Cross-Scale Interactions, Nonlinearities, and Forecasting Catastrophic Events

U.S. Department of Agriculture Agricultural Research Service, Jornada Experimental Range, New Mexico State University, Las Cruces, NM 88003, USA.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 10/2004; 101(42):15130-5. DOI: 10.1073/pnas.0403822101
Source: PubMed


Catastrophic events share characteristic nonlinear behaviors that are often generated by cross-scale interactions and feedbacks among system elements. These events result in surprises that cannot easily be predicted based on information obtained at a single scale. Progress on catastrophic events has focused on one of the following two areas: nonlinear dynamics through time without an explicit consideration of spatial connectivity [Holling, C. S. (1992) Ecol. Monogr. 62, 447-502] or spatial connectivity and the spread of contagious processes without a consideration of cross-scale interactions and feedbacks [Zeng, N., Neeling, J. D., Lau, L. M. & Tucker, C. J. (1999) Science 286, 1537-1540]. These approaches rarely have ventured beyond traditional disciplinary boundaries. We provide an interdisciplinary, conceptual, and general mathematical framework for understanding and forecasting nonlinear dynamics through time and across space. We illustrate the generality and usefulness of our approach by using new data and recasting published data from ecology (wildfires and desertification), epidemiology (infectious diseases), and engineering (structural failures). We show that decisions that minimize the likelihood of catastrophic events must be based on cross-scale interactions, and such decisions will often be counterintuitive. Given the continuing challenges associated with global change, approaches that cross disciplinary boundaries to include interactions and feedbacks at multiple scales are needed to increase our ability to predict catastrophic events and develop strategies for minimizing their occurrence and impacts. Our framework is an important step in developing predictive tools and designing experiments to examine cross-scale interactions.

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    ABSTRACT: Theoretical models suggest that scale-dependent feedbacks between plant reproductive success and plant patch size govern transitions from highly to sparsely vegetated states in drylands, yet there is scant empirical evidence for these mechanisms. Scale-dependent feedback models suggest that an optimal patch size exists for growth and reproduction of plants and that a threshold patch organization exists below which positive feedbacks between vegetation and resources can break down, leading to critical transitions. We examined the relationship between patch size and plant reproduction using an experiment in a Chihuahuan Desert grassland. We tested the hypothesis that reproductive effort and success of a dominant grass (Bouteloua eriopoda) would vary predictably with patch size. We found that focal plants in medium-sized patches featured higher rates of grass reproductive success than when plants occupied either large patch interiors or small patches. These patterns support the existence of scale-dependent feedbacks in Chihuahuan Desert grasslands and indicate an optimal patch size for reproductive effort and success in B. eriopoda. We discuss the implications of these results for detecting ecological thresholds in desert grasslands.
    Ecosystems 10/2015; 18(1-1):146-153. DOI:10.1007/s10021-014-9818-9 · 3.94 Impact Factor
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    • "Our study found the relative contributions of environmental controls on fire size to vary with spatial scale as supported by Flannigan et al. (2009) and Parisien et al. (2011). Despite the fact that a high accumulation of biomass provides sufficient fuel to promote fire spread in boreal forest ecosystems, the spatial distribution and connectivity of fuels are also considered critically important for fire spread within a heterogeneous landscape (Peters et al., 2004). Based on the moving window analysis, we found small burns were influenced by bottom-up controls (Fig. 5a). "
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    Forest Ecology and Management 03/2015; DOI:10.1016/j.foreco.2015.01.011 · 2.66 Impact Factor
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    • "By focusing on the local scale, effects of processes that operate at the landscape scale (e.g. environmental heterogeneity , landscape connectivity, dispersal limitation; Leibold 2011) as well as cross-scale interactions (Peters et al. 2004) are ignored. Assessment of metacommunity structure (i.e. "
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    Journal of Animal Ecology 10/2014; DOI:10.1111/1365-2656.12299 · 4.50 Impact Factor
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