The applied discipline of agroecological design provides a useful case study for examining broader philosophical questions about the existence and importance of ecological generalizations or “laws.” Recent developments in the availability and use of formal meta-analyses have led to the discovery of many resilient generalizations in ecology (Linquist et al. 2016). However, these “laws” face numerous challenges when it comes to their practical application. Concerns about their reliability and scope might stem from unclear logical and epistemic connections to more foundational (...) or “unifying” generalizations (Lean in Philos Top 47(1), 2019) which, in ecology, tend to be derived from first principles and in association with highly abstract models. This raises questions about the nature of those foundational generalizations themselves. In particular, how resilient are they compared to the generalizations uncovered by empirically driven methods? Here we propose a procedure for evaluating the resilience of generalizations across five ecologically relevant dimensions. This procedure was applied to seven well known foundational generalizations in ecology. Surprisingly, it turned out to be impossible to estimate the resilience of these foundational generalizations based on the available literature. This points to the need for a more centralized repository of information about ecological generalizations, created with the explicit aim of evaluating such important dimensions as causal mechanism and predictive power. (shrink)

Models provide scientists with knowledge about target systems. An important group of models are those that are called general. However, what exactly is meant by generality in this context is somewhat unclear. The aim of this paper is to draw out a distinction between two notions of generality that has implications for scientific practice. Some models are general in the sense that they apply to many systems in the world and have many particular targets. Another sense is captured by models (...) that are aimed at understanding the fundamental or underlying dynamics of a phenomenon, as opposed to how it manifests in each particular case. They have non-specific, i.e. generic targets. While both notions of generality and genericness are legitimate and correspond to different aspects of scientific practice, they must be distinguished. Failing to do so obscures the danger of overgeneralisation faced by general models and facilitates the illegitimate use of generic models as general models. This can lead to a reduction of the explanatory and predictive power of both. (shrink)