Promising the moon? Evaluation of indigenous and lunar fishing calendars using semiparametric generalized mixed models of recreational catch data

Previous studies that have investigated relationships between the lunar cycle and recreational fishing success have all suffered from various problems—most notably, the failure to account for potential confounders in a statistically rigorous manner. We propose methods to account for season, fisher identity, fishing effort, day, and variation in biomass, all of which have previously either been omitted or handled in an ad hoc way. These are applied to two sets of data on recreational fishing of the snapper Pagrus auratus in New Zealand. In addition to estimating effects due to lunar phase, we also implement these methods to analyse the performance of a lunar-based indigenous M ${{\bar{\mathrm{a}}}}$ ori fishing calendar. Recreational fishers in New Zealand often make use of such calendars in order to predict fishing success on specific days, however little is known about the performance of such predictions or whether they hold any practical use to the everyday angler. A relationship between lunar phase and fishing success is identified, as well as support for some aspects of the M ${{\bar{\mathrm{a}}}}$ ori fishing calendar predictions. The magnitudes of these effects are small, however, casting doubt on the practical relevance of lunar based fishing predictions. In addition to the known seasonal trend associated with annual migration, an unexpected second trend is detected, and postulated to be associated with intense local fishing pressure over the summer vacation period.     

Land Reform and Biodiversity Conservation in Brazil in the 1990s: Conflict and the Articulation of Mutual Interests

Abstract:  Land-reform and environmental movements, revitalized by the democratization of civil society in Brazil in the 1990s, found their objectives in conflict over forested parcels that settlers want for conversion to agriculture but that are important for wildlife conservation. In the Atlantic Forest, where 95% of the forest is gone, we reviewed three cases of Brazilian nongovernmental organization (NGOs) engagement with the land-reform movement with respect to forest remnants neighboring protected areas that have insufficient habitat for the long-term survival of unique endangered species. In the Pontal do Paranapanema (São Paulo), Poço das Antas (Rio de Janeiro), and southern Bahia, environmental NGOs have supported agricultural alternatives that improve livelihood options and provide incentives for habitat conservation planning. Where land-reform groups were better organized, technical cooperation on settlement agriculture permitted the exploration of mutual interests in conciliating the productive landscape with conservation objectives. Processes of regular consultation among NGOs, environmental agencies, and the private sector revealed that there was less zero-sum conflict over the same lands than commonly perceived. In both groups, technicians found forested lands less suitable for small-scale agriculture, and leaders took risks to justify and support claims to alternative existing agricultural lands. Based on the cases we examined, the construction of landscapes with both forest stewardship and poverty-reducing agrarian reform faces continued obstacles from contradictory agrarian and environmental sector policies and inadequate economic incentives for forest stewardship on private lands.     

Prioritization of Ecosystem Services Research: Tampa Bay Demonstration Project

The Tampa Bay Ecosystem Services Demonstration Project (TBESDP) is part of the U.S. Environmental Protection Agency’s Ecosystem Services Research Program. The principal objectives of TBESDP are to (1) quantify the ecosystem services of the Tampa Bay watershed, (2) determine the value of ecosystem services to society, (3) predict the supply of ecosystem services under future scenarios of population growth and climate change, and (4) apply this knowledge through models and tools that will support the best informed environmental decisions possible. The scope and complexity of this project required intensive effort to establish which services can be quantified by applying existing models, data, and scientific literature and which services will require supporting research. Research priorities were assessed by: (1) developing and refining conceptual models of major ecosystems in the Tampa Bay region, (2) gathering input from stakeholders about the relative importance and values of various ecosystem services, (3) preparing and reviewing a bibliometric analysis of the volume of scientific literature relevant to the ecosystems and services of interest, and (4) evaluating an integrated analysis of importance, value, and availability of scientific information. This analysis led us to focus on two research priorities, seagrass-habitat functions as support for fishery production, and wetlands as regulators of water quality.     

Space-time stick-breaking processes for small area disease cluster estimation

We propose a space-time stick-breaking process for the disease cluster estimation. The dependencies for spatial and temporal effects are introduced by using space-time covariate dependent kernel stick-breaking processes. We compared this model with the space-time standard random effect model by checking each model’s ability in terms of cluster detection of various shapes and sizes. This comparison was made for simulated data where the true risks were known. For the simulated data, we have observed that space-time stick-breaking process performs better in detecting medium- and high-risk clusters. For the real data, county specific low birth weight incidences for the state of South Carolina for the years 1997–2007, we have illustrated how the proposed model can be used to find grouping of counties of higher incidence rate.     

Investigating the link between $$\hbox {PM}_{2.5}$$ and atmospheric profile variables via penalized functional quantile regression

Fine particulate matter (\(\hbox {PM}_{2.5}\)) events negatively affect the health of numerous persons globally each year. Previous works have described the association between air pollution and surface-level meteorological conditions; however, there has been less focus on the task of linking air pollution events with meteorological conditions at higher levels of the atmosphere. Working within the functional data framework, we develop a penalized functional quantile regression (PFQR) procedure to model conditional quantiles of a continuous response based on a functional covariate, with the ability to penalize selected derivatives of the estimated coefficient function. Our aim is to investigate the relationship between atmospheric profile variables (APVs), assumed to be functional, and key quantiles of the conditional distribution of surface-level \(\hbox {PM}_{2.5}\). Via a simulation study, we find that the performance of our PFQR procedure compares favorably to other related approaches. We conclude with an analysis of \(\hbox {PM}_{2.5}\) data at two Southeastern US locations, Columbia, SC and Tampa, FL, where we estimate the coefficient functions for the APVs corresponding to both ‘typical’ and ‘high’ \(\hbox {PM}_{2.5}\) events. As we believe that the true coefficient functions are smooth and may be exactly zero over subsets of their domains, we impose penalties on the 0th and 2nd derivatives. Our analysis indicates that the corresponding atmospheric conditions differ between the two locations, and that the conditions differ seasonally within location.