Land Management Scenarios Research Articles

Modeling carbon dynamics from a heterogeneous watershed in the mid-Atlantic USA: A distributed-calibration and independent verification (DCIV) approach

The terrestrial ecosystem plays a vital role in regulating regional and global carbon budgets. Ecosystem models are extensively employed to estimate carbon fluxes across different spatial scales. However, there remains a need to reduce the uncertainties associated with model parameterization and input data. To address these limitations, we assessed a distributed-calibration and independent-verification (DCIV) approach that uses (1) remotely sensed net primary production (NPP) and evapotranspiration (ET) data from the Moderate Resolution Imaging Spectroradiometer (MODIS), (2) multi-site eddy covariance net ecosystem exchange (NEE) data; and (3) field sampling of soil organic carbon (SOC) and aboveground biomass (ABG) data to improve the overall predictability of carbon fluxes for the different land use and land cover (LULC) types at a watershed scale. The DCIV approach was applied to an advanced version of the Soil and Water Assessment Tool (SWAT)-Carbon (or SWAT-C), equipped with Century-based SOC algorithms to simulate carbon dynamics for watersheds with heterogeneous vegetation. The objective of the modeling effort was to assess carbon stocks and fluxes under different land management scenarios for a 3000-acre experimental farm and forest preserve in the northeastern United States. Our study showed that a large SOC stock of at least 100 tons ha−1 is stored under mixed forest, deciduous, shrubland, and floodplain (grass). Our study also showed that converting floodplain (grass) to deciduous forest has the potential to increase CO2 uptake (-NEE) by an order of three magnitude and ABG by 77 %, leading to an increased SOC stock of 23 % after twenty years. Similarly, we found that converting ungrazed grassland to grazed pasture leads to a non-statistically decreasing trend of SOC, especially in the 0–30 cm soil layer. Thus, the methodology used in this study can be applied to improve carbon dynamic prediction from a heterogeneous watershed at a regional scale.

Biomass inputs drive agronomic management impacts on soil health

Numerous conservation and regeneration practices are recognized as effective strategies in the management of soil health (SH), a critical factor for ensuring the sustainability of food production systems. Despite their acknowledged importance, the multifaceted impacts of these practices often lead to confounding effects, and reliance on generic categorization of agronomic practices often falls short in portraying the drivers of SH. We advocate for a paradigm shift from a label-centric approach to one rooted in processes. Our study underscores the pivotal role of aboveground biomass cycling as an indicator for assessing the potential of agronomic management practices to instigate shifts in carbon balances, and, consequently SH. Drawing on soil physical, biological, and chemical SH data from three Uruguayan long-term experiments on Pampas region Mollisols we (i) present quantitative evidence of the importance of evaluating SH through biomass inputs, and (ii) illustrate the applicability of the proposed framework for evaluating different scenarios of land management for the region. Management-induced variations in aboveground biomass inputs accounted for 50 % of the observed changes in a composite soil's physical and biological SH index and helped explain the inconsistent effect of management practices. Raising the SH Index by ten points required an increase in biomass inputs of over 50 Mg ha⁻¹. Based on this concept, substantial enhancements in SH can be made by narrowing yield gaps and intensifying cropping sequences over many years. The benefits of practices such as increased crop diversification, integration of perennial and cover crops, or reduced tillage in promoting SH depend in part on their ability to augment biomass production. This nuanced understanding underscores the importance of aligning agronomic strategies with the fundamental processes driving SH dynamics.

Deforestation and water availability as main drivers of human-elephant conflict

Climate change, land use conversion and human population growth are reducing and fragmenting historical ranges of large animals, especially in Africa. Particularly, land conversion to agriculture is leading to coexistence challenges between humans and elephants. In this study we investigated the factors affecting the intensity of elephant crop damage in the Selous-Niassa Wildlife Corridor (Tanzania). We also predicted future conflicts (crop damage intensity) for different land management (crop types) and water scarcity (drought) scenarios using model averaging. Our results show that intensity of elephant damage (proportion of area damaged in an individual farm as a percentage) increased with crop palatability and land use conversion in the last ∼30 years, particularly deforestation. Conversely, the intensity of elephant damage decreased with increasing human activity (higher proportion of settlements and farmland), and distance to waterbodies. Most farms affected by elephants (65 %) were at short distances (< 250 m) from waterbodies. We also predicted a significant increase of elephant crop damage intensity from 17 % when the farm is covered with no palatable crops, to 54 % and 63 % when palatable crops covered 50 % and 100 % of the farmland, respectively. For the predicted water stress scenario in which all small seasonal waterbodies would dry off, we predicted a 46 % reduction in the total area of farmland susceptible to damage although we expect an increase in human-wildlife competition for water. We conclude that land use changes and water availability strongly affect elephant crop damage. We hope these results contribute to the development and better implementation of management strategies that enhance long-term peaceful coexistence between humans and elephants.

Integrating water quantity- and quality-related ecosystem services into water scarcity assessment: A multi-scenario analysis in the Taihu Basin of China

Water scarcity is a growing global concern, resulting from drastic climate and societal changes witnessed over the past few decades. Previous attention has predominantly focused on inadequate water quantity as the main cause of water scarcity, but pollution-induced water scarcity has been largely overlooked. Furthermore, there is a lack of understanding about the effectiveness of policy interventions in mitigating water scarcity and its social impact. To address these knowledge gaps, we developed an ecosystem service-based approach to measure quantity- and quality-related water scarcity by comparing supply of and demand for water provision and water purification services. We also developed several water and land management scenarios to examine their potential in alleviating water scarcity under different climate conditions and water quality requirements. Our case study in the Taihu Basin of southeastern China identified four types of water scarcity status across different sub-basins, including quantity-based, quality-based, quantity- and quality-based, and no water scarcity. The degradation of water quality in the Taihu Basin has exacerbated the scarcity of clean water supply. Water conservation measures effectively alleviated quantity-based water scarcity, while nitrogen reduction and grain for green (i.e., conversion of cropland into forest land) exhibited similar efficacy in alleviating quality-based water scarcity. Integrating these measures contributed to alleviating both quantity- and quality-based water scarcity. However, the effectiveness of these measures decreased under drier climate conditions and higher water quality requirements, highlighting the importance of climate and water quality in determining the magnitude, extent, and severity of water scarcity. The approaches and findings presented here provide new insights into the sustainable management of water resources in the Taihu Basin and other similar basins worldwide.

Using modern portfolio theory to enhance ecosystem service delivery: A case study from China

：Land management strategies often prioritize agricultural supply services at the expense of other ecosystem services. To achieve a high and steady supply of multiple ecosystem services, it is essential to optimize land management practices in areas suitable for agriculture. However, many studies on land management tend to focus on their benefits to ecosystem service delivery without adequately considering the potential risks to other services that might be involved. Here we use modern portfolio theory to quantitatively measure benefits and risks from land management strategies to enhance ecosystem services. We create seven land management scenarios that balance different kinds of ecosystem services in different ways in the agricultural production area of Maoming, Guangdong Province, China. The method yielded optimal portfolios of land management patterns that enhanced ecosystem services while reducing risk as much as possible. This includes a scenario delivering a 22% increase in agricultural production service, while simultaneously increasing the provision of nature-related ecosystem services by 2%. However, no optimization scenario was perfect, and there was always a trade-off between gaining certain ecosystem service benefits and creating a risk of losing others. Our portfolio theory approach reveals that it is essential to consider both the benefits and risks of land management strategies.

Ecosystem carbon storage considering combined environmental and land-use changes in the future and pathways to carbon neutrality in developed regions

Assessing the carbon storage capacity of terrestrial ecosystems is crucial for land management and carbon reduction policymaking. There is still a knowledge gap regarding how ecosystem carbon storage will be impacted by combined environmental and land-use factors and their spatial-temporal changes, especially in developed regions where urbanization has slowed down. This study investigated how developed regions in subtropical and tropical areas might increase carbon storage and achieve carbon neutrality, using Guangdong Province in South China as an example. Based on the sustainable development assumption, three land-management scenarios were developed and simulated for 2020–2060 using the Patch-generating Land Use Simulation model. Without considering disturbance and natural losses, carbon storage was estimated by net ecosystem productivity (NEP)—the difference between net primary productivity (NPP) and heterotrophic respiration (HR). NPP was predicted using an artificial neural network model trained by historical NPP data and 16 environmental and land-use variables. HR was predicted using soil respiration models from previous research. Based on the balance between carbon storage and emissions, we predicted the allowable fossil fuel consumption to achieve net-zero CO2 emissions in 2060. The results show that Guangdong's total carbon storage changes from 73.7 MtC in 2020 to 70.6–74.8 MtC in 2060 under different scenarios. Nonlinear relationships exist between the carbon stored and the areas of different land-use types. Topography, temperatures, and land-use configurations jointly lead to significantly varied carbon storage between croplands and between forests in space and time. Protecting and regenerating forests in subtropical areas and forest edges is more effective than afforestation in lowland tropical areas for storing carbon. Net-zero CO2 emissions rely more on reducing emissions than land management. To achieve this, the proportion of fossil energy in total energy consumption should be lowered from 75.5 % in 2020 to ~25 % in 2060.

Predicting runoff and sediment responses to climate-resilient land use and management scenarios.

Soil erosion is the predominant agent affecting ecosystem services in the Ethiopian highlands. However, land management interventions aimed at controlling erosion in the region are hampered, mainly by a lack of watershed-based appropriate management practices and anticipated climate changes. This study examined the effectiveness of different land use changes and management scenarios in decreasing runoff and sediment loss under current and future climates in the drought-prone humid watershed of the Ethiopian highlands. We employed a modeling approach integrating observed data at watershed and plot scales with Soil and Water Assessment Tool. In the first step, we evaluated the impact of land use changes between 2006 and 2017 on runoff and sediment loss. Then, we developed five land use and management scenarios based on watershed land capabilities and selected land management practices. Model parameters were modified based on runoff and sediment loss results obtained from experimental plots of biophysical and agronomical land management practices in the watershed. The runoff and sediment loss were simulated under current (2014-2019) and future climates (the 2050s) for each land use and management scenario. Results revealed that land use changes (mainly an increase in Acacia decurrens plantations by 206%) alone between 2006 and 2017 reduced runoff by 31% and sediment loss by 45%. Under the current climate, the five land use and management scenarios reduced runoff by 71-95% and sediment loss by 75-96% compared to the baseline scenario. Under the future climate (2050s), these scenarios decreased runoff by 48-90% and sediment loss by 54-91%. However, their effectiveness was slightly decreased (5-23%) as a result of increases in rainfall (10-46%) and mean temperature (1.7-1.9 °C) in the 2050s. The scenario of improving vegetation cover through forage production and plantations in appropriate areas plus best land management practices was the most effective and climate-resilient of the five scenarios. This study suggests that evaluating the impact of land use and management practices under future climate change shows promise for guiding effective and sustainable interventions to adapt to climate change.

Evaluating the effectiveness of land use management as a natural flood management intervention in reducing the impact of flooding for an upland catchment

AbstractNatural flood management (NFM) is a method for reducing flooding by using a catchment‐based approach to managing flood risk. Understanding and quantifying the impact of implementing NFM at the catchment scale remains ambiguous with a clear need for robust empirical evidence. A combination of fieldwork, laboratory analysis and modelling was applied to quantify the impacts of land use management changes on catchment flood hazard. Soil hydraulic conductivity was measured under varying land management regimes and used to parameterize a physically based spatially distributed hydrological model (SD‐TOPMODEL). A suite of stakeholder informed land management scenarios was modelled, permitting the quantification of the impact of NFM interventions on the timing and the intensity of the peak discharge at the catchment outlet. The findings support the implementation of NFM interventions as a means of reducing flood hazard within a rural upland catchment. Improved soil infiltration provided the greatest reduction in the intensity and delayed timing of the flood peak for a 10‐year occurrence storm event (7% reduction in peak runoff and 8% increase in lag time) with similar reductions observed for a 100‐year storm event. Catchment wide woodland planting reduced peak flow by 11% during the 100‐year event but was not effective during the 10‐year event. Riparian buffer strips provided consistent reductions in peak flow and in the timing of the peak across both storm events with no significant differences relating to vegetation age. Critically, we observed that the effect of implementing multiple NFM interventions was not additive and that efficiencies can be made in using this modelling approach to prioritize the most effective outcomes.

Integrating climate change into projections of soil carbon sequestration from regenerative agriculture

Computational models can project how changes in land use and management will affect soil organic carbon (SOC) stocks over time, but these models usually assume an unchanging climate. We investigate how incorporating climate change projections affects carbon sequestration and SOC stocks. We apply the Rothamsted Carbon model (RothC) to study agricultural land use and management transitions in the U.S. state of Vermont, comparing several regenerative farming strategies, as well as afforestation, against business-as-usual. In 11 relatively-homogeneous Ecoregions within the study area, we run simulations for each land management scenario from 2022–2099, under both projected climate change and the static climate normal from 1991–2021. We use downscaled climate projections from four Global Climate Models, forced by RCP 4.5, that bracket the range of likely climate change. We find that rising temperatures decrease SOC stocks compared to static climate runs by 9.1% to 19.9% across management scenarios, leading to net SOC loss even under many regenerative farming scenarios. Other regenerative practices, notably rotational grazing, could maintain or slightly increase SOC through 2099, and old-growth afforestation could increase statewide stocks by up to 4.5 Mt. Although the potential for farmland management to increase SOC over current levels is diminished when accounting for climate change, it remains important to incentivize regenerative agriculture and afforestation, because this may be the only way to avoid SOC losses by end-of-century.

New land governance models and management scenarios: Fitting Forest Management Units (FMUs) for forested landscapes outside forest zones in Indonesia

Many parts of non-forest zones (Areal untuk Penggunaaan Lain/APL) in Indonesia are forested but are however under intense pressure from unsustainable practices and conversion. To help preserve forested APL zones, the Ministry of Environment of Forestry is envisioning the integration of forested APL areas into the operational activities of the Forest Management Units/ FMUs (Kesatuan Pengelolaan Hutan/KPH), a management arm of the forest administration. Under the current governance arrangements, FMUs are not tasked to manage the areas. In this paper, we developed new governance arrangements and management scenarios that permit management of forested APL by FMUs based on iterative processes and intensive consultation with related stakeholders. We developed three plausible broad scenarios: 1) the handing over forested APLs to FMUs, 2) co-management, and 3) FMUs to provide technical assistance for preserving forested APLs. We further detailed the three scenarios into five different models. Our scenarios of institutional arrangements and management models are by no means prescriptive and readily operationalized on the ground. Instead, the processes by which the scenarios and models were developed can be adopted when the FMUs intend to develop more detailed scenarios that reflect specific situations and conditions.

Integrating ecosystem services with geodesign to create multifunctional agricultural landscapes: A case study of a New Zealand hill country farm

An ecosystem-based management approach (EBM) is suggested as one solution to help to tackle environmental challenges facing worldwide farming systems whilst ensuring socio-economic demands are met. Despite its usefulness, the application of this approach at the farm-scale presents several implementation problems, including the difficulty of (a) incorporating the concept of ecosystem services (ES) into agricultural land use decision-making and (b) involving the farmer in the planning process. This study aims to propose a solution to overcome these challenges by utilising a geodesign framework and EBM approach to plan and design a sustainable multifunctional agricultural landscape at the farm scale. We demonstrate how the proposed approach can be applied to plan and design multifunctional agricultural landscapes that offer improved sustainability, using a New Zealand hill country farm as a case study. A geodesign framework is employed to generate future land use and management scenarios for the study area, visualize changes, and assess the impacts of future land use on landscape multifunctionality and the provision of associated ES and economic outcomes. In this framework, collaboration with the farmer was carried out to obtain farm information and co-design the farmed landscapes. The results from our study demonstrate that farmed landscapes where multiple land use/ land cover types co-exist can provide a wide range of ES and therefore, meet both economic and environmental demands. The assessment of impacts for different land use change scenarios demonstrates that land use change towards increasing landscape diversity and complexity is a key to achieving more sustainable multifunctional farmed landscapes. The integration of EBM and geodesign, is a transdisciplinary approach that can help farmers target land use and management decisions by considering the major ES that are, and could be, provided by the landscapes in which these farm systems are situated, therefore maximising the potential for beneficial outcomes.

Evaluating the effects of vegetation and land management on runoff control using field plots and machine learning models.

Excess surface water after heavy rainfalls leads to soil erosion and flash floods, resulting in human and financial losses. Reducing runoff is an essential management tool to protect water and soil resources. This study aimed to evaluate the effects of vegetation and land management methods on runoff control and to provide a model to predict runoff values. Filed plot data and three machine learning (ML) methods, including artificial neural network (ANN), coactive neuro-fuzzy inference system (CANFIS), and extreme gradient boosting (EGB), were used in a test site in the north of Iran. In this regard, plots with various vegetation and land management treatments including bare soil treatment, rangeland cover treatment, forest litter treatment, rangeland litter treatment, tillage treatment in the direction of slope, tillage treatment perpendicular to the slope, and repetition of treatments under forest canopy were constructed on a hillslope. After each rainfall event, the amount of rainfall and corresponding runoff generated in each plot was recorded. Three ML models (ANN, CANFIS, and EGB) were used to establish relationships between amounts of recorded runoff and its controlling factors (rainfall, antecedent soil moisture (A.M.C), shrub canopy percentage and height, tree canopy percentage and height, soil texture (clay, silt, and sand percent), slope degree, leaf litter percentage of soil, and tillage interval). These data were normalized, randomized, and divided into training and testing subsets. Results showed that the ANN performed better than the other two models in predicting runoff in training (R2 = 0.98; MSE = 0.004) and the test stages (R2 = 0.90; MSE = 0.95). Statistical analysis and sensitivity analysis of inputs factors showed that rainfall, rangeland cover, and A.M.C are the three most important factors controlling runoff generation. The adopted method can be used to predict the effect of different vegetation and land management scenarios on runoff generation in the study area and the areas with similar settings elsewhere.

Terrestrial carbon sequestration under future climate, nutrient and land use change and management scenarios: a national-scale UK case study

Carbon sequestration (Cseq) in soils and plant biomass is viewed as an important means of mitigating climate change. Recent global assessments have estimated considerable potential for terrestrial Cseq, but generally lack sensitivity to climate warming, nutrient limitations and perspective on local land use. These are important factors since higher temperatures can accelerate the decomposition of soil organic matter, nutrient availability affects plant productivity, while land use pressures put broader constraints on terrestrial organic matter inputs and storage. Here, we explore the potential for Cseq under changing land use, climate and nutrient conditions in a UK-based national scale case study. We apply an integrated terrestrial C–N–P cycle model with representative ranges of high-resolution climate and land use scenarios to estimate Cseq potential across the UK. If realistic UK targets for grassland restoration and afforestation over the next 30 years are met, we estimate that an additional 120 TgC could be sequestered by 2100 (similar to current annual UK greenhouse gas emissions or roughly 7% of net emission cuts needed in meeting net zero), conditional on climate change of <2 °C. Conversely, we estimate that UK arable expansion would reduce terrestrial carbon storage by a similar magnitude. The most pessimistic climate trajectories are predicted to cause net losses in UK soil carbon storage under all land use scenarios. Warmer climates substantially reduce the potential total terrestrial carbon storage gains offered by afforestation and grassland restoration. We conclude that although concerted land use change could make an important moderate contribution to national level Cseq for countries like the UK, soil Cseq only provides a contribution if we are on a low emission pathway, and is therefore conditional on deep global cuts to emissions from fossil fuels, deforestation and soil degradation.

Risk assessment of harmful algal blooms (HAB) occurrence in the agroecosystem: A hydro-ecologic modeling framework and environmental risk matrix

This paper was aimed at assessing the risk of HAB occurrence in a highly cultivated watershed and evaluating the effectiveness of N and P fertilizer reduction practices in mitigating this risk under future climate projections. To achieve this objective, a modelling framework was developed for HAB risk assessment under different environmental stressors including climate changes and different land management practices. The modelling framework used a fully distributed physical-based hydrologic model, MIKE SHE, and a hydrodynamic river model, MIKE 11, coupled with ECO-Lab to simulate the fate and transport of different forms of N and P in the Upper Sangamon River Basin (USRB), a highly cultivated watershed in central Illinois. Three different land management scenarios based on the N and P reduction target in “The Gulf Hypoxia Action Plan” were simulated to assess the P nonpoint source behavior and HAB risk level in the USRB from 2020 to 2050 under extreme climate projections. Our results predicted that the HAB risk in USRB is relatively low even with increased bioavailable P (BAP) concentration and longer duration with high BAP concentration due to low water temperature. Reducing N or P application rates by 50% was able to offset the negative effects on HAB occurrence from extreme climate projections apart from spring. Within P and N, regulating P was found to be more effective in reducing HAB risks in the USRB while regulating N was more effective in controlling HAB downstream. Understanding the dynamics of N and P in causing the occurrence of HAB was expected to improve the mitigation measures that we implement at the field level.

ScenaLand: a simple methodology for developing land use and management scenarios

Scenarios serve science by testing the sensitivity of a system and/or society to adapt to the future. In this study, we present a new land use scenario methodology called ScenaLand. This methodology aims to develop plausible and contrasting land use and management (LUM) scenarios, useful to explore how LUM (e.g. soil and water conservation techniques) may affect ecosystem services under global change in a wide range of environments. ScenaLand is a method for constructing narrative and spatially explicit land use scenarios that are useful for end-users and impact modellers. This method is innovative because it merges literature and expert knowledge, and its low data requirement makes it easy to be implemented in the context of inter-site comparison, including global change projections. ScenaLand was developed and tested on six different Mediterranean agroecological and socioeconomic contexts during the MASCC research project (Mediterranean agricultural soil conservation under global change). The method first highlights the socioeconomic trends of each study site including emerging trends such as new government laws, LUM techniques through a qualitative survey addressed to local experts. Then, the method includes a ranking of driving factors, a matrix about land use evolution, and soil and water conservation techniques. ScenaLand also includes a framework to develop narratives along with two priority axes (contextualized to environmental protection vs. land productivity in this study). In the context of this research project, four contrasting scenarios are proposed: S1 (business-as-usual), S2 (market-oriented), S3 (environmental protection), and S4 (sustainable). Land use maps are then built with the creation of LUM allocation rules based on agroecological zoning. ScenaLand resulted in a robust and easy method to apply with the creation of 24 contrasted scenarios. These scenarios come not only with narratives but also with spatially explicit maps that are potentially used by impact modellers and other end-users. The last part of our study discusses the way the method can be implemented including a comparison between sites and the possibilities to implement ScenaLand in other contexts.

Targeted land management strategies could halve peatland fire occurrences in Central Kalimantan, Indonesia

Indonesian peatlands and their large carbon stores are under threat from recurrent large-scale fires driven by anthropogenic ecosystem degradation. Although the key drivers of peatland fires are known, a holistic methodology for assessing the potential of fire mitigation strategies is lacking. Here, we use machine learning (convolutional neural network) to develop a model capable of recreating historic fire observations based on pre-fire season parameters. Using this model, we test multiple land management and peatland restoration scenarios and quantify the associated potential for fire reduction. We estimate that converting heavily degraded swamp shrubland areas to swamp forest or plantations can reduce fires occurrence by approximately 40% or 55%, respectively. Blocking all but major canals to restore these degraded areas to swamp forest may reduce fire occurrence by 70%. Our findings suggest that effective land management strategies can influence fire regimes and substantially reduce carbon emissions associated with peatland fires, in addition to enabling sustainable management of these important ecosystems.

Predicting the impacts of land management for sustainable development on depression risk in a Ugandan case study

Agricultural intensification and expanding protected areas are proposed sustainable development approaches. But, their consequences for mental health are poorly understood. This study aims to predict how forest conservation and contract farming may alter resource access and depression risk in rural Uganda. Residents (N = 695) in 11 communities in Masindi District were asked about their expectations under land management scenarios using scenario-based interviews, household characteristics and depression symptoms. Over 80% of respondents presented with a ‘business-as-usual forest access’ scenario expected reduced access to forest income and food over the next decade; this number climbed above 90% among ‘restricted forest access’ scenario respondents. Over 99% of those presented with two land access scenarios (‘business-as-usual land access’ and ‘sugarcane expansion land access’) expected wealthy households to gain land but poorer families to lose it, threatening to increase poverty and food insecurity among small-scale farmers. Bayesian structural equation modelling suggested that depression severity was positively associated with food insecurity (0.20, 95% CI = 0.12–0.28) and economic poverty (0.11, 95% CI 0.02–0.19). Decision-makers should evaluate the mental health impacts of conservation and agricultural approaches that restrict access to livelihood resources. Future research could explore opportunities to support mental health through sustainable use of nature.

Impact Of Agroforestry On Hydrological Functions In The Batang Merao Hulu (Micro Watershed) Bremas District, Jambi Province

Land as a limited natural resource can suffer damage and decrease productivity if it is not managed wisely. Land use of anarea affects the hydrology of the area, changing land use means changing the type and proportion of land cover which in turn affects its hydrological response. Incompatibility of land use can have an impact on decreasing land quality, so that it often resultsin floods, droughts, erosion which will reduce land productivity and community welfare. The equipment used in this researchare: (1) Computer with ArcGIS¬ 10.4 software, ArcSWAT version 2012.1_8 Microsoft Office 2013, SWAT Plot for calculating R2and NS values; (2) Global Positioning System (GPS); (3) Digital camera, stationery and external hard disk to store data.Planting with agroforestry patterns and the application of conservation techniques in the Batang Merao Hulu sub-watershedhave an effect on hydrological characteristics, this is indicated by the reduced runoff coefficient value before plantingagrofrestry with the application of conservation techniques from 0.4 to 0.09 and the flow regime coefficient from 48.49 m3/s to 17.18 m3/s. The best land management scenario is to carry out planting with agroforestry patterns and the application of conservation techniques in the form of mound terraces. This agroforestry pattern not only emphasizes the types of woodyplants and MPTs but also prioritizes local local plants which are the prima donna of the people of Kerinci Regency, namelycoffee and cinnamon, so that ecologically, the hydrological function of the watershed is maintained.

A multi-product landscape life-cycle assessment approach for evaluating local climate mitigation potential

Increasing demand for land-based climate mitigation requires more efficient management of agricultural landscapes for competing objectives. Here we develop methods for assessing trade-offs and synergies between intensification and carbon-sequestering conservation measures in annual crop production landscapes using the DayCent ecosystem model and the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) life-cycle assessment (LCA) model. We compiled county-scaled crop yields, fertilizer application rates, and tillage intensity for a corn–soybean farming case study landscape in the US state of Iowa. Using DayCent, we estimated a baseline soil organic carbon (SOC) accrual rate of 0.29 Mg C ha−1 y−1 driven by historical increases in crop productivity and reductions in tillage intensity. We then simulated the effects of management interventions targeted toward intensification (stover removal) and SOC sequestration (tillage intensity reduction and winter cover crop addition) individually and in combination. We propose a new multi-product landscape–LCA approach that analyzes marginal changes in corn grain, corn stover, and soybean production from the landscape in terms of their value for biofuel production (corn ethanol, soy biodiesel, and cellulosic ethanol from stover) and associated net displacement of conventional fossil-derived fuel use. This enables us to evaluate both intensification and sequestration effects in common CO2-equivalent mitigation units. We also used DayCent-simulated yields under the different land management scenarios to estimate farm-level costs and revenues. Our results show that intensification via collecting 30% of corn stover for biofuel production would increase the total greenhouse gas (GHG) mitigation potential of this landscape by 0.93 Mg CO2e ha−1 y−1 and provide $49 ha−1 y−1 of additional net revenue from biomass sales, but would reduce the baseline SOC accumulation rate by approximately 40%. In contrast, integrated approaches that include co-adoption of winter cover cropping and/or tillage intensity reduction would result in increased rates of SOC accumulation above the baseline, achieving simultaneous improvements in both farm profits and the overall GHG mitigation potential of the landscape.

Do Ecological Restoration Projects Improve Water-Related Ecosystem Services? Evidence from a Study in the Hengduan Mountain Region.

Land use/land cover (LULC) and climate change are major driving forces that impact ecosystem services and affect human well-being directly and indirectly. Under the future interaction between LULC and climate change, the impact of different land management and climate change scenarios on water-related services is uncertain. Based on this, the CLUMondo model, which focuses on land use intensity, was used to simulate the land system under different land management scenarios in the future. By coupling the downscaled climate scenario data, this study used the InVEST and RUSLE models to estimate the annual water yield and soil erosion in 2050 in the Hengduan Mountain region and analyzed the variation differences in different sub-watersheds. The results indicated that, under the influence of LULC and climate change, when compared with the amount for 2020, the soil erosion in the Hengduan Mountain region in 2050 was reduced by 1.83, 3.40, and 2.91% under the TREND scenario, FOREST scenario, and CONSERVATION scenario, respectively, while the water yield decreased by 5.05, 5.37, and 5.21%, respectively. Moreover, the change in soil erosion in the study area was affected by precipitation and closely related to the precipitation intensity, and the impact of climate change on the water yield was significantly greater than that of LULC change. The spatial heterogeneity of soil erosion and water yield was obvious at the sub-watershed scale. In the future, soil erosion control should be strengthened in the northern regions, while water resource monitoring and early warning should be emphasized in the central-eastern regions. Our results provide scientific guidance for policy makers to formulate better LULC policies to achieve regional water and soil balance and sustainable management.