Land Management Decisions Research Articles

Irrigation area, efficiency and water storage mediate the drought resilience of irrigated agriculture in a semi-arid catchment

We examined the effects of hydrological variables such as irrigation area, irrigation efficiency and water storage on the resilience of (mostly commercial) irrigated agriculture to drought in a semi-arid catchment in South Africa. We formulated a conceptual framework termed ‘Water, Efficiency, Resilience, Drought’ (WERD) and an accompanying spreadsheet model. These allow the resilience of irrigated agriculture to drought to be analysed via water accounts and a key resilience indicator termed Days to Day Zero (DDZ). This represents the number of days that a pre- and within-drought supply of catchment water available to irrigation is withdrawn down to zero in the face of a prolonged drought. A higher DDZ (e.g. >300 days) indicates greater resilience whilst a lower DDZ (e.g. <150 days) signals lower resilience. Drought resilience arises through land and water management decisions underpinned by four types of resilience capacities; absorptive, adaptive, anticipative and transformative. For the case study, analyses showed that irrigators, with currently approximately 23,000 ha under irrigation, have historically absorbed and adapted to drought events through construction of water storage and adoption of more efficient irrigation practices resulting in a DDZ of 260 days. However, by not fully anticipating future climate and water-related risks, irrigators are arguably on a maladaptive pathway resulting in water supply gains, efficiency and other practices being used to increase irrigation command areas to 28,000 ha or more, decreasing their capacity to absorb future droughts. This areal growth increases water withdrawals and depletion, further stresses the catchment, and reduces future DDZs to approximately 130 days indicating much lower drought resilience. Our approach, supported by supplementary material, allows stakeholders to understand the resilience consequences of future drought in order to; reconcile competition between rising water demands, consider new water storage; improve agricultural and irrigation planning; and enhance catchment governance.

A case study of the RothC soil carbon model with potential evapotranspiration and remote sensing model inputs

Soil carbon modeling is an important tool to inform scientists, land managers, and policy makers about the impacts of land management decisions on soil health and climate change mitigation. Models can require a wide range of data inputs to make predictions, not all of which are readily available but can often be substituted with estimates. Understanding the impact that inputs have on the model output is critical to understand the uncertainties of their predictions. This study evaluated the output of the RothC soil carbon model using three potential evapotranspiration (PET) models (Tegos et al., 2017; Droogers and Allan, 2002; and Thornthwaite and Mather, 1955; Te, DA, and TM, respectively) to estimate open pan evaporation, and three vegetation indices (NDVI, SAVI, and MSAVI) from satellite imagery to estimate corn (Zea mays L.), soybean (Glycine max (L.) Merr.), and wheat (Triticum aestivum L.) yield to convert to C input for the RothC model to predict soil organic carbon over 11 years at a research farm in Michigan. The objectives of this study were to evaluate the correlation with observed data for each estimated input as well as the variability in RothC output they produced. The TM, Te, and DA PET models resulted in 13%, 38%, and 40% wet bias, respectively, resulting in increases of 1.6, 5.5 and 7.4 Mg C ha−1, respectively, over the baseline model output. All three vegetation indices estimated corn yields poorly (R2 = 0.25, 0.26, and 0.26 for NDVI, SAVI, and MSAVI, respectively), but soybean yields exceptionally well (all R2 = 0.91). However, despite NDVI producing significantly higher values (p < 0.001), there were no significant differences between each index's estimated yield used to calculate C input for RothC, and the resulting model runs are almost indistinguishable.

Soil microbial diversity in conventional and organic agricultural farming systems

Microbes are the most varied category of soil creatures, although little is recognized about them. Until recently, research focused on culturable organisms; however, a lot of information is now being acquired from both culturable and, as of yet, unculturable organisms. The functions of the soil microbial community have an impact on various soil processes and, as a result, productivity. There would be no other life forms without microorganisms and their roles. A better understanding of soil microbial ecology can only improve land management decisions. Low-input agriculture systems seek to reduce the usage of synthetic fertilizers and pesticides in order to promote long-term productivity and ecosystem health. Despite the soil microbiome's critical role in agricultural output, we still have a limited grasp of microbial diversity's complex response to organic and conventional farming. The application of high input conventional farming practices, such as synthetic insecticides, herbicides, chemical fertilizers, genetically modified microorganisms, growth regulators, and other chemicals, has adversely impacted not only soil fertility but also poses serious risks to human health and the environment. Nowadays, organic farming is a viable substitute for traditional farming methods. Using sustainable agricultural practices, organic farming attempts to preserve and improve the health of the land, biodiversity, and natural resources. It plays a vital part in lowering soil erosion, nutrient leaching (especially nitrate and phosphorus), improving soil's ability to retain water, and reducing greenhouse gas emissions. One of the soil functions that agricultural land offers to civilization is the supply of habitat variety.

Integrating Social and Ecological Predictors to Understand Variation within Ecosystems: A Case Study of the Great Smoky Mountains National Park PACE

Land management decisions have profound impacts on biological communities. Various administrative units are likely to implement different management decisions, with the result that consistent biological patterns that track administrative boundaries may emerge. To assess these relationships, we collected data on land cover, disturbance evidence, and tree communities in randomized sampling sites located in National Park, US Forest Service Wilderness, and US Forest Service Non-wilderness distributed across the Great Smoky Mountains National Park Protected Area-Centered Ecosystem (GRSM PACE). We examined how present-day values for these ecological responses were linked to both biophysical site characteristics (as the foundation for ecological communities) and jurisdiction type (as categories that integrate the combination of dynamic social decisions and management practices since initial designation). The variable representing administrative unit, jurisdiction type, acted as an umbrella indicator of the management trajectory and social influences that have affected a site and emerged as an important predictor of groundcover types (grass and litter), tree diversity, and wildlife sign at sites across the GRSM PACE. This was an exploratory study with limited sample size, so more data are needed to explore the mechanisms driving these relationships. These initial findings, however, suggest that differences in management activities alter the ecological trajectory of sites across the PACE. Given dynamic and diverse management practices, our data suggest jurisdiction overlaid on biophysical site information may be useful to rapidly assess how socially defined landscape activities impact biological responses, particularly when both are stressed by global change.

Simulating burn severity maps at 30 meters in two forested regions in California

Climate change is altering wildfire and vegetation regimes in California’s forested ecosystems. Present day fires are seeing an increase in high burn severity area and high severity patch size. The ability to predict future burn severity patterns could better support policy and land management decisions. Here we demonstrate a methodology to first, statistically estimate individual burn severity classes at 30 meters and second, cluster and smooth high severity patches onto a known landscape. Our goal here was not to exactly replicate observed burn severity maps, but rather to utilize observed maps as one realization of a random process dependent on climate, topography, fire weather, and fuels, to inform creation of additional realizations through our simulation technique. We developed two sets of empirical models with two different vegetation datasets to test if coarse vegetation could accurately model for burn severity. While visual acuity can be used to assess the performance of our simulation process, we also employ the Ripley’s K function to compare spatial point processes at different scales to test if the simulation is capturing an appropriate amount of clustering. We utilize FRAGSTATS to obtain high severity patch metrics to test the contiguity of our high severity simulation. Ripley’s K function helped identify the number of clustering iterations and FRAGSTATS showed how different focal window sizes affected our ability to cluster high severity patches. Improving our ability to simulate burn severity may help advance our understanding of the potential influence of land and fuels management on ecosystem-level response variables that are important for decision-makers. Simulated burn severity maps could support managing habitat and estimating risks of habitat loss, protecting infrastructure and homes, improving future wildfire emissions projections, and better mapping and planning for fuels treatment scenarios.

English

Barriers to successful transfer of contaminated land management policy from one country to another include socio-cultural, economic and environmental differences. While weak contaminated land management regimes desire effective legislation and make efforts to transfer policies from established regimes, contextual differences or characteristics between the two countries involved is a key challenge. These differing characteristics include social values, economic strength, governance structure, and technical know-how. An investigation was conducted through workshop and interviews to determine core social values that are impacted due to contaminated land by oil spills in the Niger Delta region of Nigeria. Workshop was undertaken for participants involving community groups (N=35), while interviews involved contaminated land management regulator (N=8), experts in contaminated land management in the Niger Delta (N=6), and operators in the oil exploration industry (N=7). Water quality, soil quality for agriculture, farming and fishing, and health/wellbeing indicated core social values that influence contaminated land management decisions while stakeholders expressed long-term concern about economic losses, clean-up, environmental degradation and public engagement. It is proposed that policymakers should consider unique conditions and country-specific characteristics in the event of policy adaptation for contaminated land management. An alternative approach to improving contaminated land management is recommended that will account for core social values and accommodate varying perceptions of stakeholders. &nbsp; Key words: Socio-economic values, stakeholder participation, livelihood, drinking water, oil spills, stakeholders&rsquo; perception.

Digital inventory of agricultural land plots in the Kemerovo Region

Cadastral and geodetic land works are expensive, which makes aerial photography extremely valuable for land traceability and inventory. The present research objective was to develop a new digital survey technology for registration of agricultural lands. We assessed the accuracy of the new method and evaluated its decision support options. The study featured the case of the Kemerovo Region (Kuzbass), Russia.&#x0D; The aerial survey took place in 2021 and involved 17 municipalities of the Kemerovo Region. The software and hardware complex included an unmanned aerial vehicle (UAV) and a module for aerial photography. Photogrammetric, cartometric, and satellite methods were used to define the coordinates of feature points. We developed new software (Sovhoz.avi) to perform the land inventory. &#x0D; The photogrammetric and cartographic methods proved efficient in determining the feature points and boundaries of land plots. They also appeared accurate enough for land inventory and decision support. The study updated the available land inventory data. About 30% of all land plots were recorded incorrectly; some plots marked as agricultural appeared to belong to the local forest reserves or urban territories. Incorrect data (1.64%) were excluded from the official inventory. The survey covered a total area of 41 000 ha and revealed 1700 illegally used land plots. The updated inventory of unused lands included 3825 new plots (163 400 ha), which can attract prospective investors.&#x0D; The results can be used by the local authorities to make land management decisions and identify illegal land use.

MODIS sensors can monitor spatiotemporal trends in fog and low cloud cover at 1 km spatial resolution along the U.S. Pacific Coast

Fog and low cloud cover (FLCC) provide critical moisture for ecosystems along the Pacific Coast during the summer months and it is currently unclear how climate change has affected FLCC occurrence. Additionally, FLCC impacts visibility and transportation safety for both road and air traffic. As such, a method for the monitoring of FLCC is necessary to inform land management decisions for fog-obligate species and to improve transportation safety, among other applications. Several gaps exist in current FLCC detection methodologies and while the Moderate Resolution Spectroradiometer (MODIS) sensor has previously been used to detect fog, its utility has not been validated. In this study, we create a 20 year (2000–2020) FLCC dataset using the Terra MODIS cloud flags and examine its effectiveness in detecting daily and monthly FLCC presence along the California and southern Oregon coast for the summer months (June–September). We validate the accuracy of this method using an existing FLCC dataset derived from Geostationary Operational Environmental Satellite (GOES) observations collected at 15 min intervals from 2000 to 2009. The two FLCC datasets have a strong linear relationship for FLCC frequency for each summer month, with an average r2 of 0.82 and p-value of <0.01. This strong relationship demonstrates the ability of Terra MODIS to reliably and accurately detect FLCC. Finally, we demonstrate a case study application of our FLCC dataset in a time series analysis over five coast redwood (Sequoia sempervirens) state parks in the Big Sur region of coastal California. This case study highlights the benefits provided by a 1 km resolution FLCC dataset for ecological applications and for monitoring spatiotemporal FLCC patterns across summer months over two decades. Our case study results showed that the number of foggy days fluctuates considerably year-to-year with no discernible positive or negative trend occurring between 2000 and 2020. Finally, we present a freely-accessible Google Earth Engine application to view and download the monthly FLCC data for all summer months for the years 2000–2020. The methods and dataset presented in this paper provide a means for efficient, daily FLCC monitoring at 1 km2 resolution, as well as the capacity for historical FLCC analyses.

A comparative analysis of the value of recreation in six contrasting Nordic landscapes using the travel cost method

Nordic landscapes provide recreational benefits to local, national, and international visitors. Nordic countries are, however, actively promoting a green shift towards the bioeconomy (that is, an intensification of agriculture and forestry), which may come at the cost of other benefits of Nordic landscapes, such as recreation. Information on recreational benefits and their monetary value is therefore required to outline a more comprehensive bioeconomy policy. For this paper, we estimated the benefits associated with the recreational use of six contrasting landscapes from four Nordic countries in their current environmental conditions, using a travel cost model, with data from a standardised survey of inhabitants and visitors. We found a large variation in the monetary estimates of the current annual recreational benefits from these landscapes, with a variation from 3.1 to 120.8 million € per landscape. We found that different characteristics of these landscapes, such as the visitor structure and visitors’ perceptions of the environmental quality, influence the estimated recreational value. Among the environmental characteristics we tested, we found that water quality and the proportion of nature conservation areas influence the recreational benefits, and need to be considered when making land use and management decisions. Furthermore, it is important that a sustainable bioeconomy policy is developed and implemented in such a way that the potentially negative effects of intensified agriculture and forestry on recreational possibilities are avoided.

New techniques for old fires: Using deep learning to augment fire maps from the early satellite era

Disturbances such as fire play a critical role in forest ecosystems. However, anthropogenic fires can profoundly impact forests to the point of destabilizing ecosystems. In addition, fires have legacy effects on environments which may be observed in forests for decades after the fire is extinguished. Thus, understanding the extent of historic fires in a landscape is vital to understanding current forest structure and ecological processes (e.g., carbon sequestration capacity and provision of habitat) and, therefore, essential for informing land-management decisions. However, little work has been done to map forest fires pre 1980s due to the challenges of interpreting imagery from the 1970s-era Landsat Multispectral Scanner (MSS) platform. MSS imagery is distinguished from recent satellite missions through lower temporal, spatial, and spectral resolutions. Recent advances in image processing have brought the goal of high-quality MSS classifications within reach. In this study, we use deep learning, specifically UNet (a fully convolutional neural network (CNN)), to detect historic forest fires in MSS imagery for the forest-dominated regions of Quebec, Canada. While other studies have applied deep learning to present-day satellite data for land cover classification, hardly any work has specifically applied deep learning to MSS data for fire detection. We trained our UNet model on 206 MSS images that were labelled by applying thresholds to the Burned Area Index inside polygons drawn by the authors around burned areas. We then used the trained model to label burns in 5104 MSS images that were compiled to generate annual burned area maps. Our results identified (with a 95% confidence interval) 3503.95 ± 484.90 km2 of burns not previously reported in any database; this represents a 35.30 ± 3.94% increase in the total known burned area across the forest-dominated regions of Quebec between 1973 and 1982.

Perceptions of land use and land cover analysed using geospatial data

Considering how individuals perceive landscape is important when undertaking land management decisions. However, understanding how the community perceives a landscape is complex involving their experiences in that landscape, their lived experiences and other socio-cultural processes. One of the key challenges to understanding perception is linking the landscape properties to what is experienced when individuals interact with the landscape. Increasingly the use of geospatial data offers a tool for understanding the landscape and perceptions. This study compares satellite estimates of land use with the perceptions of the inhabitants of Yungay, Chile. Viewshed analysis is used to reconcile the differences seen in the satellite image cover estimates and those of the participants. It was found that restricting the cover estimate to the visible landscape, provided similar estimates of cover to those made by the participants. This varied between demographic groups. With differences between participants living in urban and rural settings particularly evident.

Advances on water quality modeling in burned areas: A review

Wildfires are a recurring hazard in forested catchments representing a major threat to water security worldwide. Wildfires impacts on water quality have been thoroughly addressed by the scientific community through field studies, laboratory experiments, and, to a lesser extent, the use of hydrological models. Nonetheless, models are important tools to assess on-site and off-site wildfires impacts and provide the basis for post-fire land management decisions. This study aims to describe the current state of the art of post-fire model adaptation, understanding how wildfires impacts are simulated and the options taken by the modelers in selecting parameters. For this purpose, 42 publications on modeling wildfire impacts on the hydrologic cycle and water quality were retrieved from the SCOPUS database. Most studies simulated post-fire hydrological and erosion response in the first year after the fire, while few assessed nutrients changes and long-term impacts. In addition, most simulations ended at the watershed outlet without considering the fate of pollutants in downstream waterbodies. Ash transport was identified as a major research gap, given the difficulties of its incorporation in the current models’ structure and the high complexity in predicting the heterogeneous ash layer. Including such layer would improve models’ ability to simulate water quality in post-fire conditions, being ash a source of nutrients and contaminants. Model complexity and data limitations influenced the spatial and temporal scale chosen for simulations. Post-fire model adaptations to simulate on-site soil erosion are well established, mainly using empirical equations extensively calibrated in the literature. At the watershed level, however, physical and process-based models are preferred for their ability to simulate more complex burned area characteristics. Future research should focus on the simulation of the ash transport and the development of integrated modelling frameworks, combining watershed and aquatic ecosystem models to link the on and off-site impacts of fires.

The potential of metabarcoding plant components of Malaise trap samples to enhance knowledge of plant-insect interactions

The worldwide rapid declines in insect and plant abundance and diversity that have occurred in the past decades have gained public attention and demand for political actions to counteract these declines are growing. Rapid large-scale biomonitoring can aid in observing these changes and provide information for decisions for land management and species protection. Malaise traps have long been used for insect sampling and when insects are captured in these traps, they carry traces of plants they have visited on the body surface or as digested food material in the gut contents. Metabarcoding offers a promising method for identifying these plant traces, providing insight into the plants with which insects are directly interacting at a given time. To test the efficacy of DNA metabarcoding with these sample types, 79 samples from 21 sites across Germany were analysed with the ITS2 barcode. This study, to our knowledge, is the first examination of metabarcoding plant DNA traces from Malaise trap samples. Here, we report on the feasibility of sequencing these sample types, analysis of the resulting taxa, the usage of cultivated plants by insects near nature conservancy areas and the detection of rare and neophyte species. Due to the frequency of contamination and false positive reads, isolation and PCR negative controls should be used in every reaction. Metabarcoding has advantages in efficiency and resolution over microscopic identification of pollen and is the only possible identification method for the other plant traces from Malaise traps and could provide a broad utility for future studies of plant-insect interactions.

Implementing ecosystem service assessments within agribusiness: Challenges and proposed solutions

Abstract Incorporating the assessment of ecosystem services into land management decisions is increasingly recognized as an opportunity to support sustainable development. This, however, can be particularly challenging within the productive sector, a highly technical system often driven by multi‐level private entities. Here we present five key challenges, and suggest their corresponding solutions, when promoting the operationalization of ecosystem services within agribusiness. The challenges we developed are as follows: (a) building a common understanding of ecosystem services; (b) navigating strong power dynamics; (c) a highly technical system with diverse types of expertise; (d) limited understanding of the opportunity costs of alternative practices and (e), dealing with uncertainty. We draw on our experience generated through the Wine, Climate Change and Biodiversity programme, a science‐based initiative promoting the conservation of biodiversity and strategic use of ecosystem services in Chilean vineyards. Synthesis and applications. This perspective piece provides advice to scientists and practitioners on how to navigate technical and practical challenges when promoting the incorporation of ecosystem services into agricultural management. While the assessment of ecosystem services can be a highly technical process, its successful integration into land management decisions relies on active engagement, balancing expectations and an ability to construct a shared understanding among different stakeholders. The approaches suggested here rely on principles of co‐production and are illustrated with examples that are transferable to other crop and geographical contexts.

Impact of climate change on catchment nutrient dynamics: insights from around the world

This study is a meta-analysis of global articles on hydrological nutrient dynamics to determine trends and consensus on: (1) the effects of climate change-induced hydrological and temperature drivers on nutrient dynamics and how these effects vary along the catchment continuum from land to river to lake; (2) the convergence of climate change impacts with other anthropogenic pressures (agriculture, urbanization) in nutrient dynamics; and (3) regional variability in the effects of climate change on nutrient dynamics and water-quality impairment across different climate zones. An innovative web crawler tool was employed to help critically synthesize the information in the literature. The literature suggests that climate change will impact nutrient dynamics around the globe and exacerbate contemporary water-quality challenges. Nutrient leaching and overland flow transport are projected to increase globally, promoted by extreme precipitation. Seasonal variations in streamflow are expected to emulate changing precipitation patterns, but the specific local impacts of climate change on hydrology and nutrient dynamics will vary both seasonally and regionally. Plant activity may reduce some of this load in nonagricultural soils if the expected increase in plant uptake of nutrients prompted by increased temperatures can compensate for greater nitrogen (N) and phosphorus (P) mineralization, N deposition, and leaching rates. High-temperature forest and grass fires may help reduce mineralization and microbial turnover by altering N speciation via the pyrolysis of organic matter. In agricultural areas that are at higher risk of erosion, extreme precipitation will exacerbate existing water-quality issues, and greater plant nutrient uptake may lead to an increase in fertilizer use. Future urban expansion will amplify these effects. Higher ambient temperatures will promote harmful cyanobacterial blooms by enhancing thermal stratification, increasing nutrient load into streams and lakes from extreme precipitation events, decreasing summer flow and thus baseflow dilution capacity, and increasing water and nutrient residence times during increasingly frequent droughts. Land management decisions must consider the nuanced regional and seasonal changes identified in this review (realized and predicted). Such knowledge is critical to increasing international cooperation and accelerating action toward the United Nations’s global sustainability goals and the specific objectives of the Conference of Parties (COP) 26.

The flora of Fair River Farm, Lincoln County, Mississippi, U.S.A.

Southwest Mississippi is a poorly studied, but biologically diverse region, encompassing the broad transition from the East Gulf Coastal Plain longleaf pine-bluestem ecosystem to the rich hardwood forests of the Loess bluffs and hills. A floristic inventory of an approximately 694.7-hectare privately owned natural area in Lincoln County was conducted. The Fair River Farm is situated in a region of highly dissected terrain around the Little Fair River and Kees Creek, near the transition between two major level III ecoregions, and the boundary between the Pearl River and lower Mississippi River drainage basins. 744 vascular plant taxa and 72 bryophytes were documented. 495 taxa are new to Lincoln County, and 3 are new to the state of Mississippi; 27 species are designated special concern by the Mississippi Natural Heritage Program, 13 are on the watch list and 14 are on the tracking list. Photographic records available on iNaturalist are used for some species as an alternative to physical vouchers. Plant communities present on the tract are discussed and briefly and qualitatively compared to General Land Office records, original county soil surveys, and historic descriptions of the region, with emphasis on the distribution of longleaf pine (Pinus palustris Mill.), now very rare on the tract. The number of county records highlights the need for more survey work and potentially underreported biological diversity and conservation value of the southwest region of Mississippi and other poorly collected areas of the Southeastern U.S.; this inventory may inform land management decisions on the tract and elsewhere in the region.

Fire severity and the post‐fire soil environment affect seedling regeneration success of the threatened Persoonia hirsuta (Proteaceae)

AbstractClimate change and land management decisions have considerably altered fire regimes globally resulting in increased risks of extreme fire seasons. Fire intensity is one characteristic of fire regime which is projected to increase. However, the magnitude and impact of intense fires on plant habitat and life history characteristics (such as the soil environment or seedling recruitment) remain unclear for many species. The widespread 2019–2020 Black Summer fires across Eastern Australia provided the opportunity to examine the impact of these fires on the short‐term regeneration of the Endangered Persoonia hirsuta (Proteaceae), an obligate seeding (reliant on regeneration from seed following fire) shrub presently threatened by population decline and dieback (plant death from branch and root tips backwards) of an unknown cause. In this study, we used a combination of metrics to estimate fire severity in the field at 22 plots across three fire‐affected populations which we used as a proxy to understand the relative impacts of fire intensity on P. hirsuta regeneration post‐fire. We also recorded the recruitment, growth, dieback and mortality of P. hirsuta seedlings at these plots over 21 months following the fires and examined whether the post‐fire soil environment (carbon, nitrogen and phosphorus) was related to fire severity and seedling responses. Seedling recruitment and growth were variable across sites and showed no relationship to fire severity. However, seedling dieback and mortality were significantly higher among plots exposed to high severity fires. Additionally, characteristics of the post‐fire soil environment varied by fire severity and explained variation in seedling recruitment, growth and dieback. Our work provides important evidence that already vulnerable populations of P. hirsuta may be further threatened by increasing fire severity, highlighting the importance of understanding the effects of fire on habitat and life history characteristics for threatened plants.

Limitations to the soil impacts of tree regrowth in improved cattle pasture

Tree regrowth plots are often utilised to reduce soil erosion and increase soil organic carbon (SOC) as well as providing shade for cattle. However, unfenced tree regrowth plots have been found to make limited improvements in soil health in grazing lands. To better inform land management decisions, the impact of an unfenced tree regrowth on soil erosion rates and soil properties was analysed for an improved (i.e., sown with introduced species) cattle pasture in Eastern Australia. Soil cores were collected to 20 cm depth for two paired transects: one with improved pasture and a tree plot, and one consisting only of improved pasture. Samples were analysed for soil organic carbon and soil properties and soil erosion rates were determined using the diffusion and migration model (DMM) and Revised Universal Soil Loss Equation (RUSLE). Maximum DMM erosion rates were similar for the two transects at 2.7 (tree plot) and 2.3 (pasture) t.ha−1.yr−1, with the tree plot not having a statistically significant effect. RUSLE erosion rates showed less similarity for the transects at 5.58 (pasture) and 3.08 (tree plot) t.ha−1.yr−1. SOC was lower within the tree plot compared to the rest of the transect, while it was significantly higher in the pasture than the tree plot transect (4.93% compared to 3.72%). To examine if the tree plot is buffering against higher erosion caused by this, the RUSLE cover factor was substituted for that of the pasture transect. However, no such effect was observed. Overall, the tree plot had no significant effect on SOC and erosion in this improved pasture grazing system. This has implications for the design of tree plots and their location, which is significant due to their perceived role in regenerative agriculture practices.

Land Management Change as Adaptation to Climate and Other Stressors: A Systematic Review of Decision Contexts Using Values-Rules-Knowledge

Agricultural producers are already experiencing the adverse effects of climate change, highlighting the urgent need for adaptation. While incremental changes to cope with interannual variability are widely applied, there is limited understanding of the social contexts that inform, enable, or constrain more transformational adaptations in response to anticipated or actual climate change and other stressors. Systematic review methods are used to identify 31 empirical examples of land management change as an adaptation response by agricultural producers in developed countries. We then applied the values-rules-knowledge (vrk) framework to analyse interactions between societal values, institutional rules, and scientific and experiential knowledge. The vrk is a heuristic to help decision makers analyze how the social system shapes their decision context. Three propositions highlighting the relative influence of different values–rules, values–knowledge, and rules–knowledge relationships on agri-food and forestry land-management decisions are presented and discussed. We suggest that further testing of these propositions will provide evidence for decision makers about how decision contexts can be shifted to enable anticipatory transformative adaptation in the primary industries and support sustainable transitions towards more resilient futures.

A multi-level assessment of changes in stakeholder constellations, interest and influence on ecosystem services under different landscape scenarios in southwestern Ethiopia

Growing global interconnections facilitate inter-regional flows of ecosystem services (ES). Several studies have focused on the opportunities, risks, and governance of telecoupled ES. However, considerable theoretical, methodological, and empirical gaps exist regarding how future demand for ES will shape trajectories of land use change, the bundles of ecosystem services and related livelihoods provided by future landscapes. This paper explores how multi-level stakeholder constellations, interests, and influence on ES change with a shift in the landscape from the current landscape to alternative future scenario landscapes. We integrated three methodological concepts: space-for-time substitution, scenario planning, and multi-level stakeholder interest and influence mapping. We focused on a smallholder farming landscape in southwestern Ethiopia that is characterized by, and sensitive to, rapid social-ecological change. We build on previous research that developed four plausible scenarios of landscape change for the landscape over the coming 20 years: the “Cash crops”, “Coffee investors”, “Biosphere reserve”, and “Food first” scenarios. We treated the current (focal) landscape as the baseline. Based on space-for-time substitution, we selected four existing landscapes nearby as proxies representing the types of changes described in the four scenarios. In both focal and scenario landscapes, we then identified stakeholders and interviewed them about their interest and influence related to ES (n = 122). Stakeholder constellations, interests, and influences on ES differed considerably between the focal and the scenario landscapes. Generally, a shift to the “Cash crops”, “Coffee investors”, and “Food first” scenarios increased the proportion of local, regional and global private organizations that engaged with the landscape. Many of these stakeholders sought to maximize profit through commercializing a few provisioning ES, often relying on regulatory and economic power to influence the landscape. In contrast, a change to the “Biosphere reserve” scenario increased the proportion of non-governmental organizations engaging with the landscape, and drew on stakeholders from multiple governance scales that were interested in diverse provisioning, cultural, regulating, and supporting ES. Our findings suggest that future landscapes imply divergent changes in stakeholder constellations and interests, both from proximate and remote locations. Landscape management should consider such possible changes in multi-level stakeholder constellations, interests, and influence. Our methodological approach enriches existing scenario narratives with empirically grounded social and governance layers that can improve proactive land management decisions.