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The UK sixth carbon budget has recommended domestic biomass supply should increase to meet growing demand, planting a minimum of 30,000 hectares of perennial energy crops a year by 2035, with a view to establishing 700,000 hectares by 2050 to meet the requirements of the balanced net zero pathway. Miscanthus is a key biomass crop to scale up domestic biomass production in the United Kingdom. A cohesive land management strategy, based on robust evidence, will be required to ensure upscaling of miscanthus cultivation maximizes the environmental and economic benefits and minimizes undesirable consequences. This review examines research into available land areas, environmental impacts, barriers to uptake, and the challenges, benefits, and trade‐offs required to upscale miscanthus production on arable land and grassland in the United Kingdom. Expansion of perennial biomass crops has been considered best restricted to marginal land, less suited to food production. The review identifies a trade‐off between avoiding competition with food production and a risk of encroaching on areas containing high‐biodiversity or high‐carbon stocks, such as semi‐natural grasslands. If areas of land suitable for food production are needed to produce the biomass required for emission reduction, the review indicates there are multiple strategies for miscanthus to complement long‐term food security rather than compete with it. On arable land, a miscanthus rotation with a cycle length of 10–20 years can be employed as fallow period for fields experiencing yield decline, soil fatigue, or persistent weed problems. On improved grassland areas, miscanthus presents an option for diversification, flood mitigation, and water quality improvement. Strategies need to be developed to integrate miscanthus into farming systems in a way that is profitable, sensitive to local demand, climate, and geography, and complements rather than competes with food production by increasing overall farm profitability and resilience. [ABSTRACT FROM AUTHOR]

Restoring ecosystems is an imperative for addressing biodiversity loss and climate change, and achieving the targets of the Kunming–Montreal Global Biodiversity Framework. One form of restoration, rewilding, may have particular promise but may also be precluded by requirements for other forms of land use now or in the future. This opportunity space is critical but challenging to assess. We explored the potential area available for rewilding in Great Britain until the year 2080 with a multisectoral land‐use model with several distinct climatic and socioeconomic scenarios. By 2080, areas from 5000 to 7000 km2 were either unmanaged or managed in ways that could be consistent with rewilding across scenarios without conflicting with the provision of ecosystem services. Beyond these areas, another 24,000–42,000 km2 of extensive upland management could provide additional areas for rewilding if current patterns of implementation hold in the future. None of these areas, however, coincided reliably with ecosystems of priority for conservation: peatlands, ancient woodlands, or wetlands. Repeatedly, these ecosystems were found to be vulnerable to conversion. Our results are not based on an assumption of support for or benefits from rewilding and do not account for disadvantages, such as potential losses of cultural landscapes or traditional forms of management, that were beyond the modeled ecosystem services. Nevertheless, potential areas for rewilding emerge in a variety of ways, from intensification elsewhere having a substantial but inadvertent land‐sparing effect, popular demand for environmental restoration, or a desire for exclusive recreation among the wealthy elite. Our findings therefore imply substantial opportunities for rewilding in the United Kingdom but also a need for interventions to shape the nature and extent of that rewilding to maintain priority conservation areas and societal objectives. [ABSTRACT FROM AUTHOR]

In this study, we employed the evidential belief function model (EBF) to evaluate the potential for land subsidence in the primary aquifer of Bardaskan. Through field visits, we recorded GPS coordinates for 174 land subsidence points. Factors considered in assessing land subsidence potential included well density, groundwater extraction rate, geological characteristics, proximity to faults, vegetation cover, distance from the river, slope, and land use. To develop and validate the model, 70% of the recorded points were randomly selected for training and implementation, while the remaining 30% were reserved for model validation. The number and percentage of land subsidence points in the different classes of the corresponding layers were determined by integrating the training points with influential variables maps such as distance from the river, distance from the fault, land use, and extraction volume. The EBF model rate was calculated for different layer classes. For modeling, all rates of the EBF model in each cell were summated, and the ‎potential of land subsidence was calculated.‎ Finally, the map of land subsidence potential based on the EBF model was determined with GIS. The results showed that most of the subsidence points were located in alluvial sediment of the Holocene period, in areas with high groundwater harvesting, a distance of at least 3000 m from a river, a distance of at least 6000 m from a fault, low‐density rangelands, slopes of at least 0%–2%, and farmlands and gardens. A receiver operating characteristic curve analysis of the EBF model showed that it could accurately predict land subsidence in 87.5% of cases using 30% of the validation data. This suggests that the model can be used for practical applications. Recommendations for Resource Managers: Most of the occurred subsidence points in the Bardaskan aquifer were located in the alluvial sediment of the Holocene period.Subsidence points were closely related to high groundwater harvesting, distance from a river and fault, low‐density rangelands, slopes, and farmlands and gardens.The area under the receiver operating characteristic curve was calculated to be 87.5%, indicating that the evidential belief function model accurately predicts land subsidence in the studied area. [ABSTRACT FROM AUTHOR]

The global push for renewable energy must overcome the local challenge of convincing neighboring landowners to lease their properties for wind power. Is this challenge more or less pronounced in rural landscapes with small landholdings? Our theoretical model combines ideas from literatures on the commons, anticommons, and spatial externalities to explain conditions when small landholdings could promote or inhibit voluntary leasing. Empirically, we estimate the effects of landholding size and landscape fragmentation on wind farm uptake across rural areas of the United States over the past 20 years. Evidence from three spatial levels of analysis (counties, square‐mile sections, and individual parcels) indicates that areas with more landowners have less installed wind capacity after controlling for windiness, access to transmission lines, and other relevant factors that vary across and within counties. The findings imply that fragmented ownership, which is an overlooked factor in studies of the feasibility of decarbonization, will pose an impediment to future wind expansion on private land as remaining areas without wind development become disproportionately fragmented. [ABSTRACT FROM AUTHOR]

Societal Impact Statement: Global climate models that incorporate carbon sources and sinks usually consider that forest uptake of carbon is in a state of equilibrium. Both historical and paleoecological records suggest that this is commonly not the case for Amazonia. Here, the impacts of colonial practices on Amazonian Indigenous peoples and forests are reviewed. Human activities affect forests' successional stages, trajectories, and species composition. By increasing the spatial coverage of paleoecological records that focus on pre‐ and post‐Columbian periods, the long‐term interactions between humans and Amazonian forests and their role in affecting Earth's climate may be better understood. Summary: Legacy effects left by the activities of Indigenous people in Amazonia are well known. Although severe, widespread, and recently occurring, the impacts left post‐1492 CE have been less investigated. We review the impact of colonial practices on Indigenous peoples and Amazonian forests. We suggest that forests comprise the sum of their past events, in a mosaic of different cumulative successional trajectories depending on the type, frequency, intensity, and timing of human influence. In regions with a history of minimal human influence, old‐growth species sensitive to fire would be the dominant landscape. In regions with high pre‐Columbian and low colonial influence, old‐growth forests carrying pre‐Columbian ecological legacies would be prevalent. Regions occupied by Indigenous groups post‐1492 CE would also carry similar ecological legacies. In regions influenced by the Jesuits, mid‐successional forests are expected to be enriched with cacao trees. In regions of latex extraction during the rubber boom, mid‐growth forests would present high abundances of early and mid‐successional species and depletion of some species. In deforested areas, we expect early successional forests with influence of exotic useful species. This patchwork of history probably plays a large role in shaping today's forests, and the biodiversity and carbon dynamics documented within them. Paleoecological work focusing on the last millennium, although scarce, has the potential to detect these mosaics of past human influence, and they should be considered when estimating forest ages and successional stages across the basin. [ABSTRACT FROM AUTHOR]

Rangelands are the dominant land use across a broad swath of central North America where they span a wide gradient, from <350 to >900 mm, in mean annual precipitation. Substantial efforts have examined temporal and spatial variation in aboveground net primary production (ANPP) to precipitation (PPT) across this gradient. In contrast, net secondary productivity (NSP, e.g., primary consumer production) has not been evaluated analogously. However, livestock production, which is a form of NSP or primary consumer production supported by primary production, is the dominant non‐cultivated land use and an integral economic driver in these regions. Here, we used long‐term (mean length = 19 years) ANPP and NSP data from six research sites across the Central Great Plains with a history of a conservative stocking to determine resource (i.e., PPT)–productivity relationships, NSP sensitivities to dry‐year precipitation, and regional trophic efficiencies (e.g., NSP:ANPP ratio). PPT–ANPP relationships were linear for both temporal (site‐based) and spatial (among site) gradients. The spatial PPT–NSP model revealed that PPT mediated a saturating relationship for NSP as sites became more mesic, a finding that contrasts with many plant‐based PPT–ANPP relationships. A saturating response to high growing‐season precipitation suggests biogeochemical rather than vegetation growth constraints may govern NSP (i.e., large herbivore production). Differential sensitivity in NSP to dry years demonstrated that the primary consumer production response heightened as sites became more xeric. Although sensitivity generally decreased with increasing precipitation as predicted from known PPT–ANPP relationships, evidence suggests that the dominant species' identity and traits influenced secondary production efficiency. Non‐native northern mixed‐grass prairie was outperformed by native Central Great Plains rangeland in sensitivity to dry years and efficiency in converting ANPP to NSP. A more comprehensive understanding of the mechanisms leading to differences in producer and consumer responses will require multisite experiments to assess biotic and abiotic determinants of multi‐trophic level efficiency and sensitivity. [ABSTRACT FROM AUTHOR]

Estimation of human water withdrawals is more important now than ever due to uncertain water supplies, population growth, and climate change. Fourteen percent of the total water withdrawal in the United States is used for public supply, typically including deliveries to domestic, commercial, and occasionally including industrial, irrigation, and thermoelectric water withdrawal. Stewards of water resources in the USA require estimates of water withdrawals to manage and plan for future demands and sustainable water supplies. This study compiled the most comprehensive conterminous United States water withdrawal data set to date and developed a machine learning framework for estimating public supply withdrawals and associated uncertainty for the period 2000–2020. The modeling approach provides service area resolution estimates to allow for annual and monthly water withdrawal estimation while incorporating a complex array of driving factors that include hydroclimatic, demographic, socioeconomic, geographic, and land use factors. Model results reveal highly variable and lognormally distributed per‐capita water withdrawal, spanning from 30 to 650 gallons per capita per day (GPCD), across community, regional, and national scales, with pronounced seasonal variations. Analysis of estimated withdrawal trends indicates that the national annual average withdrawal experienced a decline at a rate of 0.58 GPCD/year during the period from 2000 to 2020. Model interpretation reveals a complex interplay between public supply withdrawal and key predictors, including population size, warm‐season precipitation, counts of large buildings and houses, and areas of urban and commercial land use. The developed models can forecast future public supply driven by various climate, demographic, and socioeconomic scenarios. Key Points: Consistent, reproducible estimates of monthly water withdrawals were generated at the spatial resolution of USA water service areasSpatial and temporal variability of public supply withdrawal is driven by a complex array of explanatory featuresAn operational machine learning framework was developed to estimate water withdrawals, prediction uncertainty, and feature importance [ABSTRACT FROM AUTHOR]

Forest–grassland ecotone (FGE) has essential ecological and economic value. Unfortunately, it is impacted greatly by environmental changes and anthropogenic disturbance, and is considered one of the most severely threatened biomes in China. To protect Chinese FGE, identifying its exact boundary and exploring its landscape structure dynamic are badly needed, especially on nationwide scale at one‐year temporal resolution. Here, we mapped the annual FGE distribution of China from 1990 to 2020, investigated its changing trends of area, location and landscape patterns, and revealed the underlying driving factors. Our results showed that FGE area over the 31 years totaled 1 011 870 km2, covering about 10.54% of China's land. The FGE area first increased from 1990 and peaked in 1999, and then kept decreasing until 2020. The FGE gravity center has moved accumulatively 590.15 km over the 31 years, with the net moving distance of 228.76 km southwestward. From 1990 to 2020, forest area increased continuously while grassland and cropland area decreased, but these three landscape types had been dominating the FGE. The increase in forest area was largely converted from grassland. The decline in grassland mainly resulted from its conversion into cropland and forest. Meanwhile, the conversion of cropland to grassland supplemented grassland loss to a certain extent. At landscape level, the total area with decreased fragmentation is larger than that with increased fragmentation. Returning Farmland to Grassland Project and land reclamation were primary drivers for changes of fragmentation in the northern and middle part of the FGE, while temperature and precipitation were primary drivers in southern part. Our results will improve the understanding into the dynamic trends of distribution and pattern of FGE at nationwide scale, and thus help to optimize the designing of ecological projects and protective schemes for FGE as a unique and integral biome. [ABSTRACT FROM AUTHOR]

Recent international agreements have strengthened and expanded commitments to protect and restore native habitats for biodiversity protection ("area‐based biodiversity conservation"). Nevertheless, biodiversity conservation is hindered because how such commitments should be implemented has been strongly debated, which can lead to suboptimal habitat protection decisions. We argue that, despite the debates, there are three essential principles for area‐based biodiversity conservation. These principles are related to habitat geographic coverage, amount, and connectivity. They emerge from evidence that, while large areas of nature are important and must be protected, conservation or restoration of multiple small habitat patches is also critical for global conservation, particularly in regions with high land use. We contend that the many area‐based conservation initiatives expected in the coming decades should follow the principles we identify, regardless of ongoing debates. Considering the importance of biodiversity for maintenance of ecosystem services, we suggest that this would bring widespread societal benefits. [ABSTRACT FROM AUTHOR]

Land‐use and climate change are major pressures on terrestrial biodiversity. Species' extinction risk and responses to human pressures relate to ecological traits and other characteristics in some clades. However, large‐scale comparative assessments of the associations between traits and responses to multiple human pressures across multiple clades are needed. We investigated whether a set of ecological characteristics that are commonly measured across terrestrial vertebrates (ecological traits and geographic range area) are associated with species' responses to different land‐use types and species' likely sensitivity to climate change. We aimed to test whether generalizable patterns in response to these pressures arise across both pressures and across vertebrate clades, which could inform assessments of the global signature of human pressures on vertebrate biodiversity and guide conservation efforts. At the species level, we investigated associations between land‐use responses and ecological characteristics with a space‐for‐time substitution approach, making use of the PREDICTS database. We investigated associations between ecological characteristics and expected climate‐change sensitivity, estimated from properties of species realized climatic niches. Among the characteristics we considered, 3 were consistently associated with strong land‐use responses and high climate‐change sensitivity across terrestrial vertebrate classes: narrow geographic range, narrow habitat breadth, and specialization on natural habitats (which described whether a species occurs in artificial habitats or not). The associations of other traits with species' land‐use responses and climate‐change sensitivity often depended on species' class and land‐use type, highlighting an important degree of context dependency. In all classes, invertebrate eaters and fruit and nectar eaters tended to be negatively affected in disturbed land‐use types, whereas invertebrate‐eating and plant‐ and seed‐eating birds were estimated to be more sensitive to climate change, raising concerns about the continuation of ecological processes sustained by these species under global changes. Our results highlight a consistently higher sensitivity of narrowly distributed species and habitat specialists to land‐use and climate change, which provides support for capturing such characteristics in large‐scale vulnerability assessments. [ABSTRACT FROM AUTHOR]

Ecosystem state transitions can be ecologically devastating or be a restoration success. State transitions are common within aquatic systems worldwide, especially considering human‐mediated changes to land use and water use. We created a transferable conceptual framework to enable multiscale assessments of state resilience and early warnings of state transitions that can inform strategic restorations and avoid ecosystem collapse. The conceptual framework integrated machine learning predictions with ecosystem state concepts (e.g., state classification, gradients of vulnerability, and recovery potential leading to state transitions) and was devised to investigate possible environmental drivers. As an application of the framework, we generated prediction probabilities of submersed aquatic vegetation (SAV) presence at nearly 10,000 sites in the Upper Mississippi River (United States). Then, we used an interpretability method to explain model predictions to gain insights into possible environmental drivers and thresholds or linear responses of SAV presence and absence. Model accuracy was 89% without spatial bias. Average water depth, suspended solids, substrate, and distance to nearest SAV were the best predictors and likely environmental drivers of SAV habitat suitability. These environmental drivers exhibited nonlinear, threshold‐type responses for SAV. All the results are also presented in an online dashboard to explore results at many spatial scales. The habitat suitability model outputs and prediction explanations from many spatial scales (4 m to 400 km of river reach) can inform research and restoration planning. [ABSTRACT FROM AUTHOR]

Native ecosystem and biodiversity loss from land use conversion into human‐modified landscapes are evident in the United States and globally. In addition to public land conservation, there is an increase in private land conservation through conservation easements (CEs) across exurban landscapes. Not every CE was established strictly for biodiversity protection and permitted land uses can increase human modification. No research of which we are aware has examined the actual tax assessor's land use designations (LUDs) through time. We constructed granular CE datasets (GCED) of CEs and their parcels' tax assessment LUDs for 1997–2008/2009, based on original data from 12 counties in six US states. Using the GCED, we examined patterns in the LUDs, with implications for land uses that could impact CE biological outcomes. We show that LUDs on exurban private conservation lands were predominately residential and agricultural, with increased residential over time. Critically, the LUDs lack a biological conservation exempt designation/category. There is no consistent trend in association between the primary CE reason and its parcel's LUD, suggesting that they coincide in some circumstances but in others, the CE may be a response to contravene the LUD. The majority of the first CE reasons are focused on open space preservation, except in some counties where agricultural land uses and agricultural CEs are associated. The economically and human‐focused LUD is one of many social factors that should be considered in a classification system for private land conservation and CEs more specifically. These results prompt the land conservation, conservation biology, and environmental planning communities to explore assessed land uses' impact on biodiversity conservation objectives. [ABSTRACT FROM AUTHOR]

Many tropical landscapes have experienced the loss of traditional cultivation practices as they have transitioned to other land use systems.The Tanintharyi Region of southern Myanmar is a landscape experiencing a rapid land use regime shift from traditional subsistence farming to permanent cash crop agriculture. Despite previous research in this region on the expansion of large‐scale agribusiness, such as oil palm and rubber plantations, little is known about how the small‐scale shifting cultivation system practiced by the local Karen ethnic people in Tanintharyi has changed over recent decades or the underlying reasons for this transition.Our study explores this transition process and its drivers from a social and land system change perspective in four villages of Bokpyin Township in Tanintharyi. We investigated the drivers of land cover and land use change by collecting information through focus groups and individual interviews with community members who previously practised shifting cultivation. We also quantified the overall change in land cover and land use through remote sensing analysis of Landsat 8 (2020) and declassified KH‐9 satellite imagery (1976).Prior to a period of civil war in the 1980s, cultivators used a traditional 'slash‐and‐burn' agricultural system for subsistence use. The present land use system is dominated by permanent betel nut cultivation, which represents the primary income source for farming households. The reported drivers of the transition to cash crop farming are greater income potential and livelihood security, risk of losing fallow land due to the needs for new cultivation areas for in‐migration and new centralized land use policies and administration after the national ceasefire agreement in 2012. The documented change in land use systems has been paired with a concurrent net loss of forest that, given the conflicted governance within the landscape, seems likely to continue without additional land use planning efforts.Our study contributes to an increased understanding of changes in shifting cultivation systems that are being documented globally. Furthermore, our example of combining qualitative interviews with analysis of historical satellite imagery to detect and explain land use regime shifts can serve as a model for future work in different landscapes. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Land use and land cover changes (LULCCs) can influence surface temperature through local and nonlocal biophysical processes, which remain inadequately addressed. In this study, we separate the local and nonlocal effects of historical (1850–2014) LULCCs based on model outputs from the Coupled Model Intercomparison Project Phase 6. We also attempt to explore the sources of intermodel differences in the effects of LULCCs. The multimodel mean shows a cooling effect of −0.05°C (with an intermodel range of −0.24–0.06°C) at the global scale due to cropland and pastureland expansion, consisting of dominant nonlocal cooling of −0.06°C (with an intermodel range of −0.26–0.06°C) and slight local warming of 0.01°C (with an intermodel range of −0.01–0.05°C). The modeling results show some clear consistency in the effects of LULCCs despite considerable intermodel uncertainties. The local effects cause warming at low latitudes and cooling in boreal regions via changes in upward shortwave radiation and sensible and latent heat fluxes. The nonlocal effects mainly cause cooling via decreases in downward longwave radiation and increases in upward shortwave radiation. Intermodel differences in the total effects are dominated by those in the nonlocal effects, which are further attributed to divergent changes in downward longwave radiation and sensible heat flux across the models. This study highlights the importance of the nonlocal effects of LULCCs in terms of strength and intermodel uncertainty, with implications for designing land‐based solutions aimed at climate change mitigation. Plain Language Summary: Land use and land cover changes (LULCCs) can alter surface properties and thereby influence surface temperature through land–atmosphere interactions. LULCCs influence the climate not only at the location of LULCCs (local effects) but also elsewhere (nonlocal effects) through atmospheric and oceanic feedbacks. However, the local and nonlocal effects of realistic LULCCs still lack explicit investigation. In this study, we quantify the local and nonlocal effects of historical (1850–2014) LULCCs and their intermodel differences based on a set of simulations from four earth system models. The multimodel mean suggests that historical cropland and pastureland expansion has caused a nonlocal cooling effect of −0.06°C and a local warming effect of 0.01°C, creating a net cooling effect of −0.05°C at the global scale. The local and nonlocal effects of LULCCs can be attributed to changes in surface fluxes and atmospheric feedbacks, whereas the strength and sign vary substantially across the models. Large intermodel differences in the total effects of LULCCs mostly result from those in the nonlocal effects. This study highlights the importance of the nonlocal effects of LULCCs and has implications for developing land‐use strategies aimed at climate change mitigation. Key Points: The local and nonlocal biophysical effects of historical land use and land cover changes (LULCCs) are investigated using CMIP6 modelsThe multimodel mean shows that, overall, historical LULCCs cool the land surface through nonlocal processesThe intermodel divergence in the total effects of historical LULCCs mainly results from low intermodel agreement on the nonlocal effects [ABSTRACT FROM AUTHOR]

The increased availability of remote sensing products and new legislative agendas are driving a growing focus on farm‐level traceability and monitoring to tackle commodity‐driven deforestation. Here, we use data on land use change in Brazil (1985–2021) from Mapbiomas to demonstrate how analyses of the drivers of deforestation are sensitive to the scale of analysis: while pixel‐ or property‐level analyses identify proximate drivers of deforestation, analyses at larger scales (subnational regions or countries) capture more complex land use dynamics, including indirect land use change. We argue that initiatives which seek to monitor and address commodity‐driven deforestation—such as the European Union's deforestation due‐diligence regulation and the World Business Council on Sustainable Development's Greenhouse Gas Protocol—must be conscient of these wider land use dynamics. Only by measuring progress and defining success at multiple scales can initiatives for sustainable commodity sourcing create the right mix of incentives for addressing deforestation. [ABSTRACT FROM AUTHOR]

Premise: Competition from naturalized species and habitat loss are common threats to native biodiversity and may act synergistically to increase competition for decreasing habitat availability. We use Hawaiian dryland ferns as a model for the interactions between land‐use change and competition from naturalized species in determining habitat availability. Methods: We used fine‐resolution climatic variables and carefully curated occurrence data from herbaria and community science repositories to estimate the distributions of Hawaiian dryland ferns. We quantified the degree to which naturalized ferns tend to occupy areas suitable for native species and mapped the remaining available habitat given land‐use change. Results: Of all native species, Doryopteris angelica had the lowest percentage of occurrences of naturalized species in its suitable area while D. decora had the highest. However, all Doryopteris spp. had a higher percentage overlap, while Pellaea ternifolia had a lower percentage overlap, than expected by chance. Doryopteris decora and D. decipiens had the lowest proportions (<20%) of suitable area covering native habitat. Discussion: Areas characterized by shared environmental preferences of native and naturalized ferns may decrease due to human development and fallowed agricultural lands. Our study demonstrates the value of place‐based application of a recently developed correlative ecological niche modeling approach for conservation risk assessment in a rapidly changing and urbanized island ecosystem. [ABSTRACT FROM AUTHOR]

In pursuing advancing solar energy systems, this research uniquely occupies a position at the intersection of photovoltaic (PV) efficiency, innovative design and aesthetic integration into urban landscapes. This study explores the potential of thin solar cells applied to spherical and hemispherical surfaces and the influence of temperature variations throughout the day. By conducting a comprehensive analysis of voltage–current diagrams, the study deciphers the intricate interconnections of spherical geometries and their response to external thermal impacts, elucidating their subsequent effects on energy conversion efficiency. Moreover, it delved into the dynamics of connecting multiple spherical modules, unveiling their potential to form artistic and utilitarian constructs such as solar trees and architectural embellishments. The findings indicate that while spherical configurations provide superior aesthetics and a power generation profile comparable to solar tracking systems, hemispherical configurations offer a 32% increase in efficiency compared with the spherical configuration and a notable reduction in land footprint. This research underscores the importance of striking a balance between aesthetic appeal, efficiency and land utilization, providing valuable insights for the future of PV technology integration into urban and agricultural landscapes. [ABSTRACT FROM AUTHOR]

Deforestation in the tropics is a critical issue that interacts with global environmental changes, and the mediating role of negative agricultural shocks is ambiguous. We investigate the impact of the massive epidemic of coffee leaf rust (CLR) that affected Mexico from 2012 on deforestation. CLR is a fungal disease that negatively affects coffee production. We exploit the gradual spread of the epidemic across coffee‐growing municipalities and estimate a difference‐in‐differences model. We find that deforestation increased by 32% in CLR‐affected municipalities, but we find no increase in agricultural land. We find evidence of deforestation in cropland area, and our effects are driven by states where rustic coffee systems were predominant. These results suggest that deforestation occurred within coffee cultivation areas and point out the concurrent role of government subsidies and incentives through the PROCAFE program, launched in 2014, that promoted the replacement of traditional coffee trees by CLR‐resistant hybrids. We study the dynamic effects of CLR and exploit the delayed launch of PROCAFE to try to disentangle the impact of the epidemic from that of the policy response. Our results emphasize the vulnerability of agroforestry systems to exogenous shocks and suggest that PROCAFE, as a short‐term response to CLR, contributed to increasing deforestation and accelerating the transition of Mexican traditional coffee landscapes to monoculture. [ABSTRACT FROM AUTHOR]

The Conservation Reserve Program is the largest agricultural land retirement program in the United States, with more enrolled acreage entering the program through a competitive auction called the General Signup than any other component. In this study, we assess the land use impacts of the Conservation Reserve Program by observing the land use decisions of parcels following the 2016 General Signup. We estimate land use impacts using a regression discontinuity design based on the Environmental Benefits Index, the program's selection and ranking mechanism. Our estimates largely rely on the auction design of the General Signup, such that we observe the land use decisions of rejected offers. We also use information on the rental rates of these offers to understand what the program pays to retire land in different uses. We estimate that a marginal acre of land enrolled in the Conservation Reserve Program replaces 0.30 acres in cropland, 0.25 acres in mixed forage, 0.32 acres in grassland, 0.12 acres in idle or fallow land, and 0.01 acres in timberland. We also find that enrollments from newly offered fields are more likely to displace cropland and less likely to displace grassland than returning fields. Consequently, we estimate that new enrollments lead to 47% greater reductions in water‐driven erosion and 12% greater reductions in wind‐driven erosion, compared to fields with prior enrollment. [ABSTRACT FROM AUTHOR]

The urban agglomeration in the middle reaches of the Yangtze river (MYRUA) is the second largest national urban agglomeration in China, with an excellent ecological foundation. As the construction of urban agglomerations accelerated towards both extension and connotation, land prices of various cities rose, and the contradiction in the demand and utilization of land resources became acute. Therefore, exploring the spatiotemporal evolution and driving mechanisms of land green utilization efficiency within MYRUA had positive significance. This article focused on 28 prefecture‐level cities in the MYRUA and measured their urban land green use efficiency (ULGUE) from 2006 to 2018 using the super slack‐based measure model with undesirable output (Super‐SBM‐U). Then, the improved Fixed Malmquist–Luenberger index was developed to improve the accuracy of dynamic efficiency analysis. Further, the internal and external driving factors were explored using the index decomposition and the spatial error model with fixed effects. The results showed that the land use mode of the urban agglomeration in the middle reaches of the Yangtze River was relatively green, but efficiency gaps still existed. Although the green total factor productivity of the whole cluster has improved by 3.30% a year on average, the excessive pursuit of technological innovation has led to the stagnation of urban land management in various cities, and there are numerous inherent contradictions in urban development. But at the same time, feasible economic development directions, industrial upgrading, high‐quality employees, land marketization, and positive environmental behaviors are conducive to the green and sustainable development of ULGUE. This article depicted the internal land use characteristics of the MYRUA from the perspective of spatiotemporal evolution and efficiency, providing a theoretical reference for the green development and coordinated management of urban agglomeration land. Recommendations for Resource Managers: Natural features and socioeconomic heterogeneity lead to a significant discrepancy in the green efficiency of urban land use. Thus, they should be regarded as the scientific basis of policy design for an entire urban agglomeration.Improving regional connections is vital for enhancing the exemplary and radiation effects of core cities on green land use.While the importance of technology has been stressed, the management of related systems should keep pace to provide sustainable forces for the development of urban agglomerations. [ABSTRACT FROM AUTHOR]

There is competition for land between Maasai pastoralists and the park agency in the Serengeti ecosystem. The park agency wants to use the land for wildlife conservation while the pastoralist community wants to use it for livestock grazing. Predatory wildlife kills livestock while herbivorous wildlife competes with livestock for water and grazing. In retaliation, the Maasai hunt predators and grazers to protect their livestock and also to supply the black market for wildlife products. With both the Maasai and animal populations growing, increased conflicts are inevitable. This paper develops a bioeconomic model with three animal species to analyse the optimal combination of pastoral activities and wildlife conservation in the Serengeti ecosystem. Using Pontryagin's maximum principle, the market problem for each agent is optimized and compared to the social planner's outcome. Results show that the market solutions are suboptimal because of negative externalities affecting both agents and inadequate regard to biodiversity conservation values. Mathematical simulations of the bioeconomic model are used to generate a solution in which the Maasai pastoralists and park agency can optimally share the land for their mutual benefit. The policy implication is that the government should establish an independent regulatory institution with a primary mandate of balancing the contested socioeconomic and ecological needs of stakeholders in prime ecosystems such as the Serengeti. Recommendations for Resource Managers: Both pastoralists and park agencies must limit the amount of effort engaged in extensive livestock production and wildlife conservation, as this translates into increased demand for land by either party.In terms of welfare, a combination of antipoaching effort by the parks agency and poaching effort by the pastoralists that exceed optimum levels results in a decrease in social welfare.Increasing extensive livestock production entails greater demand for grazing space, which must be offset by a reduction in protected acreage; this, too, poses a risk of species extinction.Given that the current size of the Serengeti's wildlife stock may be near optimal, the goal of wildlife policy should be to simultaneously reduce the incentives for resource managers to exert excessive antipoaching effort to maintain a healthy wildlife population while also reducing incentives for the pastoralist community to overstock livestock. [ABSTRACT FROM AUTHOR]

Land use change (LUC) alters the global carbon (C) stock, but our estimation of the alteration remains uncertain and is a major impediment to predicting the global C cycle. The uncertainty is partly due to the limited number and geographical bias of observations, and limited exploration of its predictors. Here we generated a comprehensive global database of 5,980 observations from 790 articles. The number of sites evaluated is at least seven times larger than in previous meta‐analyses. Our constrained estimates of different LUC's effects on soil organic C (SOC) and their variations across global climates reveal underestimation/overestimation in previous estimates. Converting forests and grasslands to croplands reduced SOC by 24.5% ± 1.53% (−11.03 ± 1.06 Mg ha−1) and 22.7% ± 1.22% (−8.09 ± 0.67 Mg ha−1), while 28.0% ± 1.56% (4.46 ± 0.42 Mg ha−1) and 33.5% ± 1.68% (5.8 ± 0.38 Mg ha−1) increases, respectively, were obtained in the reverse processes. Converting forests to grasslands decreased SOC by 2.1% ± 1.22% (−1.13 ± 0.44 Mg ha−1), while the reverse process increased SOC by 18.6% ± 1.73% (3.31 ± 0.51 Mg ha−1). Modeled relative importance of 10 drivers of LUC's impact on SOC revealed that higher initial SOC (iSOC) does not solely determine SOC loss in SOC‐negative LUC scenarios as previously proposed. Across four decades, reconverting croplands to forests and grasslands recovered only 49.5% (6.1 ± 0.51 Mg ha−1) and 75.3% (7.0 ± 0.38 Mg ha−1) of the iSOC, respectively, indicating the need for protecting C‐rich ecosystems. Our global data set advances information on LUC's effect on SOC and can be valuable to constrain Earth system models to reliably estimate global SOC stocks and plan climate change mitigation strategies. Plain Language Summary: Land use change (LUC) could increase or decrease the global soil organic carbon (SOC) stock and affect carbon cycling and climate change, but estimating its effect size is the most uncertain aspect of the global carbon cycle. Available estimates vary among studies, most of which often use few observations that do not cover most global regions. To provide more accurate estimates of different LUC types' effects on SOC, we compiled a comprehensive database that contains 5,980 observations across all global regions; and revealed that previous studies have underestimated/overestimated these effects. We modeled the predictors of SOC change and found that previous conclusions that higher initial SOC is the main reason for higher organic carbon loss under negative LUC scenarios were inexact. We show that land use practices aimed at restoring SOC could only recover part of the amount lost during similar time frames; hence, it is important to protect carbon‐rich ecosystems. Our study provides robust estimates of LUC's effect on SOC and provides data sets that can reliably assess and model the global carbon cycle and plan strategies for controlling global climate change. Key Points: Comprehensive global database advances robust estimates of land use change's (LUCs) effect on soil organic carbon (SOC) vital for Earth system modelingHigher initial SOC does not solely control rapid SOC loss in carbon‐negative LUC as often proposedDespite SOC buildup in the past four decades, the amount lost cannot be regained by restoration during similar time frames [ABSTRACT FROM AUTHOR]

Microplastics are widespread pollutants, but few studies have linked field prevalence in organisms to laboratory uptakes. Aquatic filter feeders may be particularly susceptible to microplastic uptake, with the potential for trophic transfer to higher levels, including humans. Here, we surveyed microplastics from a model freshwater shrimp, common caraidina (Caridina nilotica) inhabiting the Crocodile River in South Africa to better understand microplastic uptake rates per individual. We then use functional response analysis (feeding rate as a function of resource density) to quantify uptake rates by shrimps in the laboratory. We found that microplastics were widespread in C. nilotica, with no significant differences in microplastic abundances among sampled sites under varying land uses, with an average abundance of 6.2 particles per individual. The vast majority of microplastics found was fibres (86.1%). Shrimp microplastic accumulation patterns were slightly higher in the laboratory than the field, where shrimp exhibited a hyperbolic Type II functional response model under varying exposure concentrations. Maximum feeding rates of 20 particles were found over a 6 h feeding period, and uptake evidenced at even the lowest laboratory concentrations (~10 particles per mL). These results highlight that microplastic uptake is widespread in field populations and partly density dependent, with field concentrations corroborating uptake rates recorded in the laboratory. Further research is required to elucidate trophic transfer from these taxa and to understand potential physiological impacts. [ABSTRACT FROM AUTHOR]

Aim: Species distribution models (SDMs) are increasingly applied across macroscales using detection‐nondetection data. These models typically assume that a single set of regression coefficients can adequately describe species–environment relationships and/or population trends. However, such relationships often show nonlinear and/or spatially varying patterns that arise from complex interactions with abiotic and biotic processes that operate at different scales. Spatially varying coefficient (SVC) models can readily account for variability in the effects of environmental covariates. Yet, their use in ecology is relatively scarce due to gaps in understanding the inferential benefits that SVC models can provide compared to simpler frameworks. Innovation: Here we demonstrate the inferential benefits of SVC SDMs, with a particular focus on how this approach can be used to generate and test ecological hypotheses regarding the drivers of spatial variability in population trends and species–environment relationships. We illustrate the inferential benefits of SVC SDMs with simulations and two case studies: one that assesses spatially varying trends of 51 forest bird species in the eastern United States over two decades and a second that evaluates spatial variability in the effects of five decades of land cover change on grasshopper sparrow (Ammodramus savannarum) occurrence across the continental United States. Main conclusions: We found strong support for SVC SDMs compared to simpler alternatives in both empirical case studies. Factors operating at fine spatial scales, accounted for by the SVCs, were the primary divers of spatial variability in forest bird occurrence trends. Additionally, SVCs revealed complex species–habitat relationships with grassland and cropland area for grasshopper sparrow, providing nuanced insights into how future land use change may shape its distribution. These applications display the utility of SVC SDMs to help reveal the environmental factors that drive species distributions across both local and broad scales. We conclude by discussing the potential applications of SVC SDMs in ecology and conservation. [ABSTRACT FROM AUTHOR]

Succession is defined as a directional change in species populations, the community, and the ecosystem at a site following a disturbance. Succession is a fundamental concept in ecology as it links different disciplines. An improved understanding of succession is urgently needed in the Anthropocene to predict the widespread effects of global change on succession and ecosystem recovery, but a comprehensive successional framework (CSF) is lacking. A CSF is needed to synthesize results, draw generalizations, advance successional theory, and make improved decisions for ecosystem restoration. We first show that succession is an integral part of socio‐ecological system dynamics and that it is driven by social and ecological factors operating at different spatial scales, ranging from the patch to the globe. We then present a CSF at the local scale (patch and landscape) at which succession takes place and explain the underlying successional processes and mechanisms operating at that scale. The CSF reflects the increasingly broader perspective on succession and includes recent theoretical advances by not only focusing on species replacement but also on ecosystem development, considering succession as part of a socio‐ecological system, and taking the effect of past and current land use, the landscape context, biotic interactions, and feedback loops into account. We discuss how the CSF can be used to integrate and synthesize successional studies, and its implications for ecosystem restoration. [ABSTRACT FROM AUTHOR]

River networks play a crucial role in the global carbon cycle, as relevant sources of carbon dioxide (CO2) to the atmosphere. Advancements in high‐frequency monitoring in aquatic environments have enabled measurement of dissolved CO2 concentration at temporal resolutions essential for studying carbon variability and evasion from these dynamic ecosystems. Here, we describe the adaptation, deployment, and validation of an open‐source and relatively low‐cost in situ pCO2 sensor system for lotic ecosystems, the lotic‐SIPCO2. We tested the lotic‐SIPCO2 in 10 streams that spanned a range of land cover and basin size. Key system adaptations for lotic environments included prevention of biofouling, configuration for variable stage height, and reduction of headspace equilibration time. We then examined which input parameters contribute the most to uncertainty in estimating CO2 emission rates and found scaling factors related to the gas exchange velocity were the most influential when CO2 concentration was significantly above saturation. Near saturation, sensor measurement of pCO2 contributed most to uncertainty in estimating CO2 emissions. We also found high‐frequency measurements of pCO2 were not necessary to accurately estimate median emission rates given the CO2 regimes of our streams, but daily to weekly sampling was sufficient. High‐frequency measurements of pCO2 remain valuable for exploring in‐stream metabolic variability, source partitioning, and storm event dynamics. Our adaptations to the SIPCO2 offer a relatively affordable and robust means of monitoring dissolved CO2 in lotic ecosystems. Our findings demonstrate priorities and related considerations in the design of monitoring projects of dissolved CO2 and CO2 evasion dynamics more broadly. [ABSTRACT FROM AUTHOR]

This study develops an unstructured mesh generation tool for land surface modeling using a multi‐scale hexagon discrete mesh. The tool can automatically determine the required mesh resolution for different regions based on multi‐objective criteria such as elevation, slope, land cover, and land use. The refined unstructured meshes demonstrate significant enhancement in the representation of spatial heterogeneity. The tool is coupled with the Common Land Model (CoLM) to enable land surface simulations using unstructured meshes. Evaluations focused on runoff, river discharge, and inundation indicate improved model performance compared to traditional structured mesh‐based CoLM simulations under the same computational cost constraints. This tool provides new capabilities for more efficiently capturing localized land surface processes and extreme events. Plain Language Summary: The traditional square mesh cells used in land surface models (LSMs) have limitations in capturing the hydrological processes in regions with spatial solid heterogeneity, for example, mountains and forest‐grass transition zones. This study develops a new tool to generate unstructured mesh with flexible cell shapes and sizes. The tool can automatically adjust the mesh resolution based on the various land surface features. Thus, it can represent better spatial differences in elevation, vegetation, soil, etc. For example, it can use finer meshes for mountains and coarser meshes for desert areas. The new unstructured meshes are coupled with an existing LSM called Common Land Model. Model testing shows improved runoff, river discharge, and flooding simulation compared to traditional square mesh models under the same computation cost. Overall, the new unstructured mesh modeling approach enables more efficient and accurate simulation of localized land processes and extreme events, for example, droughts and floods. It has significance for disaster prevention and environmental studies. Key Points: An unstructured mesh generation tool for land surface models can automatically refine resolution based on multi‐objective landscape criteriaCoupling refined unstructured meshes with the Common Land Model (CoLM) model improves local hydrological simulation compared to traditional mesh‐based CoLMThe tool enables more efficient and accurate modeling of localized land surface processes and extreme events such as droughts and floods [ABSTRACT FROM AUTHOR]

Land use change is a major pressure on pollinator abundance, diversity and plant–pollinator interactions. Far less is known about how land‐use alters the structure of plant–pollinator networks and their robustness to plant–pollinator coextinctions.We analysed the structure of plant–pollinator networks sampled in 12 landscapes along an urbanisation and agricultural intensity gradient, from early spring to late summer 2021, and used a stochastic coextinction model to correlate plant–pollinator coextinction risk with network structure (species and network‐level metrics) and landscape context.Networks in intensively managed (i.e., agricultural and urban) landscapes had a lower risk of initiating a coextinction cascade, while networks in less intensively managed landscapes may be less robust. Network structure modulated the frequency and severity of coextinctions and species loss, while the strength of species interactions increased robustness.Urban networks were more species rich and symmetrical due to the high diversity of ornamental plants, while intensively managed agricultural landscapes had smaller, more tightly connected and nested networks.Network structure modulated the frequency of extinctions, which was decreased by greater linkage density, interaction asymmetry and interaction dependence in the networks, while once an extinction occurred, nestedness and linkage density propagated the degree of the coextinction cascade and species loss. At the species level, species strength was inversely correlated with extinction risk, implying that generalist species with a high number of interactions with specialists had the lowest extinction risk.An interplay between land‐use and network structure affects community robustness to coextinctions with implications for pollination services and plant reproduction. Land‐use change or other global change pressures by reorganising species interactions can alter communities and their potential functioning. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Reference conditions are difficult to find in the Anthropocene but essential for effective biodiversity conservation. Aquatic ecosystems in the Andes‐Amazon transition zone of Colombia are now at high risk due to expanded human activities after peace agreements in 2016 ended armed conflict because lands formerly controlled by FARC and other armed groups are now prone to agricultural and urban expansion. Particularly, expanding human land use may reduce fish diversity across the altitudinal gradient, especially in the premontane streams (i.e., <500 m a.s.l.) because lands are more amenable to human use than at greater altitudes. We evaluated fish α‐diversity (measured as species richness, total abundance, and effective species number) and β‐diversity (spatial and temporal) in 12 sites over 8 years bracketing the end of armed conflict. All α‐diversity and β‐diversity analyses were evaluated relative to categorical altitude (< or >500 m) and continuous altitude. Strong differences in fish community structure among sites occurred as a function of altitude. Fish communities exhibit altitudinal biodiversity gradients that are consistent in space and time, and that need to be accounted for conservation and management considerations. Our results provide a reference to identify short‐ and long‐term changes due to impending human land use at a critical moment for the conservation of tropical fish diversity. Similar studies in other areas of the upper Amazon Basin are needed to evaluate effects of subsequent human activities on diversity patterns and our study area to compare to reference conditions reported here. [ABSTRACT FROM AUTHOR]

Ecologists have long documented that the world's biota is spatially organised in regions with boundaries shaped by processes acting on geological and evolutionary timescales. Although growing evidence suggests that historical human impact has been key in how biodiversity is currently assembled, its role as a driver of the geographical organisation of biodiversity remains unclear. Using non‐volant terrestrial mammals we set up a bioregionalization procedure focused on two datasets, one describing the current ranges of terrestrial mammals, and another describing their potential natural ranges in absence of historic anthropogenic land use. We then quantified the relative importance of anthropogenic land use (5000 and 2000 years ago, and present time) to predict the current and natural biogeographical regions across the Earth. In general, past and present human land use were important predictors of current bioregions but did not largely contribute to predict natural bioregions. Past anthropogenic land use seems to have left an imprint on the taxonomic differentiation of some of the largest biogeographical realms, whereas land use at present stands out as a driver of the taxonomic differences between medium‐sized subregions, i.e. within and among continents. Our findings suggest that anthropogenic actions during the last millennia have had a far‐reaching effect on the spatial organisation of the Earth's non‐volant mammals. [ABSTRACT FROM AUTHOR]

Classification with a few samples of training set has been a longstanding issue in the field of polarimetric synthetic aperture radar (PolSAR) image analysis and processing. Aiming at the small number of training samples of the PolSAR image classification task, a novel Self‐Supervised Ensemble Learning Framework (SSELF) is designed. The designed SSELF can automatically extract PolSAR features conducive to PolSAR image classification with a small number of training samples. In addition, it can significantly decrease the dependence of neural network algorithms on large labelled samples of training set. First, utilise the spatial–polarimetric features of PolSAR data perfectly, the EfficientNet‐B0 is presented and utilised as the main section of the Deep Learning (DL) model to extract DL features of PolSAR data. Then, using an optimisation function that constrains the cross‐correlation matrix of various distortions of each sample to the identity matrix, the designed DL model can obtain the effective features of homogeneous samples gathering and heterogeneous samples separating from each other in a self‐supervised manner. Moreover, following the great success of curriculum learning in the area of machine learning, a novel deep curriculum‐learning model is proposed, entitled Deep Curriculum Learning (DCL), to train the DL network in our self‐supervised model. The proposed DCL utilises the entropy‐alpha target decomposition to estimate the degree of complexity of each PolSAR image patch before applying it to the EfficientNet‐B0. Also, an accumulative mini‐batch pacing function is used to introduce more difficult patches to EfficientNet‐B0 in the training process of the designed self‐supervised model. Furthermore, two EL models, feature‐level and view‐level ensemble, are proposed to increase the feature extraction capability and classification result of PolSAR data by jointly using spatial features at different scales and polarimetric information at different bands. In fact, in the proposed feature‐level ensemble strategy, to improve the classification result, the extracted features of the different scales are used as the input of the designed feature fusion algorithm. Therefore, the extracted features are mapped to the new space with lower dimension. In general, in the proposed view‐level ensemble strategy, first, the Mutual Information (MI) between each feature and the other features calculates, and then based‐on the calculated MI, different group of features are selected as various views. Next, the final classification result of the PolSAR image classification is obtained by using the designed majority vote of the result in each view. It should be noted that unlike existing traditional methods, both amplitude and phase information of SAR images to devolve the training process of the proposed model are used. In addition, all of the parameters of the proposed network are developed to a complex domain. In addition, a complex backpropagation algorithm by using the gradient‐based model is used for training the network. Finally, experimental results on three well‐known PolSAR data sets illustrate that the designed SSELF can extract more discriminant features using the designed DL model and can achieve better classification results than the other six novel DL models in terms of small training samples and adequate labelled samples. [ABSTRACT FROM AUTHOR]

The relevance of this study lies in the specific context of the country, where the state plays a crucial role in the development and management of the agricultural sector. With the increasing development of agroindustrial complexes and the need for efficient use of agricultural land, the state has a primary responsibility to ensure optimal utilization of these resources. The purpose of the study is to investigate and compare models of intrafarm land use on the basis of agroindustrial complexes both in the territory of the Republic of Kazakhstan and in the United States as well as in countries of Asia and the European Union. In the furtherance of this goal, the following methods were used: literature review, SWOT analysis, data analysis, case studies and comparative analysis to examine the land use management (LUM) system in Kazakhstan. Specifically, to identify indicators of the economic efficiency of intrafarm land management, the criterion of national economic efficiency was used by comparing costs and benefits in the adoption of various decisions. The study analysed the operation of the land management mechanism in Kazakhstan and proposed innovative solutions on the basis of successful examples from other countries. The manuscript's contribution to the academic dialogue on sustainable land use can provide valuable information and insights for policymakers and scholars interested in improving land management practices. [ABSTRACT FROM AUTHOR]

Due to the nature of nitrogen cycling, policies designed to address water quality concerns have the potential to provide benefits beyond the targeted water quality improvements. For example, actions to protect water quality by reducing nitrate leaching from agriculture also reduce emissions of nitrous oxide, a potent greenhouse gas. These positive effects, which are incidental to the regulation's intended target, are termed "co‐benefits." To quantify the co‐benefits associated with reduced nitrate leaching, we integrate an economic model of farmer decision making with a model of terrestrial nitrogen cycling for the watershed surrounding Lake Mendota, Wisconsin, USA. Our modeling approach provides a framework that links air and water pollutants in an agri‐environmental system and offers a direction for future studies. Our model results highlight the finding that the co‐benefits from nitrous oxide abatement are substantial, and their inclusion increases the benefit–cost ratio of water quality policies. Consideration of these co‐benefits has the potential to reverse the conclusions of benefit–cost analysis in the assessment of current water quality policies. [ABSTRACT FROM AUTHOR]

Bioenergy with carbon capture and storage (BECCS) plays a vital role in most climate change mitigation scenarios, where a solution for sustainable near‐term bioenergy expansion is to grow energy crops such as perennial grasses on recently abandoned cropland. There is a need to combine model‐based insights into theoretical potential and future biomass supply with more fine‐grained sociotechnical analysis to move toward realistic policies and innovation strategies. We combine natural science insights anchored in quantitative bioenergy modeling with qualitative social science anchored in the multi‐level perspective. Using these mixed methods enables a global‐to‐local‐to‐global level assessment of near‐term bioenergy recultivation opportunities for abandoned cropland. Norway is the local case. There are three main findings. First, the ongoing recultivation trends for food/feed production risks making gains in aboveground carbon stocks from natural regrowth on the mapped abandoned cropland over a 30‐year evaluation period almost negligible. Second, delaying a BECCS recultivation of abandoned cropland will make it impossible to reach high‐end mitigation potentials, and an accelerated BECCS recultivation guided by a policy push is needed to ensure stronger mitigation. Third, we unravel several real‐world challenges associated with bioenergy resource and supply modeling. Remote‐sensing techniques alone cannot capture actual land availability for land‐based climate change mitigation strategies. Local‐level sociotechnical conditions are generally found insufficiently supportive to align with the rapid near‐term bioenergy crop expansion found in 2°C scenarios from integrated assessment. The integration of mixed quantitative and qualitative methods is key to better understand the role of BECCS in climate change mitigation. Plain Language Summary: Bioenergy with carbon capture and storage (BECCS) is a key option for mitigating climate change. The idea is to capture the carbon emitted when biomass is converted into fuels or burned for energy production and store it underground. One proposed solution to ramp‐up biomass supply involves growing energy crops, like perennial grasses, on recently abandoned farmland. To make realistic policies and strategies for the future, we need to connect the theoretical potential of BECCS with local context, considering social and technical factors. We combine two approaches: using numbers to model bioenergy and using social science to understand the human and political side. By using a mix of methods, we can assess the potential for a near‐term recultivation of abandoned cropland for bioenergy and BECCS. There were three main findings. First, the combined use of both natural science and social science methods can help us better understand the role of BECCS in climate change mitigation. Second, re‐using abandoned farmland for growing food or animal feed reduces the effectiveness of letting the land naturally recover for fighting climate change. Third a rapid BECCS recultivation of abandoned cropland increases achieved climate change mitigation relative to a delayed BECCS recultivation. Key Points: Mixed quantitative and qualitative methods are key to unravel the role of bioenergy and bioenergy with carbon capture and storage (BECCS) in climate change mitigationOngoing recultivation of abandoned cropland for food production limits aboveground carbon accumulation from natural regrowthPolicies to redirect recultivation toward BECCS are needed to maximize climate change mitigation [ABSTRACT FROM AUTHOR]

Despite their importance, wetland ecosystems protected by the Ramsar Convention are under pressure from climate change and human activities. These drivers are altering water availability in these wetlands, changing water levels or surface water extent, in some cases, beyond historical variability. Attribution of the effects of human and climate activities is usually focused on changes within the wetlands or their upstream surface and groundwater inputs. However, the reliance of wetland water availability on upwind atmospheric moisture supply is less understood. Here, we assess the vulnerability of 40 Ramsar wetlands to precipitation changes caused by land use and hydroclimatic change occurring in their upwind moisture‐supplying regions. We use moisture flows from a Lagrangian tracking model, atmospheric reanalysis data, and historical land use change (LUC) data to assess and quantify these changes. Our analyses show that historical LUC has decreased precipitation and terrestrial moisture recycling in most wetland hydrological basins, decreasing surface water availability (precipitation minus evaporation). The most substantial effects on wetland water availability occurred in the tropic subtropical regions of Central Europe and Asia. Overall, we found wetlands in Central Asia and South America to be the most vulnerable by a combination of LUC‐driven effects on runoff, high terrestrial precipitation recycling, and recent decreases in surface water availability. This study stresses the need to incorporate upwind effects of land use changes in the restoration, management, and conservation of the world's wetlands. Plain Language Summary: Wetlands protected by the Ramsar Convention face threats from climate change and human activities, impacting their water availability and altering wetland functions. While past studies often focused on threats from their immediate surroundings, our research looks into the influence of changes in their upwind atmospheric moisture supply. We evaluate the vulnerability of 40 Ramsar wetland basins to precipitation shifts caused by land use and hydroclimatic changes in upwind regions, using the output of an atmospheric moisture tracking model and historical data. The results indicate that historical land use changes have reduced precipitation and moisture recycling, leading to a decrease in water availability in some wetlands, notably affecting tropical and subtropical regions of Central Europe and Asia. We assess that wetlands in Asia and South America face are vulnerable to a combination of land use‐induced runoff impacts, high precipitation recycling, and declining surface water availability. This study highlights the need to incorporate upwind effects of land use changes in wetland restoration, management, and conservation efforts globally, recognizing their crucial role for effective strategies for wetland protection amidst evolving environmental conditions. Key Points: Land use changes have led to mean annual runoff (P–E) decreases in wetland hydrological basins globallyThe most substantial land use‐related P–E changes occurred in tropical and subtropical wetlands across Asia and South America and in EuropeWe identify eight wetlands in Asia, South America, and Australia as particularly vulnerable to changes in upwind moisture sources [ABSTRACT FROM AUTHOR]

Watershed nutrient management often focuses on actions that reduce the movement of nitrogen (N) and phosphorus (P) from agricultural lands into streams. One area of management focus is the buffer of land adjacent to streams. Wetlands and forests in this buffer can intercept and retain N and P from the landscape. In addition to directly intercepting agricultural nutrients, natural habitats in the buffer can alter stream geomorphology and influence the in‐stream processing and transformation of N and P to less labile and mobile forms. Here, we assess the influence of buffer land cover on in‐stream processing of N and P. We measured nutrient dynamics in the water column and sediments of agricultural streams in the Fox River and Duck Creek watersheds (WI, USA) during the growing season. In these streams, water column processing was low, possibly due to a lack of primary producers in the water column. Water column P processing was weakly associated with wetland land cover in the buffer, but buffer land cover had no clear effect on inorganic N processing. On the other hand, sediments were almost always a source of inorganic P and a sink for inorganic N. Sediment P release was higher in streams with more agricultural land cover in the buffer. Sediments in streams with agricultural land cover in the buffer also removed more nitrate, even after accounting for the greater availability of nitrate in those streams. The buffer land cover conditions we quantified occupy a very small portion of the overall watershed (100 m wide, for 1 km upstream of the study site) but nevertheless appear to influence in‐stream cycling of N and P. For P management, reducing agricultural land cover in buffers is already a priority due to the ability of wetlands and forests to intercept nutrients, but this study suggests there may be some additional benefit due to changes in in‐stream P processing. [ABSTRACT FROM AUTHOR]

The composition of weed floras in Central European fields has shifted creating a novel management issue: new weeds, that is, species that are currently spreading and increasing in impact. In their role as primary decision makers on the ground, farmers' perception of these new weeds plays a pivotal role in collecting information on their occurrence and control. We conducted an online survey to determine if Austrian farmers recognized 15 selected new weed taxa (12 species and 3 genera) from their farm. The 181 surveyed farmers also estimated the required management effort for these species and elicited their current management practices. Additional questions were posed to understand farmers' general perception of changes in the weed flora. We used a generalized linear mixed model to estimate differences in management effort and identify new weeds that merit monitoring and management programs. Two weed genera (Fallopia spp. and Panicum spp.) showed significantly higher than average management effort. The most commonly used management measures were manual removal, herbicide use and crop rotation. A majority of farmers reported changes in the weed flora; over two thirds reported new species and over one third reported new weeds that were difficult to control. In summary, our results suggest that respondents were aware of the challenges posed by new weeds but required more information on management and prevention strategies. [ABSTRACT FROM AUTHOR]

Land use and land cover (LULC) change has been identified as an important driver of emerging mosquito‐borne zoonotic diseases. However, studies are often limited to individual vector species, despite the potential for interspecific variation in vector competency within mosquito assemblages. This variation can affect transmission hazard, particularly in complex multi‐vector disease systems. Here, we used a joint species distribution modeling approach that included mosquito species vector competency for West Nile virus (WNV) as a trait to understand community‐level responses to land cover and predict joint species distributions in Manatee County, Florida. We assembled species presence/absence data across 61 sites and 44 species sampled from 2016 to 2020 and percent land cover within 2500 m of trap locations for five common land cover types. These data were used to investigate patterns in species richness and community‐weighted proportions of WNV‐competent vector species. The results revealed that land cover effects on individual species aligned with known habitat associations: the highest proportions of WNV‐competent species were predicted in less diverse urbanized areas, and species richness increased as urbanized areas decreased. Our findings highlight the value of community‐level analyses to predict joint vector distributions that can inform where greatest transmission hazard may occur. This information can be used by public health agencies, mosquito control, and land managers to plan more effective and optimized prevention and control efforts. [ABSTRACT FROM AUTHOR]

Several efforts have been made to model forest structure and estimate global aboveground biomass (AGB) magnitude and distribution. However, AGB models still show large uncertainties, especially over tropical mountains that are difficult to survey and understudied. Although forest disturbance and land use greatly influence forest structure and AGB accumulation, they are rarely considered in forest structure and AGB models. Including the effect of forest disturbance and land use could improve model performance. In this study, we used Landsat time series analysis and forest inventory data to assess and model the effect of small‐scale disturbance and land use on tropical montane forest structure and AGB. We explored two approaches: abrupt forest change detection, using the algorithm Breaks For Additive Seasonal Trend (BFAST), and gradual vegetation change by calculating the variation of remote sensing vegetation indices over time. We found that tropical montane landscapes are very dynamic and heterogenous. Out of the 284 forest plots analyzed, 27% had abrupt disturbances at least once between 1993 and 2014, and some of them showed abrupt disturbances several times. Forest plots with abrupt disturbances exhibit statistically significant lower basal area, tree height, and AGB than plots without abrupt disturbances. Using linear mixed‐effects models, we found that the number of breakpoints, annual Normalized Difference Vegetation Index SD, and Normalized Difference Water Index minimum values over time were the most informative variables for predicting forest structure, particularly basal area (adjusted R2 = 0.61). These variables are easy to calculate and could add significant power to forest structure and AGB models. In conclusion, incorporating small‐scale disturbance to model forest structure and AGB at regional scales is feasible through the identification of recent abrupt and gradual forest change using remote sensing time series. Including recent forest disturbance variables as predictors in forest structure models can greatly improve biomass predictability and mapping in dynamic landscapes. [ABSTRACT FROM AUTHOR]

For over 40 years, Plant Functional Types (PFTs) have been used to discretize the ∼400,000 species of terrestrial plants into "similar" classes. Within Earth System Models (ESMs), PFTs simplify terrestrial biosphere modeling in combination with soil information and other site characteristics. However, in flux analysis studies, PFT schemes are often implemented as the sole analytical lens to clarify complex behavior. This usage assumes that PFTs adequately enable a mapping between climate inputs and flux outputs. Here, we show that random forest models, trained using aggregated climate and flux measurements from 245 eddy‐covariance sites, cannot accurately predict PFT groupings, regardless of the nature of the PFT scheme. Similarly, PFTs provide negligible benefit when using site climate to predict site flux regimes and vice versa. While use of PFT classifications is convenient, our results suggest they do not aid analytical skill, which has important implications for future terrestrial flux studies. Plain Language Summary: To understand how the land surface behaves, we often divide plants into a small number (20 or less) of "similar" groups, such as evergreen forests, or grasslands, known as Plant Functional Types (PFTs). The idea is that landscapes with similar large‐scale characteristics will behave in the same way. In land surface models, these PFT groups determine how the simulated plants react to the climate in combination with soil information and other characteristics, yet analysis of observations often use PFT groups alone to try to explain variations in results between different experimental sites. We use machine learning to show that while PFTs might be visually compelling, they do not necessarily represent behavior groupings and might actually hide real world behavior if used for analysis. As such, we suggest that future studies instead try to look at more specific site characteristics when trying to explain analysis results. Key Points: Plant Functional Types (PFTs), as often used in land flux studies, are not easily empirically associated with site climate and/or flux regimesA broad selection of alternative vegetation/land cover classifications do not offer greater predictabilityThe disconnect between PFTs and climate/flux regimes has implications for modeling and analysis of terrestrial systems [ABSTRACT FROM AUTHOR]

The dynamics of inland valley wetlands landuse landcover (LULC) changes are of ecological and economical significance hence necessitating up-to-date datasets of resource status. Nalwekomba inland valley wetland is highly agriculturally utilised yet ecologically important wetland threatened with conversion. Historical LULC data sets as bench marks justifying wetland conservation are lacking. Therefore, the spatial-temporal LULC changes in Nalwekomba inland valley wetland were analysed through a combination of remote sensing and GIS, using satellite images of 1990, 2000, 2010 and 2020 as reference years. Results revealed variable dominance of grassland and tree cover for the wetland and its catchment over the years; 32.7% and 35.3% and 30.9% and 29.8%, respectively, for 1990 and 41.4% and 30.4% and 26.3% and 29.1% for 2020. The 30-year analysis revealed increasing area-shifts for cropland and built-up/settlement of 265.7% and 76.2%, respectively, reducing cover for shrubland by 78.31% in the wetland. Similar trend emerged for its catchment. Highest net cover gains and losses identified between 1990 and 2000 were for cropland and tree cover respectively. The observed trend points to the need for landuse planning and landcover management to enhance ecosystems' resilience to support sustainable livelihoods dependent on this ecosystem. [ABSTRACT FROM AUTHOR]

Black Box (Eucalyptus largiflorens F. Muell) is a dominant floodplain tree across the Murray-Darling Basin. At Hattah-Kulkyne National Park (northwest Victoria), historical changes in the hydrological regime and land use have degraded Black Box populations, with the majority of trees in poor health and with limited recruitment. To mitigate this threat, environmental watering has been implemented to improve condition, but successful regeneration has been limited. A 17-month trial (April 2021 to September 2022) was undertaken to evaluate the effectiveness of different management techniques in promoting Black Box regeneration (natural regeneration, seed-scattering, tube stock and browsing control: guarded and unguarded tube stock). At the end of the trial, only four of the initial 63 seedlings remained alive (two guarded tube stock and two natural regeneration). Most seedling death was attributed to browsing (likely kangaroos), which was evident in the first three months, with unguarded plants heavily impacted. No germinants were recorded in the seed—scattering plots. Our findings of high browsing impacts on Black Box seedling survival, corroborates existing data on browsers (abundance levels and management thresholds) and emphasises the importance of incorporating herbivore browsing management in floodplain vegetation management strategies that aim to promote regeneration within Hattah-Kulkyne National Park. [ABSTRACT FROM AUTHOR]

The Renewable Energy Directive (RED II) by the European Union (EU) provides an updated framework for the use of renewable energy in the EU transport sector until 2030, and bans the use of biofuels with a high risk of causing indirect land‐use change in high carbon stock areas (high ILUC‐risk criteria). The only biofuel feedstock affected by this criterion is palm oil. We employ the computable general equilibrium (CGE) model DART‐BIO for a scenario‐based policy analysis and evaluate a phase‐out of palm oil‐based biodiesel, and an additional phase‐out of soy oil‐based biodiesel in the EU. Our results show that the palm phase‐out has only a relatively small impact on global palm fruit production and total crop land use in tropical and subtropical regions, while the soy phase‐out leads to a comparable stronger decrease in global soy production, and a reduction in total cropland use in soy‐producing regions. Both policies lead to increased oilseed production in the EU. Therefore, farmer in Malaysia and Indonesia face a significantly reduced income. While European farmers profit the most, EU firms and households are confronted with higher expenditures. Finally, this study indicates that unilateral demand‐side regulations for a single good in a single sector is not sufficient for effective environmental protection. Enhanced binding sustainability criteria and certification schemes for the use of all vegetable oils in every sector and industry as well as improved protection schemes for sensible forest areas are necessary. [ABSTRACT FROM AUTHOR]

Aim: The sweeping transformation of the biosphere by humans over the last millennia leaves only limited windows into its natural state. Much of the forests that dominated temperate and southern boreal regions have been lost and those that remain typically bear a strong imprint of forestry activities and past land‐use change, which have changed forest age structure and composition. Here, we ask how would the dynamics, structure and function of temperate and boreal forests differ in the absence of forestry and the legacies of land‐use change? Location: Global. Time Period: 2001–2014, integrating over the legacy of disturbance events from 1875 to 2014. Major Taxa Studied: Trees. Methods: We constructed an empirical model of natural disturbance probability as a function of community traits and climate, based on observed disturbance rate and form across 77 protected forest landscapes distributed across three continents. Coupling this within a dynamic vegetation model simulating forest composition and structure, we generated estimates of stand‐replacing disturbance return intervals in the absence of forestry for northern hemisphere temperate and boreal forests. We then applied this model to calculate forest stand age structure and carbon turnover rates. Results: Comparison with observed disturbance rates revealed human activities to have almost halved the median return interval of stand‐replacing disturbances across temperate forest, with more moderate changes in the boreal region. The resulting forests are typically much younger, especially in northern Europe and south‐eastern North America, resulting in a 32% reduction in vegetation carbon turnover time across temperate forests and a 7% reduction for boreal forests. Conclusions: The current northern hemisphere temperate forest age structure is dramatically out of equilibrium with its natural disturbance regimes. Shifts towards more nature‐based approaches to forest policy and management should more explicitly consider the current disturbance surplus, as it substantially impacts carbon dynamics and litter (including deadwood) stocks. [ABSTRACT FROM AUTHOR]

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Rural to urban migration (RUM) is a key component of economic development, but its environmental consequences are not well understood. Here, we study the impacts of RUM on agriculture and land use using household panel data in combination with tree cover data from Uganda. Our results show that the labor loss and the inflow of remittances from RUM lead to a reduction in crop diversity but no shift toward less labor‐intensive crops or crops with a high up‐front investment. In addition to those results at the intensive margin, we find a reduction of cultivated area at the household level, which translates into reduced tree cover loss at the district level. These results suggest an important but nuanced role of RUM for land use change. [ABSTRACT FROM AUTHOR]

Flood risk mapping allows for informed decision making regarding personal and community planning. Resistance to flood risk mapping can be driven by potential decline of property values. This paper explores resistance to flood risk mapping through the lens of climax thinking. Climax thinking is a novel theory guiding explorations of resistance to proposed land use changes. The aim of this study was to understand flood experiences, the presence of resistance to flood risk mapping, and whether climax thinking could help explain this resistance. To address this, surveys were administered to residents in the Nova Scotian towns of Liverpool and Bridgewater. We found that one third of respondents have experienced flooding, yet the majority have not seen a flood risk map, nor were they concerned about the potential impacts of flooding. Only one sixth of respondents exhibited resistance to flood risk mapping because of potential loss to property value. Dimensions of climax thinking were predictive of this resistance, specifically ignorance of an individual's own ability to adapt and inability to recognize the impact of their adaptation decisions on others, which together quadrupled the predictive power of the ordinal regression model. These insights can be applied to support the acceptance of flood risk mapping. Key messages: Surveyed residents of southwestern Nova Scotia exhibited limited resistance to publicly available flood risk mapping.Resistance to publicly available flood risk mapping was associated with perceived loss of property value within our surveyed population.Climax thinking identified drivers of resistance to publicly available flood risk mapping, specifically ignorance regarding ability to adapt and inability to recognize impacts of adaptation decisions on others. [ABSTRACT FROM AUTHOR]

Background: Soil organic C and N data from privately managed pastures in the southeastern United States are relatively scant. Methods: A paired‐farm approach was deployed to determine how a variety of soil health parameters related to nutrient and water cycling might be altered under grazed, botanically diverse perennial pastures compared with annual monoculture croplands in three Major Land Resource Areas of the southeastern United States. Results: Soil stability index averaged 0.64 and 0.91 mm mm−1 under cropland and grazed pasture, respectively, suggesting that pastures had a more stable soil surface that was resistant to erosion and allowed rapid water infiltration. Surface‐soil organic C and N fractions (i.e., total, particulate, and mineralizable fractions at 0–10 cm depth) were greater under pasture than under cropland. Across locations, root‐zone enrichments (0–30 cm depth) of organic C and N fractions were greater under pasture than under cropland. Within locations, root‐zone enrichment of total soil N was greater (p < 0.05) under pasture than under cropland in the Blue Ridge (2.87 vs. 1.10 Mg N ha−1, respectively) and the Piedmont (2.80 vs. 2.10 Mg N ha−1), but not in the Blackland Prairie (2.40 vs. 2.12 Mg N ha−1). Conclusions: This study provides evidence that rotationally grazed, perennial grasslands can store more soil organic C and N and improve soil surface stability conditions compared with neighboring croplands producing commodity feed grains for feedlot finishing. [ABSTRACT FROM AUTHOR]

Aim: Soils harbour a large number of unicellular eukaryotic parasites of metazoans, particularly Apicomplexa. Apicomplexan distribution, their associations with hosts, and impacts of human‐dominated land use are little studied. We aimed to fill this gap by a biodiversity survey across large spatial scales. Location: China. Time period: May to September 2021. Major taxa studied: Soil Apicomplexa and Metazoa Methods: We used metabarcoding to investigate the biogeography of and links between Apicomplexa and soil Metazoa in three human‐dominated ecosystem types (farmlands, residential areas and parks) and more natural forest ecosystems across subtropical, warm‐temperate and mid‐temperate climatic regions in China. Results: Human‐dominated land use indirectly reduced apicomplexan taxon richness by reducing metazoan taxon richness. However, the richness reduction of parasites was generally more pronounced in subtropical and mid‐temperate regions than in the warm‐temperate region. Mechanisms driving the richness reduction of parasites also differed between climatic regions, with the reduction in the subtropical region less related to the decrease in metazoan richness than in the mid‐temperate region. Human‐dominated ecosystems reduced richness associations between parasites and Metazoa, and this disrupted the cascading effect of climatic factors from metazoan to parasite communities. Moreover, co‐occurrence analyses showed that metazoan taxa more abundant in human‐dominated land‐use systems with dryer and hotter conditions were less likely associated with apicomplexan taxa. Main conclusions: We conclude that decreased host taxon richness is an important, but not the only driver of reduced parasite taxon richness in soil systems. Apicomplexan richness was largely decoupled from metazoan richness in human‐dominated ecosystems, which emphasizes the important role of human activities in rewiring fundamental ecological patterns with global change. Overall, the results advance our understanding of principle characteristics of and interactions in soil communities, and their response to human activities, especially agriculture and urbanization. [ABSTRACT FROM AUTHOR]

1.Conserving species' ability to traverse the landscape is vital for maintaining biodiversity in the face of global change. Connectivity conservation requires identifying important pathways for species' movements and aligning societal support for conservation of those pathways. Contemporary connectivity analyses emphasize the impacts of topography, vegetation and human footprint on species' movements; but largely ignore the role that attitudes, economics and institutions play in practitioners' ability to conserve those movements.2.We introduce implementation resistance as an analogue of biophysical resistance that combines social, economic and institutional factors that promote or impede connectivity conservation. We demonstrate the utility of integrating implementation resistance as a means of choosing between competing connectivity conservation strategies using wolves in Colorado (USA) as a case study.3.Our analysis of five potential corridor locations based on biophysical costs revealed substantial differences in the social costs associated with implementing each corridor despite relatively minimal differences in the biophysical costs.4.Our comparison of hypothetical interventions to reduce implementation resistance illustrates that interventions that reduce conflicts between land use and wolves may substantially reduce overall resistance, those reductions are not as well aligned with connectivity priorities as those resulting from changes in land management agency policy.5.Our results highlight the need to design conservation interventions that fit both the social and ecological landscape and provide a framework for developing robust, interdisciplinary methods that facilitate implementable connectivity conservation. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]