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Debra P C Peters

Publications and source records attributed to Debra P C Peters.

2 recordsLinked to original sources

Population and clonal level responses of a perennial grass following fire in the northern Chihuahuan Desert.

Relationships involving fire and perennial grasses are controversial in Chihuahuan Desert grasslands of southern New Mexico, USA. Research suggests that fire delays the resprouting of perennial grasses well after two growing seasons. However, such results are confounded by livestock grazing, soil erosion, and drought. Additionally, post-fire grass responses may depend on initial clone size. We evaluated the effects of fire, grazing, and clone size on Bouteloua eriopoda (black grama) in southern New Mexico grasslands. Four 2-ha plots were established in each of four sites. Fire and grazing were applied or not applied in 1999 such that four treatment combinations were assigned randomly to plots within each site. Within each plot, small (0-10 cm(2) basal area), medium (10-30 cm(2)), and large ( > 30 cm(2)) clones were initially mapped in five 0.91-m(2) quadrats where grass attributes and litter cover were evaluated before and at the end of two growing seasons following fire. Maximum fire temperature was also measured. At a population level, canopy and litter cover were each approximately 50% less in burned than unburned areas. However, compared to initial levels, canopy height had increased by 10% at the end of the study, regardless of fire. At a clonal level, basal cover reductions were attributed mostly to large clones that survived fire. Smaller clone densities had decreased by as much as 19% in burned compared to unburned areas, and fire reduced the basal cover of medium clones. Basal and canopy cover, recruitment, and clone basal area decreased with increased fire temperatures. Almost all responses were independent of grazing, and interactive effects of grazing and fire were not detected. Fire did not kill all perennial grass clones, regardless of size. However, rapid responses were likely influenced by above-average precipitation after fire. Future studies in desert grasslands should examine how perennial grass dynamics are affected by fire, precipitation patterns, and interactions with grazing.

Analysis of Variance↗

Cross-scale interactions, nonlinearities, and forecasting catastrophic events.

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.

Animals↗