Environmental Stewardship: A Conceptual Review and Analytical Framework.

There has been increasing attention to and investment in local environmental stewardship in conservation and environmental management policies and programs globally. Yet environmental stewardship has not received adequate conceptual attention. Establishing a clear definition and comprehensive analytical framework could strengthen our ability to understand the factors that lead to the success or failure of environmental stewardship in different contexts and how to most effectively support and enable local efforts. Here we propose such a definition and framework. First, we define local environmental stewardship as the actions taken by individuals, groups or networks of actors, with various motivations and levels of capacity, to protect, care for or responsibly use the environment in pursuit of environmental and/or social outcomes in diverse social-ecological contexts. Next, drawing from a review of the environmental stewardship, management and governance literatures, we unpack the elements of this definition to develop an analytical framework that can facilitate research on local environmental stewardship. Finally, we discuss potential interventions and leverage points for promoting or supporting local stewardship and future applications of the framework to guide descriptive, evaluative, prescriptive or systematic analysis of environmental stewardship. Further application of this framework in diverse environmental and social contexts is recommended to refine the elements and develop insights that will guide and improve the outcomes of environmental stewardship initiatives and investments. Ultimately, our aim is to raise the profile of environmental stewardship as a valuable and holistic concept for guiding productive and sustained relationships with the environment.

Estimation of biomass and canopy height in bermudagrass, alfalfa, and wheat using ultrasonic, laser, and spectral sensors.

Non-destructive biomass estimation of vegetation has been performed via remote sensing as well as physical measurements. An effective method for estimating biomass must have accuracy comparable to the accepted standard of destructive removal. Estimation or measurement of height is commonly employed to create a relationship between height and mass. This study examined several types of ground-based mobile sensing strategies for forage biomass estimation. Forage production experiments consisting of alfalfa (Medicago sativa L.), bermudagrass [Cynodon dactylon (L.) Pers.], and wheat (Triticum aestivum L.) were employed to examine sensor biomass estimation (laser, ultrasonic, and spectral) as compared to physical measurements (plate meter and meter stick) and the traditional harvest method (clipping). Predictive models were constructed via partial least squares regression and modeled estimates were compared to the physically measured biomass. Least significant difference separated mean estimates were examined to evaluate differences in the physical measurements and sensor estimates for canopy height and biomass. Differences between methods were minimal (average percent error of 11.2% for difference between predicted values versus machine and quadrat harvested biomass values (1.64 and 4.91 t·ha(-1), respectively), except at the lowest measured biomass (average percent error of 89% for harvester and quad harvested biomass < 0.79 t·ha(-1)) and greatest measured biomass (average percent error of 18% for harvester and quad harvested biomass >6.4 t·ha(-1)). These data suggest that using mobile sensor-based biomass estimation models could be an effective alternative to the traditional clipping method for rapid, accurate in-field biomass estimation.