A fuzzy logic expert system for evaluating policy progress towards sustainability goals

Evaluating progress towards environmental sustainability goals can be difficult due to a lack of measurable benchmarks and insufficient or uncertain data. Marine settings are particularly challenging, as stakeholders and objectives tend to be less well defined and ecosystem components have high natural variability and are difficult to observe directly. Fuzzy logic expert systems are useful analytical frameworks to evaluate such systems, and we develop such a model here to formally evaluate progress towards sustainability targets based on diverse sets of indicators. Evaluation criteria include recent (since policy enactment) and historical (from earliest known state) change, type of indicators (state, benefit, pressure, response), time span and spatial scope, and the suitability of an indicator in reflecting progress toward a specific objective. A key aspect of the framework is that all assumptions are transparent and modifiable to fit different social and ecological contexts. We test the method by evaluating progress towards four Aichi Biodiversity Targets in Canadian oceans, including quantitative progress scores, information gaps, and the sensitivity of results to model and data assumptions. For Canadian marine systems, national protection plans and biodiversity awareness show good progress, but species and ecosystem states overall do not show strong improvement. Well-defined goals are vital for successful policy implementation, as ambiguity allows for conflicting potential indicators, which in natural systems increases uncertainty in progress evaluations. Importantly, our framework can be easily adapted to assess progress towards policy goals with different themes, globally or in specific regions.     

Bristle-like integumentary structures at the tail of the horned dinosaur Psittacosaurus

A specimen of the horned dinosaur Psittacosaurus from the early Cretaceous of China is described in which the integument is extraordinarily well-preserved. Most unusual is the presence of long bristle-like structures on the proximal part of tail. We interpret these structures as cylindrical and possibly tubular epidermal structures that were anchored deeply in the skin. They might have been used in display behavior and especially if one assumes that they were colored, they may have had a signal function. At present, there is no convincing evidence which shows these structures to be homologous to the structurally different integumentary filaments of theropod dinosaurs. Independent of their homology, however, the discovery of bristle-like structures in Psittacosaurus is of great evolutionary significance since it shows that the integumentary covering of at least some dinosaurs was much more complex than has ever been previously imagined.     

LAND USE AND ENVIRONMENTAL PLANNING: AN APPLICATION IN THE SOUTH CAROLINA COASTAL ZONE1

ABSTRACT: The purpose of this paper is to describe a land use and environmental planning model. Map overlays were used for analyzing and aggregating economic, social, and environmental data. Various land use categories were evaluated using a numerical scoring system. These scores were then used to assist in the development of land use regulations in a coastal county in South Carolina.     

Decrease in water-soluble 17beta-Estradiol and testosterone in composted poultry manure with time

Little attention has been paid to the environmental fate of the hormones 17beta-estradiol and testosterone excreted in animal waste. Land application of manure has a considerable potential to affect the environment with these endocrine disrupting compounds (EDCs). Composting is known to decompose organic matter to a stable, humus-like material. The goal of the present study was to quantitatively assess levels of water-soluble 17beta-estradiol and testosterone in composting chicken manure with time. Chicken layer manure was mixed with hay, straw, decomposed leaves, and starter compost, adjusted to approximately 60% moisture, and placed into a windrow. A clay-amended windrow was also prepared. Windrows were turned weekly, and temperature, oxygen, and CO(2) in the composting mass were monitored for either 133 or 139 d. Commercial enzyme immunoassay kits were used to quantitate the levels of 17beta-estradiol and testosterone in aqueous sample extracts. Water-soluble quantities of both hormones diminished during composting. The decrease in 17beta-estradiol followed first-order kinetics, with a rate constant k = -0.010/d. Testosterone levels declined at a slightly higher rate than 17beta-estradiol (i.e., k = -0.015/d). Both hormones could still be measured in aqueous extracts of compost sampled at the conclusion of composting. The decline in water-soluble 17beta-estradiol and testosterone in extracts of clay-amended compost was not statistically different from normal compost. These data suggest that composting may be an environmentally friendly technology suitable for reducing, but not eliminating, the concentrations of these endocrine disrupting hormones at concentrated animal operation facilities.     

Community Sustainability Auditing

This paper presents a method for assessing a community's sustainability prospects at a point in time. It argues that an improved methodology is needed to support the development of local area indicators. The method presented is community sustainability auditing. The ethical, conservative, competitive and co-operative aspects of sustainability are emphasized.The method uses an indicator approach within a protocol loosely inspired by International Standards Organization procedures. This involves the development of a set of questions for audit purposes, definition of indicators, analysis of the indicators in the light of the questions and a report summarizing a community's sustainability prospects.     

Multivariate Bayesian analysis of atmosphere–ocean general circulation models

Numerical experiments based on atmosphere–ocean general circulation models (AOGCMs) are one of the primary tools in deriving projections for future climate change. Although each AOGCM has the same underlying partial differential equations modeling large scale effects, they have different small scale parameterizations and different discretizations to solve the equations, resulting in different climate projections. This motivates climate projections synthesized from results of several AOGCMs’ output. We combine present day observations, present day and future climate projections in a single highdimensional hierarchical Bayes model. The challenging aspect is the modeling of the spatial processes on the sphere, the number of parameters and the amount of data involved. We pursue a Bayesian hierarchical model that separates the spatial response into a large scale climate change signal and an isotropic process representing small scale variability among AOGCMs. Samples from the posterior distributions are obtained with computer-intensive MCMC simulations. The novelty of our approach is that we use gridded, high resolution data covering the entire sphere within a spatial hierarchical framework. The primary data source is provided by the Coupled Model Intercomparison Project (CMIP) and consists of 9 AOGCMs on a 2.8 by 2.8 degree grid under several different emission scenarios. In this article we consider mean seasonal surface temperature and precipitation as climate variables. Extensions to our model are also discussed.