Grasslands support vital ecosystem services but face growing threats from climate change and human pressures. Earth observations offer useful information for monitoring vegetation degradation across broad scales, yet traditional ground-to-satellite models often suffer from plot-to-pixel mismatches and limited field coverage. To address these challenges, we developed a two-step remote sensing framework in the central Mongolian steppe that links field measurements to unoccupied aerial vehicle (UAV) data and UAV data to Sentinel-2 imagery. Our study asked: (1) to what extent UAV data can accurately predict vegetation structure (cover and height), (2) whether a two-step modeling approach improves landscape-scale prediction accuracy relative to single-step ground-to-satellite models, and (3) how applicable the two-step approach remains when transferred across space or time. UAV models predicted vegetation cover and height with mean R-2 values of 0.64 and 0.56, respectively. Incorporating UAV-derived predictions into satellite models substantially improved performance, with R-2 values of 0.90 for cover and 0.82 for height. Stratified cross-validation (CV) produced lower error estimates but applied to only similar to 60% of the study area based on the Area of Applicability (AOA). In contrast, spatial leave-site-outs (LSO) CV produced higher errors but remained applicable to similar to 90% of the region and was stable across years. These results show that the clustered nature of two-step training data makes LSO CV a more rigorous and representative evaluation strategy. More broadly, our framework demonstrates how multiscale validation and AOA-based assessment support transferable models capable of detecting emerging patterns of vegetation structural change to inform timely, targeted conservation actions.

Shifts in precipitation regimes due to climate change are significantly impacting dryland ecosystems, including vegetation composition and structure. Unoccupied aerial vehicles (UAVs) are widely used to monitor vegetation, but whether models built to predict changes in these characteristics are robust under extreme precipitation regimes is unclear. We aimed to predict key vegetation characteristics under three precipitation regimes (ambient, drought, and water addition) and assess model performance across these moisture conditions. We also evaluated how models built under ambient conditions predicted vegetation characteristics under extreme precipitation regimes. UAV surveys were conducted at five sites subject to long-term precipitation manipulation along an elevation gradient in northern Arizona, United States (U.S.). Twenty-one vegetation indices and point cloud data from the UAV imagery were used to develop models to predict vegetation structure and composition characteristics. Model performance and transferability were assessed via error and directional bias within each treatment (i.e., in situ) and from ambient to precipitation treatments (i.e., model transfer). UAV-based models accurately measured vegetation characteristics across all regimes, but maximum height showed significantly higher error under drought conditions. Models developed under ambient precipitation and applied to extreme precipitation treatments exhibited significant differences in the error and directional bias, indicating they may not be suitable under climate change. UAV-based models are effective for monitoring vegetation characteristics but may lose accuracy under extreme precipitation regimes expected under climate change. This study emphasizes the need to improve model transferability and suggests refining landscape monitoring approaches to consider extreme changes in precipitation and associated vegetation responses.

The problem of insect pollinator declines and pollination scarcity is impacting food production and ecosystem integrity worldwide. The term “pollinator commons” has often been invoked in existing literature, but there is little actual evidence of collective action to manage pollinators, pollination services or foraging resources. This may be due to the availability of a technical fix to the problem of pollination scarcity in some places, or the purported lack of awareness and undervaluation of pollination services. Given the increasing extent of the problem, there may be some conditions under which collective governance of the pollinator commons could emerge. We predict that collective action to manage a pollinator commons is more likely to emerge among farmers: (a) whose farms are small, and livelihoods are dependent on high-value crops for which wild pollination services cannot be easily substituted; (b) whose neighbors are similarly dependent on pollinator-dependent crops; and (c) who are able to make reasonable cost-benefit determinations based on information about other farmers and pollinator status. Geographers are particularly well-positioned with the theoretical and methodological tools to engage with this important, yet under-explored system to understand the potential for collective action to manage pollinators as a common pool resource.

Apples are a highly pollinator-dependent crop that require a minimum number of accumulated chill hours to break dormancy in preparation for bud development and blooming. In the Indian Western Himalayas, apple production is shifting to higher elevations to counteract climate change-associated temperature increases. But it is unclear if and to what extent pollinators are able to match these shifts, or how these altitudinal shifts impact pollinator contribution to apple production. To address these knowledge gaps, we manipulated pollination conditions for apple blossom clusters in 13 orchards distributed along an elevational gradient (1680-2360 m) and measured early fruit set. Fruit set was significantly impacted by pollination treatment and elevation, and in some cases by their interaction. Averaged across elevations, fruit set in the pollinator exclusion treatment was only 6% of that observed under open pollination conditions, but fruit set in the open pollination treatment decreased markedly with elevation. Predicted pollinator contribution to fruit set also decreased with elevation, from 0.96 at the lowest modeled elevation to 0.76 at the highest modeled elevation. Fruit set was enhanced by supplementary hand pollination, demonstrating pollination limitation. We found that pollination deficit increased with elevation, ranging from 0.05 at the lowest modeled elevation (1650 m) to 0.24 at the highest modeled elevation (2400 m). Our findings demonstrate that at least some of the productivity gains realized with increased availability of chilling units at higher elevations might be compromised by pollination limitation. Future studies to determine more clearly the extent and underlying causes of elevation effects on pollination deficits are needed.

Globally, rangelands face interacting pressures from climate, land-use, socio-economic and political changes, all of which threaten herder livelihoods and grassland health. Given these dynamics, it is often unclear which policies would best support sustainable land use and livelihoods in the future. There are multiple theories for how tenure, rules, social relations and environmental variability intersect to influence pastoral resource governance, but these have largely been developed based on empirical data from specific social and environmental contexts. Few studies have attempted to evaluate empirically how the factors driving pastoral management decisions might vary across a social-ecological gradient. In this work we attempt to reconcile the current diversity of theories around pastoral resource governance with an empirical dataset on household herd and pasture management decisions in Mongolia, where there is ongoing debate over proposed rangeland policies, including formalization of land tenure. We assess the relationship between theorized predictors of herder behavior (i.e. formal rights, formal rules, social capital, and environmental variability), and household-level management decisions about pastoral mobility and storage. We compare our findings from a survey of 760 households across four ecozones to predictions from pastoral resource governance theories to assess which theories best match the complex realities on the ground. We observed a continuum of de facto pastoral governance regimes that roughly map onto a social-ecological gradient defined by (i) resource variability and predictability, and (ii) the relative prevalence of formal rule-based vs. implicit norm-based governance. We find that rules, social capital, and forage availability are the strongest predictors of whether a household will reserve forage, with consistent effects across ecological zones. In contrast, social ties and environmental conditions most strongly predict mobility practices. While most households reserved pastures regardless of tenure status, those households who do not reserve pastures are more likely to lack formal use rights. Our findings reinforce the importance of avoiding “one size fits all” rangeland governance policies. We demonstrate that herders make decisions in response to environmental productivity and variability over space and time, and that social ties and mobility are critical for maintaining access to forage. This may explain why many herders remain skeptical of formal pasture tenure, which could restrict this flexibility. Policies that ensure herders’ collective rights to pasture through large-scale zoning rather than tenure could potentially achieve both secure pasture rights and maximum flexibility.

Soil microbe diversity plays a key role in dryland ecosystem function under global climate change, yet little is known about how plant-soil microbe relationships respond to climate change. Altered precipitation patterns strongly shape plant community composition in deserts and steppes, but little research has demonstrated whether plant biodiversity attributes mediate the response of soil microbial diversity to long- and short-term precipitation changes. Here we used a comparative study to explore how altered precipitation along the natural and experimental gradients affected associations of soil bacterial and fungal diversity with plant biodiversity attributes (species, functional and phylogenetic diversity) and soil properties in desert-shrub and steppe-grass communities. We found that along both gradients, increasing precipitation increased soil bacterial and fungal richness in the desert and soil fungal richness in the steppe. Soil bacterial richness in the steppe was also increased by increasing precipitation in the experiment but was decreased along the natural gradient. Plant biodiversity and soil properties explained the variations in soil bacterial and fungal richness from 43 % to 96 % along the natural gradient and from 19 to 46 % in the experiment. Overall, precipitation effects on soil bacterial or fungal richness were mediated by plant biodiversity attributes (species richness and plant height) or soil properties (soil water content) along the natural gradient but were mediated by plant biodiversity attributes (functional or phylogenetic diversity) in the experiment. These results suggest that different mechanisms are responsible for the responses of soil bacterial and fungal diversity to long- and short-term precipitation changes. Long- and short-term precipitation changes may modify plant biodiversity attribute effects on soil microbial diversity in deserts and steppes, highlighting the importance of precipitation changes in shaping relationships between plant and soil microbial diversity in water-limited areas.

Remittances-funds sent by migrants to family and friends back home-are an important source of global monetary flows, and they have implications for the maintenance and transformation of land systems. A number of published reviews have synthesized work on a variety of aspects of remittances (e.g., rural livelihoods, disasters, and economic development). To our knowledge, there are no reviews of work investigating the linkages between remittances and land change, broadly understood. This knowledge gap is important to address because researchers have recognized that remittances flows are a mechanism that helps to explain how migration can affect land change. Thus, understanding the specific roles remit-tances play in land system changes should help to clarify the multiple processes associated with migra-tion and their independent and interactive effects. To address the state of knowledge about the connection between remittances and land systems, this paper conducts a systematic review. Our review of 51 journal articles finds that the linkages uncovered were commonly subtle and/or indirect. Very few studies looked at the direct connections between receipt of remittances and quantitative changes in land. Most commonly, the relationship between remittances and land change was found to occur through pathways from labor migration to household income to agricultural development and productivity. We find four non-exclusive pathways through which households spend remittances with consequent changes to land systems: (1) agricultural crops and livestock, (2) agricultural labor and technologies, (3) land purchases, and (4) non-agricultural purchases and consumables. In the papers reviewed, these expenditures are linked to various land system change outcomes, including land use change, soil degra-dation, pasture degradation, afforestation/deforestation/degradation, agricultural intensification/extensi fication/diversification, and no impact. These findings suggest four avenues for future research. One ave-nue is the use of the theoretical lens of telecoupling to understand how remittances may produce widerscale changes in land systems. A second avenue is further examination of the impacts of shocks and dis-turbances to remittance flows on land change both in migrant sending and in remittance receiving areas. A third avenue is scholarship that examines the extent that household uses of remittances have a "ripple effect" on land uses in nearby interlinked systems. A fourth avenue for future work is the use of spatially explicit modeling that leverages land cover and land use data based on imagery and other geospatial information.(c) 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).

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High-resolution Corona imagery acquired by the United States through spy missions in the 1960s presents an opportunity to gain critical insight into historic land cover conditions and expand the timeline of available data for land cover change analyses, particularly in regions such as Northern China where data from that era are scarce. Corona imagery requires time-intensive pre-processing, and the existing literature lacks the necessary detail required to replicate these processes easily. This is particularly true in landscapes where dynamic physical processes, such as aeolian desertification, reshape topography over time or regions with few persistent features for use in geo-referencing. In this study, we present a workflow for georeferencing Corona imagery in a highly desertified landscape that contained mobile dunes, shifting vegetation cover, and a few reference points. We geo-referenced four Corona images from Inner Mongolia, China using uniquely derived ground control points and Landsat TM imagery with an overall accuracy of 11.77 m, and the workflow is documented in sufficient detail for replication in similar environments.

Drought events induced by global climate change strongly modify ecosystem structure and function in grasslands. Higher plant biodiversity can enhance ecosystem resistance to drought; however, the potential effects of drought on the relationships between above-ground productivity (ANPP) and biodiversity along a natural aridity gradient remain poorly understood. Here, we studied the effects of experimental drought on plant community structure and ANPP during the two different dry years (2015 and 2017) spanning three temperate steppe sites with low-, medium- and high-aridity levels. We also examined the effects of drought and aridity on the associations of plant species (richness and abundance), functional (community-weighted trait means and functional dispersion) and phylogenetic diversity (evolutionary lineages) with ANPP. A structural equation modelling (SEM) was used to elucidate how the drought affected ANPP by altering biodiversity attributes. We found that experimental drought shaped the biodiversity-ANPP relationships, and the biodiversity-ANPP relationships differed among three sites. At the low-aridity site, ANPP was correlated with plant functional traits, whereas ANPP was correlated with functional dispersion, species and phylogenetic diversity at the medium-aridity site. At the high-aridity site, ANPP was correlated with species richness, functional traits and phylogenetic diversity. Compared with 2015, natural drought in 2017 strengthened the associations of species diversity, functional dispersion, leaf dry matter content and leaf nitrogen content with ANPP across three sites. SEM further showed that both experimental and natural drought directly decreased ANPP and indirectly decreased ANPP by reducing community-weighted mean of plant height. Synthesis. These results suggest that the aridity increase or drought occurrence is likely to induce the shifts in the associations of ANPP with species and functional diversity, highlighting the important role of water availability or precipitation conditions in regulating the biodiversity-ANPP relationships in temperate steppes. Overall, functional traits related to plant size play a crucial role in modulating the response of productivity to drought across three steppe sites. Thus, to buffer the negative effects of drought on steppe ANPP should pay attention to protect the species with large plant size. Read the free Plain Language Summary for this article on the Journal blog.

Spatial heterogeneity plays a crucial role in affecting the ecologial processes in natural ecosystems, yet how spatial heterogeneity of herbaceous vegetation in desert-grassland transitional zone varies with increased spatial scale are still poorly known. We measured plant height, density, species richness and aboveground plant biomass (AGB) at the small (0.25 × 0.5 km), medium (0.5 × 0.5 km) and large (0.5 × 1 km) spatial scales in two adjacent plant communities (shrub- and grass-dominated) in desert steppe, Inner Mongolia. We used the geostatistical methods to examine the magnitude and degree of spatial heterogeneity of herbaceous vegetation characteristics with the increasing scale in both two plant communities. We found that compared to grass-dominated community, shrub-dominated community had the lower plant height and density at the large scale, the higher AGB at the small or medium scale, and the lower species richness at all three scales. Plant height, density and AGB in grass-dominated community were higher at the large scale than at the small scale, but they did not differ across three scales in shrub-dominated community. Species richness in both two communities were higher at the small scale than at the medium or large scale. All vegetation characteristics at three scales had the higher spatial heterogeneity in shrub- than in grass-dominated community. Spatial heterogeneity of all vegetation characteristics in shrub-dominated community decreased from the small to the large scale, while their spatial heterogeneity of plant height, density and species richness in grass-dominated community increased with the increasing scale. Our study highlights that shrub encroachment can simplify community composition and amplify spatial heterogeneity of herbaceous vegetation at multiple scales. Scale effects on spatial heterogeneity of herbaceous vegetation in desert steppe are dependent on plant community dominated by shrub or grass.