Impact of cropland displacement on the potential crop production in China:a multi-scale analysis

Changes in the amount and location of cropland areas may affect the potential crop production at different spatial scales. However, most studies ignore the impacts of cropland displacement on potential crop production. In many countries, cropland protection policies mainly aim for no loss in cropland area, while there is no restriction on change of cropland location. Taking China as the study area, we analyze the impacts of cropland displacement on potential crop production at four administrative levels during the period 2000 and 2018. At the national level, we find a net decrease in cropland area of 0.81 Mha, while another 19.63 Mha was displaced. The former led to a decrease of 4.20 Mton in potential crop production, while the latter resulted in a decrease of 43.26 Mton as a result of lower quality of the newly cultivated lands. In other words, cropland displacement explains 91% of the total loss in potential crop production at the national scale. However, the contribution of cropland displacement to total change in potential crop production is increasingly smaller at provincial level, municipal level, and county levels. These findings highlight the importance of geographic location on crop production and suggest that cropland policies should consider geographic location in addition to cropland area

Modelling land system evolution and dynamics of terrestrial carbon stocks in the Luanhe River Basin, China: a scenario analysis of trade-offs and synergies between sustainable development goals

A more holistic understanding of land use and land cover (LULC) will help minimise trade-offs and maximise synergies, and lead to improved future land use management strategies for the attainment of Sustainable Development Goals (SDGs). However, current assessments of future LULC changes rarely focus on the multiple demands for goods and services, which are related to the synergies and trade-offs between SDGs and their targets. In this study, the land system (combinations of land cover and land use intensity) evolution trajectories of the Luanhe River Basin (LRB), China, and major challenges that the LRB may face in 2030, were explored by applying the CLUMondo and InVEST models. The results indicate that the LRB is likely to experience agricultural intensification and urban growth under all four scenarios that were explored. The cropland intensity and the urban growth rate were much higher under the historical trend (Trend) scenario compared to those with more planning interventions (Expansion, Sustainability, and Conservation scenarios). Unless the forest area and biodiversity conservation targets are implemented (Conservation scenario), the forest areas are projected to decrease by 2030. The results indicate that water scarcity in the LRB is likely to increase under all scenarios, and the carbon storage will increase under the Conservation scenario but decrease under all other scenarios by 2030. Our methodological framework and findings can guide regional sustainable development in the LRB and other large river basins in China, and will be valuable for policy and planning purposes to the pursuance of SDGs at the sub-national scale

Modelling land system evolution and dynamics of terrestrial carbon stocks in the Luanhe River Basin, China: a scenario analysis of trade-offs and synergies between Sustainable Development Goals

A more holistic understanding of land use and land cover (LULC) will help minimise trade-offs and maximise synergies, and lead to improved future land use management strategies for the attainment of Sustainable Development Goals (SDGs). However, current assessments of future LULC changes rarely focus on the multiple demands for goods and services, which are related to the synergies and trade-offs between SDGs and their targets. In this study, the land system (combinations of land cover and land use intensity) evolution trajectories of the Luanhe River Basin (LRB), China, and major challenges that the LRB may face in 2030, were explored by applying the CLUMondo and InVEST models. The results indicate that the LRB is likely to experience agricultural intensification and urban growth under all four scenarios that were explored. The cropland intensity and the urban growth rate were much higher under the historical trend (Trend) scenario compared to those with more planning interventions (Expansion, Sustainability, and Conservation scenarios). Unless the forest area and biodiversity conservation targets are implemented (Conservation scenario), the forest areas are projected to decrease by 2030. The results indicate that water scarcity in the LRB is likely to increase under all scenarios, and the carbon storage will increase under the Conservation scenario but decrease under all other scenarios by 2030. Our methodological framework and findings can guide regional sustainable development in the LRB and other large river basins in China, and will be valuable for policy and planning purposes to the pursuance of SDGs at the sub-national scale

Land-change dynamics and ecosystem services using expert-based assessment and GIS: methodological implications for improving decision-making

Tesis por compendio[ES] Los servicios ecosistémicos de montaña han adquirido importancia entre los científicos, los administradores y los encargados de formular políticas de todo el mundo; sin embargo, las actividades humanas están amenazando su conservación, en particular los cambios en el uso del suelo debido al aumento de la urbanización, la expansión agrícola y la deforestación. La Puna Altoandina es un ecosistema montañoso representativo que enfrenta estos serios y crecientes desafíos. La Puna Altoandina, cuyos principales socioecosistemas consisten en pastizales naturales, matorrales y zonas agrícolas, puede proporcionar múltiples servicios ecosistémicos influenciados por el tipo de cobertura terrestre y sus dinámicas. En este contexto, se han explorado las dinámicas entre los usos representativos de la superficie terrestre y su potencial para proporcionar servicios ecosistémicos en la Puna húmeda Altoandina a lo largo del tiempo. Asimismo, se ha completado un análisis espacio-temporal que describe cómo diferentes patrones de 6 dinámicas de cambio del uso del suelo impactan en la provisión de 7 servicios ecosistémicos durante un período de 13 años (de 2000 a 2013), y en el territorio de 25 provincias. Además, con el fin de mejorar la gestión de los servicios ecosistémicos, abordamos los efectos de aplicar dos análisis "clúster" (estáticos y dinámicos) para evaluar los conjuntos de servicios ecosistémicos en cuatro escalas de observación diferentes (dos ámbitos administrativos y dos tamaños de pixel geográfico: 0.25 y 9 km2). En general, este estudio proporciona un enfoque para facilitar la incorporación de los servicios ecosistémicos a múltiples escalas que permite una interpretación fácil del desarrollo de la región y que puede contribuir a mejorar las acciones para la gestión del uso del suelo y las decisiones de política ambiental.[CA] Els serveis ecosistèmics muntanya han adquirit importància entre els científics, els administradors i els encarregats de formular polítiques de tot el món; no obstant això, les activitats humanes estan amenaçant la seua conservació, en particular els canvis en l'ús del sòl a causa de l'augment de la urbanització, l'expansió agrícola i la desforestació. La Puna Altoandina és un ecosistema muntanyenc representatiu que enfronta aquests seriosos i creixents desafiaments. La Puna Altoandina que els seus principals soci-ecosistemes consisteixen en pasturatges naturals, matolls i zones agrícoles, pot proporcionar múltiples serveis ecosistèmics influenciats per les diferents categories de cobertura terrestre y els seus dinàmiques. En aquest context, s'han explorat les dinàmiques entre els usos representatius de la superfície terrestre i el seu potencial per a proporcionar serveis ecosistèmics en la Puna humida Altoandina al llarg del temps. Així mateix, s'ha completat una anàlisi espai-temporal que descriu com diferents patrons de 6 dinàmiques de canvi de l'ús del sòl impacten en la provisió de 7 serveis ecosistèmics durant un període de 13 anys (de 2000 a 2013), i en el territori de 25 províncies. A més, amb la finalitat de millorar la gestió dels serveis ecosistèmics, abordem els efectes d'aplicar dues anàlisis "clúster" (estàtics i dinàmics) per a avaluar els conjunts de serveis ecosistèmics en quatre escales d'observació diferents (dos àmbits administratius i dues grandàries de píxel geogràfic: 0.25 y 9 km2). En general, aquest estudi proporciona un enfocament per a facilitar la incorporació dels serveis ecosistèmics a múltiples escales que permet una interpretació fàcil del desenvolupament de la regió i que pot contribuir a millorar les accions per la gestió de l'ús del sòl i les decisions de política ambiental.[EN] Mountain ecosystem services have gained relevance among scientists, managers, and policy-makers worldwide; but, human activities are threatening its conservation, particularly land changes due to increased urbanization, agricultural expansion and deforestation. The high-Andean Puna is a representative mountain ecosystem that is facing these serious and growing challenges. The high-Andean Puna, whose main socialecosystems consist of natural grassland, shrubland and agricultural areas, can provide multiple regulating ecosystem services influenced by the land cover/use type and their dynamics. In this context, we explored the dynamics between the representative land-cover classes and its potential to provide ecosystem services in the high-Andean moist Puna over time. We completed a spatiotemporal analysis that describes how different patterns of 6 landchange dynamics impact on the supply of 7 ecosystem services over a period of 13 years (from 2000 to 2013), and across 25 provinces. Moreover, in order to improve the management of ecosystem services, we addressed the effects of applying two cluster analyses (static and dynamic) for assessing bundles of ecosystem services across four different scales of observation (two administrative boundaries and two sizes of grids: 0.25 and 9 km2). Overall, this study provides an approach to facilitate the incorporation of ES at multiple scales allowing an easy interpretation of the region development that can contribute to land management actions and policy decisions.Madrigal Martínez, S. (2021). Land-change dynamics and ecosystem services using expert-based assessment and GIS: methodological implications for improving decision-making [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/172369TESISCompendi

Advancing large-scale analysis of human settlements and their dynamics

Due to the importance for a range of sustainability challenges, it is important to understand the spatial dynamics of human settlements. The rapid expansion of built-up land is among the most extensive global land changes, even though built-up land occupies only a small fraction of the terrestrial biosphere. Moreover, the different ways in which human settlements are manifested are crucially important for their environmental and socioeconomic impacts. Yet, current analysis of human settlements heavily relies on land cover datasets, which typically have only one class to represent human settlements. Consequently, the analysis of human settlements does often not account for the heterogeneity within urban environment or their subtle changes. This simplistic representation severely limits our understanding of change processes in human settlements, as well as our capacity to assess socioeconomic and environmental impacts. This thesis aims to advance large-scale analysis of human settlements and their dynamics through the lens of land systems, with a specific focus on the role of land-use intensity. Chapter 2 explores the use of human settlement systems as an approach to understanding their variation in space and changes over time. Results show that settlement systems exist along a density gradient, and their change trajectories are typically gradual and incremental. In addition, results indicate that the total increase in built-up land in village landscapes outweighs that of dense urban regions. This chapter suggests that we should characterize human settlements more comprehensively to advance the analysis of human settlements, going beyond the emergence of new built-up land in a few mega-cities only. In Chapter 3, urban land-use intensity is operationalized by the horizontal and vertical spatial patterns of buildings. Particularly, I trained three random forest models to estimate building footprint, height, and volume, respectively, at a 1-km resolution for Europe, the US, and China. The models yield R2 values of 0.90, 0.81, and 0.88 for building footprint, height, and volume, respectively. The correlation between building footprint and building height at a pixel level was 0.66, illustrating the relevance of mapping these properties independently. Chapter 4 builds on the methodological approach presented in chapter 3. Specifically, it presents an improved approach to mapping 3D built-up patterns (i.e., 3D building structure), and applies this to map building footprint, height, and volume at a global scale. The methodological improvement includes an optimized model structure, additional explanatory variables, and updated input data. I find distance decay functions from the centre of the city to its outskirts for all three properties for major cities in all continents. Yet, again, the height, footprint (density), and volume differ drastically across these cities. Chapter 5 uses built-up land per person as an operationalization for urban land-use intensity, in order to investigate its temporal dynamics at a global scale. Results suggest that the decrease of urban land-use intensity relates to 38.3%, 49.6%, and 37.5% of the built-up land expansion in the three periods during 1975-2015, but with large local variations. In the Global South, densification often happens in regions where human settlements are already used intensively, suggesting potential trade-offs with other living standards. These chapters represent the recent advancements in large-scale analysis of human settlements by revealing a large variation in urban fabric. Urban densification is widely acknowledged as one of the tangible solutions to satisfy the increased land demand for human settlement while conserving other land, suggesting the relevance of these findings to inform sustainable development. Nevertheless, local settlement trajectories towards intensive forms should also be guided in a large-scale context with broad considerations, including the quality of life for inhabitants, because these trade-offs and synergies remain largely unexplored in this analysis

Socioeconomic contexts for the spatial variations of ecosystem services and the associated uncertainties

Ecosystem services are strongly underpinned by ecological processes and functions and influenced by socioeconomics in human-environmental systems. As the prerequisites for human well-being, ecosystem services can reflect the interactions of human and environmental systems. Being pervading the process of ecosystem service assessments, uncertainties should be uncovered and preferably reduced before the assessing results are adopted for the decision-making of regional environmental management. This study explores the interrelationships between ecosystem services and socioeconomic variables at regional scales, develops a methodological framework of uncertainty analysis and applies it to investigate the uncertainties emerged in the assessments of ecosystem services of the study areas. Chapter 1 provides a brief review of the fields concerning the ecosystem service issues addressed in this thesis. The introduction involves the basic concepts related to ecosystem services, the state of the art of ecosystem service quantification and mapping, the role of ecosystem services in human-environmental systems, ecosystem services’ linkages with socioeconomics as well as the uncertainties in ecosystem service assessments. After uncovering the respective research gaps, this chapter identifies and elucidates the objectives of the study and raises the associated four research questions. Chapter 2 explores the socioeconomic influences on biodiversity, ecosystem services and human well-being at the regional scale of Jiangsu, China on the basis of the DPSIR (Driver-Pressure-State-Impact-Response) conceptual model. Additionally, the study investigates the quantitative linkages between the five sectors of the DPSIR model. The results show that urbanization and industrialization in the urban areas can have positive influences on regional biodiversity, agricultural productivity, tourism services and rural residents’ living standards. Besides, the knowledge, technology and finance inputs for agriculture have positive impacts on these system components. Concerning regional carbon storage, non-cropland vegetation cover obviously plays a significant positive role. Contrarily, the expansion of farming land and the increase of total food production are two important negative influential factors of biodiversity, ecosystems’ food provisioning capacity, regional tourism income and the well-being of the rural population. Finally, the linkages of the DPSIR sectors in a network pattern are quantitatively evidenced. Chapter 3 characterizes the urban-rural gradients of ecosystem services and socioeconomics of Leipzig, Germany and Kunming, China. It further quantifies the linkages between the gradients of ecosystem services and socioeconomics and conducts gradient comparisons between different gradient patterns in the two study areas. The chapter ends with the revelation of the uncertainties in creating the gradients. The results show some similar regularities in the spatial patterns of ecosystem services and socioeconomic dimensions in both study areas. Habitat quality and f-evapotranspiration of Leipzig and habitat quality of Kunming demonstrate apparent trends of increases along all gradient patterns. However, the other ecosystem services present divergent spatial variability in different gradient patterns. Road density, urban fabric and population density show identical declining trends in both study areas except for the soaring of population density around the center of Leipzig. Differently, household size, housing area and unemployment rate in Leipzig present inconsistent spatial dynamics with considerable fluctuations. Regarding the gradient interrelations, road density, urban fabric and population density are strongly correlated with most ecosystem service types in both case study areas. In contrast, the gradients of household size, housing area and unemployment rate of Leipzig show inconsistent correlations with the ecosystem services gradients. The introduced uncertainty gradient method shows appropriateness to quantitatively capture the uncertainties in exploring ecosystem services and socioeconomic gradients in urban-rural areas. Chapter 4 addresses the spatial characteristics of ecosystem services and the respective socioeconomic influences in a heavily human-disturbed watershed in Southwest China. It firstly quantifies and maps five ecosystem services of nine river basins of the Dianchi Lake Watershed. The quantification is based on the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and the biophysical and socioeconomic data. Thereafter, a confirmatory research is conducted by using a hypothesis-test methodology to investigate the socioeconomic causes of the spatial changes of the five ecosystem services. On the basis of the modeling results of nitrogen retention and water yield, this chapter exemplifies the distinctions between ecosystem services potential, flow and demand and performs a sensitivity analysis to test the influences of input data and parameter uncertainties on the modeling results. The hypothesis-test analysis reveals only a small number of socioeconomic influential factors, most of which are related to land use structure. The hypothesis-test methodology provided in this study is applicable in the investigation of socioeconomic influences on ecosystem services in the situation of socioeconomic data uncertainty and scarcity. Chapter 5 summarizes the sources of uncertainties in landscape analysis and ecosystem service assessments and proposes a methodology to analyze and reduce the uncertainties. The fundamental uncertainty origins of landscape analysis are landscape complexity and methodological uncertainties. The major uncertainty sources of ecosystem service assessments include the complexity of the natural system, respondents’ preferences and technical problems. Among these uncertainty source categories, initial data uncertainty pervades the whole assessment process and the limited knowledge about the complexity of ecosystems is the focal uncertainty origin. To analyze the uncertainties in assessments, systems analysis, scenario simulation and the comparison method are promising strategies. Lastly, we assume that the actions to reduce uncertainties should integrate continuous learning, expanding respondent numbers and sources, considering representativeness, improving and standardizing assessment methods and optimizing spatial and geobiophysical data. Chapter 6 reaches the general conclusions of this thesis. It firstly answers the four research questions asked in the introduction. In the answers, the close connections between ecosystem services and socioeconomics are confirmed, the applicability of the mainstreaming quantification methods is debated, the strength of ecosystem service mapping is illustrated and the necessity and possibility of uncertainty analysis are argued. In ending the entire thesis, chapter 6 further generally evaluates the ecosystem service approach and identifies and main obstacles and problems in the application of ecosystem services. Moreover, it proposes potential solutions to the overcome the impediments and finally calls for an optimistic attitude to propel ecosystem services research

Indicators of Agricultural intensity and intensification: a review of the literature

Since the 1960s, research has dealt with agricultural intensification (AI) as a solution to ensure global food security. Recently, sustainable intensification (SI) has increasingly been used to describe those agricultural and farming systems that ensure adequate ecosystem service provision. Studies differ in terms of the application scales and methodologies, thus we aim to summarize the main findings from the literature on how AI and SI are assessed, from the farm to global levels. Our literature review is based on 7865 papers selected from the Web of Science database and analysed using CorText software. A further selection of 105 relevant papers was used for an in-depth full-text analysis on: i) farming systems studied; ii) related ecosystem services; iii) indicators of intensity; and iv) temporal and spatial scales of analysis. Through this two-step analysis we were able to highlight three main research gaps in the AI research indicators. Firstly, the farming systems analysed for assessing AI are often quite simplified or monoculture- oriented, and they do not take the diversity and complex organisation of farming systems into account. Secondly, these studies mainly focus on northern countries or developing countries, whereas there is a gap of knowledge in Mediterranean areas, which are the areas with a high complexity of farming systems and diversity in ecosystem services. Finally, AI is mostly assessed through nitrogen inputs and economic yield, which are used the most both at very local and global levels. Intermediate regional or local levels, which are relevant for policy implementation and local planning, are often neglected