Land Use Composition Research Articles

The effects of spatial survey bias and habitat suitability on predicting the distribution of threatened species living in remote areas

SummaryKnowledge of a species’ potential distribution and the suitability of available habitat are fundamental for effective conservation planning and management. However, the quality of information on the distribution of species and their required habitats is highly variable in terms of accuracy and availability across taxa and regions, particularly in tropical landscapes where accessibility is especially challenging. Species distribution models (SDMs) provide predictive tools for addressing gaps for poorly surveyed species, but they rarely consider biases in geographical distribution of records and their consequences. We applied SDMs and variation partitioning analyses to investigate the relative importance of habitat characteristics, human accessibility, and their joint effects in the global distribution of the Critically Endangered Blue-throated MacawAra glaucogularis, a species endemic to the Amazonian flooded savannas of Bolivia. The probability of occurrence was skewed towards more accessible areas, mostly secondary roads. Variability in observed occurrence patterns was mostly accounted for by the pure effect of habitat characteristics (76.2%), indicating that bias in the geographical distribution of occurrences does not invalidate species-habitat relationships derived from niche models. However, observed spatial covariation between land-use at a landscape scale and accessibility (joint contribution: 22.3%) may confound the independent role of land-use in the species distribution. New surveys should prioritise collecting data in more remote (less accessible) areas better distributed with respect to land-use composition at a landscape scale. Our results encourage wider application of partitioning methods to quantify the extent of sampling bias in datasets used in habitat modelling for a better understanding of species-habitat relationships, and add insights into the potential distribution of our study species and opportunities for its conservation.

Contemporary Composition of Land Use, Ecosystems, and Conservation Status along the Lewis and Clark National Historic Trail

The national historic trails in the National Trails System of the United States are designated with the purpose of identifying and protecting historic routes and their artifacts for public use and enjoyment. In 1978, the Lewis and Clark National Historic Trail was established to commemorate the expedition of 1804–1806 through preservation of historical, cultural, and natural resources. We conducted a quantitative assessment of the condition and character of the landscape immediately surrounding the Trail. Specifically, we investigated the composition of land cover and status of vegetation condition, as well as the proportions of the trail passing through federal, state, and private ownership with various levels of conservation protections. We used a national index of “wildness” (i.e., ecological condition and impact of human development) to summarize landscape qualities and identify the wildest sections along the Trail. Much of the Trail has been altered through agricultural development and land use, but several areas remain relatively wild. Most of the Trail passes through land with no known conservation strategy and very little passes through wilderness or national parks. We did identify several areas where the Trail passes through existing federal land administered as “roadless” where permanent legislative protections could ensure the remaining wild and intact lands be preserved for future generations.

Potential use of ionic species for identifying source land-uses of stormwater runoff

Identifying critical land-uses or source areas is important to prioritize resources for cost-effective stormwater management. This study investigated the use of information on ionic composition as a fingerprint to identify the source land-use of stormwater runoff. We used 12 ionic species in stormwater runoff monitored for a total of 20 storm events at five sites with different land-use compositions during the 2012-2014 wet seasons. A stepwise forward discriminant function analysis (DFA) with the jack-knifed cross validation approach was used to select ionic species that better discriminate the land-use of its source. Of the 12 ionic species, 9 species (K+, Mg2+, Na+, NH4+, Br-, Cl-, F-, NO2-, and SO42-) were selected for better performance of the DFA. The DFA successfully differentiated stormwater samples from urban, rural, and construction sites using concentrations of the ionic species (70%, 95%, and 91% of correct classification, respectively). Over 80% of the new data cases were correctly classified by the trained DFA model. When applied to data cases from a mixed land-use catchment and downstream, the DFA model showed the greater impact of urban areas and rural areas respectively in the earlier and later parts of a storm event.

Effects of local and landscape factors on exotic vegetation in the riparian zone of a regulated river: Implications for reservoir conservation

Riparian zones of regulated rivers are susceptible to species invasion due to a variety of anthropogenic disturbances. Adjacent land use and landscape patterns may be significant drivers in this process in conjunction with direct effects of flow regulation. Understanding different influences on invasion is necessary for regional landscape management. Here we explored the effects of local and adjacent landscape factors on exotic vegetation distribution along the Pengxi River controlled by the Three Gorges Dam. Vegetation data were collected in 5×1m quadrats along transect lines perpendicular to the riverbank between 172m and 178m elevation. A total of 21 exotic herbs were found, accounting for 11.3% of all identified taxa. There was greater exotic species richness below 175m zone directly affected by reservoir flooding. Variation partitioning indicated that landscape structure played a more important role in explaining the degree of invasion than did local variables. As expected, the landscape subgroup “landscape composition” appeared to be more influential than “landscape configuration”. Hierarchical partitioning showed that overall invasion increased with increasing adjacent agricultural land uses and flooding presence, but decreased with greater distance to human impacts. Given that re-regulation of the reservoir flow regime is unlikely at this time, we support a landscape approach to riparian vegetation management, where the nature and impacts of the surrounding landscape matrix, and the particular composition and forms of land use and human activity should be considered. Suggestions include establishing buffer reserves, reclaiming abandoned agricultural land, and stricter urban greening regulations.

Modelling and mapping the economic value of supplemental irrigation in a humid climate

Irrigation is an essential component of crop production to meet retailer demands for premium quality when rainfall is insufficient. Under drought conditions, irrigation can be constrained by water resources availability, with consequent impacts on yield, quality and revenue. Whilst most agriculture in Europe is rainfed, greater dependence on supplemental irrigation could become more important in humid environments due to a changing climate with greater rainfall uncertainty and higher frequency of droughts. By combining industry and farm level economic data, with geospatial information on agricultural land use, agroclimate, soils and irrigation practices within a GIS, this paper estimates the total financial benefit of outdoor irrigated production in England and Wales assuming no constraints in resource availability and optimal irrigation practices. The analysis suggests that the total net benefits of irrigation in a ‘design’ dry year are around £665 million, with an average irrigation water productivity in excess of £3.3 per m3 (close to £1.1 per m3 excluding soft fruit). Map outputs highlight significant regional differences in water productivity reflecting the composition of land use and the importance of crop mix in determining economic value. A sensitivity analysis to changes in agroclimate, market conditions (crop prices) and water supply (costs) illustrates how the benefits might change under contrasting scenario. The study highlights the importance of supplemental irrigation, even in a humid climate, and the risks that future droughts and/or constraints in water resource availability might have on agricultural systems, livelihoods and the rural economy. The implications for water resources and drought management are discussed.

Implementing Effective Monitoring Sites for Emerging Contaminants from the Assessment of Their Critical Areas: Comparative Studies of Multiple Watersheds in the United States

AbstractEmerging contaminants traditionally have not been measured in the environment, but they recently have been detected in various water systems as a result of advancements in analytical methods. These contaminants pose potential threats to ecosystems and public health, but are generally not regulated, nor are they required to be routinely monitored. This paper presents the implementation of watershed-scale monitoring-site selection as an effective monitoring design for emerging contaminants. The study aimed to identify critical areas of emerging contaminants for both point and nonpoint sources in five selected watersheds in the United States with different land-use compositions and climate conditions. Spatial association analysis using the Getis-Ord’s Gi* statistic was employed to identify clusters of point and nonpoint emerging contaminants considering the impact of neighboring subwatersheds. This analysis identified subbasins containing major wastewater treatment systems as point-source hotspots an...

Application of partial least squares regression and WetSpa model to determine factors controlling sediment yield in Chardavol watershed, Iran

This paper examines the effects of watershed complexity in terms of physiography and land use on the specific sediment yield of the Chardavol watershed (1012.946 km2) in Iran. First, specific sediment yield was simulated using spatially distributed hydrological WetSpa model, then the influential factors such as morphometric variables, land-use composition and pattern and soil properties of the watershed were calculated at the sub-watershed scale. Due to the inter-reliant of these watershed characteristics, a partial least squares regression (PLSR) was used to illustrate the relationship between the specific sediment yield and data of 15 selected watershed characteristics. The results showed that the land-use composition and soil properties had the maximum effects on the specific sediment yield and clarified 79% of the variation in the specific sediment yield. Regarding the availability of digital spatial database over the watershed, this simple PLSR procedure could be applied in different watersheds.

Including land use information for the spatial estimation of groundwater quality parameters – 1. Local estimation based on neighbourhood composition

Summary Most groundwater recharge comes from the infiltration of water through the land surface. Data analysis shows that solute concentrations at the water table vary between land use categories and depending on the land use composition within a certain neighbourhood. Driven by these observations, the goal of this paper is to estimate the solute distribution at a location depending on the composition of land use in the neighbourhood, even though land use information is categorical. This goal is achieved by mixing pure distributions of homogeneous land use according to their frequency of occurrence in the vicinity of, and their distance from an estimation location. These pure distributions are jointly inverted using a maximum likelihood-based approach. The neighbourhood size is optimized using cross-validation. Measurements below detection limit are included via their probabilities of non-exceedance. A solute-specific, spatially distributed measure of information content of the secondary information is presented. The method is applicable for many types of secondary information and can be used as drift for spatial estimation of the primary variable. This estimation is a local estimation and does not include larger scale spatial information. The information of measurements is included via the optimized concentration distributions for land use groups, not via a model of spatial dependence. The global estimation is described in the companion paper.

Land-use structure, urban growth, and periurban landscape: a multivariate classification of the European cities

Assessment of urbanization and suburbanization patterns and processes in the European Union is becoming increasingly urgent for the formulation of common territorial policies. We hypothesize that the intrinsic characteristics of landscape at the city scale reflect both the local socioeconomic context and the regional trends towards urbanization, possibly representing the contrasting attitude towards suburbanization found in European countries. Using comprehensive information provided by Urban Atlas maps, we propose an exploratory multivariate analysis of eighty-five variables describing land-use composition, landscape structure, and urban form in 283 cities with the aim being to classify the urbanization patterns observed in five European macroregions. Landscape metrics seem to be more powerful in discriminating cities among regions than indicators of land-use composition. The most relevant metrics discriminating among cities are (i) those describing fragmentation processes along the urban gradient and (ii) those evaluating form and patchiness of discontinuous settlements. Landscape and class average patch size and edge density correctly classified cities in more than 80% of cases. In particular, cities in Southern, Eastern, and Northern Europe were identified as three homogeneous groups as far as landscape structure is concerned, confirming the converging urbanization trends in the Mediterranean countries and the peculiar morphological characteristics of post-socialist urban areas

Tree cover mediates the effect on rapeseed leaf damage of excluding predatory arthropods, but in an unexpected way

Birds and predatory arthropods are often implicated in pest control, but their relative impact and how this is mediated by variation in tree cover requires elucidation. We excluded birds and ground predatory arthropods from rapeseed plants in 2.5×1m plots in 26 homegardens in Ethiopia, leaving the same sized control plots. From six groups of plants in bird exclosure and control plots, respectively, three groups were excluded from ground predatory arthropods. Data on leaf damage were surveyed four times at weekly intervals. The tree cover and land-use composition within 100×100m surrounding each plots were recorded in the field and from a satellite image within 200 and 500m buffer zones. The results show that the mean leaf damage was higher on rapeseed plants from which predatory arthropods were excluded than on control plants. However, excluding birds had no or only a weak impact on leaf damage. The mean leaf damage within predatory arthropod exclosures decreased with increasing tree, forest and perennial cover but increased with increasing grazing land cover and annual crop cover, while on control plants it was low across the tree cover variation. This pattern may indicate the presence of a higher density of herbivores on rapeseed plants and also more predatory arthropods (i.e., to control them) in tree-poor homegardens compared to tree-rich homegardens. Hence, tree-poor homegardens in this landscape have sufficient habitat heterogeneity to support natural enemies to deliver significant pest control on rapeseed. Our results show that there was variation in the dynamics of pests and predatory arthropods across the tree cover variation, suggesting changes in landscape composition could affect the pest control services and the outcomes for local farmers.

Influence of land-use misrepresentation on the accuracy of WRF wind estimates: Evaluation of GLCC and CORINE land-use maps in southern Spain

In this work, we evaluate the influence of land-use representation accuracy on the reliability of wind speed and direction estimates derived from the Weather Research and Forecasting (WRF) model. To this end, the 100-m spatial resolution Coordination of Information on the Environment (CORINE) land-use dataset was implemented as static geographic data in WRF. Next, a set of one-year long simulations at 1-km spatial resolution was conducted using both the CORINE and Global Land Cover Characterization (GLCC) land-use datasets, the latter the default in WRF. The simulations were conducted for three locations in southern Spain, and were characterized by variable land-use composition and topography. At these locations, wind speed and direction estimates were compared against observations at different measurement elevations. Results showed that the selection of land-use database has a major influence on wind estimate bias. The effect on the wind direction distribution is also significant, whereas that on the standard deviation is much weaker. CORINE provided a more reliable land-use representation than GLCC. Nevertheless, as a consequence of the interpolation procedure used for land use in the domain setup, this representation did not necessarily translate to a superior roughness length, thereby affecting wind speed and direction estimates. This was particularly so for areas of high spatial variability in land-use categories. In such areas, the misrepresentation of land use may result in large wind speed estimation errors.

The effect of local and landscape level land-use composition on predatory arthropods in a tropical agricultural landscape

It has been suggested that the composition of different non-crop land-use types along with tree density regulate local biodiversity in agricultural landscapes. However, specific data is limited, not least from tropical regions. We examined how different land-use types and forest cover at different scales influenced the abundance and species composition of predatory arthropods in 40 homegardens of southwest Ethiopia. We collected specimens using pitfall traps during two separate months and related sample composition to land-use in the vicinity (1 ha plot, local scale, field data) and tree cover within 200 and 500 m radius zones (landscape scale, satellite data). Spiders, beetles and ants were most common. A high abundance of ants was found in tree-rich homegardens while the variation in abundance of spiders was best explained by the interaction between tree cover at the local and landscape scales. The highest spider abundances were found when either the homegarden or the surroundings had high tree-cover and was lower in both the most tree-rich and tree-poor landscape–garden combinations. In addition, open non-crop cover (mostly grasslands) and ensete (a banana-like perennial crop) favored spiders. This pattern demonstrates that different land-use types at different scales can interact to create variations in biodiversity across an agricultural landscape. To enhance numbers of predatory arthropods in homegardens, which may be beneficial for natural pest control, our results suggest that different strategies are needed depending on the target group or species. Grasslands, ensete fields and tree-rich habitats seem to play important roles.

High resolution modelling and forecasting of soil sealing density at the regional scale

The on-going growth of urban areas results in increased sealed surface cover, affecting the environment through fragmentation of the landscape, increased surface runoff and obstruction of water infiltration. Within Flanders (Belgium), which is characterized by a highly sprawled urban network and a sealed surface density much higher than in many other European metropolitan regions, there is a strong need for more accurate high-resolution forecasting of soil sealing densities. This study attempts to meet this need by developing a spatial explanatory model for soil sealing density that is applicable at the regional scale and that can be applied in combination with the Flanders cellular automata land-use change model for evaluating the impact of future land-use scenarios on soil sealing. In the modelling, neighbourhood characteristics such as land-use composition and positioning with respect to the urban network and its major transport axes are considered as attraction/repulsion factors for soil sealing. Global multiple regression and regression tree models are compared with a simple average model. The regression models yield clear improvements in overall estimation accuracy and a favourable distribution of the remaining error. Applying a two-rule partitioning model on a future land-use map, produced by the Flanders land-use change model, shows an increase of 23.6% and 44.6% of sealed surface cover within residential/mixed areas in the study area by 2030 and 2050, respectively.

Incorporating Bayesian learning in agent-based simulation of stakeholders’ negotiation

This paper describes the incorporation of a Bayesian learning algorithm into an agent-based model designed to simulate stakeholders’ negotiation when evaluating scenarios of land development. The objective is to facilitate reaching an agreement at an earlier stage in the negotiation by providing the opportunity to the proposer agent to learn his opponents’ preferences. The modeling approach is tested in the Elbow River watershed, in southern Alberta, Canada, that is under considerable pressure for land development due to the proximity of the fast growing city of Calgary. Five agents are included in the model respectively referred to as the Developer agent, the Planner agent, the Citizen agent, the AgricultureConcerned agent, and the WaterConcerned agent. Two types of land development scenarios are evaluated; in the first case, only the geographical location is considered while in the second case, the internal land-use composition is also varied. The Developer agent that is equipped with the Bayesian learning capability attempts to approximate its opponents’ fuzzy evaluation functions based on the responses he receives from them at each round of the negotiation. The results indicate that using this approach, an agreement can be reached in fewer number of negotiation rounds than in the case where the Developer agent selects the subsequent offers based merely on its own utility. The model also indicates how the satisfaction of each agent evolves during the negotiation. This information is very useful for decision makers who wish to consider stakeholders’ perspectives when dealing with multiple objectives in a spatial context.

Isotopic values in oysters indicate elemental sources constrained by multiple gradients

Stable nitrogen and carbon isotopes (δ15N and δ13C) and elemental content (% nitrogen, % carbon) in oysters (Crassostrea virginica) grown by a network of 132 citizen–scientists (11,600km2, 87.9km2site−1) were examined to test effects of land use, salinity, flushing time, and oyster size on bioindication of human and/or animal nitrogen sources. Oyster δ15N sampled from shallow waters sites throughout Chesapeake Bay and its tributaries exhibited nested spatial patterns: (1) decreasing toward the mouth of Chesapeake Bay (1000skm2) and (2) decreasing, increasing, and not changing toward tributary mouths (100skm2). Distinct isotopic ‘signatures’ in tributaries were associated with the composition of land use, water quality in tributaries and freshwater streams, human and/or animal nitrogen sources, and marine vs. terrestrial nitrogen and carbon sources. Yet at 1000skm2, oyster δ15N varied with flushing time, salinity, and bioindicator size, thus constraining the upper extent for inferring nitrogen sources from bioindicator δ15N to the scale of gradients in these confounding physical and biological factors. Nevertheless, at 100skm2 isotopic ‘signatures’ can be used to infer nutrient sources and transport mechanisms and might have implications for fishery management/enforcement. Ultimately, δ15N and δ13C in bioindicators distributed to citizen–scientists may add substantial value to existing and ongoing programs, networks, monitoring and databases, and might have some use for imputing data gaps where intensive water quality monitoring is lacking.

Habitat selection in the fossorial toad Pelobates fuscus insubricus (Amphibia: Pelobatidae): does the soil affect species occurrence?

For their rapid and alarming decline, the Italian populations of the Italian spadefoot toad ( Pelobates fuscus insubricus ) are of high conservation importance. In this study we examined habitat use by the spadefoot toads in north-west Italy, where one of the largest remaining populations lives. We used compositional analysis and logistic regression models to elaborate land-use and soil composition in order to determine the habitat preferences of the spadefoot toads. We found that the two main variables predicting the occurrence of spadefoot toads in the study area were the percentages of sandy-loam soil texture and the presence of Entisols. Our results showed that spadefoot toads preferred soils that keep soft and malleable structure: Entisols with sand texture, where sand represents the major component, and mature soils, with a high degree of pedogenesis and a relatively high natural fertility and humidity. Conversely, Pelobates fuscus avoids Inceptisols, probably too hard to be dug by the species. This study demonstrates that, at least in the Italian range, the choice of areas in which to reintroduce P. fuscus , or where re-create favourable habitats for it, must take into account the soil types, which, in intensely cultivated areas, seems to be decisive for the possibility of survival of the species in the medium and long time.

Habitat Preferences and Spatial Overlap Between Three Species of Bunting (Emberiza hortulana, emberiza cirlus, miliaria calandra) in Farmlands of Central Italy

Buntings species are mainly associated to agricultural landscapes and constitute a high conservation concern because farmlands are ecosystems subject to rapid changes and may cause the loss of animal species in just a few years. We studied the occurrence of Ortolan Bunting, Cirl Bunting and Corn Bunting (Emberiza hortulana, Emberiza cirlus, Miliaria calandra) on farmlands of Central Italy, considering the landuse composition, crop typologies and several structural parameters of environment occupied by these species, as presence of power lines, road type and Shannon biodiversity index of landscape. Furthermore the geographical overlap among the three bunting species was studied, in order to find witch species show an habitat overlap. The study was carried out in central-eastern Italy, between the end of April and mid-July 2010, through 159 sampled sites, uniformly distributed on in the study area. Cirl Bunting is the most widespread species of Bunting in the farmlands that were studied. Ortolan Bunting and Corn Bunting are the two species with greater spatial habitat overlap, even though land-use composition in their territories was different. However, Ortolan Bunting can be found at a lower altitude range than Corn Bunting (less 550 m a.s.l.) and it is associated to territories with minor landscape heterogeneity. Preferences by crop types seem to be a possible cause of the spatial habitat overlap between Ortolan and Corn Bunting (both species had selected sugar beet, and coriander, avoiding mainly vegetables, vineyards and orchards). On the other hand, Cirl Bunting was less related to crop types.

Grid-Based Land-Use Composition and Configuration Optimization for Watershed Stormwater Management

This paper demonstrates a new method of optimizing land-use patterns to reduce the negative impacts of urbanization on watershed stormwater systems. The Yong-Ding watershed in western Beijing, China, serves as a case study for this research. A regression model that estimates watershed hydrology response to land use pattern changes is integrated with a land-use allocation model to determine the optimal landuse pattern for minimizing peak flow or total volume at the watershed outlet. This system also uses the CLUE-S model to generate empirical land-use patterns under different development intensities and then determines the land use pattern change constraints for each optimization process. The impacts of optimization are detected by comparing the land use pattern characteristics and watershed hydrology of empirical and optimal scenarios under the same development intensity. The results of the hydrological evaluation suggest that, compared to land-use location control, land-use composition and configuration control may be a more powerful method for minimizing the negative hydrological impact of urbanization.

A land use change model: Integrating landscape pattern indexes and Markov-CA

Landscape pattern indexes are quantitative descriptions of the spatial composition and configuration of land use, which can influence a variety of ecological phenomena. In this paper, we propose a land use change simulation model based on landscape pattern indexes, Markov chain and cellular automata. In the model, Markov Chain is applied to predict the amount of land use change; transition potential maps generated from natural and socioeconomic indexes are used to control the spatial distribution of land use; landscape pattern indexes in the start year are used to differentiate the transition probabilities of land use classes within different sub-regions of the study area. First, the principles and implementation of the model were described. Then the model was successfully applied to the simulation of land use change in Changping, a district of Beijing. Based on land use maps in years 1988 and 1998, the land use map in year 2008 was simulated. By analyzing the simulation result, the effectiveness of the model for land use change simulation was demonstrated. By comparing results simulated by this model and the results simulated by Markov-CA model with the actual land use map, the advantage of this model in spatial accuracy was shown.

Influence of seasonal and inter-annual hydro-meteorological variability on surface water fecal coliform concentration under varying land-use composition

Quantifying the influence of hydro-meteorological variability on surface source water fecal contamination is critical to the maintenance of safe drinking water. Historically, this has not been possible due to the scarcity of data on fecal indicator bacteria (FIB). We examined the relationship between hydro-meteorological variability and the most commonly measured FIB, fecal coliform (FC), concentration for 43 surface water sites within the hydro-climatologically complex region of British Columbia. The strength of relationship was highly variable among sites, but tended to be stronger in catchments with nival (snowmelt-dominated) hydro-meteorological regimes and greater land-use impacts. We observed positive relationships between inter-annual FC concentration and hydro-meteorological variability for around 50% of the 19 sites examined. These sites are likely to experience increased fecal contamination due to the projected intensification of the hydrological cycle. Seasonal FC concentration variability appeared to be driven by snowmelt and rainfall-induced runoff for around 30% of the 43 sites examined. Earlier snowmelt in nival catchments may advance the timing of peak contamination, and the projected decrease in annual snow-to-precipitation ratio is likely to increase fecal contamination levels during summer, fall, and winter among these sites. Safeguarding drinking water quality in the face of such impacts will require increased monitoring of FIB and waterborne pathogens, especially during periods of high hydro-meteorological variability. This data can then be used to develop predictive models, inform source water protection measures, and improve drinking water treatment.