We highlight the complexity of land-use/cover change and propose a framework for a more general understanding of the issue, with emphasis on tropical regions. The review summarizes recent estimates on changes in cropland, agricultural intensification, tropical deforestation, pasture expansion, and urbanization and identifies the still unmeasured land-cover changes. Climate-driven land-cover modifications interact with land-use changes. Land-use change is driven by synergetic factor combinations of resource scarcity leading to an increase in the pressure of production on resources, changing opportunities created by markets, outside policy intervention, loss of adaptive capacity, and changes in social organization and attitudes. The changes in ecosystem goods and services that result from land-use change feed back on the drivers of land-use change. A restricted set of dominant pathways of land-use change is identified. Land-use change can be understood using the concepts of complex adaptive systems and transitions. Integrated, place-based research on land-use/land-cover change requires a combination of the agent-based systems and narrative perspectives of understanding. We argue in this paper that a systematic analysis of local-scale land-use change studies, conducted over a range of timescales, helps to uncover general principles that provide an explanation and prediction of new land-use changes.

Dynamics of Land-Use and Land-Cover Change in Tropical Regions

This comprehensive text and reference work on numerical weather prediction, first published in 2002, covers not only methods for numerical modeling, but also the important related areas of data assimilation and predictability. It incorporates all aspects of environmental computer modeling including an historical overview of the subject, equations of motion and their approximations, a modern and clear description of numerical methods, and the determination of initial conditions using weather observations (an important science known as data assimilation). Finally, this book provides a clear discussion of the problems of predictability and chaos in dynamical systems and how they can be applied to atmospheric and oceanic systems. Professors and students in meteorology, atmospheric science, oceanography, hydrology and environmental science will find much to interest them in this book, which can also form the basis of one or more graduate-level courses.

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Atmospheric Modeling, Data Assimilation and Predictability

Land change science has emerged as a fundamental component of global environmental change and sustainability research. This interdisciplinary field seeks to understand the dynamics of land cover and land use as a coupled human-environment system to address theory, concepts, models, and applications relevant to environmental and societal problems, including the intersection of the two. The major components and advances in land change are addressed: observation and monitoring; understanding the coupled system-causes, impacts, and consequences; modeling; and synthesis issues. The six articles of the special feature are introduced and situated within these components of study.

/pdf/the-emergence-of-land-change-science-for-global-4aymnjwgng.pdf

The emergence of land change science for global environmental change and sustainability

Dynamics ofland-use andland-coverchange intropicalregions

https://www.ukm.my/ipi/wp-content/uploads/2013/07/70_2002_Consequences-of-climate-change-for-European-agricultural.pdf

Consequences of climate change for European agricultural productivity, land use and policy

A method to analyze upper air charts numerically is presented. The analysis is expressed by the height values of the pressure surface in gridpoints. The computed height in a gridpoint is obtained as a weighted mean of height values derived from the surrounding height and wind observations, the forecast height in the point and the corresponding normal height. Nine 500 mb maps are analyzed with the aid of the Swedish computor BESK, six of these consecutive. The size of the grid was 32 × 41 points. The analyses have been compared with two independent conventional analyses. The mean values of the root mean square of the differences between the numerical and the conventional analyses were 26 m and 24 m respectively and 26 m between the two conventional ones. The root mean square of the differences between the observed and analyzed heights was 22 m in the mean. This is roughly what should be expected judging from the existing knowledge about observation errors. Three barotropic forecasts have been computed from the numerical analyses. They are compared with the corresponding numerical forecasts from conventionally analyzed maps. It was not possible to find any significant difference between the goodness of the forecasts based on the numerical analyses and the conventional analyses. DOI: 10.1111/j.2153-3490.1955.tb01170.x

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.2153-3490.1955.tb01170.x

Numerical Weather Map Analysis

I discuss the loss of cropland in developing countries in connection with the ongoing land conversion caused by the growing population and socio-economic development, resulting in an increased demand for housing, industry, infrastructure, etc. Based on assumptions about the required space per capita for other purposes than agriculture, the portion of this area that is removed from presently used cropland, and the quality of the available land reserves, the required demand for land reserves has been calculated. The main conclusions are that during the next three decades (i) the loss of cropland is likely to be within the range 30–60 Mha, (ii) the reserve land utilized will be about 100–200 Mha, and (iii) the reserve land still in use after 30 years, about 50–100 Mha.

Population growth and loss of arable land

In view of the increasing degradation of the global environment it can be expected that the number of environmental refugees will be increasing significantly during the next few decades. An attempt is made to examine the question to what extent such migrations are predictable? In particular, attention is given to the prediction of migrations caused by the declining availability of food per capita in the developing world, and the migration from low lying coastal areas driven by the rising sea level. Although it is not possible to make detailed predictions of such migrations, there are compelling reasons to believe they can be predicted with sufficient reliability to motivate implementation of mitigation measures.

Can large-scale environmental migrations be predicted?

This paper attempts to estimate the effects of the ongoing environmental degradation to the global food production. The environmental degradation processes being considered here are soil erosion salinization chemical contamination ultraviolet radiation and biotic stress. Estimates have also been made of available opportunities to improve food production efficiency by increasing the use of fertilizers irrigation and biotechnology as well as improvement in management. Also taken into consideration are the expected losses and gains of agricultural land in competition with urbanization industrial development and forest which could affect food productivity. Although estimated gains in food production deliberately have been overestimated and losses underestimated calculations indicate that during the next 30-35 years the annual net gain in food production will be significantly lower than the rate of world population growth. An attempt was also made to identify possible scenarios for large-scale migrations caused mainly by rapid population growth in combination with insufficient local food production and poverty.

Environmental degradation global food production and risk for large-scale migrations.

An attempt is made to assess the sensitivity of food production to various aspects of global change and environmental degradation during the next few decades. As a tool for this study a spreadsheet accounting system for food demand and supply is used. Taking into account the uncertainties of the various influencing factors, such as new technologies, improved management, increased fertilizer use, climatic change, expansion of irrigation, soil degradation and loss of agricultural land, the study indicates that one cannot say with any certainty whether or not food supply will meet expected demand in 2025, especially in Less Developed Countries. Bringing into use 10% of available potential cropland will make little difference.

Bo R. Döös

Papers

Numerical Weather Map Analysis

Population growth and loss of arable land

Can large-scale environmental migrations be predicted?

Environmental degradation global food production and risk for large-scale migrations.

Can we predict the future food production? A sensitivity analysis