The Need for Scale Sensitive Approaches in Spatially Explicit Land Use Change Modeling

This paper introduces some of the issues that are relevant to the spatially explicit modeling of land use systems. A short overview is given of the ways and means in which a number of different land use change models describe the land use system. Specific attention is given to the empirical modeling approach used in the CLUE (Conversion of Land Use and its Effects) modeling framework. This approach is demonstrated for three case studies in China, Ecuador and the Atlantic Zone of Costa Rica. These case-studies illustrate the methodology for multi-scale analysis of land use driving factors and their application in spatially explicit modeling exercises. Model functioning, performance and limitations are discussed. The presented case-studies indicate that empirical modeling results can contribute to a better theoretic imbedding of land use change research in scale sensitive and integrated theories.     

Prediction models of CO, SPM and SO2 concentrations in the Campo de Gibraltar Region, Spain: a multiple comparison strategy

The 'Campo de Gibraltar' region is a very industrialized area where very few air pollution studies have been carried out. Up to date, no model has been developed in order to predict air pollutant levels in the different towns spread in the region. Carbon monoxide (CO), Sulphur dioxide (SO(2)) and suspended particulate matter (SPM) series have been investigated (years 1999-2000-2001). Multilayer perceptron models (MLPs) with backpropagation learning rule have been used. A resampling strategy with two-fold crossvalidation allowed the statistical comparison of the different models considered in this study. Artificial neural networks (ANN) models were compared with Persistence and ARIMA models and also with models based on standard Multiple Linear Regression (MLR) over test sets with data that had not been used in the training stage. The models based on ANNs showed better capability of generalization than those based on MLR. The designed procedure of random resampling permits an adequate and robust multiple comparison of the tested models. Principal component analysis (PCA) is used to reduce the dimensionality of data and to transform exogenous variables into significant and independent components. Short-term predictions were better than medium-term predictions in the case of CO and SO(2) series. Conversely, medium-term predictions were better in the case of SPM concentrations. The predictions are significantly promising (e.g., d (SPM 24-ahead) = 0.906, d (CO 1-ahead) = 0.891, d (SO2 1-ahead) = 0.851).     

Development of an integrated sensor to measure odors

Odorous air samples collected from several sources were presented to an olfactometer, an electronic nose, a hydrogen sulfide (H(2)S) detector and an ammonia (NH(3)) detector. The olfactometry measurements were used as the expected values while measurements from the other instrumentation values became input variables. Five hypotheses were established to relate the input variables and the expected values. Both linear regression and artificial neural network analyses were used to test the hypotheses. Principal component analysis was utilized to reduce the dimensionality of the electronic nose measurements from 33 to 3 without significant loss of information. The electronic nose or the H(2)S detector can individually predict odor concentration measurements with similar accuracy (R (2) = 0.46 and 0.50, respectively). Although the NH(3) detector alone has a very poor relationship with odor concentration measurements, combining the H(2)S and NH(3) detectors can predict odor concentrations more accurately (R (2) = 0.58) than either individual instrument. Data from the integration of the electronic nose, H(2)S, and NH(3) detectors produce the best prediction of odor concentrations (R (2) = 0.75). With this accuracy, odor concentration measurements can be confidently represented by integrating an electronic nose, and H(2)S and NH(3) detectors.     

Temporal and spatial variations of nutrients in the Ten Mile Creek of South Florida, USA and effects on phytoplankton biomass

Water quality throughout south Florida has been a major concern for many years. Nutrient enrichment in the Indian River Lagoon (IRL) is a major surface water issue and is suggested as a possible cause of symptoms of ecological degradation. In 2005-06, water samples were collected weekly from seven sites along Ten Mile Creek (TMC), which drains into the Indian River Lagoon, to investigate and analyze spatial and temporal fluctuations of nutrients nitrogen (N) and phosphorus (P). The objective of this study was to understand the relationships among chlorophyll a concentration, nutrient enrichment and hydrological parameters in the surface water body.High median concentrations of total P (TP, 0.272 mg L(-1)), PO4-P (0.122 mg L(-1)), and dissolved total P (DTP, 0.179 mg L(-1)); and total N (TN, 0.988 mg L(-1)), NO3(-)-N (0.104 mg L(-1)), NH4+-N (0.103 mg L(-1)), and total Kjeldahl N (TKN, 0.829 mg L(-1)), were measured in TMC. The concentrations of TP, PO4-P, DTP, TN, NO3(-)-N, NH4+-N, and TKN were higher in summer and fall than in winter and spring. However, chlorophyll a and pheophytin concentrations during this period in TMC varied in the range of 0.000-60.7 and 0.000-17.4 microg L(-1), with their median values of 3.54 and 3.02 microg L(-1), respectively. The greatest mean chlorophyll a (10.3 microg L(-1)) and pheophytin (5.71 microg L(-1)) concentrations occurred in spring, while the lowest chlorophyll a (1.49 microg L(-1)) and pheophytin (1.97 mug L(-1)) in fall. High concentrations of PO4-P (>0.16 mg L(-1)), DTP (>0.24 mg L(-1)), NO3(-)-N (>0.15 mg L(-1)), NH4+-N (>0.12 mg L(-1)), and TKN (>0.96 mg L(-1)), occurred in the upstream of TMC, while high concentrations of chlorophyll a (>6.8 mug L(-l)) and pheophytin (>3.9 microg L(-l)) were detected in the downstream of TMC. The highest chlorophyll a (11.8 mug L(-l)) and pheophytin (6.06 microg L(-l)) concentrations, however, were associated with static and open water conditions. Hydrological parameters (total dissolved solid, electrical conductivity, salinity, pH, and water temperature) were positively correlated with chlorophyll a and pheophytin concentrations (P < 0.01) and these factors overshadowed the relationships between N and P concentrations and chlorophyll a under field conditions. Principal component analysis and the ratios of DIN/DP and TN/TP in the water suggest that N is the limiting nutrient factor for phytoplankton growth in the TMC and elevated N relative to P is beneficial to the growth of phytoplankton, which is supported by laboratory culture experiments under controlled conditions.     

Magnesium hydroxide bulk and colloid-associated 152Eu in an alkaline environment: colloid characterisation and sorption properties in the presence and absence of carbonate

The distribution of 152Eu between magnesium hydroxide bulk, colloids and solution has been assessed under alkaline conditions, such as those in nuclear fuel storage ponds. The colloidal phase has been characterised by two complementary methods: coupled ultrafiltration-ICP-AES and scanning electron microscopy. The quantity and the size distribution of the colloidal phase is strongly ionic strength-dependent. A decrease of the quantity of colloids, in particular the larger size ranges, has been observed with increasing ionic strength. Small colloids (1 kDa-10 kDa fraction) are predominant at all ionic strengths. The morphology of colloids, observed by field-emission gun scanning electron microscopy, appears to change from hexagonal prismatic (characteristic to the mineral) to spherical (energetically more favourable) as size decreases. The distribution of 152Eu between the solid and liquid/colloidal phases has been investigated at carbonate concentrations ranging from 0 to 10(-2) M by coupled ultrafiltration and gamma-spectrometry. Mg(OH)2 bulk appears to be a very strong sorbent for 152Eu, since complete sorption onto the bulk happens for carbonate concentrations as high as 10(-3) M. Scavenging of 152Eu by Mg(OH)2 colloids is negligible in the presence of Mg(OH)2 bulk. The distribution of 152Eu between liquid and colloidal phases has been investigated in the absence of bulk at various carbonate concentrations. A significant uptake of 152Eu by the colloids in solution has been observed, which decreases with increasing carbonate concentration. 152Eu appears to be mainly associated to the smallest colloids (1 kDa-10 kDa fraction). There is a strong correlation between the sorption properties and the surface area of the colloids.     

Preliminary assessment of polybrominated diphenyl ethers (PBDEs) in the Scottish aquatic environment, including the Firth of Clyde

This paper presents preliminary data on polybrominated diphenyl ethers (PBDEs) in the Scottish aquatic environment. Sediment and biota (fish liver, fish muscle and mussels) from a number of locations around Scotland were analysed for PBDEs with samples being from both remote and from potentially contaminated areas such as the former sewage sludge dump site at Garroch Head in the Clyde. PBDEs were measured in both cultivated, rope grown mussels and wild mussels collected from 5 sites around Scotland in 2006. Total PBDE concentrations (sum of tri- to hepta-BDEs) ranged from 相似文献   

A Model for Landscape Planning Under Complex Spatial Conditions

We present a new mathematical programming framework that is adaptable to a variety of spatially explicit landscape problems in environmental investment, conservation, and land-use planning, transport planning, and agriculture. As part of capturing spatial interdependencies, the framework considers decision variables at two levels, finely spaced grid cells and landholdings. We applied the framework to an environmental investment problem using objective functions representing biodiversity and carbon sequestration. We also tested the model to optimize the path of a road through part of the landscape. Using the Nambucca case study in eastern Australia, we applied a hybrid greedy randomised adaptive search procedure (GRASP) to find solutions to the model.     

Development and Parameterization of a Rain- and Fire-driven Model for Exploring Elephant Effects in African Savannas

We describe the development and parameterization of a grid-based model of African savanna vegetation processes. The model was developed with the objective of exploring elephant effects on the diversity of savanna species and structure, and in this formulation concentrates on the relative cover of grass and woody plants, the vertical structure of the woody plant community, and the distribution of these over space. Grid cells are linked by seed dispersal and fire, and environmental variability is included in the form of stochastic rainfall and fire events. The model was parameterized from an extensive review of the African savanna literature; when available, parameter values varied widely. The most plausible set of parameters produced long-term coexistence between woody plants and grass, with the tree–grass balance being more sensitive to changes in parameters influencing demographic processes and drought incidence and response, while less sensitive to fire regime. There was considerable diversity in the woody structure of savanna systems within the range of uncertainty in tree growth rate parameters. Thus, given the paucity of height growth data regarding woody plant species in southern African savannas, managers of natural areas should be cognizant of different tree species growth and damage response attributes when considering whether to act on perceived elephant threats to vegetation.     

Quantitative arsenic speciation in two species of earthworms from a former mine site

The relationship between the total arsenic concentration and the chemical speciation of arsenic in two species of earthworm (Lumbricus rubellus and Dendrodrilus rubidus) in relation to the host soil, was investigated for 13 sites of varying arsenic content, including a background level garden soil and a former mine site at the Devon Great Consols, UK. Earthworms were collected with the host soil (As soil concentration range 16-12, 466 mg kg(-1) dry weight) and measured for their total arsenic (concentration range 7-595 mg kg(-1) dry weight) using inductively coupled plasma mass spectrometry (ICP-MS). A methanol-water mixture was used to extract arsenic species from the earthworms prior to determination of the individual arsenic species by a combination of anion and cation exchange high performance liquid chromatography coupled to inductively coupled plasma mass spectrometry (HPLC-ICP-MS). A gradient elution anion exchange method is presented whereby nine arsenic species could be measured in one sample injection. Arsenic species were identified by comparison of retention times and sample spiking with known standards and a fully characterised seaweed extract. Arsenic was generally present in the earthworm as arsenate (As(V)) or arsenite (As(III)) and arsenobetaine (AB). Methylarsonate (MA), dimethylarsinate (DMA) and three arsenosugars (glycerol, phosphate, sulfate) were present as minor constituents. These results are discussed in relation to the mechanisms for coping with exposure to soil bound arsenic.