Environmental impact analysis: Its relevance for the U.K.'s extractive industries

The paper gives the background to the current debate in the U.K. concerning the possible need to introduce a standardised and perhaps mandatory system of environmental impact analysis for developmental proposals. This is shown to be a subject of very considerable interest to those concerned with mineral extraction and its environmental effects. The paper considers some of those features of the extractive industries which are of particular importance when selecting an approach to environmental assessment. It discusses the appropriate content for such a study. Attention is given to the socio-economic factors which are almost inevitably associated with the extractive industries. The paper concludes with a plea for a more systematic assessment of the potential impact of both new and continued extraction of raw materials and fossil fuels and suggests that there should be more emphasis on environmental issues when national, regional and local policies and plans for the extractive industries are prepared.     

Geoadditive regression modeling of stream biological condition

Indices of biotic integrity have become an established tool to quantify the condition of small non-tidal streams and their watersheds. To investigate the effects of watershed characteristics on stream biological condition, we present a new technique for regressing IBIs on watershed-specific explanatory variables. Since IBIs are typically evaluated on an ordinal scale, our method is based on the proportional odds model for ordinal outcomes. To avoid overfitting, we do not use classical maximum likelihood estimation but a component-wise functional gradient boosting approach. Because component-wise gradient boosting has an intrinsic mechanism for variable selection and model choice, determinants of biotic integrity can be identified. In addition, the method offers a relatively simple way to account for spatial correlation in ecological data. An analysis of the Maryland Biological Streams Survey shows that nonlinear effects of predictor variables on stream condition can be quantified while, in addition, accurate predictions of biological condition at unsurveyed locations are obtained.     

Estimating rainforest biomass stocks and carbon loss from deforestation and degradation in Papua New Guinea 1972–2002: Best estimates,uncertainties and research needs

Reduction of carbon emissions from tropical deforestation and forest degradation is being considered a cost-effective way of mitigating the impacts of global warming. If such reductions are to be implemented, accurate and repeatable measurements of forest cover change and biomass will be required. In Papua New Guinea (PNG), which has one of the world's largest remaining areas of tropical forest, we used the best available data to estimate rainforest carbon stocks, and emissions from deforestation and degradation. We collated all available PNG field measurements which could be used to estimate carbon stocks in logged and unlogged forest. We extrapolated these plot-level estimates across the forested landscape using high-resolution forest mapping. We found the best estimate of forest carbon stocks contained in logged and unlogged forest in 2002 to be 4770 Mt (±13%). Our best estimate of gross forest carbon released through deforestation and degradation between 1972 and 2002 was 1178 Mt (±18%). By applying a long-term forest change model, we estimated that the carbon loss resulting from deforestation and degradation in 2001 was 53 Mt (±18%), rising from 24 Mt (±15%) in 1972. Forty-one percent of 2001 emissions resulted from logging, rising from 21% in 1972. Reducing emissions from logging is therefore a priority for PNG. The large uncertainty in our estimates of carbon stocks and fluxes is primarily due to the dearth of field measurements in both logged and unlogged forest, and the lack of PNG logging damage studies. Research priorities for PNG to increase the accuracy of forest carbon stock assessments are the collection of field measurements in unlogged forest and more spatially explicit logging damage studies.     

STORM RUNOFF CHARACTERISTICS OF GRAZED WATERSHEDS IN EASTERN OREGON1

ABSTRACT: Rainfall and runoff data from 485 storms during the summers of 1979–84 were evaluated to characterize storm runoff volumes (SF) and peak flows (QP) for 13 small watersheds in the Blue Mountains of eastern Oregon and to determine differences among grazing intensities and vegetation types. Storm hydrographs were separated by using watershed-specific baseflow rise rates of 0.002–0.013 cfsm/hr. Median SF and QP were 0.0014 in and 0.43 cfsm, respectively, for all storms. Total storm rainfall (PPT) and initial flow (QI) were important stepwise regression variables in accounting for the variation in SF and peak flow above initial flow (QPI); 30- and 60-mm rainfall intensities and rainfall duration were relatively unimportant. Two classes of vegetation were evaluated: (1) western larch-Douglas-fir (nine watersheds), and (2) other (four watersheds representing fir-spruce, lodgepole pine, mountain meadow, and ponderosa pine). Mean SF and QP did not differ (P=0.05) among vegetation classes but significant differences were apparent in the relation of SF to PPT and QI, and QPI to PPT and QI. As PPT and QI increased, SF and QPI from larch-Douglas-fir watersheds increased at a slower rate than they did from the other watersheds. Four levels of grazing intensity had no effect on storm runoff.     

Climate change and disaster management

Climate change, although a natural phenomenon, is accelerated by human activities. Disaster policy response to climate change is dependent on a number of factors, such as readiness to accept the reality of climate change, institutions and capacity, as well as willingness to embed climate change risk assessment and management in development strategies. These conditions do not yet exist universally. A focus that neglects to enhance capacity-building and resilience as a prerequisite for managing climate change risks will, in all likelihood, do little to reduce vulnerability to those risks. Reducing vulnerability is a key aspect of reducing climate change risk. To do so requires a new approach to climate change risk and a change in institutional structures and relationships. A focus on development that neglects to enhance governance and resilience as a prerequisite for managing climate change risks will, in all likelihood, do little to reduce vulnerability to those risks.     

Insuring Southeast Asian commercial forests: Fire risk analysis and the potential for use of data in risk pricing and reduction of forest fire risk

The author uses his own data gleaned from over 10 years of commercial forestry insurance across the world to propose that despite a low intrinsic fire risk across most of Southeast Asia, especially Indonesia, commercial fire losses are unacceptably high, and could be reduced substantially within the current financial legal and political framework within which forestry companies operate. Opening with a statement about the dearth of forest fire loss data in the commercial sector, it is observed that the consequent inability of general insurers to estimate the rate of fire loss leads to very low insurance participation in forestry within Indonesia. A summary is then provided of the financial and environmental benefits of insurance participation in commercial forestry were this situation to be changed. A short discussion on risk perceptions is introduced to make the point that without reliable commercial forest fire loss data, risk perceptions of fire exposure in Southeast Asia by the financial sector, including insurers, is a barrier to risk transfer and investment. While real fire risk and perceived fire risk for Indonesia seem at present to be in agreement, the paper challenges that this should the case. Comparisons are made with different parts of the world with the knowledge that, in commercial terms, plantations in the low latitudes behave similarly everywhere in terms of fire causes, fire propagation factors, and characteristics of plantation or managed mixed forest fires. A review of the fire sizes within commercial forests is a good indicator of the efficiency of fire management strategies, and profiles from a high fire risk territory and Indonesia are compared. Using commercial and unidentified data the author then demonstrates that commercial growers in Indonesia have a high annual rate of forest fire loss and may also have a significant catastrophe fire exposure. This ‘cat’ exposure is far greater than for equivalent plantations in clearly higher fire risk environments. These conclusions are and should be discussed with forestry companies to change attitude and investment levels. Practical points for improved plantation fire management are made along with comments about the resources required. A parallel discussion then reviews fire risk assessment and management by the insurers to prevent their own ‘forest fire’ losses if they are to get further involved with the provision of Indonesian commercial forest risk transfer. The explanation of how insurers price risk within a portfolio helps identify the specific data needed for a proper risk management strategy to be developed.     

Using expert knowledge to support Endangered Species Act decision-making for data-deficient species

Many questions relevant to conservation decision-making are characterized by extreme uncertainty due to lack of empirical data and complexity of the underlying ecologic processes, leading to a rapid increase in the use of structured protocols to elicit expert knowledge. Published ecologic applications often employ a modified Delphi method, where experts provide judgments anonymously and mathematical aggregation techniques are used to combine judgments. The Sheffield elicitation framework (SHELF) differs in its behavioral approach to synthesizing individual judgments into a fully specified probability distribution for an unknown quantity. We used the SHELF protocol remotely to assess extinction risk of three subterranean aquatic species that are being considered for listing under the U.S. Endangered Species Act. We provided experts an empirical threat assessment for each known locality over a video conference and recorded judgments on the probability of population persistence over four generations with online submission forms and R-shiny apps available through the SHELF package. Despite large uncertainty for all populations, there were key differences between species’ risk of extirpation based on spatial variation in dominant threats, local land use and management practices, and species’ microhabitat. The resulting probability distributions provided decision makers with a full picture of uncertainty that was consistent with the probabilistic nature of risk assessments. Discussion among experts during SHELF's behavioral aggregation stage clearly documented dominant threats (e.g., development, timber harvest, animal agriculture, and cave visitation) and their interactions with local cave geology and species’ habitat. Our virtual implementation of the SHELF protocol demonstrated the flexibility of the approach for conservation applications operating on budgets and time lines that can limit in-person meetings of geographically dispersed experts.