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Invader traits (including plant growth form) may play an important, and perhaps overlooked, role in determining macroscale patterns of biological invasions and therefore warrant greater consideration in future investigations aimed at understanding these patterns. To assess this need, we used empirical data from a national-level survey of forest in the contiguous 48 states of the USA to identify geographic hotspots of forest plant invasion for three distinct invasion characteristics: invasive species richness, trait richness (defined as the number of the five following plant growth forms represented by the invasive plants present at a given location: forbs, grasses, shrubs, trees, and vines), and species richness within each growth form. Three key findings emerged. 1) The hotspots identified encompassed from 9 to 23% of the total area of our study region, thereby revealing many forests to be not only invaded, but highly invaded. 2) Substantial spatial disagreement among hotspots of invasive species richness, invasive trait richness, and species richness of invasive plants within each growth form revealed many locations to be hotspots for invader traits, or for particular growth forms of invasive plants, rather than for invasive plants in general. 3) Despite eastern forests exhibiting higher levels of plant invasion than western forests, species richness for invasive forbs and grasses in the west were respectively greater than and equivalent to levels found in the east. Contrasting patterns between eastern and western forests in the number of invasive species detected for each growth form combined with the spatial disagreement found among hotspot types suggests trait-based variability in invasion drivers. Our findings reveal invader traits to be an important contributor to macroscale invasion patterns. [ABSTRACT FROM AUTHOR]

Aim Stronger inferences about biological invasions may be obtained when accounting for multiple invasion measures and the spatial heterogeneity occurring across large geographic areas. We pursued this enquiry by utilizing a multimeasure, multiregional framework to investigate forest plant invasions at a subcontinental scale. Location United States of America ( USA). Methods Using empirical data from a national survey of USA forests, we compiled and mapped invasion richness (number of invasive species) and invasion prevalence (percentage of plots invaded) for 2524 counties. We then modelled each of these invasion measures as functions of 22 factors reflective of propagule pressure and/or habitat invasibility for eastern and western forests separately using simultaneous autoregressive spatial error models. Results Eastern forests had higher mean invasion richness (6.1) and prevalence (48%) than western forests (3.2 and 10%, respectively). Spatial patterns of invasion richness and prevalence differed, especially in the West. Propagule pressure factors were always positively associated with both invasion measures. Factors associated with human legacy were nearly six times more strongly associated with western than eastern invasions. Unlike propagule pressure factors, habitat invasibility factors shared inconsistent associations with invasion measures. Main conclusions The weaker associations between human legacy and invasions in the heavily invaded East, compared to the less-invaded West, suggest a declining effect of propagule pressure over time with increasing invasion intensity. The importance of propagule pressure in less-invaded western forests suggests that spatial variability in propagule inputs, coupled with lags between establishment and commonness, drives the spatial differences between invasion richness and prevalence during early invasion stages. Meanwhile, declining spatial disagreement between invasion measures and the relative unimportance of propagule pressure, in heavily invaded eastern forests, suggest that species-specific variation in response to habitat invasibility drives spatial differences between invasion measures during later invasion stages. These insights further illustrate the importance of spatial heterogeneity in invasive plant management and policy at macroscales. [ABSTRACT FROM AUTHOR]

Modern biogeography now encompasses an impressive diversity of patterns and phenomena of the geography of nature, providing insights fundamental to understanding the forces influencing the spatial and temporal dynamics of biological diversity. However, rather than praise our discipline for its great breadth of visions, our purpose here is to point out our glaring oversight of a potentially transformative frontier in the geography of nature. A new, emerging area called soundscape ecology, if guided by the principles of biogeography, holds the promise of 'opening the ears' of our field and providing fresh perspectives on fundamental problems being addressed by biogeographers. [ABSTRACT FROM AUTHOR]

ABSTRACT Both land-cover/land-use change ( LCLUC) and greenhouse gas ( GHG) concentrations have been shown to influence regional climate, albeit at different spatial scales. In East Africa, climate changes due to changing GHG concentrations are broadly projected to be warmer and wetter. LCLUC projections include trends towards both agricultural intensification and agricultural expansion into savannas, which may result in complex climate interactions and impacts. The primary objective of this study was to examine the regional responses to future GHG, LCLUC, and their combined effects in East Africa, and to better understand how hydrometeorological mechanisms might be altered by LCLUC in future scenarios. In this study, we present high-resolution decadal simulations from a regional climate model that compare the relative and combined effects of projected LCLUC and GHG. This research suggests that taken separately, these two climate forcings may significantly alter regional precipitation patterns both temporally and spatially but in potentially different and independent ways. In combination, some portions of the region exhibit responses dominated by either LCLUC or GHG effects, but certain areas show complex effects resulting from the combined influence of these two forcings. Perhaps most importantly, the results suggest that projected precipitation changes around major population areas may be as strongly influenced by LCLUC as by GHG effects. [ABSTRACT FROM AUTHOR]

Land uses and their legacies are a major driver of human impacts on the environment. Decision makers have recognized that the legacies of land-use activities continue to influence ecosystems, particularly aquatic ones, for decades or centuries. The main objectives of this paper are to develop land use legacy maps to (1) assess historical and future (predicted) shifts in dominant land use classes (urban, agriculture, forest) in the Ohio River Basin (ORB), and (2) determine the past and future location of catchments in the ORB exceeding critical land use thresholds (10% and 38% urban and agricultural use of catchment respectively) for water quality and other aquatic resources. Our land use legacy simulations show that approximately 80% of the ORB has remained as agriculture (∼37%), forest (∼34%), urban (∼7%) and other classes (∼2%) from 1930 to 1990. Within the remainder of landscape, agriculture to forest (∼16%) and agriculture to urban (∼1.5%) transitions were the most common land use changes between 1930 and 1990. Our forecast model shows that approximately 94% of the ORB will remain as forest (∼47.46%), agriculture (∼35.77%), urban (∼8.84%) and other classes (∼2.07%) between 2000 and 2050. 1.44% and 1.37% of the ORB is predicted to transition from forest to urban and agriculture to urban between 2000 and 2050, respectively. Our results also demonstrate that 13% and 74% of the catchments in the ORB already exceeded critical urban and agricultural land use thresholds in 1930, respectively. We predict that 37% of catchments in the ORB will have exceeded critical urban land use thresholds by 2050, whereas the proportion of catchments to exceed critical agricultural use will decrease to 45%. [ABSTRACT FROM AUTHOR]

This paper compares one global parametric land use change model, the artificial neural network – based Land Transformation Model, with two local non-parametric models: a classification and regression tree and multivariate adaptive regression spline model. We parameterized these three models with identical data from different regions of the world; one region undergoing extensive agricultural expansion (East Africa), another region where forests are re-growing (Muskegon River Watershed in the United States), and a third region where urbanization is prominent (South-Eastern Wisconsin in the United States). Independent training data and testing data were used to train and calibrate each model, respectively. Comparisons of simulated maps from the three kinds of land use change patterns were made using conventional goodness-of-fit metrics in land use change science. The results of temporal and spatial comparison of the data mining models show that the artificial neural network outperformed all other models in a short-time interval (East Africa; 5 years) and for coarse resolution data (East Africa; 1 km); however, the three data mining models obtained similar accuracies in a long-time interval (Muskegon River Watershed; 20 years) and for fine resolution data with large numbers of cells (Muskegon River Watershed; 30 m). Furthermore, the results showed that the probability of agriculture gain was more likely in locations closer to towns and large cities in East Africa, urbanization was more likely in locations closer to roads and urban areas in South-Eastern Wisconsin and the probability of forest gain was more likely in locations closer to the forest and shrub land cover and farther away from roads in Muskegon River Watershed. [ABSTRACT FROM AUTHOR]

Soundscape ecology is an emergent and potentially transformative scientific discipline. However, the majority of research within the field has been conducted by natural scientists focused on quantifying the characteristics and dynamics of soundscapes and examining their effect on non-human biota. A more holistic approach to the science and management of soundscapes requires full integration with the social and policy sciences. To facilitate the development of this integration, we propose an integrative human and policy dimensions of soundscape ecology framework that conceptualizes the complex and dynamic relationships between humans and their acoustic environments. The framework is grounded in four distinct disciplines – health, psychology, economics and anthropology – that have used different methodologies and metrics to focus on certain aspects of human–soundscape interactions. We provide a review of previous empirical research within each of these fields. Along the way, we identify unexplored avenues of discipline-specific research that can further the field of soundscape ecology. The human and policy dimensions of soundscape ecology framework provide the logic and structure upon which an interdisciplinary body of scholarship can be built in the future. We conclude by utilizing our review and integrative framework to propose specific focused soundscape policy and management recommendations. We argue the anthropogenic dominance of soundscapes can be mitigated through more proactive, integrative and holistic soundscape policies and management practices. [ABSTRACT FROM AUTHOR]

Abstract: The Land Transformation Model (LTM) is a Land Use Land Cover Change (LUCC) model which was originally developed to simulate local scale LUCC patterns. The model uses a commercial windows-based GIS program to process and manage spatial data and an artificial neural network (ANN) program within a series of batch routines to learn about spatial patterns in data. In this paper, we provide an overview of a redesigned LTM capable of running at continental scales and at a fine (30m) resolution using a new architecture that employs a windows-based High Performance Computing (HPC) cluster. This paper provides an overview of the new architecture which we discuss within the context of modeling LUCC that requires: (1) using an HPC to run a modified version of our LTM; (2) managing large datasets in terms of size and quantity of files; (3) integration of tools that are executed using different scripting languages; and (4) a large number of steps necessitating several aspects of job management. [Copyright &y& Elsevier]

Abstract: Decreases in both quantity and quality of cultivated land in China have drawn close attention recently due to the threat to food security. China has implemented a set of cultivated land balance (CLB) programs since the late 1990s, aiming to maintain the quantity and quality of cultivated land across the country. We assessed the outcomes of CLB policy in terms of both quantity balance and quality balance. In particular, we evaluated the effects of CLB policy on potential land productivity (PLP) of cultivated land. During 1999–2008, a total of 21,011 km2 of cultivated land was lost due to urbanization and economic development while 27,677 km2 of cultivated land was gained by land exploitation, consolidation and rehabilitation. Thus, the quantity balance aimed for by CLB was achieved. In contrast, quality balance was not met due to both the loss of highly productive cultivated land from urban expansion and economic development and a flawed approach to adding newly cultivated land. In particular, China has typically relied on adding cultivated land by exploitation instead of consolidation, which would add higher productivity land. Therefore, the PLP of the added cultivated land has been rather poor. Nevertheless, the average PLP did increase slightly during 1999–2008, but this was despite CLB rather than because of it. The main cause of the PLP increase was actually a grain-for-green policy that induced considerable reduction in cultivation of low productivity cultivated land. [Copyright &y& Elsevier]

Cities have shown remarkable growth due to attraction, economic, social and facilities centralization in the past few decades. Population and urban expansion especially in developing countries, led to lack of resources, land use change from appropriate agricultural land to urban land use and marginalization. Under these circumstances, land use activity is a major issue and challenge for town and country planners. Different approaches have been attempted in urban expansion modelling. Artificial Neural network (ANN) models are among knowledge-based models which have been used for urban growth modelling. ANNs are powerful tools that use a machine learning approach to quantify and model complex behaviour and patterns. In this research, ANN and logistic regression have been employed for interpreting urban growth modelling. Our case study is Sanandaj city and we used Landsat TM and ETM+ imageries acquired at 2000 and 2006. The dataset used includes distance to main roads, distance to the residence region, elevation, slope, and distance to green space. Percent Area Match (PAM) obtained from modelling of these changes with ANN is equal to 90.47% and the accuracy achieved for urban growth modelling with Logistic Regression (LR) is equal to 88.91%. Percent Correct Match (PCM) and Figure of Merit for ANN method were 91.33% and 59.07% and then for LR were 90.84% and 57.07%, respectively. [ABSTRACT FROM AUTHOR]

We relate the historical (1850-2000) spatial and temporal changes in cropland cover in the conterminous United States to several socio-economic and biophysical determinants using an eco-region based spatial framework. Results show population density as a major determinant during the nineteenth century, and biophysical suitability as the major determinant during the twentieth century. We further examine the role of technological innovations, socio-economic and socio-ecological feedbacks that have either sustained or altered the cropland trajectories in different eco-regions. The cropland trajectories for each of the 84 level-III eco-regions were analyzed using a nonlinear bi-analytical model. In the Eastern United States, low biophysically suitable eco-regions, e.g., New England, have shown continual decline in the cropland after reaching peak levels. The cropland trajectories in high biophysically suitable regions, e.g., Corn Belt, have stabilized after reaching peak levels. In the Western United States, low-intensity crop cover (<10 %) is sustained with irrigation support. A slower rate of land conversion was found in the industrial period. Significant effect of Conservation Reserve Program on planted crop area is found in last two decades (1990-2010). [ABSTRACT FROM AUTHOR]

Abstract: While crop rotation patterns can be complex with multiple crops rotated over several years, the most common rotation practice in the Central United States is biannual rotation between corn and soybeans. We analyzed the changes in crop rotation patterns from 2003 to 2010 using the Cropland Data Layer (CDL), which provides remotely sensed land cover layers for agricultural crops in the Central United States. The accuracy of the CDL was validated by comparing the total acreage for a state or county present in the CDL with the total planted crop acreage available from the National Agricultural Statistics Service. The data layers were combined into two time periods 2003–2006 and 2007–2010, and specific rotation patterns were determined for every location in the study area. The combinations resulted in unique sequences such as single, double, triple and quadruple, the latter of which is equivalent to the same crop class present all four years at a particular location. Corn and soybeans were analyzed to determine the amount of area used for production as well as the amount of change between unique crop rotation sequences. While the total area under production of major crops in the second half of our study period increased only slightly, the extent to which major crops (e.g., corn and soybeans) were grown in continuous cropping sequences increased significantly. For example, the amount of land impacted by corn in the first time period increased by only 2% in the second time period. However, the amount of corn grown in quadruple sequence doubled from the first half to the second half of our study period. We conclude that, although crop rotation patterns are very complex in this region, involving considerable amount of non-cropland, the footprint of major crops such as corn have moved toward monoculture cropping practices in the last decade. [Copyright &y& Elsevier]

Aim Human land use activities are creating a biodiversity crisis. However, it is not clear how species respond to different intensities of land use at a global scale. We used spatial analyses to determine the relationships between human settlements, croplands, rangelands and forests of varying intensities and the endangerment status of mammal species across the globe. In doing so, we sought to assess the role of different land use and land management strategies in global biodiversity conservation. Location Global. Methods A GIS database with distribution ranges for 4734 Red- Listed and non-threatened terrestrial mammal species was obtained from the IUCN and combined with the global anthropogenic biomes dataset, which uses population density class (dense, residential, populated and remote) as a proxy for land use intensity. Ordered logistic regression was used to predict the effect of each land use intensity class on the probability of having a more endangered IUCN status for all mammal species together and for species within major mammal groups separately. Results The probability of having a more endangered status generally increased for mammal species as the proportion of urban settlements, mosaic and cropped 'villages', and residential and populated croplands within their distribution ranges increased. In contrast, endangerment probability of mammals decreased with proportion of irrigated, pastoral and rainfed 'villages', remote croplands and all rangeland classes. Endangerment probability also decreased with proportion of wildlands and remote forests, but increased with proportion of populated forests for several mammal groups. Main conclusions Urbanization and high-intensity crop production pose a significant threat to mammals worldwide. In contrast, rangelands, low-intensity croplands and certain low-intensity human settlements may in fact help maintain mammal diversity at global scales. While the area of wild habitat available to species is also highly important for biodiversity conservation, forested lands that are disturbed or over utilized by humans do not benefit and may even endanger species. [ABSTRACT FROM AUTHOR]

Abstract: Groundwater models coupled with GIS analyses can be used to estimate the time for groundwater and solutes to be transported from each location across a watershed to surface water bodies. Coupled to backcast land use models, these estimates can be used to create land use “legacy” maps that quantify the contribution of historic land uses to the groundwater signal arriving at streams. However, groundwater models and backcast land use models contain uncertainties inherent to each model. These uncertainties may affect the outcome of the coupled model and hence their reliability to natural resource and land use planning. In this paper we demonstrate how a simple spatially explicit, multi-uncertainty metric can be used to assess uncertainties from our backcast land use change and groundwater travel time model. We couple five variants of groundwater travel time (GWTT) simulations with 12 variants of historic land uses, and analyze the resulting 60 realizations of land use legacy maps using a spatially explicit, multi-metric uncertainty score. We apply this approach to the Muskegon River Watershed in Michigan, where groundwater flow provides the vast majority of streamflow. Our results indicate that despite uncertainties inherent in both models, townships located in the north-central portion of the study watershed can benefit from using legacy maps as planning tools despite a wide range of evaluated uncertainties. [Copyright &y& Elsevier]

Abstract: This study examines the role of urban spatial development on hydrologic response at both catchment (sub-grid) and river basin (between grid) scales in central Indiana. At the catchment scale, effective impervious area (EIA) was estimated using high density urban area and the patch size of low density urban area. The impact of urban spatial arrangement on floods was investigated using the estimated EIA for the entire White River basin, Indiana, as input to the Variable Infiltration Capacity (VIC) hydrology model with urban representation. A geographic information systems (GIS)-based routing scheme was introduced to the VIC model to route the total runoff. Seven theoretical scenarios were developed with equal urban area distributed in different isochrone zones. For return periods up to and including 100-year, the flood peaks at the basin outlet are largest if the travel time from urban cells is approximate to the mode of all pixels’ travel time (plus the time for runoff rate to reach its maximum in a storm event) of the basin. Flood peaks tend to be smaller and arrive earlier with urbanization if development occurs in areas with shorter travel time, so the largest impacts of urbanization are not necessarily seen immediately downstream of the development. This research demonstrated that the spatial pattern of urban development can affect the hydrologic regime by influencing the hydrologic connectivity of urban area at a catchment scale, while at the river basin scale it is the travel time of urban location that controls flood patterns. [Copyright &y& Elsevier]

Abstract: Land use/cover maps derived from aerial photography for five areas in the Upper Great Lake States were analyzed for rates and patterns of change using our framework for spatial–temporal analysis. The Detroit (1978–2000), Chicago (1990–2000), Milwaukee (1963–2000), and Twin Cities (1990–1997) Metropolitan Areas, along with the Muskegon River Watershed (1978–1998), were examined for five spatial levels (global, regional, zonal, landscape, and patch) and two temporal rates (referred to as first and second order) of change. We found that all regions gained considerable amounts of urban, lost land in agriculture, and either gained (MRW) or lost (all others) forest land. Urban doubled in most areas over 20 years, even in study areas where agricultural land was not initially prevalent. The amount of land in shrubland was substantial in many of these areas, at times exceeding the amount of land in subclasses of urban (e.g., commercial). The transitional shrubland cover type was involved most commonly in land use transitions (“into” and “out of”) throughout the five study regions. In general, ratios of agricultural loss to residential gain varied between 1.04 and 2.72. The amount of fragmentation of land use/cover varied over time and across 5km buffer zones but increased substantially over the study periods. On average, the rate of urban growth exceeded population growth rates by a factor of four. Urbanization and fragmentation are clear characteristics of land use change across the Upper Great Lakes States, and our analysis framework allowed for a rigorous comparison across regions both spatially and temporally. [Copyright &y& Elsevier]

Abstract: Urban Growth Boundaries (UGBs) that limit urban expansion out are being implemented by planning agencies worldwide. Thus, there is a need to create models that can simulate changes in urban boundaries. The aim of this paper is to present two rule-based spatial–temporal models, one which employs a Distance Dependent Method (DDM) and the other a Distance Independent Method (DIM), to simulate UGBs. These rule-based Urban Growth Boundary Models (UGBMs) use azimuths and distances, vector-based predictive variables, directed from central points within the urban area, to simulate UGB change. DDM employs a single urban boundary in the initial time step to predict the urban boundary in any subsequent time according to the increment of distances across different azimuths. Similarly, the DIM uses the change in distance between two boundaries, one in the initial time step and one in subsequent time step, across different azimuths, to predict the future urban boundary. We use the two rule-based models, DDM and DIM, to project the urban boundary of the Tehran Metropolitan Area in 2012 using data from 1988 to 2000. We compare these rule-based simulation UGBMs to a null UGBM developed from the same data but lacking in specificity of predictive variables. Percent Area Match (PAM) quantity and location goodness of fit metrics are used to assess the agreement between simulated and observed urban boundaries. Results indicate that rule-based UGBMs have a better goodness of fit compared to a null UGBM using PAM quantity and location goodness of fit metrics. We discuss how UGBMs can be used to assist planners in developing future UGBs. [Copyright &y& Elsevier]

This article presents a unifying theory of soundscape ecology, which brings the idea of the soundscape -- the collection of sounds that emanate from landscapes -- into a research and application focus. Our conceptual framework of soundscape ecology is based on the causes and consequences of biological (biophony), geophysical (geophony), and human-produced (anthrophony) sounds. We argue that soundscape ecology shares many parallels with landscape ecology, and it should therefore be considered a branch of this maturing field. We propose a research agenda for soundscape ecology that includes six areas: (1) measurement and analytical challenges, (2) spatial-temporal dynamics, (3) soundscape linkage to environmental covariates, (4) human impacts on the soundscape, (5) soundscape impacts on humans, and (6) soundscape impacts on ecosystems. We present case studies that illustrate different approaches to understanding soundscape dynamics. Because soundscapes are our auditory link to nature, we also argue for their protection, using the knowledge of how sounds are produced by the environment and humans. [ABSTRACT FROM AUTHOR]

The article presents a study which aims to adapt the vegetational fractional cover (FC) products and leaf area index (LAI) through the use of products derived from moderate resolution imaging spectroradiometer (MODIS). The study proved the hypothesis, which assumes that better phenological parameterisations has the ability to lessen precipitation error and land surface temperature (LST). Results show the absence of annual precipitation improvement in other areas.

Abstract: The primary objective of this paper is to quantify the areal footprint of parking lots across a four state region including Illinois, Indiana, Michigan and Wisconsin located in the Upper Great Lakes Basin. Parking lots are virtually everywhere in urban and suburban environments, are often larger than the building footprints they serve yet they are largely unregulated on a regional scale. We focus on a method that estimates parking lot coverage over the four state region and use independent studies to estimate model parameters and validate our model. In total, we estimate that the states of Illinois, Indiana, Michigan and Wisconsin allocate 1260km2 of their land to parking lots, with the lower bound of the estimate at 976km2 and the upper bound at 1745km2. This accounts for approximately 4.97% of urban land use and over 43 million parking spaces whereas the number of adults over 18 years old in these four states amounted to just over 25 million. The estimated number of spaces per vehicle in each state ranges from 2.49 in Indiana to 2.95 in Michigan. Within the four states studied, states that had a higher proportion of their urban land devoted to parking lots were states where urban sprawl was more prevalent. [Copyright &y& Elsevier]

Abstract: Urban sprawl is considered by most environmental scientists and urban planners to be a serious environmental problem. However, public perception about parking availability often forces planning offices to recommend parking lot sizes that exceed daily demands. The recent trend of increasing the size of stores, churches and even schools comes with increasing the size of parking lots that service these buildings. The objective of this paper is to analyze space allocation of parking lots in a typical midwestern county and to estimate the supply of parking spaces to potential demand. We also estimate the loss of ecosystem services represented by the area of parking lots in this county. We found that parking lots cover 5.65km2 (1 397acres) of Tippecanoe County, Indiana which implies that 0.44% of the county area is devoted to parking lots. Our results show that there are approximately 2.2 parking spaces per registered vehicle, that parking lots make up more than 6.57% of the total urban footprint in this county, that the area of parking lots exceeded the area of parks in the city limits by a factor of three and that parking lot runoff and pollutants are significant compared to runoff and pollutants from these areas prior to their conversion to parking lots. As other authors have done before us we lament the poor use of land in urban regions of the United States, and encourage planners to think creatively about the use of land for parking. [Copyright &y& Elsevier]