Verifiable and non-verifiable anonymous mechanisms for regulating a polluting monopolist

Optimal regulation of a polluting natural monopolist must correct for both external damages and market power to achieve a social optimum. Existing non-Bayesian regulatory methods require knowledge of the demand function, while Bayesian schemes require knowledge of the underlying cost distribution. We introduce mechanisms adapted to use less information. Our Price-based Subsidy (PS) mechanisms give the firm a transfer that matches or approximates the incremental surplus generated each period. The regulator need not observe the abatement activity or know the demand, cost, or damage functions of the firm. All of the mechanisms induce the firm to price at marginal social cost, either immediately or asymptotically.     

Public sector perspectives and policy implications for the Pitons Management Area World Heritage Site,St. Lucia

St. Lucia faces numerous challenges associated with striking a balance between its economic and conservation goals with respect to the Pitons Management Area (PMA) World Heritage Site. Among the various stakeholders, the public sector, which largely constitutes the administrative authorities representing the general public, plays an instrumental role in site management. They are primarily responsible for policy formulation as well as the provision of fiscal incentives and funds to assist in the maintenance of the site. Based on a qualitative inquiry approach, this study explored the perspectives of key persons among pertinent public and non-profit organizations. Semi-structured interviews were conducted among local and national representatives from the public sector. Results revealed that the designation of the PMA as a World Heritage Site has presented both opportunities and challenges to the management of the site. Findings strongly indicate that the integrity and sustainability of the site is at stake due to a lack of commitment, coordination and political will in the public sector.     

Combining a generic process-based productivity model and a statistical classification method to predict the presence and absence of tree species in the Pacific Northwest,U.S.A.

Although long-lived tree species experience considerable environmental variation over their life spans, their geographical distributions reflect sensitivity mainly to mean monthly climatic conditions. We introduce an approach that incorporates a physiologically based growth model to illustrate how a half-dozen tree species differ in their responses to monthly variation in four climatic-related variables: water availability, deviations from an optimum temperature, atmospheric humidity deficits, and the frequency of frost. Rather than use climatic data directly to correlate with a species’ distribution, we assess the relative constraints of each of the four variables as they affect predicted monthly photosynthesis for Douglas-fir, the most widely distributed species in the region. We apply an automated regression-tree analysis to create a suite of rules, which differentially rank the relative importance of the four climatic modifiers for each species, and provide a basis for predicting a species’ presence or absence on 3737 uniformly distributed U.S. Forest Services’ Forest Inventory and Analysis (FIA) field survey plots. Results of this generalized rule-based approach were encouraging, with weighted accuracy, which combines the correct prediction of both presence and absence on FIA survey plots, averaging 87%. A wider sampling of climatic conditions throughout the full range of a species’ distribution should improve the basis for creating rules and the possibility of predicting future shifts in the geographic distribution of species.     

Turbinaria ornata as an herbivory refuge for associate algae

Habitat associations are an integral part of coral reef community structure. Commonly, one organism lives in such close association within or near another that a spatial refuge occurs, whereby one of the organisms provides protection to the other. This is often the result of defenses of the host deterring an associate organism’s consumers. In Moorea, French Polynesia, the range and abundance of the brown macroalga, Turbinaria ornata, have increased drastically since 1980 such that dense aggregations of this macroalga are a dominant component of the backreef habitat. Turbinaria ornata is both mechanically and chemically defended from herbivores. Other species of macroalgae grow within aggregations of Turbinaria and may benefit from these defenses. This study investigates whether aggregations of Turbinaria create a refuge from herbivory for associate macroalgae. When Turbinaria aggregations were removed experimentally, there was a significant increase in the number of associate algal species. Moreover, an herbivory assay using the palatable local alga Acanthophora spicifera identified herbivory as the mechanism for lower diversity on bommies lacking Turbinaria aggregations. The local increase in algal richness due to the refuge from herbivory afforded by Turbinaria may be an important contribution to macroalgal and community dynamics on reefs in Moorea, French Polynesia.     

Predicting tree diversity across the United States as a function of modeled gross primary production.

At the regional and continental scale, ecologists have theorized that spatial variation in biodiversity can be interpreted as a response to differences in climate. To test this theory we assumed that ecological constraints associated with current climatic conditions (2000-2004) might best be correlated with tree richness if expressed through satellite-derived measures of gross primary production (GPP), rather than the more commonly used, but less consistently derived, net primary production. To evaluate current patterns in tree diversity across the contiguous United States we acquired information on tree composition from the USDA Forest Service's Forest Inventory and Analysis program that represented more than 17,4000 survey plots. We selected 2693 cells of 1000 km2 within which a sufficient number of plots were available to estimate tree richness per hectare. Our estimates of forest productivity varied from simple vegetation indices indicative of the fraction of light intercepted by canopies at 16-d intervals, a product from the MODIS (Moderate Resolution Imaging Spectro-radiometer), to 8- and 10-d GPP products derived with minimal climatic data (MODIS) and SPOT-Vegetation (Systeme Pour l'Observation de la Terre), to 3-PGS (Physiological Principles Predicting Growth with Satellites), which requires both climate and soil data. Across the contiguous United States, modeled predictions of gross productivity accounted for between 51% and 77% of the recorded spatial variation in tree diversity, which ranged from 2 to 67 species per hectare. When the analyses were concentrated within nine broadly defined ecoregions, predictive relations largely disappeared. Only 3-PGS predictions fit a theorized unimodal function by being able to distinguish highly productive forests in the Pacific Northwest that support lower than expected tree diversity. Other models predicted a continuous steep rise in tree diversity with increasing productivity, and did so with generally better or nearly equal precision with fewer data requirements.     

A multidecadal oscillation in precipitation and temperature series is pronounced in low flow series from Puget Sound streams

In Pacific Northwest streams, summer low flows limit water available to competing instream (salmon) and out-of-stream (human) uses, creating broad interest in how and why low flows are trending. Analyses that assumed linear (monotonic) change over the last ~60 years revealed declining low flow trends in minimally disturbed streams. Here, polynomials were used to model flow trends between 1929 and 2015. A multidecadal oscillation was observed in flows, which increased initially from the 1930s until the 1950s, declined until the 1990s, and then increased again. A similar oscillation was detected in precipitation series, and opposing oscillations in surface temperature, Pacific Decadal Oscillation, and Interdecadal Pacific Oscillation series. Multidecadal oscillations with similar periods to those described here are well known in climate indices. Fitted model terms were consistent with flow trends being influenced by at least two drivers, one oscillating and the other monotonic. Anthropogenic warming is a candidate driver for the monotonic decline, and variation in (internal) climatic circulation for the oscillating trend, but others were not ruled out. The recent upturn in streamflows suggests that anthropogenic warming has not been the dominant factor driving streamflow trends, at least until 2015. Climate projections based on simulations that omit drivers of multidecadal variation are likely to underestimate the range, and rate of change, of future climatic variation.     

Assessing flood mitigation,management, and enforcement using insurance data,California and the USA

Previous research found that National Flood Insurance Program (NFIP) premiums collected in some U.S. states, including California, have far exceeded damage payments. However, this finding raises the question of whether such an imbalance represents systematically good flood management or, instead, merely short-term hydrologic good luck. This study investigated patterns in flood losses on structures that pre-date and post-date the first available flood maps (“pre-Flood Insurance Rate Map [FIRM]” vs. “post-FIRM”) in California, several peer states, and nationwide. California has a larger inheritance of pre-FIRM structures than the national average, apparently reflecting development during the latter half of the 20th Century but before most Federal Emergency Management Agency (FEMA) flood maps. Pre-FIRM properties are a disproportionate cost burden on the system, and the number of pre-FIRM policies has declined over time, but only slowly. Local patterns in pre-FIRM claims suggest targeted areas for enhanced mitigation efforts, including buyouts. Conversely, we find that claims on post-FIRM policies are a reasonable metric of good floodplain management and enforcement, and California's 38% of post-FIRM policies generated just 24% of the state's NFIP claims. Local “post-FIRM claim hotspots” suggest areas to examine more closely. California continues to be a net payer into the National Flood Insurance Program, with $102 million in payouts 2009–2018 versus $2.3 billion in premiums collected, or 4.5 cents of premiums collected for every dollar of premiums. In California, its peer states, and nationwide, future management of flood risk depends on: (1) continued investment in flood control and mitigation of existing floodplain structures, and (2) prudent planning and limitations on new floodplain and coastal development.     

Scaling range sizes to threats for robust predictions of risks to biodiversity

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems.     

The role of rhizofiltration and allelopathy on the removal of cyanobacteria in a continuous flow system

Environmental Science and Pollution Research - A continuous flow filtration system was designed to identify and quantify the removal mechanisms of Cyanobacteria (Microcystis aeruginosa) by...     

Park isolation in anthropogenic landscapes: land change and livelihoods at park boundaries in the African Albertine Rift

Regional Environmental Change - Landscapes are changing rapidly in regions where rural people live adjacent to protected parks and reserves. This is the case in highland East Africa, where many...