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Monitoring ecosystems at regional or continental scales is paramount for biodiversity conservation, climate change mitigation, and sustainable land management. Effective monitoring requires satellite imagery with both high spatial resolution and high temporal resolution. However, there is currently no single, freely available data source that fulfills these needs. A seamless fusion of data from the Sentinel-3 and Sentinel-2 optical sensors could meet these monitoring requirements as Sentinel-2 observes at the required spatial resolution (10 m) while Sentinel-3 observes at the required temporal resolution (daily). We introduce the Efficient Fusion Algorithm across Spatio-Temporal scales (EFAST), which interpolates Sentinel-2 data into smooth time series (both spatially and temporally). This interpolation is informed by Sentinel-3's temporal profile such that the phenological changes occurring between two Sentinel-2 acquisitions at a 10 m resolution are assumed to mirror those observed at Sentinel-3's resolution. The EFAST consists of a weighted sum of Sentinel-2 images (weighted by a distance-to-clouds score) coupled with a phenological correction derived from Sentinel-3. We validate the capacity of our method to reconstruct the phenological profile at a 10 m resolution over one rangeland area and one irrigated cropland area. The EFAST outperforms classical interpolation techniques over both rangeland (−72% in the mean absolute error, MAE) and agricultural areas (−43% MAE); it presents a performance comparable to the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) (+5% MAE in both test areas) while being 140 times faster. The computational efficiency of our approach and its temporal smoothing enable the creation of seamless and high-resolution phenology products on a regional to continental scale. [ABSTRACT FROM AUTHOR]

Trophic rewilding is gaining rapid momentum as a means of restoration across the world. Advances in research are elucidating the wide‐ranging effects of trophic rewilding and megafauna re‐establishment on ecosystem properties and processes including resilience, nutrient cycling, carbon sequestration, productivity and plant richness.A substantial gap remains in trophic rewilding research on how rewilding affects the frequency and expression of plant functional traits, a key hypothesised avenue by which megafauna can affect biodiversity and ecosystem processes. Yet, there is extensive literature examining the effects of mammal herbivory and exclusion on plant traits from which we may infer potential effects of megafauna reintroductions.Here, we synthesise the literature to show the multifaceted ways that plant functional composition responds to mammalian herbivory and explore how these responses are modulated by the density and identity of herbivores as well as resource availability, ecosystem productivity and historical contingency. We further explore these interactions in a quantitative analysis on European plant species. In addition, we link these broad patterns between mammal herbivory and traits to literature on plant invasions to predict how trophic rewilding may be able to reduce invasive plant dominance, as ecosystems around the world are transitioning towards novel states, occupied by a mix of native and introduced species.Expanding current research on herbivore effects (and their implications for trophic rewilding) beyond plant species richness and towards measurable functional traits can help assess and quantify processes that were not previously possible. Trait approaches can help to test mechanistic hypotheses on the top‐down impacts of large herbivores on plant communities to reveal links between trophic rewilding and ecosystem processes and properties.Synthesis. Given the rapid, much‐needed expansion of restoration and rewilding activities across the world, trait‐based ecology offers a pathway to generalisable predictions of the ecosystem impacts of rewilding, particularly in the context of both the unique landscape processes associated with rewilding (e.g. landscape scale spatiotemporal variability, dispersal) and of widely emerging novel ecosystems. [ABSTRACT FROM AUTHOR]

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Mapping land use and land cover (LULC) using remote sensing is fundamental to environmental monitoring, spatial planning and characterising drivers of change in landscapes. We develop a new, general and versatile approach for mapping LULC in landscapes with relatively gradual transition between LULC categories such as African savannas. The approach integrates a well-tested hierarchical classification system with the computationally efficient random forest (RF) classifier and produces detailed, accurate and consistent classification of structural vegetation heterogeneity and density and anthropogenic land use. We use Landsat 8 OLI imagery to illustrate this approach for the Extended Greater Masai Mara Ecosystem (EGMME) in southwestern Kenya. We stratified the landscape into eight relatively homogeneous zones, systematically inspected the imagery and randomly allocated 1,697 training sites, 556 of which were ground-truthed, proportionately to the area of each zone. We directly assessed the accuracy of the visually classified image. Accuracy was high and averaged 88.1% (80.5%-91.7%) across all the zones and 89.1% (50%-100%) across all the classes. We applied the RF classifier to randomly selected samples from the original training dataset, separately for each zone and the EGMME. We evaluated the overall and class-specific accuracy and computational efficiency using the Out-of-Bag (OOB) error. Overall accuracy (79.3%-97.4%) varied across zones but was higher whereas the class-specific accuracy (25.4%-98.1%) was lower than that for the EGMME (80.2%). The hierarchical classifier identified 35 LULC classes which we aggregated into 18 intermediate mosaics and further into five more general categories. The open grassed shrubland (21.8%), sparse shrubbed grassland (10.4%) and small-scale cultivation (13.3%) dominated at the detailed level, grassed shrubland (31.9%) and shrubbed grassland (28.9%) at the intermediate level, and grassland (35.7%), shrubland (35.3%) and woodland (12.5%) at the general level. Our granular LULC map for the EGMME is sufficiently accurate for important practical purposes such as land use spatial planning, habitat suitability assessment and temporal change detection. The extensive ground-truthing data, sample site photos and classified maps can contribute to wider validation efforts at regional to global scales. [ABSTRACT FROM AUTHOR]

Questions: Does the non‐native evergreen Chinese windmill palm (Trachycarpus fortunei) affect native plant community and forest regeneration in deciduous forests? Are effects modulated by soil moisture? What are the implications for forest management and nature conservation? Location: Broadleaved deciduous low‐elevation forests on the southern slope of the Alps across the Swiss–Italian border region. Methods: We compared the native herbaceous and woody plant composition, species richness, Shannon diversity and abundance at ten deciduous forest sites on two moisture conditions (six mesic–moist sites and four mesic–dry sites). Each site consisted of three plots measuring 400 m2 along a gradient of T. fortunei presence, ranging from "dominant", to "present but not dominant" to "absent". Results: In mesic–moist forests with high densities of T. fortunei, species richness and Shannon diversity of native plants and recruiting woody species in the herb and shrub layers were significantly reduced compared to similar sites where T. fortunei is absent or not dominant. However, in mesic–dry forests these variables did not differ between palm‐invaded and uninvaded plots. The abundance of recruiting woody individuals did not differ between plots invaded by palms and uninvaded control plots in either forest type. Conclusions: We expect detrimental consequences for plant diversity in mesic–moist alluvial forests with high T. fortunei densities and few detrimental consequences in the more widespread non‐alluvial forests. We recommend multifaceted management, including targeted eradication in alluvial forests identified as hotspots of native plant diversity, accompanied by hands‐off management of T. fortunei in non‐alluvial forests, recognizing the ongoing and inevitable "laurophyllisation"; a biome shift toward mixed‐evergreen forest that may increase ecosystem climate resilience under ongoing climatic warming. [ABSTRACT FROM AUTHOR]

Climate change will cause substantial vegetation shifts across the world. Africa may face varying dynamics such as tree decline, savannization, and woody encroachment due to rising temperatures and rainfall changes. This study examines the potential effects of climate change on Kenyan vegetation and vegetation shifts for 2050 and 2100, employing a statistical model to predict vegetation state as driven by environmental variables, including temperature, soil moisture, livestock density, and topography. We evaluate the model by hindcasting it from 2020 to 2000 and then project future vegetation states for 2050 and 2100 under SSP 2–4.5 and SSP 5–8.5. In response to moderate emissions, a notable increase in arid-associated shrubland vegetation (53–58%) is forecasted, leading to the expansion of drylands at the expense of savannas, grasslands, and forests. Under high-emission scenarios, savannas are forecasted to expand (52–65%) at the expense of forested areas. Overall, dense forest cover declines across scenarios, affecting protected areas by promoting increased savanna cover and reducing forest area (40% to 50%). These projected shifts in major vegetation types would likely alter ecosystem functioning and associated services, impacting pastoralists and wildlife and raising biodiversity concerns. Protected areas in Kenya could lose 50% of their forests, highlighting the urgency of climate change mitigation. These findings offer a crucial foundation for future research and action on Kenya's vegetation. [ABSTRACT FROM AUTHOR]

African wildlife populations are declining at an alarming rate. To stop further population declines and restore ecosystems, more areas for wildlife are needed. Community‐based conservation with wildlife‐livestock coexistence in the vast rangelands of Africa presents a major opportunity. However, the efficacy of wildlife conservation in mixed land‐use areas remains an outstanding question. To assess the ecological outcomes of land‐sharing between regulated livestock herds and wildlife populations in African savannas, we test how rotational cattle grazing affects spatiotemporal dynamics of 15 large herbivore species in the Maasai Mara, Kenya.First, we tested how wild herbivore distributions across the Greater Mara Ecosystem (the Mara, ~2600 km2) are related to cattle density and environmental variables using 584,561 observations of wild herbivores (ecosystem scale). In a second analysis, we tested how rotational cattle grazing affects wild herbivore distributions in a 300 km2 subsection of the Mara using 30,583 observations (landscape scale). Finally, we tested how functional traits of wild herbivores affect species‐level spatiotemporal responses to cattle grazing.At the ecosystem scale, the presence of five wild herbivore species was positively correlated with cattle density, while cattle effects on wild herbivore abundances were species‐dependent with both increases and decreases. At the landscape scale, rotational cattle grazing strongly impacted the spatiotemporal habitat selection of wild herbivores, resulting in distinct lag periods with which different species are attracted to areas previously grazed by cattle. These lag periods were linked to functional traits, with body mass and herd size explaining 35% of the interspecific differences. Small to medium‐sized herbivores with large herds select areas recently grazed by cattle, whereas large species with large herd sizes and small species with small herd sizes avoid recently grazed areas.Synthesis and applications: Our results revealed that the effect of cattle on wild herbivores varies considerably among species, suggesting that cattle‐wildlife interactions range from facilitation to competition. To maintain species that strongly avoid cattle, designated livestock‐free zones remain essential, also in rotational grazing systems. Rotational grazing systems with regulated livestock densities present an important opportunity to better manage wildlife‐livestock coexistence and thus improve wildlife conservation in African rangelands. [ABSTRACT FROM AUTHOR]

Ecological processes and biodiversity patterns are strongly affected by how animals move through the landscape. However, it remains challenging to predict animal movement and space use. Here we present our new r package enerscape to quantify and predict animal movement in real landscapes based on energy expenditure.enerscape integrates a general locomotory model for terrestrial animals with GIS tools in order to map energy costs of movement in a given environment, resulting in energy landscapes that reflect how energy expenditures may shape habitat use. enerscape only requires topographic data (elevation) and the body mass of the studied animal. To illustrate the potential of enerscape, we analyse the energy landscape for the Marsican bear (Ursus arctos marsicanus) in a protected area in central Italy in order to identify least‐cost paths and high‐connectivity areas with low energy costs of travel.enerscape allowed us to identify travel routes for the bear that minimize energy costs of movement and regions that have high landscape connectivity based on movement efficiency, highlighting potential corridors. It also identifies areas where high energy costs may prevent movement and dispersal, potentially exacerbating human–wildlife conflicts in the park. A major strength of enerscape is that it requires only widely available topographic and body size data. As such, enerscape permits a first cost‐effective way to estimate landscape use and movement corridors even when telemetry data are not readily available, such as for the example with the bear.enerscape is built in a modular way and other movement modes and ecosystem types can be implemented when appropriate locomotory models are available. In summary, enerscape is a new general tool that quantifies, using minimal and widely available data, the energy costs of moving through a landscape. This can clarify how and why animals move in real landscapes and inform practical conservation and restoration decisions. [ABSTRACT FROM AUTHOR]

Defaunation is a global threat to biodiversity that can be counteracted through trophic rewilding, a restoration strategy that promotes self-regulating ecosystems through active reintroductions or passive management. In order to estimate success in restoration initiatives, progress of the rewilding projects is measured and monitored. However, a spatially explicit understanding of rewilding and rewilding potential in a rewilding site has been absent so far. We present a novel approach for monitoring rewilding progress that focuses on a spatially explicit estimate of progress and ecological integrity within rewilding initiatives. This framework uses habitat classification of the site and tracking data of the reintroduced animals, to model their habitat selection. Through this we measure and map realized and potential rewilding. We operationalize the framework in an ongoing rewilding project in the Iberá Wetlands, Corrientes, Argentina. The majority of areas (76%) predicted to be occupied by reintroduced fauna were only predicted to be selected by one species. Of the four species in the rewilding project, only the giant anteater (Myrmecophaga tridactyla) filled the majority of its potential distribution, whereas pampas deer (Ozotoceros bezoarticus), collared peccary (Pecari tajacu) and lowland tapir (Tapirus terrestris) filled less than 23% of theirs. After rewilding we found a 10% increase in the proportion of the study area with high ecological integrity. Through this case study, we showed that this framework can be used to assess the spatial progress of a rewilding site. By incorporating wildlife tracking and satellite-based remote sensing, we are integrating a spatial component to monitoring of rewilding projects that should lead to more detailed understanding of the progress of rewilding. Applying this framework would facilitate decision-making for practitioners and inform species management plans. [ABSTRACT FROM AUTHOR]

Aim: Theory suggests that increasing productivity and climate stability towards the tropics favours specialization, thus contributing to the latitudinal richness gradient. A positive relationship between species richness and specialization should therefore emerge as a fundamental biogeographical pattern. However, land‐use and climate changes disproportionally increase the local extirpation risk for specialists, potentially weakening the relationship between richness and specialization. Here, we quantify empirically the richness–specialization prediction and test how 50 years of climate and land‐use change has affected the richness–specialization relationship. Location: USA. Time period: 1966–2015. Major taxa studied: Birds. Methods: We used the North American Breeding Bird Survey to quantify bird community richness and specialization to habitat and climate. We (a) quantify temporal change in the slope of the richness–specialization relationship, using a generalized mixed model; (b) assess how this change translates spatially, using generalized additive models; and (c) attribute spatio‐temporal change in the richness–specialization relationship to land use, climate and topographic drivers. Results: We found evidence for a positive but weak richness–specialization relationship in bird communities that greatly weakened over time. Given that specialization was not the main driver of richness, this relationship did not translate spatially into a linear spatial covariation between richness and specialization. Instead, the spatial covariation in richness and specialization followed a unimodal pattern, the peak of which shifted towards less specialized communities over time. These temporal changes were associated with precipitation change, decreasing temperature stability and land use. Main conclusions: Recent climate and land‐use changes have induced two contrasting types of community responses. In human‐dominated areas, the decoupling of richness and specialization drove a general trend for biotic homogenization. In areas of low human impact experiencing increasing climate harshness, specialization increased, whereas richness decreased. Our results offer new support for specialization as a key driver of macroecological diversity patterns and show that global changes are weakening this fundamental macroecological pattern. [ABSTRACT FROM AUTHOR]

The satellite record has revealed substantial land surface "greening" in the northern hemisphere over recent decades. Process‐based Earth system models (ESMs) attribute enhanced vegetation productivity (greening) to CO2 fertilisation. However, the models poorly reproduce observed spatial patterns of greening, suggesting that they ignore crucial processes. Here, we explore whether fine‐scale land cover dynamics, as modified by ecological and land‐use processes, can explain the discrepancy between models and satellite‐based estimates of greening. We used 500 m satellite‐derived Leaf Area Index (LAI) to quantify greening. We focus on semi‐natural vegetation in Europe, and distinguish between conservation areas and unprotected land. Within these ecological and land‐use categories, we then explored the relationships between vegetation change and major climatic gradients. Despite the relatively short time‐series (15 years), we found a strong overall increase in LAI (i.e., greening) across all European semi‐natural vegetation types. The spatial pattern of vegetation change identifies land‐use change, particularly land abandonment, as a major initiator of vegetation change both in‐ and outside of protected areas. The strongest LAI increases were observed in mild climates, consistent with more vigorous woody regrowth after cessation of intensive management in these environments. Surprisingly, rates of vegetation change within protected areas did not differ significantly from unprotected semi‐natural vegetation. Overall, the detected LAI increases are consistent with previous, coarser‐scale, studies. The evidence indicates that woody regrowth following land abandonment is an important driver of land surface greening throughout Europe. The results offer an explanation for the large discrepancies between ESM‐derived and satellite‐derived greening estimates and thus generate new avenues for improving the ESMs on which we rely for crucial climate forecasts. The satellite record revealed substantial land surface "greening" in the northern hemisphere over recent decades, but process‐based Earth system models (ESMs) poorly reproduce observed spatial patterns of greening. Here, we show strong greening over Europe during the past 15 years. The spatial patterns of vegetation change indicate that woody regrowth following land abandonment is an important driver of land surface greening throughout Europe. The results offer an explanation for the large discrepancies between ESM‐derived and satellite‐derived greening estimates, and thus generate new avenues for improving the ESMs on which we rely for crucial climate forecasts. [ABSTRACT FROM AUTHOR]

C3 plants can increase nutrient uptake by increasing transpiration, which promotes the flow of water with dissolved nutrients towards the roots. However, it is not clear if this mechanism of nutrient acquisition, termed 'mass flow', also operates in C4 plants. This is an important question, as differences in mass flow capacity may affect competitive interactions between C3 and C4 species. To test if mass flow can be induced in C4 species, we conducted an experiment in a semiarid seasonal savanna in South Africa. We grew six C4 grasses in nutrient-poor sand and supplied no nutrients, nutrients to the roots or nutrients spatially separated from the roots. Wemeasured the rates of photosynthesis and transpiration, wateruse efficiency (WUE), nitrogen gain and biomass. For all species biomass, N gain, photosynthesis and transpiration were lowest in the treatment without any nutrient additions. Responses to different nutrient positioning varied among species from no effect on N gain to a 50% reduction when nutrients were spatially separated. The ability to access spatially separated nutrients showed a nonsignificant positive relationship with both the response of transpiration and the response of WUE to spatial nutrient separation. This indicates that nutrient acquisition is not regulated by decreasing WUE in C4 grasses. Overall, our study suggests that under elevated CO2, when evaporative demand is lower, C4 species may be at a competitive disadvantage to C3 species when it comes to nutrient acquisition. [ABSTRACT FROM AUTHOR]

Biomes are important constructs for organizing understanding of how the worlds' major terrestrial ecosystems differ from one another and for monitoring change in these ecosystems. Yet existing biome classification schemes have been criticized for being overly subjective and for explicitly or implicitly invoking climate. We propose a new biome map and classification scheme that uses information on (i) an index of vegetation productivity, (ii) whether the minimum of vegetation activity is in the driest or coldest part of the year, and (iii) vegetation height. Although biomes produced on the basis of this classification show a strong spatial coherence, they show little congruence with existing biome classification schemes. Our biome map provides an alternative classification scheme for comparing the biogeochemical rates of terrestrial ecosystems. We use this new biome classification scheme to analyse the patterns of biome change observed over recent decades. Overall, 13% to 14% of analysed pixels shifted in biome state over the 30-year study period. A wide range of biome transitions were observed. For example, biomes with tall vegetation and minimum vegetation activity in the cold season shifted to higher productivity biome states. Biomes with short vegetation and low seasonality shifted to seasonally moisture-limited biome states. Our findings and method provide a new source of data for rigorously monitoring global vegetation change, analysing drivers of vegetation change and for benchmarking models of terrestrial ecosystem function. [ABSTRACT FROM AUTHOR]

Changes in the phenology of vegetation activity may accelerate or dampen rates of climate change by altering energy exchanges between the land surface and the atmosphere and can threaten species with synchronized life cycles. Current knowledge of long-term changes in vegetation activity is regional, or restricted to highly integrated measures of change such as net primary productivity, which mask details that are relevant for Earth system dynamics. Such details can be revealed by measuring changes in the phenology of vegetation activity. Here we undertake a comprehensive global assessment of changes in vegetation phenology. We show that the phenology of vegetation activity changed severely (by more than 2 standard deviations in one or more dimensions of phenological change) on 54% of the global land surface between 1981 and 2012. Our analysis confirms previously detected changes in the boreal and northern temperate regions. The adverse consequences of these northern phenological shifts for land-surface-climate feedbacks, ecosystems and species are well known. Our study reveals equally severe phenological changes in the southern hemisphere, where consequences for the energy budget and the likelihood of phenological mismatches are unknown. Our analysis provides a sensitive and direct measurement of ecosystem functioning, making it useful both for monitoring change and for testing the reliability of early warning signals of change. [ABSTRACT FROM AUTHOR]

Soil water potential is crucial to plant transpiration and thus to carbon cycling and biosphere-atmosphere interactions, yet it is difficult to measure in the field. Volumetric and gravimetric water contents are easy and cheap to measure in the field, but can be a poor proxy of plant-available water. Soil water content can be transformed to water potential using soil moisture retention curves. We provide empirically derived soil moisture retention curves for seven soil types in the Kruger National Park, South Africa. Site-specific curves produced excellent estimates of soil water potential from soil water content values. Curves from soils derived from the same geological substrate were similar, potentially allowing for the use of one curve for basalt soils and another for granite soils. It is anticipated that this dataset will help hydrologists and ecophysiologists understand water dynamics, carbon cycling and biosphere-atmosphere interactions under current and changing climatic conditions in the region. [ABSTRACT FROM AUTHOR]

While the key role of termites in the decomposition of litter in the tropics has been acknowledged for a long time, much less information exists on their importance in the recycling of dung of primary consumers, especially herbivores. A review of published studies shows that a diverse group of termites (at least 126 species) has been reported to feed on a wide range of mammalian dung (18 species). Predominantly, wood-feeding and polyphagous wood-litter feeding species were found to feed also frequently on dung. Moreover, we found that termites can quickly remove large amounts of mammalian dung, especially in the dry season, when on average about 1/3 of the dung deposited in a given habitat is removed by termites within one month (with the highest rates observed in savannas). No distinctive preference for mammalian dung over other organic food sources was observed for fungusgrowing termites (Macrotermitinae), whereas the majority of the non-fungus growing taxa studied prefer dung over other food. As termites bring large quantities of dung below the soil surface, disturb and enrich soils with nutrients, dung feeding by termites appears to be a previously underestimated process important in the functioning of tropical ecosystems. [ABSTRACT FROM AUTHOR]

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives., (© 2019 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

C3 plants can increase nutrient uptake by increasing transpiration, which promotes the flow of water with dissolved nutrients towards the roots. However, it is not clear if this mechanism of nutrient acquisition, termed 'mass flow', also operates in C4 plants. This is an important question, as differences in mass flow capacity may affect competitive interactions between C3 and C4 species. To test if mass flow can be induced in C4 species, we conducted an experiment in a semiarid seasonal savanna in South Africa. We grew six C4 grasses in nutrient-poor sand and supplied no nutrients, nutrients to the roots or nutrients spatially separated from the roots. We measured the rates of photosynthesis and transpiration, water-use efficiency (WUE), nitrogen gain and biomass. For all species biomass, N gain, photosynthesis and transpiration were lowest in the treatment without any nutrient additions. Responses to different nutrient positioning varied among species from no effect on N gain to a 50% reduction when nutrients were spatially separated. The ability to access spatially separated nutrients showed a nonsignificant positive relationship with both the response of transpiration and the response of WUE to spatial nutrient separation. This indicates that nutrient acquisition is not regulated by decreasing WUE in C4 grasses. Overall, our study suggests that under elevated CO2, when evaporative demand is lower, C4 species may be at a competitive disadvantage to C3 species when it comes to nutrient acquisition.