Fire and restoration of the largest urban forest of the world in Rio de Janeiro City,Brazil

National Park of Tijuca in Rio de Janeiro (Brazil) is about 3,300 ha and considered the largest urban forest in the world. Its floristic composition is typical of Atlantic Rain Forest. The reserve is being altered because of fire occurrences and urban expansion. This study identified locations and causes of forest fires, and makes management recommendations to restore damaged areas. From 1991 to 2000, forest firefighters recorded an average of 75-fire occurrences/year. Identified causes included hot air balloons (24%), intentional (24%), rubbish burning (21%) and religious practices (17%). Primary fuels included invasive grasses and ferns. Although hot air balloons destroyed larger areas of forest in each occurrence, a greater number of fires started in the invasive vegetation along roads that bisect the forest. In response to recurrent forests, invasive vegetation has spread gradually into the forest increasing forest degradation. To decrease fire damage, sites with high fire frequencies and density of invasive vegetation were planted with less flammable species. Results indicate that fire frequency decreased and density of invasive vegetation declined. This approach appears to prevent fire incidence, reduce the need for fire fighting, and preserve existing biodiversity.     

Book reviews

Statistical Papers -     

When the Export of Social Problems Is No Longer Possible: Immigration Policies and Unemployment in Switzerland

Throughout the twentieth century, Switzerland has been one of the OECD countries with the highest proportion of immigrants in its population. The aim of this article is to show how institutional factors have shaped the opportunities for change in immigration and immigrant‐employment‐related policies there in the 1990s. Whereas unemployment had remained low in the 1970s and 1980s, there was a marked increase at the beginning of the 1990s. Existing migration policies were considered a central cause of this increase, since the great majority of foreigners who had come and settled in Switzerland in the periods of economic expansion were low‐skilled, and were now over‐represented among the unemployed. The reforms undertaken in the field of immigration and integration policy to respond to these new problems have been determined by specific institutional factors: direct democracy, a defensive migration regime, the development of immigrant rights and the weak autonomy of the central state. These factors account to a large extent for the limited scope and specific pathways of policy reforms in these two domains.     

Risk Modeling, Assessment, and Management of Lahar Flow Threat

The 1991 eruption of Mount Pinatubo in the Philippines is considered one of the most violent and destructive volcanic activities in the 20th century. Lahar is the Indonesian term for volcanic ash, and lahar flows resulting from the massive amount of volcanic materials deposited on the mountain's slope posed continued post-eruption threats to the surrounding areas, destroying lives, homes, agricultural products, and infrastructures. Risks of lahar flows were identified immediately after the eruption, with scientific data provided by the Philippine Institute of Volcanology, the U.S. Geological Survey, and other research institutions. However, competing political, economic, and social agendas subordinated the importance of scientific information to policy making. Using systemic risk analysis and management, this article addresses the issues of multiple objectives and the effective integration of scientific techniques into the decision-making process. It provides a modeling framework for identifying, prioritizing, and evaluating policies for managing risk. The major considerations are: (1) applying a holistic approach to risk analysis through hierarchical holographic modeling, (2) applying statistical methods to gain insight into the problem of uncertainty in risk assessment, (3) using multiobjective trade-off analysis to address the issue of multiple decisionmakers and stakeholders in the decision-making process, (4) using the conditional expected value of extreme events to complement and supplement the expected value in quantifying risk, and (5) assessing the impacts of multistage decisions. Numerical examples based on ex post data are formulated to illustrate applications to various problems. The resulting framework from this study can serve as a general baseline model for assessing and managing risks of natural disasters, which the Philippines' lead agency-the National Disaster Coordinating Council (NDCC)-and other related organizations can use for their decision-making processes.     

The complexity of diversity and importance for equitable philanthropy

The current U.S. climate of racial and social injustice has prompted a renewed call for diverse and equitable ways to rethink community philanthropy. Community foundations are vehicles for community philanthropy which offer vast benefits for social improvement and community development. The board of directors ensures these organizations fulfill their mission, making decisions on funding priorities and holding the organization functionally and fiscally responsible. Drawing on constructs of diversity and representative bureaucracy and a case study of Florida community foundations, we suggest that diversity is understood in different ways and the presence of diverse board members may be linked to advancing the interests of diverse communities and in achieving outcomes that assist in the needs of certain social groups. Increased understanding of diversity can improve foundation and philanthropic effectiveness and bring broader social change by promoting equity and social justice among community‐based philanthropic organizations.     

Stable and visualizable Gaussian parsimonious clustering models

Gaussian mixture model-based clustering is now a standard tool to determine a hypothetical underlying structure in continuous data. However, many usual parsimonious models, despite either their appealing geometrical interpretation or their ability to deal with high dimensional data, suffer from major drawbacks due to scale dependence or unsustainability of the constraints after projection. In this work we present a new family of parsimonious Gaussian models based on a variance-correlation decomposition of the covariance matrices. These new models are stable when projected into the canonical planes and, so, faithfully representable in low dimension. They are also stable by modification of the measurement units of the data and such a modification does not change the model selection based on likelihood criteria. We highlight all these stability properties by a specific graphical representation of each model. A detailed Generalized EM (GEM) algorithm is also provided for every model inference. Then, on biological and geological data, we compare our stable models to standard ones (geometrical models and factor analyzer models), which underlines all the profit to obtain unit-free models.