Marquette University Milwaukee, Wisconsin, United States
Abstract: A thorough understanding of processes that enhance and maintain the diversity of living things is critically important to conserving this diversity in the face of threats like pollution, habitat loss, and climate change. When plants of the same type grow too close together, many of them die from shared disease or intense competition. Those deaths create opportunities for plants of different types to establish, and this process can enhance plant diversity. These feedbacks are known as negative conspecific feedbacks or negative conspecific density dependence. Conspecifics can also generate positive feedbacks on survival and growth, which are mediated through host-specific mutualists such as mycorrhizae or foliar endophytes. However, a multitude of approaches to assess these feedbacks and substantial debate among leading scientists have hampered understanding of the extent to which local interactions among plants contribute to biological diversity around the world. Here, we present a conceptual synthesis of conspecific density dependence and methodological recommendations from an NSF-funded working group of leading scientists, which include robust methodological approaches to measuring density-dependent feedbacks and assessing their potential importance for diversity maintenance in a changing environment.
We present conceptual synthesis and robust methodological approaches to measuring density-dependent feedbacks. In order to facilitate broader advances in this area, we attempt to clarify concepts and terminology across different disciplines that have studied density-dependent feedbacks, including plant-soil feedbacks, conspecific negative density dependence (CNDD), and negative frequency dependence. Such insights provide a critical common currency to evaluate ecological influences on the maintenance of plant-species diversity. We also present approaches to assess conspecific density dependence, including: 1) integration of flexible neighborhood density functions that explicitly account for size- and distance-dependencies as well as nonlinear responses of survival and growth to increasing densities (i.e. thresholds and saturating responses); 2) hierarchical Bayesian approaches to measure density-dependent feedbacks; and 3) approaches that allow for longitudinal repeated census visits to forest stands. We also discuss how the study of density-dependent feedbacks with these robust approaches will enhance our understanding of diversity maintenance and help us predict how ecological communities will respond to climate change and other environmental stressors.
