In the spirit of explanatory pluralism, this chapter argues that causal and noncausal explanations of a phenomenon are compatible, each being useful for bringing out different sorts of insights. After reviewing a model-based account of scientific explanation, which can accommodate causal and noncausal explanations alike, an important core conception of noncausal explanation is identified. This noncausal form of model-based explanation is illustrated using the example of how Earth scientists in a subfield known as aeolian geomorphology are explaining the formation (...) of regularlyspaced sand ripples. The chapter concludes that even when it comes to everyday "medium-sized dry goods" such as sand ripples, where there is a complete causal story to be told, one can find examples of noncausal scientific explanations. (shrink)

Do mountains exist? The answer to this question is surely: yes. In fact, ‘mountain’ is the example of a kind of geographic feature or thing most commonly cited by English speakers (Mark, et al., 1999; Smith and Mark 2001), and this result may hold across many languages and cultures. But whether they are considered as individuals (tokens) or as kinds (types), mountains do not exist in quite the same unequivocal sense as do such prototypical everyday objects as chairs or people.

While the predominant focus of the philosophical literature on scientific modeling has been on single-scale models, most systems in nature exhibit complex multiscale behavior, requiring new modeling methods. This challenge of modeling phenomena across a vast range of spatial and temporal scales has been called the tyranny of scales problem. Drawing on research in the geosciences, I synthesize and analyze a number of strategies for taming this tyranny in the context of conceptual, physical, and mathematical modeling. This includes several strategies (...) that can be deployed in physical modeling, even when strict dynamical scaling fails. In all cases, I argue that having an adequate conceptual model—given both the nature of the system and the particular purpose of the model—is essential. I draw a distinction between depiction and representation, and use this research in the geosciences to advance a number of debates in the philosophy of modeling. (shrink)

The shape of the Earth's surface, its topography, is a fundamental dimension of the environment, shaping or mediating many other environmental flows or functions. But there is a major divergence in the way that topography is conceptualized in different domains. Topographic cartographers, information scientists, geomorphologists and environmental modelers typically conceptualize topographic variability as a continuous field of elevations or as some discrete approximation to such a field. Pilots, explorers, anthropologists, ecologists, hikers, and archeologists, on the other hand, typically conceptualize this (...) same variability in terms of hills and valleys, mountains and plains, barrows and trenches, that is, as (special sorts of) objects, with locations, shapes, and often names of their own. In this chapter, we sketch an approach to bridging this fundamental gap in geographic information infrastructure. (shrink)