North East Scotland River Catchment Nitrate Loading in Relation to Agricultural Intensity

Modern agricultural practices have been strongly linked with increased NO₃-N loadings in surface waters. Nitrate leaching increases as land use progresses from forest and moorland through grassland, to arable agriculture. There are, within the UK, few studies on a regional scale capable of displaying a relationship between land cover (agricultural intensity) and water quality. This relationship can be investigated using computer manipulation of spatial geographic information together with conventional river and agricultural census data.

Simple regression analysis against primary land cover suggests that agriculture is reponsible for annual losses of nitrate in North East Scotland river catchments. Further multi-linear regression analysis, using the GIS data and agricultural census returns indicate that most of the outstanding variation can be accounted for if the agricultural variable is related to agricultural practice, such as spring, winter and grass cropping.     

Parcels versus pixels: modeling agricultural land use across broad geographic regions using parcel-based field boundaries

Land use and land cover (LULC) change occurs at a local level within contiguous ownership and management units (parcels), yet LULC models primarily use pixel-based spatial frameworks. The few parcel-based models being used overwhelmingly focus on small geographic areas, limiting the ability to assess LULC change impacts at regional to national scales. We developed a modified version of the Forecasting Scenarios of land use change model to project parcel-based agricultural change across a large region in the United States Great Plains. A scenario representing an agricultural biofuel scenario was modeled from 2012 to 2030, using real parcel boundaries based on contiguous ownership and land management units. The resulting LULC projection provides a vastly improved representation of landscape pattern over existing pixel-based models, while simultaneously providing an unprecedented combination of thematic detail and broad geographic extent. The conceptual approach is practical and scalable, with potential use for national-scale projections.     

Hierarchical Bayesian scaling of soil properties across urban, agricultural, and desert ecosystems.

Ecologists increasingly use plot-scale data to inform research and policy related to regional and global environmental change. For soil chemistry research, scaling from the plot to the region is especially difficult due to high spatial variability at all scales. We used a hierarchical Bayesian model of plot-scale soil nutrient pools to predict storage of soil organic carbon (oC), inorganic carbon (iC), total nitrogen (N), and available phosphorus (avP) in a 7962-km2 area including the Phoenix, Arizona, USA, metropolitan area and its desert and agricultural surroundings. The Bayesian approach was compared to a traditional approach that multiplied mean values for urban mesic residential, urban xeric residential, nonresidential urban, agricultural, and desert areas by the aerial coverage of each land-use type. Both approaches suggest that oC, N, and avP are correlated with each other and are higher (in g/m2) in mesic residential and agricultural areas than in deserts or xeric residential areas. In addition to traditional biophysical variables, cultural variables related to impervious surface cover, tree cover, and turfgrass cover were significant in regression models predicting the regional distribution of soil properties. We estimate that 1140 Gg of oC have accumulated in human-dominated soils of this region, but a significant portion of this new C has a very short mean residence time in mesic yards and agricultural soils. For N, we estimate that 130 Gg have accumulated in soils, which explains a significant portion of "missing N" observed in the regional N budget. Predictions for iC differed between the approaches because the Bayesian approach predicted iC as a function of elevation while the traditional approach employed only land use. We suggest that Bayesian scaling enables models that are flexible enough to accommodate the diverse factors controlling soil chemistry in desert, urban, and agricultural ecosystems and, thus, may represent an important tool for ecological scaling that spans land-use types. Urban planners and city managers attempting to reduce C emissions and N pollution should consider ways that landscape choices and impervious surface cover affect city-wide soil C, N, and P storage.     

A Bayesian network approach to modelling land-use decisions under environmental policy incentives in the Brazilian Amazon

ABSTRACT

Deforestation driven by agricultural expansion is a major threat to the biodiversity of the Amazon Basin. Modelling how deforestation responds to environmental policy implementation has thus become a policy relevant scientific undertaking. However, empirical parameterization of land-use/cover change (LUCC) models is challenging due to the high complexity and uncertainty of land-use decisions. Bayesian Network (BN) modelling provides an effective framework to integrate various data sources including expert knowledge. In this study, we integrate remote sensing products with data from farm-household surveys and a decision game to model LUCC at the BR-163, in Brazil. Our ‘business as usual’ scenario indicates cumulative forest cover loss in the study region of 8,000 km² between 2014 and 2030, whereas ‘intensified law-enforcement’ would reduce cumulative deforestation to 1,600 km² over the same time interval. Our findings underline the importance of conservation law enforcement in modulating the impact of agricultural market incentives on land cover change.     

Can the 2050 zero land take objective of the EU be reliably monitored? A comparative study

The European Union has defined an ambitious objective for the future concerning sustainable land use to stop the process of land take by 2050. But can this objective be reliably monitored? In this paper, which is based on the case study of Luxembourg and the neighbouring regions, we show that the tools that are used to monitor land-take produce different results that prevent from comparing the figures from one region to another. Moreover, a comparison of the strategic documents related to land use in this cross-border region shows that land-use policies are the product of very different contexts and relationships towards land as a resource, which need to be addressed with tailored strategies.     

The role of the rural settlements in the Brazilian savanna deforesting process

Although the drivers of deforestation in Brazil are relatively well known, there is still limited understanding of the role of family farm-based rural settlements in land cover changes, particularly in the Brazilian savanna. This research aims to identify land use patterns within rural settlements and examine how they are influenced by regional dynamics. The study is based on GIS techniques and satellite image classification (Landsat 5-TM and RapidEye imagery), combined with geo-referenced fieldwork data in three different regions of the State of Goiás. The results reveal that the deforestation arrangement within the studied rural settlements is very similar to the deforestation found in the surrounding regions. As a positive outcome, the rural settlements have a higher share of remnant vegetation when compared to the surrounding areas, but this is still concentrated within legal reserves. We conclude that the changing patterns of rural settlement land cover are highly influenced by regional dynamics.     

Developing indicators for assessing land-use sustainability in a tropical agro-ecosystem: The case of Sakaekrang watershed,Thailand

While the concept of sustainable land management is now widely accepted, there remains considerable scope for developing location-specific land-use indicators for sustainability evaluation. A study was conducted to investigate the indicators of land-use sustainability in the context of tropical agro-ecosystems using the case of Sakaekrang watershed, Thailand. The biophysical data were generated from Geographic Information Systems (GIs) and the socioeconomic data were collected through a field survey. In the light of sustainable land management objectives, a total of 32 criteria were considered in the analysis to determine land-use sustainability and identify indicators that best explain the sustainability level. About one quarter of the agricultural area in the watershed meets the sustainability threshold, indicating a substantial unstable area in the watershed. Among 11 indicators that showed a significant relationship with the computed land-use sustainability, land quality, source of farm income, and evapo transpiration were the most important.     

Quantifying inconsistencies in old cadastral maps and their impact on land-use reconstructions

ABSTRACT

Old cadastral maps represent a historical reference dataset for long-term land-use reconstructions. This study presents identification of inconsistencies in the nineteenth century Franziscean cadastre, one of the largest sets of old cadastral maps worldwide, by comparing three versions of the maps and written documents created in the same period. We identified all parcels and their land-use in the four sub-sources in six study areas. The overall share of inconsistencies among 5 771 identified parcels is 7.4%, with the biggest share of inconsistency in agroforestry and forestry classes. The most frequent inconsistencies are of ‘Not differentiable land use’ (n = 212) and ‘Different land-use’ categories across the sub-sources (n = 113). We conclude that the frequency of uncertainties in old cadastral maps may limit the validity of historical land-use reconstructions, affecting the eventual restoration and management efforts based on such data. We provide a summary for the use of Franziscean cadastre.     

Studying crop sequences with CarrotAge,a HMM-based data mining software

We have developed a knowledge discovery system based on high-order hidden Markov models for analyzing spatio-temporal data bases. This system, named CarrotAge , takes as input an array of discrete data – the rows represent the spatial sites and the columns the time slots – and builds a partition together with its a posteriori probability. CarrotAge has been developed for studying the cropping patterns of a territory. It uses therefore an agricultural drench database, named Ter-Uti , which records every year the land-use category of a set of sites regularly spaced. The results of CarrotAge are interpreted by agronomists and used in research works linking agricultural land use and water management. Moreover, CarrotAge can be used to find out and study crop sequences in large territories, that is a main question for agricultural and environmental research, as discussed in this paper.     

Forest Management Patterns in the Floodplain of the Amazon Estuary

In the Amazon basin, few studies have focused on environmentally sound land-use alternatives that are linked to markets. This paper analyzes land uses carried out by traditional inhabitants ( ribeirinhos ) on three islands in the Amazon estuary. Management of the native floodplain forest is the most extensive form of land use on these islands. Such management varies in response to local economic and ecological conditions but invariably targets key nontimber forest resources destined for local markets, requires minimal input of labor and capital, and maintains a considerable stock of biotic resources. While restricted to a specific forest type, this form of land use is associated with relatively high population densities and, if supported by appropriate development policies, could provide an environmentally sound land-use alternative for hundreds of thousands of rural inhabitants of Amazonia.     

Modeled historical land use and land cover for the conterminous United States

The landscape of the conterminous United States has changed dramatically over the last 200 years, with agricultural land use, urban expansion, forestry, and other anthropogenic activities altering land cover across vast swaths of the country. While land use and land cover (LULC) models have been developed to model potential future LULC change, few efforts have focused on recreating historical landscapes. Researchers at the US Geological Survey have used a wide range of historical data sources and a spatially explicit modeling framework to model spatially explicit historical LULC change in the conterminous United States from 1992 back to 1938. Annual LULC maps were produced at 250-m resolution, with 14 LULC classes. Assessment of model results showed good agreement with trends and spatial patterns in historical data sources such as the Census of Agriculture and historical housing density data, although comparison with historical data is complicated by definitional and methodological differences. The completion of this dataset allows researchers to assess historical LULC impacts on a range of ecological processes.     

Using earth observation data from multiple sources to map rare habitats in a coastal conservation area

Kenfig NNR (National Nature Reserve) is a coastal sand dune system in south Wales, UK. The site is an important location for the conservation of the fen orchidLiparis loeselii, a significant proportion of the UK population is found solely on the site. Approaches to the mapping and monitoring of the habitats at Kenfig NNR using EO (Earth Observation) methods are investigated. Typical airborne EO missions over such sites produce more than a single source of EO data; these may include various optical imaging sensors with different spectral ranges, film cameras and ranging devices to measure topography. Conservation managers are thus presented with the problem of which sources of data to use when producing a land cover map of the site of interest. Using a data set gathered over the Kenfig NNR site, we investigate land cover mapping methods for conservation. The land cover types of interest typically cover small areas within a much larger site so they present a hard problem for the EO data and associated classification methods to solve. Land cover classifications produced from the data sets provide a set of competing hypotheses of land cover type for the site. Methods we use to resolve this competition between the data sets include voting methods, data fusion methods and a method utilising fuzzy logic to aggregate information. This paper is intended to act as an introduction to some of the issues involved in using EO data for habitat mapping in highly heterogeneous coastal dune environments and to present some preliminary results of the performance of each method.     

Economic-based projections of future land use in the conterminous United States under alternative policy scenarios

Land-use change significantly contributes to biodiversity loss, invasive species spread, changes in biogeochemical cycles, and the loss of ecosystem services. Planning for a sustainable future requires a thorough understanding of expected land use at the fine spatial scales relevant for modeling many ecological processes and at dimensions appropriate for regional or national-level policy making. Our goal was to construct and parameterize an econometric model of land-use change to project future land use to the year 2051 at a fine spatial scale across the conterminous United States under several alternative land-use policy scenarios. We parameterized the econometric model of land-use change with the National Resource Inventory (NRI) 1992 and 1997 land-use data for 844 000 sample points. Land-use transitions were estimated for five land-use classes (cropland, pasture, range, forest, and urban). We predicted land-use change under four scenarios: business-as-usual, afforestation, removal of agricultural subsidies, and increased urban rents. Our results for the business-as-usual scenario showed widespread changes in land use, affecting 36% of the land area of the conterminous United States, with large increases in urban land (79%) and forest (7%), and declines in cropland (-16%) and pasture (-13%). Areas with particularly high rates of land-use change included the larger Chicago area, parts of the Pacific Northwest, and the Central Valley of California. However, while land-use change was substantial, differences in results among the four scenarios were relatively minor. The only scenario that was markedly different was the afforestation scenario, which resulted in an increase of forest area that was twice as high as the business-as-usual scenario. Land-use policies can affect trends, but only so much. The basic economic and demographic factors shaping land-use changes in the United States are powerful, and even fairly dramatic policy changes, showed only moderate deviations from the business-as-usual scenario. Given the magnitude of predicted land-use change, any attempts to identify a sustainable future or to predict the effects of climate change will have to take likely land-use changes into account. Econometric models that can simulate land-use change for broad areas with fine resolution are necessary to predict trends in ecosystem service provision and biodiversity persistence.     

Identification of agricultural factors for improving sustainable land resource management in northern Thailand: A case study in Chiang Mai Province

This paper aims to identify the land-use factors benefiting sustainable land management in terms of environmental conservation. For evaluating the impacts of land use on the environment, the following parameters were used: chemical fertiliser and pesticide use, land-use structure and diversity. The farmers' income, land tenure and farming scale were selected for their influence on agricultural sustainability. The analysis shows a rapid increase in use of chemical fertiliser and pesticide in the past 40 years, and an observable increase in land-use diversity. The amount of chemical fertiliser used per unit area in large-scale farming was lower than that at small scales, but large-scale farming consumes more pesticide than small-scale farming. A significant negative correlation was observed between the proportions of the holdings possessing land and the holdings using the chemical fertiliser. In order to achieve sustainable agriculture, it is necessary to manage crop systems and land use towards selecting new strains and varieties of crops and fruits with a lower demand for chemical fertiliser and a higher resistance to disease and pests, balancing large- and small-scale farming, and ensuring land tenure and economic incentives.     

Projecting landscape changes in southern Chile: Simulation of human and natural processes driving land transformation

We describe a simulation model representing the most important human and natural factors driving land use and cover changes (LUCC) in southern Chile. We evaluate the model by examining its ability to simulate LUCC observed over the past three decades, conduct a sensitivity analysis of simulated trends to changes in important model parameters, and use the model to project likely landscape transformations over the next decade under “as usual,” “pessimistic,” and four “optimistic” scenarios. The model consists of five submodels representing LUCC on two distinct soil formations (volcanic ash and gleysols) and four major land use categories: native forest, agricultural land, shrubland, and urban land. Land use and cover sub-categories include old growth forests, secondary forests, and low and flooded shrubland. The model simulated well general historic trends in forest cover, agricultural land, shrubland, and urban land: from a forest-dominated landscape in 1976 to a landscape dominated by shrubland and agricultural land by 2007. Forest loss, forest degradation by logging and clearing for agriculture were the most important direct drivers of LUCC: forest logging and clearing were most important from 1976 to 1985, whereas after 1985 logging for firewood, driven by population growth, was most important. Sensitivity analysis indicated that model projections of general trends in the main land use and cover categories were not overly sensitive to changes in important model parameters, although further study is necessary to improve our estimates of the proportion of pasture requirements supplied by clearing low shrubland. Projections of LUCC suggested that a reduced amount of secondary forest would be left by 2017 if no actions are taken to reduce forest loss (“as usual”). Increasing population (“pessimistic scenario”) resulted in similar trajectories than those predicted by the as usual scenario, whereas reducing logging for firewood and increasing forest recruitment from shrubland could reduce loss of native forest by nearly one-third (“optimistic scenarios”). Surprisingly, shrubland exhibited the most complex and influential dynamics in all scenarios, being the immediate outcome of forest loss and the main long-term source of land for agriculture, urban expansion, and forest recovery. Few studies in Chile, or elsewhere, have considered the importance of this intermediate successional stage. Of the scenarios simulated, financial incentives targeted toward channeling shrubland into regenerated forest seemed most promising, although obstacles to such a management strategy exist.     

Rainfall-human-spatial interactions in a salinity-prone agricultural region of the Western Australian wheat-belt

To explore the complexity of temporal and spatial dynamics of an agricultural landscape under various external and internal driven scenarios, SimKat, an agent-based model, has been developed with the simulation computer program CORMAS. This model combines simplified bio-physical processes of land cover, regional dry-land salinity changes, rainfall impact on productivity, farm profitability and the complexity of land-use decisions of individual farmers in a dry-land agricultural catchment (no irrigation). In this model, simulated farmers formulate individual decisions dealing with land-use changes based on the combined performance of their past land cover productivity and market returns. The willingness to adapt to market drivers and the ability to maximize returns vary between farmers. In addition, farmers in the model can demonstrate various attitudes towards dry-land salinity mitigation as a consequence of experiencing and perceiving salinity on their farm, in the neighborhood or across the entire region. Consequently, farmers can adopt land cover strategies aimed at reducing dry-land salinity. Aggregating the simulated individual behavior of farmers combined with historical rainfall and market price records, reproduced similar aggregated trends of land-cover changes, regional salinity change and farm number decline as observed in the last 20 years in the subject region (Katanning, Western Australia). Using the model in an initial exploratory study on the impact of rainfall variability and change highlighted the importance of average rainfall decline and the widespread willingness of farmers to adapt perennial vegetation in their farming systems to combat regional dry-land salinity. Rainfall decline, as one of the observed consequences of climate change in this region, can also lead to prolonged sequences of dry seasons in the future. Adaptation by farmers to sequences of dry and wet seasons, rather than an average trend in rainfall, seems to be critical for farm survival in this region. Intensifying cropping during wet seasons to maximize farm returns can increase vulnerability in subsequent periods of dry seasons, in particular where alternative income from pasture and sheep production has been lost in the adaptation process.     

Effect of Widespread Agricultural Chemical Use on Butterfly Diversity across Turkish Provinces

Although agricultural intensification is thought to pose a significant threat to species, little is known about its role in driving biodiversity loss at regional scales. I assessed the effects of a major component of agricultural intensification, agricultural chemical use, and land‐cover and climatic variables on butterfly diversity across 81 provinces in Turkey, where agriculture is practiced extensively but with varying degrees of intensity. I determined butterfly species presence in each province from data on known butterfly distributions and calculated agricultural chemical use as the proportion of agricultural households that use chemical fertilizers and pesticides. I used constrained correspondence analyses and regression‐based multimodel inference to determine the effect of environmental variables on species composition and richness, respectively. The variation in butterfly species composition across the provinces was largely explained (78%) by the combination of agricultural chemical use, particularly pesticides, and climatic and land‐cover variables. Although overall butterfly richness was primarily explained by climatic and land‐cover variables, such as the area of natural vegetation cover, threatened butterfly richness and the relative number of threatened butterfly species decreased substantially as the proportion of agricultural households using pesticides increased. These findings suggest that widespread use of agricultural chemicals, or other components of agricultural intensification that may be collinear with pesticide use, pose an imminent threat to the biodiversity of Turkey. Accordingly, policies that mitigate agricultural intensification and promote low‐input farming practices are crucial for protecting threatened species from extinction in rapidly industrializing nations such as Turkey. Efectos del Uso Extensivo de Agroquímicos sobre la Diversidad de Mariposas en Provincias Turcas     

Accounting for monogastric livestock as a driver in global land use and cover change assessments

Land systems are described based on various characteristics, including land cover composition and agricultural production. However, it is uncertain to what extent livestock, particularly monogastric livestock, determines land systems. We included monogastrics in a land system classification, and statistically analyzed the land cover composition and agricultural production of otherwise similar land systems with and without monogastric livestock. The results indicate that land systems with monogastrics are statistically different from their counterparts in the classification without monogastrics in terms of grassland area and crop yields, but are less different in terms of tree area, crop area, and ruminant livestock production. We then used a land systems map that includes monogastrics in the classification and a similar map that does not include monogastrics to project future changes in a novel manner that integrates livestock as a determinant of land systems. The results show that including monogastrics in otherwise similar projections yields less cropland intensification and more cropland expansion in several world regions, including Northern Africa and the Middle East. Other regions, such as Europe and Australia, were characterized by less decrease or more increase in tree area in the application with monogastrics, mainly due to the occurrence of open forests with monogastrics. This study prompts a call for improved characterization of land systems for land use and cover change (LUCC) assessments in order to better represent LUCC driven by monogastric livestock.     

Industrial development and land use/cover change and their effects on local environment: a case study of Changshu in eastern coastal China

The interactions among industrial development, land use/cover change (LUCC), and environmental effects in Changshu in the eastern coastal China were analyzed using high-resolution Landsat TM data in 1990, 1995, 2000, and 2006, socio-economic data and water environmental quality monitoring data from research institutes and governmental departments. Three phases of industrial development in Changshu were examined (i.e., the three periods of 1990 to 1995, 1995 to 2000, and 2000 to 2006). Besides industrial development and rapid urbanization, land use/cover in Changshu had changed drastically from 1990 to 2006. This change was characterized by major replacements of farmland by urban and rural settlements, artificial ponds, forested and constructed land. Industrialization, urbanization, agricultural structure adjustment, and rural housing construction were the major socio-economic driving forces of LUCC in Changshu. In addition, the annual value of ecosystem services in Changshu decreased slightly during 1990–2000, but increased significantly during 2000–2006. Nevertheless, the local environmental quality in Changshu, especially in rural areas, has not yet been improved significantly. Thus, this paper suggests an increased attention to fully realize the role of land supply in adjustment of environment-friendly industrial structure and urban-rural spatial restructuring, and translating the land management and environmental protection policies into an optimized industrial distribution and land-use pattern.     

Satellite detection of bird communities in tropical countryside.

The future of biodiversity hinges partly on realizing the potentially high conservation value of human-dominated countryside. The characteristics of the countryside that promote biodiversity preservation remain poorly understood, however, particularly at the fine scales at which individual farmers tend to make land use decisions. To address this problem, we explored the use of a rapid remote sensing method for estimating bird community composition in tropical countryside, using a two-step process. First, we asked how fine-grained variation in land cover affected community composition. Second, we determined whether the observed changes in community composition correlated with three easily accessible remote sensing metrics (wetness, greenness, and brightness), derived from performing a tasseled-cap transformation on a Landsat Enhanced Thematic Mapper Plus image. As a comparison, we also examined whether the most commonly used remote sensing indicator in ecology, the Normalized Difference Vegetation Index (NDVI), correlated with community composition. We worked within an agricultural landscape in southern Costa Rica, where the land comprised a complex and highly heterogeneous mosaic of remnant native vegetation, pasture, coffee cultivation, and other crops. In this region, we selected 12 study sites (each < 60 ha) that encompassed the range of available land cover possibilities in the countryside. Within each site, we surveyed bird communities within all major land cover types, and we conducted detailed field mapping of land cover. We found that the number of forest-affiliated species increased with forest cover and decreased with residential area across sites. Conversely, the number of agriculture-affiliated species using forest increased with land area devoted to agricultural and residential uses. Interestingly, we found that the wetness and brightness metrics predicted the number of forest- and agriculture-affiliated species within a site as well as did detailed field-generated maps of land cover. In contrast, NDVI and the closely correlated greenness metric did not correlate with land cover or with bird communities. Our study shows the strong potential of the tasseled-cap transformation as a tool for assessing the conservation value of countryside for biodiversity.