Land Management Strategies Research Articles

Spatiotemporal Differentiation of Land Ecological Security and Optimization Based on GeoSOS-FLUS Model: A Case Study of the Yellow River Delta in China Toward Sustainability

Land ecological security (LES) is a crucial issue pertaining to the sustainability of landscapes or land systems. Nevertheless, previous studies largely neglected the impacts of landscape structure on LES. This study, taking the Yellow River Delta (YRD) as the case area, analyzed the spatiotemporal differentiation patterns of regional LES in 19 counties (cities and districts) from 2000 to 2020 through the application of landscape metrics and employed GeoSOS-FLUS to forecast the landscape structure and corresponding land ecological security in 2030 under four different scenarios to advance sustainability. The results show that, first, landscape fragmentation and irregularity are decreasing, while aggregation and connectivity are increasing. The primary landscape change involves the transition from farmland to developed areas. Second, the LES index is rising. In 2020, about 73.68% of the research units reached level IV, while most were at level III. Third, it is projected that by 2030, the LES index will rise under all scenarios, exhibiting an eastward-declining gradient in its geographic distribution, with higher values prevailing in the eastern regions and gradually tapering off towards the west. It is expected that in the business-as-usual scenario, the proportion of LES reaching level V will be the highest. This study not only reveals the impact mechanism of the landscape structure on land ecological security but also provides an important basis for formulating scientific and rational land use planning and management strategies from the perspectives of sustainable land governance and sustainable land use.

Modeling future projections of land use and land cover in the Kakataibo territory

Abstract. The Amazon region is undergoing a dynamic and extensive transformation from forested areas to human-altered landscapes, significantly impacting forests and indigenous territories. This research aims to create future land use and land cover (LULC) scenarios by examining past trends (2014–2022) and predicting future patterns for 2030, focusing on the Kakataibo territory in central Peru. Using the Dinamica EGO modelling platform, we projected LULC changes based on historical data and various predictive factors. Our findings reveal notable forest loss between 2014 and 2022, with this trend likely continuing through 2030. Within indigenous territories, deforestation was less severe, with a reduction of 30,247.4 hectares compared to the more significant loss in non-indigenous areas. This underscores the vital role these territories play in mitigating forest loss. However, the rapid expansion of agriculture and infrastructure within these regions signals an urgent need for stronger legal protections to halt further deforestation. This study highlights the critical importance of indigenous territories in forest conservation and offers valuable insights for future land management and conservation strategies in the Amazon.

Salinity drives niche differentiation of soil bacteria and archaea in Hetao Plain, China

Soil salinization is a critical environmental issue that limits plant productivity and disrupts ecosystem functions. As important indicators of soil environment, soil microbes play essential roles in driving nutrient cycling and sustaining ecosystem services. Therefore, understanding how microbial communities and their functional potentials respond to varying levels of soil salinization across different land use types is crucial for the restoration and management of salt-affected ecosystems. In this study, we randomly selected 63 sites across the Hetao Plain, covering an area of ∼2500 km2. Our results showed that both salinity- and fertility-related soil parameters were significantly correlated with bacterial and archaeal diversities, with soil salinity emerging as the stronger predictor of prokaryotic diversity. Intriguingly, bacterial and archaeal communities were tightly interlinked but displayed opposite trends in response to environmental factors, indicating a clear microbial niche differentiation driven by soil salinity. Moreover, the generalist functions of bacteria and archaea (e.g., chemoheterotrophy) exhibited contrasting responses to environmental parameters, while their specialist functions (e.g., nitrification) responded consistently. These findings highlight the pivotal role of soil salinity in shaping the niche differentiation of bacterial and archaeal communities in saline soils, providing insights to guide salinity-centered restoration strategies for effective marginal land management.

Missing the biodiversity for the bee: Natural land management strategies impact functional invertebrate diversity in commercial cranberry production

Abstract Simplification of agricultural environments is linked to declines in biodiversity. Improving the floral diversity within and around these areas may result in more robust and diverse ecosystems. We investigated how floral resource abundance, diversity, and species composition in a cranberry agricultural system correlated to the abundance and overall invertebrate diversity and to the abundance and diversity of specific invertebrate groups of agricultural importance (e.g. parasitoids, phytophagous taxa, pollinators and predators). This study focused on habitats immediately surrounding cranberry production and included grassy dikes under a managed system (‘dike’), and semi‐natural areas growing on the surrounding support land (‘semi‐natural’). Floral resource availability and diversity tended to be similar between habitats, while invertebrate richness, diversity and composition differed. As the availability of floral resources increased, invertebrate abundance increased but diversity decreased. Overall invertebrate community composition differed with the specific species and availability of floral resources. The habitat type and floral resource composition impacted some agriculturally important groups, as pollinator abundance was higher in the semi‐natural habitat, and parasitoid abundance varied with floral resource composition across both habitats. These results suggest that managing the structural and floral resource diversity associated with agroecosystems can help support local biodiversity. However, these systems may disproportionately benefit more common taxonomic groups. The difference in responses of individual taxonomic groups also highlights the potential tradeoffs of focusing on only a subset of biodiversity aspects.

Spatially Explicit Impact of Land Use Changes in the Bay Area on Anthropogenic Phosphorus Emissions and Freshwater Eutrophication Potential.

Land use changes significantly impact anthropogenic phosphorus (P) emissions, their migration to a water environment, and the formation of freshwater eutrophication potential (FEP), yet the spatiotemporally heterogeneous relationships at the regional scale have been less explored. This study combines land use classification, P-flow modeling, spatial analysis, and cause-effect chain modeling to assess P emissions and P-induced FEP at a fine spatial resolution in Guangdong-Hong Kong-Macao Greater Bay Area and reveals their dynamic responses to land use changes. We find that land conversion from cultivated land to impervious land corresponded to an increase in P emissions of 4.1, 1.8, and 0.5 Gg during 2000-2005, 2005-2010, and 2010-2015 periods, respectively, revealing its dominant but weakening role in the intensification of P emissions especially in less-developed cities. Expansion of aquacultural land gradually became the primary contributor to the increase in both the amount and intensity of P emissions. Land conversions from cultivated land to impervious land and from natural water bodies to aquacultural land led to 35.9% and 25.3% of the increase in FEP, respectively. Our study identifies hotspots for mitigating the environmental pressure from P emissions and provides tailored land management strategies at specific regional development stages and within sensitive areas.

Towards sustainable development goals: Leveraging multi-data remote sensing fusion for monitoring groundwater-induced bedrock subsidence dynamics in Egypt's Nile Valley

Egypt's Golden Triangle megaproject within Egypt's vision 2030, involving land reclamation in Qena Bend's densely populated governorate, develops sustainable land management strategies. Advanced technologies and low-cost remote sensing multi-data fusion are utilized to understand subsidence dynamics influenced by geologic structure, groundwater, climate change, and human activities in Egypt's Nile Valley. This approach identifies environmental hazards and provides a detailed explanation for groundwater-induced bedrock subsidence, aiding in informed decision-making and risk avoidance. Landsat images reveal 13% increased cultivation, 28.28% urban-growth, and decreased water by 8.46%, impacting groundwater resources and controlling the situation. The Gravity Recovery and Climate Experiment(GRACE) and Global Land Data Assimilation System (GLDAS) satellite observations reveal changes in water storage, impacting climate change, groundwater storage dynamics, and aquifer behavior. Historical data indicates a significant southwest-northeast gradient in precipitation from 5 to 60 mm. GLDAS shows soil moisture decline from 0.25 to 0.23 mm. GRACE (total water storage) depleting, then slightly increasing from 2020 to 2023 with an average value (−5 cm/yr). Groundwater storage increases in wet seasons, in 2015 showing (+3–4 mm), less than (+1 mm) in (2018), and (+6–8 mm) in (2020–2023). The NE-SW and NW-SE faults increase hydraulic connection and recharge from aquifers, causing groundwater circulation and karstification in Eocene limestone aquifers, posing risks to urban development and human safety. The InSAR (Synthetic Aperture Radar) measures ground subsidence over time, revealing a range of (−0.04 to −0.07m) in the northwest to (+0.03m) in the southeast, with average subsidence (-4 cm), primarily associated with increased groundwater storage motivate the interaction between the carbonate and groundwater. The ArcGIS overlay model divides the region into three zones: northern, middle, and southern, each with varying degrees of displacement and groundwater storage. The findings emphasize the significance of remote sensing in hazard evaluation for development planning due to its cost-effectiveness and accuracy, applicable globally in hydrogeologically similar areas.

Mapping anthropogenic impacts on natural resources in the northeastern Sahara region: A case study on the past 26 years over the Ziban region (Algeria)

The objective of this research was to map and analyze anthropogenic impacts on natural resources in the Ziban region of Algeria using remote sensing imagery from 1995 to 2021. Medium-resolution satellite images from Landsat TM and OLI were utilized, with image processing techniques such as colorful compositions and supervised classification to map land cover. Seven land use and land cover (LULC) classes were identified, distinguishing human-derived categories (palm, agriculture, urban, and greenhouses) from natural surfaces (nebka, natural vegetation, and bare soil). The results indicated significant increases in human-driven elements like palm, urban areas, agriculture, greenhouses, and nebka, and notable decreases in natural components like vegetation and bare soil. Specifically, the rate of change (Tc) showed increases of 0.9% for palm, 1.14% for urban, 1.55% for agriculture, 1.91% for greenhouses, and 9.37% for nebka, and decreases of -3.68% for vegetation and -11.19% for bare soil. These findings highlight the impact of agricultural policies, population growth, and natural and human-induced conditions on natural resources. Palm areas remained largely unchanged due to state policies, whereas agriculture saw significant conversions to bare soil and palm. Vegetation declined substantially due to adverse climatic conditions and agricultural expansion. Nebka and urban areas had moderate to high conversion rates, and bare soil saw notable changes due to sand movement and urban/agricultural development. The study highlights the role of remote sensing and land cover analysis in managing natural resources sustainably, considering factors like agricultural policies and population growth. It emphasizes developing data-driven strategies for effective land use and management.

Evaluation of nature-based climate solutions for agricultural landscapes in the Galápagos Islands

The Galápagos Islands are highly vulnerable to climate and environmental change, and nature-based solutions can help local communities adapt local agricultural systems. Through a comparative analysis, we evaluated the effects of three land management strategies on soil temperature, soil water availability and storage, and carbon stocks in Santa Cruz Island (Galápagos Archipelago). We installed six monitoring sites that consisted of two replicates per pathway: (i) the avoided loss of tropical forest, (ii) the conservation of scattered trees and living fences in at-risk agroforestry system, and (iii) the increase in biomass after a reduction of the grazing intensity. The monitoring sites were equipped with a dense network of rain gauges, air temperature and relative humidity sensors, and capacitance/frequency probes that registered volumetric water content and soil temperature. After pedological characterization of the soil profiles, the soil physico-chemical and hydrophysical properties were determined in laboratory. Over a period of 30 months (July 2019 to December 2021), hydrometeorological and soil environmental data were collected.We assessed differences in soil temperature, moisture availability and soil organic carbon content between native forests, sites under traditional agroforestry and under passive restoration. Forest soils were 12 % cooler;, and soil moisture under forest was 20 % higher than in parcels with silvopastural management. Forest soils had a lower dry bulk density, lower saturated hydraulic conductivity and higher water retention capacity in comparison with the other two management types. In silvopastural systems, a decrease of grazing intensity had a positive effect on soil carbon stocks, that were about 50 % higher than in soils under traditional management. This study shows that avoided loss of tropical forest within an agricultural landscape is a promising strategy to mitigate increasing soil temperatures, agricultural drought, and decline in soil organic carbon content. Continued monitoring of the experimental sites is necessary to corroborate the findings of this investigation at longer temporal scales.

Monitoring Türkiye’s Vegetation Cover with NDVI: Terrestrial and Temporal Perspectives

This study aims to monitor and analyze the temporal and spatial dynamics of Türkiye's vegetation cover from 2000 to 2023 using MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI (Normalized Difference Vegetation Index) data. The primary objective is to assess the changes in vegetation density across various geographical regions of Türkiye and determine how these changes are influenced by environmental factors such as land use and climate variability. NDVI data from July of each year were processed using ArcGIS to classify vegetation into six categories, ranging from water bodies to dense forests. The study reveals significant fluctuations in NDVI values, indicating both vegetation growth and degradation across different regions over time. Key findings include a positive correlation between NDVI values and forested areas, and a negative correlation in regions affected by drought or land use change. These results provide valuable insights into the long-term trends of vegetation dynamics in Türkiye and can help inform future conservation and land management strategies.

Temporal dynamics of leaf area index and land surface temperature correlation using Sentinel-2 and Landsat OLI data

BackgroundUnderstanding the complex relationship between vegetation dynamics and land surface temperature (LST) is crucial for comprehending ecosystem functioning, climate change impacts, and sustainable land management. Hence, this study conducts a temporal analysis of leaf area index (LAI) and LST data derived from Sentinel-2 and Landsat Operational Land Imagery (OLI) in the Mille River Basin, a tropical region in Ethiopia. LAI data were generated using Sentinel-2 imagery processed with the Sentinel Application Platform (SNAP) toolbox, an open-access earth observation analysis tool, while Landsat OLI collection 2 level 2 data were utilized for precise LST retrieval. The Mann–Kendall test was used to detect trends in the time series data.ResultsThe trends in the mean LAI were statistically significant at P values of 0.05 and 0.10 for the annual and seasonal trends, respectively. The mean LST trends were insignificant throughout the study period except for the summer season, for which the P value was 0.07. The correlation between the LAI and LST was weak (R2 = 0.36) during the crop-growing seasons (summer and spring) but moderate in winter (R2 = 0.46) and autumn (R2 = 0.41).ConclusionThe findings of this research clarify the complex relationships between variations in surface temperature and vegetation growth patterns, providing insight into the environmental mechanisms driving the dynamics of localized ecosystems. The study underscores the implications of these findings for informed decision-making in sustainable land management, biodiversity conservation, and climate change mitigation strategies.

Assessment of soil chemical characteristics in the context of Bangladesh: A comprehensive review

This study presents a thorough examination of the chemical properties inherent to soil, with a focus on the unique context of Bangladesh. Soil functions are intricately linked to its chemical composition, which plays a vital role in determining agricultural productivity and ecological vitality. The soil within Bangladesh's geographical boundaries is characterized by its richness and fertility, contributing significantly to its agricultural output and overall ecosystem health. By delving into the chemical properties of Bangladeshi soil, this review aims to enhance our understanding of this dynamic ecosystem. Insights gained from this exploration can shed light on factors influencing soil fertility, nutrient availability, and overall ecosystem health, thereby informing strategies for sustainable land management and agricultural practices in Bangladesh and beyond.

GIS-Based Land Use and Land Cover Change Assessment Around Assosa District, Upper Blue Nile Basin, Ethiopia

Land, with its intricate blend of geological, topographical, hydrological, and ecological elements, reflects the interplay of natural processes and human activities. In Ethiopia, traditional agricultural practices often lack systematic planning based on land suitability and physical characteristics, hindering agricultural productivity and economic progress. Understanding shifts in land use and cover is crucial for comprehending broader global transformations. Early studies have unveiled significant alterations in land use and cover between 2009 and 2013. Our investigation extends from 2013 to 2023, employing Landsat 8 imagery at three-year intervals (2013, 2018, and 2023) to analyze five key land cover categories: forests, farmland, built-up areas, barren land, and water bodies. Notably, farmland and built-up areas witnessed substantial expansion over these periods, juxtaposed with a significant decline in forest cover. Forests decreased by 27% from 2013 to 2018, with an additional 7% decrease from 2018 to 2023. Conversely, farmland expanded by 19% from 2013 to 2018 and by 2% from 2018 to 2023, while built-up areas saw respective increases of 4% and 10% over the same periods. These trends underscore potential environmental challenges if unaddressed. Effective land management strategies are crucial to mitigate adverse impacts on ecosystems, agricultural productivity, and overall socio-economic stability. By integrating scientific insights with sustainable practices, we can navigate the intricate dynamics of land use, paving the way for a resilient and prosperous future.

Principle, structure and application progress of the forest landscape model FireBGCv2.

Forest landscape model can quantitatively simulate the spatiotemporal variations in forest structure and function at the landscape scale based on traditional field survey data and mathematical models, providing a reference for the formulation of scientific forest management strategies. FireBGCv2 is one of the representative models currently used in the research area of forest landscape changes. It can simulate ecological processes at various scales, including trees scale (tree growth, establishment, and mortality), stand scale (carbon and nitrogen pools, fuel treatment, decomposition), site scale (resource competition and species phenology), and landscape scale (seed dispersal and wildfire disturbances), and the effects of those processes on forest landscape structure and function. The advantage of this model lies in its ability to simulate multiple ecological processes while considering the diversity and complexity of ecosystems. However, it also has drawbacks, such as high computational demands and complexity of use. We summarized the basic principles and structure of FireBGCv2 and introduced its application progress in forest landscape research and management. Currently, the application of the FireBGCv2 model, both domestically and internationally, mainly focused on exploring the interactions between fire, climate, and vegetation, quantifying the spatial and temporal dynamics of fires, and describing potential fire dynamics under future climate scenarios and land management strategies. With the in-depth development of forest landscape model theories and applications, the future prospects of FireBGCv2 include improving and updating the model's algorithms, adding new functional modules to explore fire management issues, and meeting the needs of different users.

Spatiotemporal dynamics of land use land cover change and its drivers in the western part of Lake Abaya, Ethiopia.

Understanding the dynamics of land use/land cover (LU/LC) changes and what drives these changes is essential for creating effective strategies for sustainable land management. It also helps to monitor the impact on ecosystems and biodiversity, which is crucial for policy-making. This study focused on assessing the trends, rates, and extent of LU/LC change and its causes in the western part of Lake Abaya in Ethiopia. To achieve this, we used a supervised classification method with a maximum-likelihood algorithm to map different land use land cover types. Additionally, we gathered information through field observations, focus group discussions (FGDs), and key informant interviews (KIIs) to identify the factors driving LU/LC change and its consequences between 1990 and 2022. The study findings revealed that vegetation and wetlands significantly decreased over this period, while water bodies, agricultural land, and settlements expanded at the expense of other land uses. The average normalized difference vegetation index (NDVI) values decreased from 0.368 in 1990 to 0.135 in 2022, indicating declining vegetation health. Local communities point to several factors responsible for these changes, including the expansion of agricultural land, increased settlement, firewood collection, and charcoal production (as proximate/immediate drivers), as well as population growth, poverty, unemployment, climate change, and policy-related issues (as underlying causes). Thus, it needs the development and implementation of an integrated and sustainable land management system, and strong land use and restoration policies in order to halt or reduce the rapid expansion of agricultural land and settlement areas at the expense of vegetation and wetlands.

A picit jeu: Agent-based modelling with serious gaming for a fire-resilient landscape

Wildfire governance requires addressing driving physical, biological and socio-economic processes, by promoting the development of fire-resistant and resilient landscapes. These landscapes can best be achieved by strategies that integrate fuel management for direct prevention with allied socio-economic activities, through the collaboration of stakeholders with different and sometimes conflicting interests. This work aims to address the need for new approaches supporting the participatory process of collective decision-making, helping stakeholders explore land management strategies for landscape fire resilience. We present and discuss a methodology combining agent-based modelling with a role-playing game. It was tested in a valley of the Italian Alps, involving 23 local stakeholders in forest and pasture management in three game sessions. Evaluation was based on observation of game sessions, collection of feedback via immediate post-session debriefing and questionnaires, and long-term (multi-year) assessment carried out through semi-structured interviews. We found the methodology valuable for facilitating discussion among different stakeholders, who were able to identify context-related challenges (land fragmentation and land abandonment, stakeholders' limited collaboration, controversial drives of European funding) and possible strategies for producing a fire-resilient landscape (community management forms of pastoralists activities for maintaining land cover diversity). The approach also triggered a positive process for longer-term change. By analysing the outcomes, we are able to identify four key recommendations for future work using serious gaming for sustainable landscapes: 1) aim for an even composition of session groups, 2) consider the multiple levels of organisation in the area, 3) use the allocation of game roles to disrupt power dynamics, and 4) seek to involve the broadest stakeholder spectrum in developing the game itself.

Ideals and practicalities of policy co-design – Developing England’s post-Brexit Environmental Land Management (ELM) schemes

There are few examples of where co-design has been applied to active policy development on the scale or level of complexity of England’s post-Brexit Environmental Land Management (ELM) schemes. ELM offers a fascinating ‘laboratory’ to analyse how co-design at this scale works in practice. This paper offers the first in-depth empirical assessment of the process from the perspectives of both the policy makers and stakeholders who were involved in the initial phase of ELM co-design from 2018 to 2020. Using interview data, we provide critical insights for both academics and government on 'pragmatic' applications of co-design to active policy development and reflect on what this tells us about the wider processes of policy development that may need to change in order to accommodate this more ‘democratic’ approach. Our analysis, which identified key barriers to co-design as articulated by institutional stakeholders and civil servants, revealed a mismatch between the principles and practices of ‘co-design’ in the initial development of ELM. These early-stage challenges included: (i) a lack of shared decision-making and empowering stakeholders to contribute to problem-definitions; (ii) confidentiality requirements that introduced barriers to information-sharing; (iii) insufficient transparency and feedback on what happened to stakeholder’s contributions in terms of policy development; (iv) an absence of detail on the schemes, including proposed approaches, payment rates, advice, baseline measures, the kinds of ‘outcomes’ expected, and monitoring mechanisms; and (v) a repetition of themes that participants had already discussed. Many of these mismatches may be common to other policy arenas. We argue that improved application of policy co-design in government will rely on wider changes to political processes and the institutional culture and practices within the civil service.

Spatio-temporal dynamics of net primary productivity and the economic value of Spartina alterniflora in the coastal regions of China

This study employs an improved Carnegie–Ames–Stanford Approach (CASA) model to calculate the Net Primary Productivity (NPP) of Spartina alterniflora (SA) and various other land use/land cover types (LULC) across coastal China over multiple years. The research aims to provide significant theoretical and practical insights into carbon sink research in coastal zones, sustainable development, and resource management. Key findings include identifying the first εmax value of 2.219 g C/MJ for SA, addressing a critical data gap in CASA modeling research on invasive plants. SA's NPP exhibited higher values in Shanghai and Zhejiang due to factors such as genetic diversity, invasion duration, and tidal dynamics. In contrast, other LULC exhibited higher NPP values in southern and inland regions, characterized by greater vegetation cover and favorable growing conditions. In 2020, SA and other LULC sequestered 16.352 kt C and 0.821*106 kt C, respectively. From 2000 to 2020, the average annual NPP and total carbon storage of SA and other LULC increased significantly, primarily driven by Shanghai and deciduous needleleaf forests, respectively. Seasonal NPP trends followed summer> spring> autumn> winter, influenced by climate conditions and plant life activities. Economic assessments in 2020 estimated SA's carbon storage value at RMB0.409 billion (Market Value method) or RMB5.562 billion (Carbon Tax method), with RMB2.054 billion attributed to oxygen release values, underscoring its economic and ecological potential. Among other LULC, evergreen broadleaf forests showed the highest carbon storage value (RMB183.463 billion). The study emphasizes the critical role of all LULC in carbon storage and oxygen release, advocating for targeted conservation and land management strategies. It suggests that managing SA should balance stringent control in high-risk areas, lenient measures in low-risk areas, eradication of scattered populations, and maximizing ecological benefits in retention areas, with continuous monitoring and adaptive management strategies to balance conservation and development efforts.

An ensemble estimate of Australian soil organic carbon using machine learning and process-based modelling

Abstract. Spatially explicit prediction of soil organic carbon (SOC) serves as a crucial foundation for effective land management strategies aimed at mitigating soil degradation and assessing carbon sequestration potential. Here, using more than 1000 in situ observations, we trained two machine learning models (a random forest model and a k-means coupled with multiple linear regression model) and one process-based model (the vertically resolved MIcrobial-MIneral Carbon Stabilization, MIMICS, model) to predict the SOC stocks of the top 30 cm of soil in Australia. Parameters of MIMICS were optimised for different site groupings using two distinct approaches: plant functional types (MIMICS-PFT) and the most influential environmental factors (MIMICS-ENV). All models showed good performance with respect to SOC predictions, with an R2 value greater than 0.8 during out-of-sample validation, with random forest being the most accurate; moreover, it was found that SOC in forests is more predictable than that in non-forest soils excluding croplands. The performance of continental-scale SOC predictions by MIMICS-ENV is better than that by MIMICS-PFT especially in non-forest soils. Digital maps of terrestrial SOC stocks generated using all of the models showed a similar spatial distribution, with higher values in south-eastern and south-western Australia, but the magnitude of the estimated SOC stocks varied. The mean ensemble estimate of SOC stocks was 30.3 t ha−1, with k-means coupled with multiple linear regression generating the highest estimate (mean SOC stocks of 38.15 t ha−1) and MIMICS-PFT generating the lowest estimate (mean SOC stocks of 24.29 t ha−1). We suggest that enhancing process-based models to incorporate newly identified drivers that significantly influence SOC variation in different environments could be the key to reducing the discrepancies in these estimates. Our findings underscore the considerable uncertainty in SOC estimates derived from different modelling approaches and emphasise the importance of rigorous out-of-sample validation before applying any one approach in Australia.

The Environmental Land Management Scheme: Public goods and levels of ambition

The Environmental Land Management Scheme is now established as the central plank of financial assistance for farmers in England post-Brexit. Early articulations of policy directed the focus of the Scheme to the delivery of public goods, with a high level of ambition. More recently, however, greater weight is being accorded to food production and food security, with particular reference to the Sustainable Farming Incentive component, which is achieving broad coverage and accounting for the majority of the Scheme budget, but the environmental actions which it requires to unlock payment would not seem materially to be raising the bar. By contrast, the Landscape Recovery component remains ambitious in terms of scheme design, collaborative approach, emphasis on outcomes, duration and implementation at landscape scale, with the consequence that good reasons may be presented for its expansion within the policy mix.

Spatio-temporal Dynamics of Land Use/Cover Change and Associated Carbon Stocks in Kanyabaha Wetland in Rukiga District, Uganda

Wetlands play an important ecological function of sequestering atmospheric carbon dioxide and thereby moderating adverse impacts of climate change. It is therefore important to understand the dynamics of carbon stocks in wetland vegetation and soils. This study investigated the spatio-temporal dynamics of aboveground, belowground, and total carbon stocks in Kanyabaha Wetland, located in Rukiga District, Uganda, spanning from 1990 to 2021. Through field sampling and laboratory analysis, aboveground carbon stocks were assessed by harvesting vegetation biomass and converting it to carbon stock using established conversion factors. Soil samples collected at different depths (0-20cm, 20-50cm, 50-100cm) were analyzed for soil organic carbon content to determine belowground carbon stocks. The study reveals variable spatio-temporal patterns of carbon stocks across land use types, with papyrus-dominated areas exhibiting the highest aboveground carbon stocks (49.66 tC/ha), followed by small-scale farmlands (33.73 tC/ha) and tree plantations (23.01 tC/ha). Conversely, built-up areas exhibit the lowest carbon stocks (1.29 tC/ha). Temporal analysis reveals fluctuating patterns in carbon stocks, with increases observed in built-up areas and small-scale farmlands, and decreases in grasslands and tree plantations that could be due to changes in hydrological cycle. Belowground carbon stocks follow similar trends, with papyrus areas maintaining the highest stocks (39.96 tC/ha), particularly at deeper soil depths that exhibit the highest carbon accumulation due to its extensive network of papyrus rhizome. Changes in land use, especially reclamation of the wetlands for farming and settlements affected carbon capture and storage in the wetland ecosystem. These findings highlight the importance of targeted conservation of natural wetlands and sustainable land management strategies in the Kanyabaha Wetland catchment for enhanced carbon sequestration. Further, in depth studies in the variability of carbon stocks due to various eco-climatic factors and anthropogenic activities are necessary to support sustainable wetland land management practices in Uganda.