M. Said et al., 'Challenges and impacts of land use and land use planning on ecosystem, biodiversity, and people', ILRI, 2017

Introduction: Land-use management strategies play a major role in biodiversity change. In many parts of the world, local governments are under increasing pressure to regulate human activity to mitigate negative impacts on ecosystems. Outcomes/other: This study aimed to analyze the effects of different land-use patterns on biodiversity change across a typical artificial desert watershed. We first analyzed land-cover change based on past and future management scenarios in a watershed spanning Gaotai, Linze, and Ganzhou counties in northwest China. We then analyzed the effect of different land-use patterns on biodiversity change in the watershed. We found that the crucial land-cover changes are likely to occur in the wetland reserves and areas established for the Grain for Green Project around the oases, and such changes could affect biodiversity throughout the entire watershed landscape. Discussion: The use of spatial analysis to illustrate explicit changes in ecosystems is useful in fostering biodiversity awareness and the need for decision-making at different scales. Conclusion: Thus, these findings indicate that land-use management strategies for the middle and southeast parts of the watershed are particularly important for future management of biodiversity and the integrated ecosystem services of the entire watershed landscape.

Since the mid 1980s, freshwater ecosystems have experienced larger declines in biodiversity than terrestrial and marine ecosystems. Pressures on freshwater ecosystems are mainly human-induced and driven by land use changes. The objective of this paper is to evaluate how land-use adaptation to climate change affects freshwater ecosystems in France. For this purpose, we use data on land use shares (agriculture, pasture, forest and urban) and on an indicator of the ecological status of surface water, namely a fish-based index (FBI) measured for various French rivers observed between 2001 and 2013. We estimate two models: a spatial econometric land use share model and a statistical spatial panel FBI model. The land use share model describes how land use is affected by economic, physical and demographic factors, while the FBI model explains the spatial and temporal distribution of the FBI score by land use and pedo-climatic variables. Our estimation results indicate that land-use adaptation to climate change reduces freshwater biodiversity. We use our estimation results to analyze how two command-and-control policy options could help France to comply with the EU Water Framework directive and mitigate the adverse impacts of climate change on freshwater biodiversity.

Land‐use change is the single biggest driver of biodiversity loss in the tropics. Biodiversity models can be useful tools to inform policymakers and conservationists of the likely response of species to anthropogenic pressures, including land‐use change. However, such models generalize biodiversity responses across wide areas and many taxa, potentially missing important characteristics of particular sites or clades. Comparisons of biodiversity models with independently collected field data can help us understand the local factors that mediate broad‐scale responses. We collected independent bird occurrence and abundance data along two elevational transects in Mount Kilimanjaro, Tanzania and the Taita Hills, Kenya. We estimated the local response to land use and compared our estimates with modelled local responses based on a large database of many different taxa across Africa. To identify the local factors mediating responses to land use, we compared environmental and species assemblage information between sites in the independent and African‐wide datasets. Bird species richness and abundance responses to land use in the independent data followed similar trends as suggested by the African‐wide biodiversity model, however the land‐use classification was too coarse to capture fully the variability introduced by local agricultural management practices. A comparison of assemblage characteristics showed that the sites on Kilimanjaro and the Taita Hills had higher proportions of forest specialists in croplands compared to the Africa‐wide average. Local human population density, forest cover and vegetation greenness also differed significantly between the independent and Africa‐wide datasets. Biodiversity models including those variables performed better, particularly in croplands, but still could not accurately predict the magnitude of local species responses to most land uses, probably because local features of the land management are still missed. Overall, our study demonstrates that local factors mediate biodiversity responses to land use and cautions against applying biodiversity models to local contexts without prior knowledge of which factors are locally relevant.

This thesis studies how modern spatio temporal databases of land use changes can be created based on historical maps. The entire study was conducted based on the available maps over the study area, in southern Sweden. The research was conducted in such a manner that it presents to what extent can land use changes affect biodiversity and climate change. The thesis is not focused on what are the drivers for land use conversions, but rather how could changes in land use be easier identified when working with a set of (historical) maps over the same area. Based on a very first decision, in terms of what land use data can be used in further studies by different research communities, a study was conducted as to determinate what are the available historical sources. A database was created, containing land use data, classified accordingly to modern international land cover classification, extracted from historical maps, during the time frame 1812 - 2006. Considering the needs in terms of land use conversion for the biodiversity and carbon modeling communities, analyzing tools were developed to provide a fast and efficient way to easily identify in which time frame drastic land use conversions occurred and how much the study area was affected. The tools were created as to ease the preliminary analysis on land use maps, to quickly identify changes based on statistics, rather than visual analysis. The historical land-use database was tested over a study area in southern Sweden. The tool developed is able to extract statistics from at least 2 maps simultaneous and express how much of land class there is on each map. The users can quickly retrieve statistics when the surfaces for each land class are available. | According to the Intergovernmental Panel on Climate Change (IPCC, 2017), both land use conversions and use of fossil fuels are the sources of the increase of GHG, leading to global warming. Due to the high demand of land use conversions (such as increased areas of cultivated soil, forest clearance, urban areas development etc.), the land use suffers changes, some of them irreversible, whose effects can be measured in the amounts of greenhouse gas emissions released in the atmosphere. Furthermore, the land use and land cover change highly affect the local biodiversity, in terms of biodiversity loss or biodiversity alterations. Many of these changes were captured either in historical maps, in cadastral dossiers or written texts, by the authorized representatives in charge at that time. The GIS communities aim to process historical datasets in order to provide modern databases to other research communities, such the present study case. The methodology was structured into five processing steps. The first step was to identify the need for historical land use data, analyzed both from a carbon modeling and biodiversity perspective. The second part focused on checking the availability of historical land-use map resources, for the study area (Hyltemossa, Sweden), between the time frame 1812-2006. Once the needs and available map resources for such a database were known, the next step was to decide what land-use/land cover classification to use. It was chosen the modern Corine Land Cover Classification (Corine CLC). An important part was the actual creation of the historical land use database and the tools for analyzing the database, processing step number four. The historical maps were georeferenced and digitized, and stored as raster images into a database, using the GIS software ArcMap. To interpret changes over time, an analyzing tool was developed, with the capacity to detect changes from several overlaid maps of the same area (the fifth processing step). The function was developed from detecting pixel level changes to larger areas and the results are presented a table with statistics of a number of pixels that changed their values from one map to the other. The results and discussion focused on the resources used in this project, the digitized historical maps and the feasibility of the analyzing tool.

Understanding the responses of biodiversity to different land use regimes is critical for managing biodiversity in the face of future land use change. However, there is still significant uncertainty around how consistent the responses of different taxonomic groups to land use change are. Here, we use a combination of high‐throughput environmental DNA sequencing and traditional field‐based survey methods to examine how patterns of richness and community composition correlate among four domains/kingdoms (bacteria, fungi, plants, and metazoans) and the four most‐abundant animal taxonomic groups (arachnids, Collembola, insects, and nematodes) across five different land use types (natural forest, planted forest, unimproved grassland, improved grassland, and vineyards). Richness for each taxonomic group varied between land use types, yet different taxa showed inconsistent responses to land use, and their richness was rarely correlated. This contrasted with community composition of taxonomic groups, for which there was relatively good discrimination of land use types and there was strong correlation between group responses. We found little evidence for consistent drivers of taxonomic richness, yet identified several significant drivers of community composition that were shared across many groups. Drivers of composition were not the same as the drivers of diversity, suggesting diversity and composition are independently controlled. While land use intensification has been viewed as having generally negative effects on biodiversity, our results provide evidence that different taxa respond divergently across different land uses. Further, our study demonstrates the power of high‐throughput sequencing of environmental DNA as a tool for addressing broad ecological patterns relating to landscape biodiversity.

International audience | Life Cycle Assessment (LCA) is a widely used tool to assess environmental sustainability of products. The LCA should optimally cover the most important environmental impact categories such as climate change, eutrophication and biodiversity. However, impacts on biodiversity are seldom included in LCAs due to methodological limitations and lack of appropriate characterization factors. When assessing organic agricultural products the omission of biodiversity in LCA is problematic, because organic systems are characterized by higher species richness at field level compared to the conventional systems. Thus, there is a need for characterization factors to estimate land use impacts on biodiversity in life cycle assessment that are able to distinguish between organic and conventional agricultural land use that can be used to supplement and validate the few currently suggested characterization factors. Based on a unique dataset derived from field recording of plant species diversity in farmland across six European countries, the present study provides new midpoint occupation Characterization Factors (CF) expressing the Potentially Disappeared Fraction (PDF) to estimate land use impacts on biodiversity in the 'Temperate Broadleaf and Mixed Forest' biome in Europe. The method is based on calculation of plant species on randomly selected test sites in the biome and enables the calculation of characterization factors that are sensitive to particular types of management. While species richness differs between countries, the calculated CFs are able to distinguish between different land use types (pastures (monocotyledons or mixed), arable land and hedges) and management practices (organic or conventional production systems) across countries. The new occupation CFs can be used to supplement or validate the few current CF's and can be applied in LCAs of agricultural products to assess land use impacts on species richness in the 'Temperate Broadleaf and Mixed Forest' biome.

Land-use change is one of the greatest threats to biodiversity, especially in the tropics where secondary and plantation forests are expanding while primary forest is declining. Understanding how well these disturbed habitats maintain biodiversity is therefore important—specifically how the maturity of secondary forest and the management intensity of plantation forest affect levels of biodiversity. Previous studies have shown that the biotas of different continents respond differently to land use. Any continental differences in the response could be due to differences in land-use intensity and maturity of secondary vegetation or to differences among species in their sensitivity to disturbances. We tested these hypotheses using an extensive dataset collated from published biodiversity comparisons within four tropical regions—Asia, Africa, Central America and South America—and a wide range of animal and plant taxa. We analysed responses to land use of several aspects of biodiversity—species richness, species composition and endemicity—allowing a more detailed comparison than in previous syntheses. Within each continent, assemblages from secondary vegetation of all successional stages retained species richness comparable to those in primary vegetation, but community composition was distinct, especially in younger secondary vegetation. Plantation forests, particularly the most intensively managed, supported a smaller—and very distinct—set of species from sites in primary vegetation. Responses to land use did vary significantly among continents, with the biggest difference in richness between plantation and primary forests in Asia. Responses of individual taxonomic groups did not differ strongly among continents, giving little indication that species were inherently more sensitive in Asia than elsewhere. We show that oil palm plantations support particularly low species richness, indicating that continental differences in the response of biodiversity to land use are perhaps more likely explained by Asia’s high prevalence of oil palm plantations.

As one of the largest biodiversity pools, soil biodiversity is affecting ecosystem services significantly. However, soil biodiversity is hidden below ground and has often been overlooked. It is extremely urgent for us to protect soil biodiversity. Here, we briefly illustrate the relationship among factors affecting soil biodiversity and the mechanisms of these factors influencing soil diversity. After evaluating seven factors expected to affect soil biodiversity (land-use change, organic carbon loss, agriculture/land-use intensity, soil erosion, soil compaction and sealing, soil pollution and soil acidification), we quantified and mapped the composite threats to soil biodiversity in Nanjing using a weighted sum method. The correlative relationships between the composite threats index and the seven factors were also used to identify the main threats to soil biodiversity. We found that threats to soil biodiversity generally decreased with distance from the city centre. Soil pollution, agriculture/land-use intensity and soil compaction were the main threats to soil biodiversity in Nanjing. Some suggestions for urban planning are also tentatively provided based on the main threats to soil biodiversity in urban, suburban and rural areas. The quantification of threats to soil biodiversity can provide a useful tool for decision-making and improving ecosystem services.

AIM: Land‐use change is considered a major threat to biodiversity. Species–area relationships (SARs), which are often used to assess biodiversity changes, assume that land use leads to the loss of natural habitats. Yet, in regions with long land‐use histories, such as Europe, many species have persisted in, or even depend on, landscapes heavily influenced by land use (i.e., countryside landscapes). Here, we develop a SAR model that considers the conservation value of such landscapes, and we assess how land use affects plant‐species richness at broad spatial scales. LOCATION: Countries in the European Union (EU‐27). METHODS: We first predicted species richness at a 50 × 50 km resolution using a biome‐specific SAR and used these predictions as a baseline estimate for (semi‐)natural vegetation. Then, we parameterized a countryside SAR (sensu Pereira & Daily, 2006) with habitat affinities derived from a meta‐analysis. We estimated changes in species richness as the difference in predictions between the two SAR models. RESULTS: At a 50 × 50 km resolution, predicted species richness has increased by up to 184 species due to land use in 73% of all cells across Europe compared to the (semi‐)natural baseline. However, our model also highlights regions with dramatic species losses (in 25% of cells, losses of up to 900 species) due to an unfavourable combination of land‐use changes. Averaged across all cells, we predict a loss of 26 plant species (SD = 119, median = 49). MAIN CONCLUSIONS: Adopting the countryside SAR model to broader spatial scales overcomes the unrealistic assumptions of previous approaches about generally negative effects of land use. Our approach predicts how local‐scale land‐use effects translate to biodiversity changes at broader geographic scales. Thus, it allows land‐use scenarios being studied in relation to their trade‐offs with biodiversity and can be used to target conservation efforts across large areas.