Modeling the relationships between land use and land cover on private lands in the Upper Midwest, USA

This paper presents an approach to modeling land-cover change as a function of land-use change. We argue that, in order to model the link between socio-economic change and changes in forest cover in a region that is experiencing residential and recreational development and agricultural abandonment, land-use and land-cover change need to be represented as separate processes. Forest-cover change is represented here using two transition probabilities that were calculated from Landsat imagery and that, taken together, describe a Markov transition matrix between forest and non-forest over a 10-year period. Using a three-date land-use data set, compiled and interpreted from digitized parcel boundaries, and scanned aerial photography for 136 sites (c. 2500 ha) sampled from the Upper Midwest, USA, we test functional relationships between forest-cover transition probabilities, standardized to represent changes over a decade, and land-use conditions and changes within sample sites. Regression models indicated that about 60% of the variation in the average forest-cover transition probabilities (i.e. from forest to non-forest and vice versa) can be predicted using three variables: amount of agricultural land use in a site; amount of developed land use; and the amount of area increasing in development. In further analysis, time lags were evaluated, showing that agricultural abandonment had a relatively strong time-lag effect but development did not. We demonstrate an approach to using forest-cover transition probabilities to develop spatially-constrained simulations of forest-cover change. Because the simulations are based on transition probabilities that are indexed to a particular time and place, the simulations are improved over previous applications of Markov transition models. This modeling approach can be used to predict forest-cover changes as a result of socio-economic change, by linking to models that predict land-use change on the basis of exogenous human-induced drivers.     

Modeling the relationship between land use and surface water quality

It is widely known that watershed hydrology is dependent on many factors, including land use, climate, and soil conditions. But the relative impacts of different types of land use on the surface water are yet to be ascertained and quantified. This research attempted to use a comprehensive approach to examine the hydrologic effects of land use at both a regional and a local scale. Statistical and spatial analyses were employed to examine the statistical and spatial relationships of land use and the flow and water quality in receiving waters on a regional scale in the State of Ohio. Besides, a widely accepted watershed-based water quality assessment tool, the Better Assessment Science Integrating Point and Nonpoint Sources (BASINS), was adopted to model the plausible effects of land use on water quality in a local watershed in the East Fork Little Miami River Basin. The results from the statistical analyses revealed that there was a significant relationship between land use and in-stream water quality, especially for nitrogen, phosphorus and Fecal coliform. The geographic information systems (GIS) spatial analyses identified the watersheds that have high levels of contaminants and percentages of agricultural and urban lands. Furthermore, the hydrologic and water quality modeling showed that agricultural and impervious urban lands produced a much higher level of nitrogen and phosphorus than other land surfaces. From this research, it seems that the approach adopted in this study is comprehensive, covering both the regional and local scales. It also reveals that BASINS is a very useful and reliable tool, capable of characterizing the flow and water quality conditions for the study area under different watershed scales. With little modification, these models should be able to adapt to other watersheds or to simulate other contaminants. They also can be used to study the plausible impacts of global environmental change. In addition, the information on the hydrologic effects of land use is very useful. It can provide guidelines not only for resource managers in restoring our aquatic ecosystems, but also for local planners in devising viable and ecologically-sound watershed development plans, as well as for policy makers in evaluating alternate land management decisions.     

Modelling land use change with generalized linear models--a multi-model analysis of change between 1860 and 2000 in Gallatin Valley, Montana

This paper develops an approach to modelling land use change that links model selection and multi-model inference with empirical models and GIS. Land use change is frequently studied, and understanding gained, through a process of modelling that is an empirical analysis of documented changes in land cover or land use patterns. The approach here is based on analysis and comparison of multiple models of land use patterns using model selection and multi-model inference. The approach is illustrated with a case study of rural housing as it has developed for part of Gallatin County, Montana, USA. A GIS contains the location of rural housing on a yearly basis from 1860 to 2000. The database also documents a variety of environmental and socio-economic conditions. A general model of settlement development describes the evolution of drivers of land use change and their impacts in the region. This model is used to develop a series of different models reflecting drivers of change at different periods in the history of the study area. These period specific models represent a series of multiple working hypotheses describing (a) the effects of spatial variables as a representation of social, economic and environmental drivers of land use change, and (b) temporal changes in the effects of the spatial variables as the drivers of change evolve over time. Logistic regression is used to calibrate and interpret these models and the models are then compared and evaluated with model selection techniques. Results show that different models are 'best' for the different periods. The different models for different periods demonstrate that models are not invariant over time which presents challenges for validation and testing of empirical models. The research demonstrates (i) model selection as a mechanism for rating among many plausible models that describe land cover or land use patterns, (ii) inference from a set of models rather than from a single model, (iii) that models can be developed based on hypothesised relationships based on consideration of underlying and proximate causes of change, and (iv) that models are not invariant over time.     

Identifying sources of fecal contamination inexpensively with targeted sampling and bacterial source tracking

Most bacterial source tracking (BST) methods are too expensive for most communities to afford. We developed targeted sampling as a prelude to BST to reduce these costs. We combined targeted sampling with three inexpensive BST methods, Enterococcus speciation, detection of the esp gene, and fluorometry, to confirm the sources of fecal contamination to beaches on Georgia's Jekyll and Sea Islands during calm and stormy weather conditions. For Jekyll Island, the most likely source of contamination was bird feces because the percentage of Ent. faecalis was high (30%) and the esp gene was not detected. For the Sea Island beach during calm conditions, the most likely sources of fecal contamination were leaking sewer lines and wildlife feces. The leaking sewer lines were confirmed with fluorometry and detection of the esp gene. For the Sea Island beach during stormflow conditions, the most likely sources of fecal contamination were wildlife feces and runoff discharging from two county-maintained pipes. For the pipes, the most likely source of contamination was bird feces because the percentage of Ent. faecalis was high (30%) and the esp gene was not detected. Sediments were also a reservoir of fecal enterococci for both Jekyll and Sea Islands. Combining targeted sampling with two or more BST methods identified sources of fecal contamination quickly, easily, and inexpensively. This combination was the first time targeted sampling was conducted during stormy conditions, and the first time targeted sampling was combined with enterococcal speciation, detection of the esp gene, and fluorometry.     

Agroecology in the tropics: Achieving a balance between land use and preservation

Agroecology is the application of ecological concepts and principles to the design and management of sustainable agricultural systems. An agroecological approach to agriculture has special importance in the humid tropics where agricultural development and the preservation of tropical forests are most often in direct conflict. It is proposed that a more sustainable approach to development is needed, where agroecosystems depend on low external inputs, function more on the use of locally available and renewable resources, have benign impacts on the environment, and are based on the knowledge and culture of the local inhabitants. Examples of traditional agroecosystem management in Mesoamerica that can provide this basis are presented. The preservation of both biological and cultural diversity are integral to the long-term sustainable management of natural resources in the tropics.     

Structuring international development decisions: confronting trade-offs between land use and community development in Costa Rica

For more than half a century, research and practice in international development has focused on improving the quality of life of people living in developing regions of the world. Recently, researchers, practitioners, and policy makers have recognized the need to blend insights from experts and community stakeholders in development decisions. Research in the decision sciences tells us that these kinds of multiparty and multiattribute decisions are extremely challenging. However, recent experience using structured decision-making (SDM) approaches suggests that the quality of both expert and stakeholder input, and resulting decisions, can be improved by ensuring that people address a series of basic principles relating to identifying objectives and their associated attributes, estimating the consequences of proposed actions, and directly confronting trade-offs that arise during the evaluation of management alternatives. In this paper, we provide an overview of SDM and then discuss a research initiative aimed at applying the approach to a pressing international development problem in rural Costa Rica: management of the lucrative but also environmentally destructive pineapple industry. The objectives of this research were twofold: First, we sought to help inform policy decisions by eliciting land management preferences regarding the pineapple industry from people living in communities surrounding plantations. Second, we evaluated the effectiveness of the SDM approach in a developing community context.     

Estimation of biogenic emissions with satellite-derived land use and land cover data for air quality modeling of Houston-Galveston ozone nonattainment area

The Houston-Galveston Area (HGA) is one of the most severe ozone non-attainment regions in the US. To study the effectiveness of controlling anthropogenic emissions to mitigate regional ozone nonattainment problems, it is necessary to utilize adequate datasets describing the environmental conditions that influence the photochemical reactivity of the ambient atmosphere. Compared to the anthropogenic emissions from point and mobile sources, there are large uncertainties in the locations and amounts of biogenic emissions. For regional air quality modeling applications, biogenic emissions are not directly measured but are usually estimated with meteorological data such as photo-synthetically active solar radiation, surface temperature, land type, and vegetation database. In this paper, we characterize these meteorological input parameters and two different land use land cover datasets available for HGA: the conventional biogenic vegetation/land use data and satellite-derived high-resolution land cover data. We describe the procedures used for the estimation of biogenic emissions with the satellite derived land cover data and leaf mass density information. Air quality model simulations were performed using both the original and the new biogenic emissions estimates. The results showed that there were considerable uncertainties in biogenic emissions inputs. Subsequently, ozone predictions were affected up to 10 ppb, but the magnitudes and locations of peak ozone varied each day depending on the upwind or downwind positions of the biogenic emission sources relative to the anthropogenic NOx and VOC sources. Although the assessment had limitations such as heterogeneity in the spatial resolutions, the study highlighted the significance of biogenic emissions uncertainty on air quality predictions. However, the study did not allow extrapolation of the directional changes in air quality corresponding to the changes in LULC because the two datasets were based on vastly different LULC category definitions and uncertainties in the vegetation distributions.     

Regional characteristics of land use in Northeast and Southern Blue Ridge Province: Associations with acid rain effects on surface-water chemistry

The Direct/Delayed Response Project (DDRP) is one of several studies being conducted by the United States Environmental Protection Agency to assess risk to surface waters from acidic deposition in the eastern United States. In one phase of DDRP, land use, wetland, and forest cover data were collected for statistical samples of 145 Northeast lake and 35 Southern Blue Ridge Province stream watersheds in the United States. Land-use and other data then were extrapolated from individual to target watershed populations. Project statistical design allows summarization of results for various subsets of the target population. This article discusses results and implications of the land-use and land-cover characterization for both regions. Forest cover was the primary land use in both regions. In the Northeast, developed (agriculture and urban) land was positively associated with surface-water chemistry values for acid neutralizing capacity, Ca plus Mg, pH, and sulfate in the Pocono/Catskill subregion. Extensive wetlands and beaver activity occur in parts of the Northeast region, whereas topography limits wetland and riparian development in the Southern Blue Ridge Province. Northeast soils have low sulfate adsorption capacity, most watersheds are near sulfur steady state, and lake sulfate concentrations are controlled principally by levels of sulfur deposition. Net annual sulfur retention in Northeast watersheds is positively correlated with occurrence of wetlands and beaver impoundments. In contrast, most Southern Blue Ridge Province soils have high sulfate adsorption capacities, resulting in high net watershed sulfur retention. At the present time, stream sulfate concentrations and percent sulfur retention are controlled principally by soil chemical properties related to adsorption rather than atmospheric deposition and land use. The information in this document has been funded wholly by the United States Environmental Protection Agency. It has been subjected to the agency's peer and administrative review, and it has been approved for publication as an EPA document. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.     

Nutrients and suspended solids in dry weather and storm flows from a tropical catchment with various proportions of rural and urban land use

The results of an investigation characterizing the nutrients and suspended solids contained in stormwater from Kranji Catchment in Singapore are reported in this paper. Stormwater samples were collected from 4 locations and analyzed for the following eleven analytes: TOC, DOC, TN, TDN, NH₄⁺, NO₂⁻ + NO₃⁻ (NO_x), TP, TDP, OP, SiO₂ and TSS. Stormwater was sampled from catchments with various proportions of rural and urban land use, including forested areas, grassed areas, agricultural and residential and commercial areas. The event mean concentrations (EMCs) of nutrients and TSS from sampling stations which have agricultural land use activities upstream were found to be higher. Comparison of site EMCs (SMCs) with published data showed that the SMCs of the nutrients and TSS are generally higher than SMCs reported for forested areas but lower than published SMCs for urban areas. Positive correlations (p < 5%) were found between loading and peak flow at locations most impacted by ubanisation or agricultural activities. Correlation between loading and rainfall variables was less distinct. EMC was found to correlate less with rainfall and flow variables compared to pollutant loading. Unlike loading, no consistent pattern exists linking EMC to any particular storm or flow variable in any of the catchments. Lastly, positive correlations were obtained between the particulate forms of nitrogen and phosphorus and TSS.     

Coherence between marine and land use planning: public attitudes to landscapes in the context of siting a wind park along the Latvian coast of the Baltic Sea

The aim of this paper is to contribute to coherence in marine, coastal and land use planning and management from the perspective of landscape values. At a time when new sea uses are emerging and marine spatial planning laws and regulations are being adopted, but have not yet been put into practice, research studies are required that provide spatial planners with informed insights concerning public stakeholder attitudes to controversial policies. The undertaken research explored the attitudes of two important social groups (local residents and tourists/recreational users) regarding locating wind parks in the marine and/or terrestrial environment along the Latvian coast of the Baltic Sea. The results of the study indicate that both groups support land-based wind park development versus offshore. Moreover, the visibility of wind turbines influences the willingness of tourists to visit recreation sites and impacts directly on their duration of stay. Research findings indicate that policy makers and spatial planners from both marine and land domains should adopt a broader and more integrated approach when setting priorities and allocating space for development activities where both domains are involved.     

Unveiling soil degradation and desertification risk in the Mediterranean basin: a data mining analysis of the relationships between biophysical and socioeconomic factors in agro-forest landscapes

Soil degradation and desertification processes in the Mediterranean basin reflect the interplay between environmental and socioeconomic drivers. An approach to evaluate comparatively the multiple relationships between biophysical variables and socioeconomic factors is illustrated in the present study using the data collected from 586 field sites located in five Mediterranean areas (Spain, Greece, Turkey, Tunisia and Morocco). A total of 47 variables were chosen to illustrate land-use, farm characteristics, population pressure, tourism development, rainfall regime, water availability, soil properties and vegetation cover, among others. A data mining approach incorporating non-parametric inference, principal component analysis and hierarchical clustering was developed to identify candidate syndromes of soil degradation and desertification risk. While field sites in the same study area showed a substantial similarity, the multivariate relationship among variables diverged among study areas. Data mining techniques proved to be a practical tool to identify spatial determinants of soil degradation and desertification risk. Our findings identify the contrasting spatial patterns for biophysical and socioeconomic variables, in turn associated with different responses to land degradation.