我们所知,我们首次尝试基于为新热带森林收集的最广泛的长期数据集来量化演替过程中的可预测性和不确定性。我们开发了一种新颖的方法,将确定性和随机性成分整合到不同的候选模型中,这些模型描述了三种广泛使用且相互关联的森林属性——茎密度、断面积和物种密度之间的动态相互作用。在七个研究地点中的每一个地点,即使在控制了这些属性的先前土地利用、环境和初始条件后,演替轨迹仍然高度特异。在解释演替轨迹方面,样地因素远比林分年龄重要。对于每个地点,只有当确定性和随机性成分都设置为相似大小时,最佳拟合模型才能仅在某些属性中捕捉到完整的时间序列集。令人惊讶的是,茎密度、断面积和物种密度的可预测性在不同属性、研究地点或土地利用历史之间并未表现出一致的趋势,并且与样地大小和时间序列长度无关。这里开发的模型代表了迄今为止表征自生演替动态的最佳方法,并证明了演替轨迹的低可预测性。这些高度的不确定性表明,外源因素对热带森林演替过程中变化速率的影响比以前认为的要广泛得多,这对生态学家看待和研究森林更新的方式提出了挑战。