The non-industrial private forest owner's optimal harvesting and investment strategies are studied at forest holding level by including individual forest stands in an asset class portfolio. The forest owner can either clearcut mature stands and invest the capital in financial or real asset classes (bank deposits, government bonds, stocks, apartments) or postpone clearcutting and retain capital in standing trees.

One consequence of the transition of rural communities from industrialised agriculture and natural resource extraction to sustainable development principles has been the rise of community-based natural resource management (CBNRM). CBNRM entails collaborative efforts, typically involving local, state and federal agencies, private firms and landowners, non-governmental organisations such as environmental and economic development groups, and watershed councils. There are no agreed-upon metrics or even broadly accepted approaches for assessing the effectiveness of these new institutions.

Managing the forest to store carbon is a relatively new concept. Various regional greenhouse gas initiatives and new Federal legislation are providing financial incentives for forest owners to manage for carbon in addition to other forest products. These incentives are intended for landowners who engage in activities that go beyond business as usual practices. Managing for carbon will likely involve foregoing other investment alternatives and increasing rotation lengths.

Rapid conversion of rural land to exurban development and the ensuing impacts on natural resources have been well-documented, but information about exurban landowners is lacking. To address this knowledge gap, we surveyed exurban landowners in six Wyoming counties and documented demographic characteristics, motivations, knowledge, and attitudes about natural resources and land management. The overall response rate was 55.6%. Generally, respondents were of retirement age, had lived in Wyoming for about 13 yr, and were raised in areas with a population

In Mexico, forest fires are strongly influenced by environmental, topographic, and anthropogenic factors. A government-based database covering the period 2000–2011 was used to analyze the spatial heterogeneity of the factors influencing forest fire size in the state of Durango, Mexico. Ordinary least squares and geographically weighted regression models were fit to identify the main factors as well as their spatial influence on fire size. Results indicate that fire size is greatly affected by distance to roads, distance to towns, precipitation, temperature, and a population gravity index.

Relatively narrow (

Urbanisation is an important driver of biodiversity loss, also contributing to habitat loss and fragmentation of grasslands at the urban-rural interface. While urban green spaces are known to include many grassland habitats, it is uncertain to what extent urban land use types harbour grasslands of special conservation interest and whether patch characteristics and connectivity of these differ from grasslands on agricultural land.

Wildlife organizations often engage landowners in habitat management. Landowner typology research can provide suggestions for how to work with diverse types of landowners. We explored how typologies can inform selection of tools to engage landowners in early successional habitat (ESH) management. Using a survey, effectiveness of three kinds of tools were assessed: (a) basic needs, (b) learning, and (c) social. Across all types and typologies, learning tools were most likely to influence landowner behavior, whereas social tools (e.g., recognition) were least likely.

A hypothetical market for renting and converting forested land into row cropping for biofuel production revealed that nearly half of the 1060 non-industrial landowners sampled in Florida are willing to accept payments for land type conversion and the resulting supply function is inelastic and positive.

This paper describes an environmental conservation planning model used in Queensland, Australia to purchase agreements on 66 sites covering 81,046ha at a cost of A$1.9 million. The model was used as part of a competitive tendering program called “NatureAssist”. The model maximises conservation benefit subject to a cost constraint using binary combinatorial optimisation. Multiple criteria analysis (MCA) is used to capture investor preferences and measure benefit over multiple outcomes. Conservation costs are drawn from real market data; i.e.