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Plant population modelling has been around since the 1970s, providing a valuable approach to understanding plant ecology from a mechanistic standpoint. It is surprising then that this area of research has not grown in prominence with respect to other approaches employed in modelling plant systems. In this review, we provide an analysis of the development and role of modelling in the field of plant population biology through an exploration of where it has been, where it is now and, in our opinion, where it should be headed. We focus, in particular, on the role plant population modelling could play in ecological forecasting, an urgent need given current rates of regional and global environmental change. We suggest that a critical element limiting the current application of plant population modelling in environmental research is the trade-off between the necessary resolution and detail required to accurately characterize ecological dynamics pitted against the goal of generality, particularly at broad spatial scales. In addition to suggestions how to overcome the current shortcoming of data on the process-level we discuss two emerging strategies that may offer a way to overcome the described limitation: (1) application of a modern approach to spatial scaling from local processes to broader levels of interaction and (2) plant functional-type modelling. Finally we outline what we believe to be needed in developing these approaches towards a 'science of forecasting'.
Trait-based studies have become extremely common in plant ecology. Trait-based approaches often rely on the tacit assumption that intraspecific trait variability (ITV) is negligible compared to interspecific variability, so that species can be characterized by mean trait values. Yet, numerous recent studies have challenged this assumption by showing that ITV significantly affects various ecological processes. Accounting for ITV may thus strengthen trait-based approaches, but measuring trait values on a large number of individuals per species and site is not feasible. Therefore, it is important and timely to synthesize existing knowledge on ITV in order to (1) decide critically when ITV should be considered, and (2) establish methods for incorporating this variability. Here we propose a practical set of rules to identify circumstances under which ITV should be accounted for. We formulate a spatial trait variance partitioning hypothesis to highlight the spatial scales at which ITV cannot be ignored in ecological studies. We then refine a set of four consecutive questions on the research question, the spatial scale, the sampling design, and the type of studied traits, to determine case-by-case if a given study should quantify ITV and test its effects. We review methods for quantifying ITV and develop a step-by-step guideline to design and interpret simulation studies that test for the importance of ITV. Even in the absence of quantitative knowledge on ITV, its effects can be assessed by varying trait values within species within realistic bounds around the known mean values. We finish with a discussion of future requirements to further incorporate ITV within trait-based approaches. This paper thus delineates a general framework to account for ITV and suggests a direction towards a more quantitative trait-based ecology.