Integrating Subjective and Objective Dimensions of Resilience in Fire-Prone Landscapes.

Resilience has become a common goal for science-based natural resource management, particularly in the context of changing climate and disturbance regimes. Integrating varying perspectives and definitions of resilience is a complex and often unrecognized challenge to applying resilience concepts to social-ecological systems (SESs) management. Using wildfire as an example, we develop a framework to expose and separate two important dimensions of resilience: the inherent properties that maintain structure, function, or states of an SES and the human perceptions of desirable or valued components of an SES. In doing so, the framework distinguishes between value-free and human-derived, value-explicit dimensions of resilience. Four archetypal scenarios highlight that ecological resilience and human values do not always align and that recognizing and anticipating potential misalignment is critical for developing effective management goals. Our framework clarifies existing resilience theory, connects literature across disciplines, and facilitates use of the resilience concept in research and land-management applications.

Biomarkers of Animal Nutrition: From Seasonal to Lifetime Indicators of Environmental Conditions.

Nutrition underpins survival and reproduction in animal populations; reliable nutritional biomarkers are therefore requisites to understanding environmental drivers of population dynamics. Biomarkers vary in scope of inference and sensitivity, making it important to know what and when to measure to properly quantify biological responses. We evaluated the repeatability of three nutritional biomarkers in a large, iteroparous mammal to evaluate the level of intrinsic and extrinsic contributions to those traits. During a long-term, individual-based study in a highly variable environment, we measured body fat, body mass, and lean mass of mule deer (Odocoileus hemionus) each autumn and spring. Lean mass was the most repeatable biomarker (0.72 autumn; 0.61 spring), followed by body mass (0.64 autumn; 0.53 spring), and then body fat (0.22 autumn; 0.01 spring). High repeatability in body and lean mass likely reflects primary structural composition, which is conserved across seasons. Low repeatability of body fat supports that it is the primary labile source of energy that is largely a product of environmental contributions of the previous season. Based on the disparate levels in repeatability among nutritional biomarkers, we contend that body and lean mass are better indicators of nutritional legacies (e.g., maternal effects), whereas body fat is a direct and sensitive reflection of recent nutritional gains and losses.