Mapping of population growth influence on land use transformation from 1994 to 2015 in Madaba Governorate, Jordan.

The Madaba Governorate, as the second-largest wheat producer in Jordan, holds a crucial position in safeguarding regional food security. Its evolving landscape, marked by changes in land use, presents environmental and socio-economic challenges that necessitate sustainable urban planning and land management practices. This study delves into the intricate relationship between the conversion of agricultural lands into urban areas and the concurrent rise in population within the Madaba Governorate. Utilizing a Markov model, this research employs land use and land cover (LULC) data from 1994, 2004, and 2015 to project future changes in 2025 and 2035 with an impressive 80% accuracy (kappa coefficient). The findings reveal a projected 6% increase in urban areas over the next decade and a notable 11.81% decline in rural lands, signifying a substantial urbanization trend. In response to these population-driven LULC dynamics, there is an urgent need for the implementation of sustainable land use planning and management solutions. Given the constraints of limited water resources in the region, this study also places emphasis on water resource management. Recommendations include measures such as restricting urban sprawl, preserving agricultural lands, managing population growth, and implementing water conservation strategies. These insights provide invaluable information for stakeholders in the Madaba Governorate, including policymakers and land use planners, fostering a comprehensive understanding of the complex interplay between regional water resources, population expansion, and land use changes.

Biodiversity Impact Assessment Considering Land Use Intensities and Fragmentation.

Land use is a major threat to terrestrial biodiversity. Life cycle assessment is a tool that can assess such threats and thereby support environmental decision-making. Within the Global Guidance for Life Cycle Impact Assessment (GLAM) project, the Life Cycle Initiative hosted by UN Environment aims to create a life cycle impact assessment method across multiple impact categories, including land use impacts on ecosystem quality represented by regional and global species richness. A working group of the GLAM project focused on such land use impacts and developed new characterization factors to combine the strengths of two separate recent advancements in the field: the consideration of land use intensities and land fragmentation. The data sets to parametrize the underlying model are also updated from previous models. The new characterization factors cover five species groups (plants, amphibians, birds, mammals, and reptiles) and five broad land use types (cropland, pasture, plantations, managed forests, and urban land) at three intensity levels (minimal, light, and intense). They are available at the level of terrestrial ecoregions and countries. This paper documents the development of the characterization factors, provides practical guidance for their use, and critically assesses the strengths and remaining shortcomings.

Changes in forest areas and land cover and their causes using intensity analysis: the case of Alabarda forest planning unit.

The examination of land cover change, as the main driving force of global climate change, and the determination of its economic, ecological, and social effects are necessary for making the right decisions in sustainable development, planning, and management. This study, conducted in the local forest areas of Alabarda, located in Tavsanli District (Turkey), examined temporal and spatial changes in land cover using an intensity analysis consisting of three levels: interval, category, and transition. Using the three maps of 1994, 2004, and 2015, we analyzed the land use changes during two time intervals (1993-2004 and 2004-2015) in the area for six categories, including three for forest areas (Productive, Degraded, and Treeless) and three for non-forest areas (Others, e.g., mine sites, roads, wetlands; Settlement; and Cultivated). The interval level results of the analysis showed that the land change rate was more rapid in the 2004-2015 time interval compared to 1993-2004. According to the category level results, in both time intervals, the Productive category was dormant in terms of loss and gain, whereas the Cultivated category was active. The level showing transitions between categories indicated that the Productive category targeted the Treeless and Cultivated losses in the first time interval and targeted the Degraded losses most intensely in the second time interval. The successful forestry activities (afforestation and rehabilitation) carried out by the government as of 2006 and the ongoing migration of the population from the region have had a joint effect on the increase of forest areas and the transformation of Degraded forest areas into Productive ones in the study area.

Global change biology: A primer.

Because of human action, the Earth has entered an era where profound changes in the global environment are creating novel conditions that will be discernable far into the future. One consequence may be a large reduction of the Earth's biodiversity, potentially representing a sixth mass extinction. With effective stewardship, the global change drivers that threaten the Earth's biota could be alleviated, but this requires clear understanding of the drivers, their interactions, and how they impact ecological communities. This review identifies 10 anthropogenic global change drivers and discusses how six of the drivers (atmospheric CO2 enrichment, climate change, land transformation, species exploitation, exotic species invasions, eutrophication) impact Earth's biodiversity. Driver impacts on a particular species could be positive or negative. In either case, they initiate secondary responses that cascade along ecological lines of connection and in doing so magnify the initial impact. The unique nature of the threat to the Earth's biodiversity is not simply due to the magnitude of each driver, but due to the speed of change, the novelty of the drivers, and their interactions. Emphasizing one driver, notably climate change, is problematic because the other global change drivers also degrade biodiversity and together threaten the stability of the biosphere. As the main academic journal addressing global change effects on living systems, GCB is well positioned to provide leadership in solving the global change challenge. If humanity cannot meet the challenge, then GCB is positioned to serve as a leading chronicle of the sixth mass extinction to occur on planet Earth.

Changing pattern of urban landscape and its effect on land surface temperature in and around Delhi.

The last couple of decades have seen remarkable spatial growth in the urban areas of developing countries. The process of urbanization is directly linked with land transformation which can be an effective way to monitor the spatio-temporal pattern of urban growth. New Delhi, the capital city of India has experienced a large-scale urban growth during the last decade. In order to identify the pattern of urban expansion in and around Delhi, the present study aims to assess the process of land transformation using multi-temporal Landsat datasets (1977-2014). The areas under various land use and land cover (LULC) extracted by support vector machine (SVM) hybrid classifier reveal asignificant change in the LULC pattern of the area. A good agreement was found between field-based information and maps generated using satellite images (kappa ≥ 0.84). Land transformation maps indicate rapid growth of few urban centres located outside Delhi National Capital Territory (NCT), like Gurgaon, Gautam Buddha Nagar, Faridabad and Ghaziabad. These centres have been remarkably expanded because of transformation of agricultural and vegetated lands. However, green patches within the city have not been affected by the consequences of urbanization. In tune with the rapid urbanization in the periurban centres of Delhi, the Moderate Resolution Imaging Spectro-radiometer (MODIS)-derived land surface temperature (LST) images revealed significant change in the level of LST. The inter-relationship of impervious surface fraction (ISF) and LST proves a good agreement between them. The increasing trend observed in the long-term (1987-2011) summer temperature data obtained from India Meteorological Department (IMD) indicates the rise of mean summer temperature in the last few decades. Land transformation along with rapid urbanization especially in the periurban areas of Delhi NCT played a key role in the increasing trend of surface temperature.

Soil quality index: Exploring options for a comprehensive assessment of land use impacts in LCA.

Impacts associated with land use are increasingly recognized as important aspects to consider when conducting Life Cycle Assessment (LCA). Across the existing models accounting for land use activities in life cycle impact assessment, a balance is yet to be found between complexity and comprehensiveness on one hand, and applicability on the other hand. This work builds on the LANd use indicator value CAlculation (LANCA®) model, assessing the impacts of land use activities on five soil properties, and aims at developing an aggregated index to improve its applicability. First a statistical analysis is conducted, leading to the shortlisting of the four most significant soil quality indicators. Then two options for aggregating the selected indicators are presented: the soil quality index (SQI), based on linear aggregation, and the normalisation-based soil quality index (NSQI), where the aggregation process involves normalisation integrated into the characterisation step. Country-specific and global average characterisation factors (CFs) are calculated for 57 land use types considering both land occupation and land transformation interventions with the two suggested approaches. The two indices present similar ranking of land use types but the relative contribution of the separate indicators to the aggregated index varies according to the approach adopted. The differences between the aggregation approaches suggested are discussed, together with the limitations related to both the LANCA® model and the aggregation approaches. This work represents a first step towards the widespread application of a comprehensive and robust land use model at midpoint level in LCA. Finally, a number of recommendations for the future development of the LANCA® model and of the related soil quality models are provided.

Agricultural implications of providing soil-based constraints on urban expansion: Land use forecasts to 2050.

Urbanization onto adjacent farmlands directly reduces the agricultural area available to meet the resource needs of a growing society. Soil conservation is a common objective in urban planning, but little focus has been placed on targeting soil value as a metric for conservation. This study assigns commodity and water storage values to the agricultural soils across all of the watersheds in Michigan's Lower Peninsula to evaluate how cities might respond to a soil conservation-based urbanization strategy. Land Transformation Model (LTM) simulations representing both traditional and soil conservation-based urbanization, are used to forecast urban area growth from 2010 to 2050 at five year intervals. The expansion of urban areas onto adjacent farmland is then evaluated to quantify the conservation effects of soil-based development. Results indicate that a soil-based protection strategy significantly conserves total farmland, especially more fertile soils within each soil type. In terms of revenue, ∼$88 million (in current dollars) would be conserved in 2050 using soil-based constraints, with the projected savings from 2011 to 2050 totaling more than $1.5 billion. Soil-based urbanization also increased urban density for each major metropolitan area. For example, there were 94,640 more acres directly adjacent to urban land by 2050 under traditional development compared to the soil-based urbanization strategy, indicating that urban sprawl was more tightly contained when including soil value as a metric to guide development. This study indicates that implementing a soil-based urbanization strategy would better satisfy future agricultural resource needs than traditional urban planning.

Forest conversion into pasture selects dung beetle traits at different biological scales depending on species pool composition.

The conversion of forests into open areas has large effects on the diversity and structure of native communities. The intensity of these effects may vary between regions, depending on the existence of native species adapted to open habitats in the regional pool or the time since habitat change.We assess the differences in species richness and functional diversity of dung beetle communities (Coleoptera: Scarabaeinae) between native forests and novel pasturelands of the Atlantic Forest and the Cerrado, two biomes with contrasting histories of human occupation in Brazil. We conducted standardized surveys in seven forest fragments and adjacent pastures in each region and measured 14 traits in individuals collected in each type of habitat at each particular site. We calculated functional richness, functional evenness, functional divergence, and community-weighted mean of traits for each area, and analyzed individual variation through nested variance decomposition and Trait Statistics.Communities were richer and more numerous at the Cerrado. We did not find any consistent relationship between functional diversity and forest conversion beyond the changes in species diversity. Although landscape changes were more recent at the Cerrado, the colonization of the new habitat by native species already adapted to open habitats lessens the functional loss in this biome. This indicates that habitat change's effects on trait diversity depend on the regional species pool rather than on time since land conversion.Forest conversion effects were primarily due to internal filtering. The effects of external filtering only appear at the intraspecific variance level, with contrasting differences between the Cerrado, where traits related to relocation behavior and size are selected, and the Atlantic Forest, where selection operates for traits related to relocation behavior and flight. These results evidence the importance of considering individual variance to address the responses of dung beetle communities to forest conversion.

A conversão de florestas em áreas abertas tem grandes efeitos sobre a diversidade e estrutura das comunidades nativas. A intensidade desses efeitos pode variar entre regiões, dependendo da existência de espécies nativas adaptadas a habitats abertos no pool regional ou do tempo de mudança de habitat.Avaliamos as diferenças na riqueza de espécies e diversidade funcional de comunidades de rola­bosta (Coleoptera: Scarabaeinae) entre florestas nativas e pastagens da Mata Atlântica e do Cerrado, dois biomas com histórias contrastantes de ocupação humana no Brasil. As comunidades foram amostradas em sete fragmentos florestais e pastagens adjacentes de cada região. Medimos quatorze caracteres de indivíduos coletados em cada ponto amostral de cada habitat e região. Posteriormente, calculamos a riqueza funcional, a equidade funcional, a divergência funcional e a média dos caracteres ponderada pela comunidade (CWM) para cada ponto amostral e analisamos a variação individual por meio de decomposição de variância aninhada e estatística T.As comunidades do Cerrado foram mais ricas e numerosas. Não encontramos nenhuma relação consistente entre diversidade funcional e conversão florestal além das mudanças na diversidade de espécies. Surpreendentemente, embora as mudanças na paisagem tenham sido mais recentes no Cerrado, a colonização do novo habitat por espécies nativas já adaptadas a habitats abertos diminuiu a perda funcional nos novos habitats deste bioma em comparação com a Mata Atlântica, onde as pastagens foram colonizadas apenas por espécies florestais generalistas e invasores exóticos. Isso indica que os efeitos da mudança de habitat na diversidade de caracteres dependem do conjunto regional de espécies e não do tempo desde a conversão da paisagem.Além disso, os efeitos da conversão florestal foram principalmente devidos à efeitos de filtros internos. Os efeitos de filtros externos apareceram apenas no nível de variância intraespecífica, com diferenças contrastantes entre o Cerrado, onde são selecionados caracteres relacionados ao comportamento de realocação e tamanho (Comprimento da Metatíbia, Comprimento, Volume e Largura do Pronoto) e a Mata Atlântica, onde a seleção opera em caracteres relacionadas ao comportamento de realocação e voo (Metatibia Length e Wing Load). Esses resultados evidenciam a importância de se considerar a variância individual para abordar as respostas das comunidades de rola­bostas à conversão florestal.

Integrating Prediction and Performance Models into Scenario-based Resilient Community Design.

Urban expansion can worsen climate change conditions and enlarge hazard zones. Sea level rise due to climate change makes coastal populations more susceptible to flood risks. The use of land change prediction modelling to inform scenario-based planning has been shown to help increase capabilities when dealing with uncertainties in urbanization such as urban growth and flood risk, when compared to singular comprehensive plans. This research uses the Land Transformation model to predict three different urban growth scenarios for Tampa, FL to determine how effective the current comprehensive plan is in adapting urban growth to decreasing flood risk and pollutant load. To achieve this, the research develops master plans according to each scenario then assesses their probable impact using the Long-Term Hydrologic Impact Analysis Low Impact Development Spreadsheet as a performance model. Findings show that the current future land use plan for Tampa, while it appears to be better than current patterns of development, has higher flood exposure, stormwater runoff, and pollutant discharge that current conditions but more than a purely resilient approach to future growth.

Advancing Scenario Planning through Integrating Urban Growth Prediction with Future Flood Risk Models.

High uncertainty about future urbanization and flood risk conditions limits the ability to increase resiliency in traditional scenario-based urban planning. While scenario planning integrating urban growth prediction modeling is becoming more common, these models have not been effectively linked with future flood plain changes due to sea level rise. This study advances scenario planning by integrating urban growth prediction models with flood risk scenarios. The Land Transformation Model, a land change prediction model using a GIS based artificial neural network, is used to predict future urban growth scenarios for Tampa, Florida, USA, and future flood risks are then delineated based on the current 100-year floodplain using NOAA level rise scenarios. A multi-level evaluation using three urban prediction scenarios (business as usual, growth as planned, and resilient growth) and three sea level rise scenarios (low, high, and extreme) is conducted to determine how prepared Tampa's current land use plan is in handling increasing resilient development in lieu of sea level rise. Results show that the current land use plan (growth as planned) decreases flood risk at the city scale but not always at the neighborhood scale, when compared to no growth regulations (business as usual). However, flood risk when growing according to the current plan is significantly higher when compared to all future growth residing outside of the 100-year floodplain (resilient growth). Understanding the potential effects of sea level rise depends on understanding the probabilities of future development options and extreme climate conditions.

Climate Change Preparedness: Comparing Future Urban Growth and Flood Risk in Amsterdam and Houston.

Rising sea levels and coastal population growth will increase flood risk of more people and assets if land use changes are not planned adequately. This research examines the efficacy of flood protection systems and land use planning by comparing Amsterdam in the Netherlands (renown for resilience planning methods), with the city of Houston, Texas in the US (seeking ways of increasing resilience due to extreme recent flooding). It assesses flood risk of future urban growth in lieu of sea level rise using the Land Transformation Model, a Geographic Information Systems (GIS)-based Artificial Neural Network (ANN) land use prediction tool. Findings show that Houston has currently developed much more urban area within high-risk flood-prone zones compared to Amsterdam. When comparing predicted urban areas under risk, flood-prone future urban areas in Amsterdam are also relatively smaller than Houston. Finally, the increased floodplain when accounting for sea level rise will impact existing and future urban areas in Houston, but do not increase risk significantly in Amsterdam. The results suggest that the protective infrastructure used in the Netherlands has protected its future urban growth from sea level rise more adequately than has Houston.

Global relative species loss due to first-generation biofuel production for the transport sector.

The global demand for biofuels in the transport sector may lead to significant biodiversity impacts via multiple human pressures. Biodiversity assessments of biofuels, however, seldom simultaneously address several impact pathways, which can lead to biased comparisons with fossil fuels. The goal of the present study was to quantify the direct influence of habitat loss, water consumption and greenhouse gas (GHG) emissions on potential global species richness loss due to the current production of first-generation biodiesel from soybean and rapeseed and bioethanol from sugarcane and corn. We found that the global relative species loss due to biofuel production exceeded that of fossil petrol and diesel production in more than 90% of the locations considered. Habitat loss was the dominating stressor with Chinese corn, Brazilian soybean and Brazilian sugarcane having a particularly large biodiversity impact. Spatial variation within countries was high, with 90th percentiles differing by a factor of 9 to 22 between locations. We conclude that displacing fossil fuels with first-generation biofuels will likely negatively affect global biodiversity, no matter which feedstock is used or where it is produced. Environmental policy may therefore focus on the introduction of other renewable options in the transport sector.

A Comparison of Vacancy Dynamics between Growing and Shrinking Cities Using the Land Transformation Model.

Every city seeks opportunities to spur economic developments and, depending on its type, vacant land can be seen as a potential threat or an opportunity to achieve these developments. Although vacant land exists in all cities, the causes and effects of changes in vacant land can differ. Growing cities may have more vacant land than shrinking cities because of large scale annexation. Meanwhile, depopulation and economic downturn may increase the total amount of vacant and abandoned properties. Despite various causes of increase and decrease of vacant land, the ability to predict future vacancy patterns - where future vacant parcels may occur-could be a critical test to set up appropriate development strategies and land use policies, especially in shrinking cities, to manage urban decline and regeneration efforts more wisely. This study compares current and future vacancy patterns of a growing city (Fort Worth, TX, USA) and a shrinking city (Chicago, IL, USA), by employing the Land Transformation Model (LTM) to predict for future vacant lands. This research predicts and produces possible vacancy pattern scenarios by 2020 and deciphers the ranking of determinants of vacant land in each city type. The outcomes of this study indicate that the LTM can be useful for simulating vacancy patterns and the causes of vacancy vary in both growing and shrinking cities. Socio-economic factors such as unemployment rate and household income are powerful determinants of vacancy in a growing city, while physical and transportation-related conditions such as proximity to highways, vehicle accessibility, or building conditions show a stronger influence on increasing vacant land in a shrinking city.

Exploring an Ecologically Sustainable Scheme for Landscape Restoration of Abandoned Mine Land: Scenario-Based Simulation Integrated Linear Programming and CLUE-S Model.

Understanding abandoned mine land (AML) changes during land reclamation is crucial for reusing damaged land resources and formulating sound ecological restoration policies. This study combines the linear programming (LP) model and the CLUE-S model to simulate land-use dynamics in the Mentougou District (Beijing, China) from 2007 to 2020 under three reclamation scenarios, that is, the planning scenario based on the general land-use plan in study area (scenario 1), maximal comprehensive benefits (scenario 2), and maximal ecosystem service value (scenario 3). Nine landscape-scale graph metrics were then selected to describe the landscape characteristics. The results show that the coupled model presented can simulate the dynamics of AML effectively and the spatially explicit transformations of AML were different. New cultivated land dominates in scenario 1, while construction land and forest land account for major percentages in scenarios 2 and 3, respectively. Scenario 3 has an advantage in most of the selected indices as the patches combined most closely. To conclude, reclaiming AML by transformation into more forest can reduce the variability and maintain the stability of the landscape ecological system in study area. These findings contribute to better mapping AML dynamics and providing policy support for the management of AML.