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European beech (Fagus sylvatica L.) forests have recently experienced severe diebacks that are expected to increase in future. Oriental beech (Fagus sylvatica spp. orientalis (Lipsky) Greut. & Burd) is a potential candidate for assisted migration (AM) in European forests due to its greater genetic diversity and potentially higher drought resistance. Yet AM entails not only benefits, but also risks, and it is therefore important to monitor the progression of introduced (sub)species. Here, we demonstrate the potential of leaf spectroscopy to replace resource-intensive genetic analysis and field phenotyping for the discrimination and characterization of these two beech subspecies. We studied two European beech forests, one in France and one in Switzerland, where Oriental beech from the Greater Caucasus was introduced over 100 years ago. During two summers (2021, 2022), we measured leaf spectral reflectance, leaf morphological and biochemical traits from genotyped adult trees. Subspecies prediction models were developed separately for top-of-canopy leaves (amenable to remote sensing) and bottom-of-canopy leaves (easier to harvest) using partial least squares discriminant analysis (PLS-DA) and different sets of spectral predictors. Morphological, biochemical and spectra-derived leaf traits indicated that Oriental beech trees at the sites studied were characterized by higher lignin and nitrogen per unit leaf area than European beech, suggesting more protein-rich leaves on a per-area basis. The model based on top-of-canopy leaf reflectance spectra in the short-wave-infrared region (SWIR I: 1450–1750 nm) most accurately distinguished Oriental from European beech (BA = 0.86 ± 0.08, k = 0.72 ± 0.15), closely followed by models based on SWIR II, and on spectra-derived traits (BA ≥ 0.84, k ≥ 0.67). This study provides a proof-of-principle for the development of spectroscopy-based approaches when monitoring introduced species, subspecies or provenances. Our findings hold promise for upscaling to large forest areas using airborne remote sensing.

Genetic diversity influences the evolutionary potential of forest trees under changing environmental conditions, thus indirectly the ecosystem services that forests provide. European beech (Fagus sylvatica L.) is a dominant European forest tree species that increasingly suffers from climate change-related die-back. Here, we conducted a systematic literature review of neutral genetic diversity in European beech and created a meta-data set of expected heterozygosity (He) from all past studies providing nuclear microsatellite data. We propose a novel approach, based on population genetic theory and a min–max scaling to make past studies comparable. Using a new microsatellite data set with unprecedented geographic coverage and various re-sampling schemes to mimic common sampling biases, we show the potential and limitations of the scaling approach. The scaled meta-dataset reveals the expected trend of decreasing genetic diversity from glacial refugia across the species range and also supports the hypothesis that different lineages met and admixed north of the European mountain ranges. As a result, we present a map of genetic diversity across the range of European beech which could help to identify seed source populations harboring greater diversity and guide sampling strategies for future genome-wide and functional investigations of genetic variation. Our approach illustrates how to combine information from several nuclear microsatellite data sets to describe patterns of genetic diversity extending beyond the geographic scale or mean number of loci used in each individual study, and thus is a proof-of-concept for synthesizing knowledge from existing studies also in other species.

Imaging spectroscopy is currently the best approach for continuously mapping forest canopy traits, which is important for ecosystem and biodiversity assessments. Ideally, models are trained with trait data from fully sunlit leaves from the top of the canopy. However, sampling leaves at the top of the canopy is often difficult, and sunlit foliage from the crown periphery is collected instead, assuming minimal within-crown trait variation among sunlit leaves. We tested the degree to which crown position affects foliar traits and spectra using mixed-effects models comparing sun leaves from the crown centre of mature sugar maple (Acer saccharum Marsh.) trees collected with DeLeaves, a novel twig-sampling unmanned aerial system device, with sun leaves from the crown periphery collected with a pole pruner. Sun leaves from the crown centre differed from sun leaves from the crown periphery in absorption, reflectance, transmittance, and a series of foliar traits, including leaf thickness, leaf mass, and leaf nitrogen content per unit area, demonstrating differences in resource allocation depending on sun exposure. Our study highlights the importance of accurately matching the location of foliar samples and spectral data and of sampling across gradients of intra-individual variation for the accurate prediction of foliar trait distributions across and within canopies using imaging spectroscopy.

Societal Impact Statement Biodiversity is essential to food security and nutrition locally and globally. By reviewing the global state of edible plants and highlighting key neglected and underutilized species (NUS), we attempt to unlock plant food resources and explore the role of fungi, which along with the wealth of traditional knowledge about their uses and practices, could help support sustainable agriculture while ensuring better protection of the environment and the continued delivery of its ecosystem services. This work will inform a wide range of user communities, including scientists, conservation and development organizations, policymakers, and the public of the importance of biodiversity beyond mainstream crops. Summary As the world's population is increasing, humanity is facing both shortages (hunger) and excesses (obesity) of calorie and nutrient intakes. Biodiversity is fundamental to addressing this double challenge, which involves a far better understanding of the global state of food resources. Current estimates suggest that there are at least 7,039 edible plant species, in a broad taxonomic sense, which includes 7,014 vascular plants. This is in striking contrast to the small handful of food crops that provide the majority of humanity's calorie and nutrient intake. Most of these 7,039 edible species have additional uses, the most common being medicines (70%), materials (59%), and environmental uses (40%). Species of major food crops display centers of diversity, as previously proposed, while the rest of edible plants follow latitudinal distribution patterns similarly to the total plant diversity, with higher species richness at lower latitudes. The International Union for Conservation of Nature Red List includes global conservation assessments for at least 30% of edible plants, with ca. 86% of them conserved ex situ. However, at least 11% of those species recorded are threatened. We highlight multipurpose NUS of plants from different regions of the world, which could be key for a more resilient, sustainable, biodiverse, and community participation‐driven new “green revolution.” Furthermore, we explore how fungi could diversify and increase the nutritional value of our diets. NUS, along with the wealth of traditional knowledge about their uses and practices, offer a largely untapped resource to support food security and sustainable agriculture. However, for these natural resources to be unlocked, enhanced collaboration among stakeholders is vital.

Novel strategies are required to reduce uncertainties in the assessment of ecosystem transpiration (T). A major problem in modelling T is related to the complexity of constraining canopy stomatal resistance (rsc), accounting for the main biological controls on T besides non biological controls such as aerodynamic resistances or energy constraints. The novel Earth observation signal sun-induced chlorophyll fluorescence (SIF) is the most direct measure of plant photosynthesis and offers new pathways to advance estimates of T. The potential of using SIF to study ecosystem T either empirically or in combination with complex mechanistic models has already been demonstrated in recent studies. The diversity of environmental drivers determining diurnal and seasonal dynamics in T and SIF independently requires additional investigation to guide further developments towards robust SIF-informed T retrievals. This study consequently aims to identify relevant biotic and abiotic environmental drivers affecting the capability of SIF to inform estimates of ecosystem T. We used observational data from a temperate mixed forest during the leaf-on period and a Penman-Monteith (PM) based modelling framework, and observed varying sensitivities of SIF-informed approaches for diurnal and seasonal T dynamics (i.e. r2 from 0.52 to 0.58 and rRMSD from 17 to 19%). We used the PM based modelling framework to investigate systematically the sensitivity of SIF to diurnal and seasonal variations in rsc when empirically and mechanistically embedded in the models. We used observations and the Soil-Vegetation-Atmosphere-Transfer model SCOPE to study the dependence of SIF and T on abiotic and biotic environmental drivers including net radiation, air temperature, relative humidity, wind speed, and leaf area index. We conclude on the potential of SIF to advance estimates of T and suggest preferring more sophisticated modelling frameworks constrained with SIF and other Earth observation data over the single use of SIF to assess reliably ecosystem T across scales.

Shifts in phenology are important traces of climate change affecting mountainous ecosystems. We present an analysis of changes in spring phenology using a suite of Earth observation based parameters, i.e., start of season (SOS), snow cover extent and meteorological variables from 1991 up to 2012/2014 for the European Alps. Our results show that SOS tends to occur earlier throughout the Alps during this period and spring temperatures have increased in the Eastern Alps. Spring temperatures presented a predominant influence on SOS for both, grasslands and forests across elevations between 500–2,200 m asl, while this effect is particularly pronounced in the northeastern Alps. Snow cover duration and snow cover melting days showed secondary impact on SOS. Our research provides a comprehensive observation of spatiotemporal changes in alpine spring vegetation phenology and its driving factors. They improve our understanding of the sensitivity of the European Alps ecosystems to a changing climate.

Societal Impact Statement Bioenergy is a major component of the global transition to renewable energy technologies. The plant and fungal kingdoms offer great potential but remain mostly untapped. Their increased use could contribute to the renewable energy transition and addressing the United Nations Sustainable Development Goal 7 “Ensure access to affordable, reliable, sustainable and modern energy for all.” Current research focuses on species cultivated at scale in temperate regions, overlooking the wealth of potential new sources of small‐scale energy where they are most urgently needed. A shift towards diversified, accessible bioenergy technologies will help to mitigate and adapt to the threats of climate change, decrease energy poverty, improve human health by reducing indoor pollution, increase energy resilience of communities, and decrease greenhouse gas emissions from fossil fuels. Summary Bioenergy derived from plants and fungi is a major component of the global transition to renewable energy technologies. There is rich untapped diversity in the plant and fungal kingdoms that offers potential to contribute to the shift away from fossil fuels and to address the United Nations Sustainable Development Goal 7 (SDG7) “Ensure access to affordable, reliable, sustainable and modern energy for all.” Energy poverty—the lack of access to modern energy services—is most acute in the Global South where biodiversity is greatest and least investigated. Our systematic review of the literature over the last 5 years (2015–2020) indicates that research efforts have targeted a very small number of plant species cultivated at scale, mostly in temperate regions. The wealth of potential new sources of bioenergy in biodiverse regions, where the implementation of SDG7 is most urgently needed, has been largely overlooked. We recommend next steps for bioenergy stakeholders—research, industry, and government—to seize opportunities for innovation to alleviate energy poverty while protecting biodiversity. Small‐scale energy production using native plant species in bioenergy landscapes overcomes many pitfalls associated with bioenergy crop monocultures, such as biodiversity loss and conflict with food production. Targeted trait‐based screening of plant species and biological screening of fungi are required to characterize the potential of this resource. The benefits of diversified, accessible bioenergy go beyond the immediate urgency of energy poverty as more diverse agricultural landscapes are more resilient, store more carbon, and could also reduce the drivers of the climate and environmental emergencies.

Major boreal forest disturbance and associated carbon emissions have been reported in the coldest region of the Northern Hemisphere. Related biophysical feedbacks to climate remain highly uncertain but might reduce warming effects expected from carbon emissions. This study quantifies albedo change after disturbance, primarily fires, in larch‐dominated forests around Yakutsk as compared to undisturbed areas with natural albedo variability, using satellite‐based time series. The related annual mean shortwave radiative forcing was −6.015 W/m2 for the 13 years following forest disturbance. It was highly negative during snow‐covered months (−3.738 to −13.638 W/m2), but positive (+5.441 W/m2) for the summer months in the first year after disturbance, decreasing afterward and also turning into a negative forcing after 5 years. Forcing by surface shortwave radiation must be considered to assess the impact of boreal forest disturbance on climate and additional feedbacks, such as increased permafrost thaw or transition to alternative ecosystem states., Plain Language Summary: Boreal forests of northeastern Siberia are experiencing disturbances such as fires and permafrost degradation. These disturbances can trigger changes in biomass and heating dynamics resulting in major feedbacks to the local and regional climate. This study quantifies albedo, the ratio of reflected sunlight to incoming sunlight, in a larch‐dominated forest area in Siberia over a time span of 13 years after fire disturbance. Land surface albedo showed significant changes due to larch forest disturbance, which often recovered to a birch‐dominated forest. During summer months of the first 4 years after the forest fire, the decrease in albedo caused a local warming. For snow‐covered seasons, forest disturbance and the corresponding albedo change caused low local cooling directly after disturbance, and this cooling effect increased during the following decade., Key Points: Major boreal forest cover disturbance in the coldest region of the Northern Hemisphere (Yakutsk, Siberia) during 2001–2014 resulted in a significant change in surface albedo Surface albedo change‐related mean annual surface shortwave radiative forcing was −6.015 W/m2 but varied with season and strongly decreased during the 13 years following disturbance Shortwave radiative forcing can be directly linked to a vegetation trajectory from deciduous needleleaf to broadleaf dominated forest

Grossflachige Klassifikation von Gebuschwald mit Fernerkundungsdaten Informationen uber die Ausdehnung und die Entwicklung von Gebuschwaldern sind fur verschiedene forstliche und okologische Fragestellungen von Bedeutung, jedoch sind aktuelle und flachendeckende Datensatze kaum verfugbar. Im Rahmen dieser Arbeit wurde die Kartierung des Gebuschwaldes mit Dominanz von Alpenerle, Legfohre und Hasel fur den Kanton Graubunden auf Basis von landesweit verfugbaren Fernerkundungsdaten untersucht. Es wurden die Satellitendaten von Sentinel-1 und Sentinel-2 sowie ein Vegetationshohenmodell und ein Gelandemodell verwendet. Fur die uberwachte Klassifikation mit Random Forest, einem auf Entscheidungsbaumen basierenden Verfahren des maschinellen Lernens, wurden vom Kanton bereitgestellte und durch Luftbildinterpretation erganzte Trainingsflachen verwendet. Die unabhangige Validierung der Ergebnisse wurde mit Daten des Landesforstinventars (LFI) durchgefuhrt. Alpenerlen- und Legfohrenwalder liessen sich mit einer hohen Genauigkeit von 92.1% bzw. 86.7% klassifizieren, fur Haselwalder betrug die interne Modellgute hingegen nur 66.7%. Die resultierende Flachenausdehnung des Gebuschwaldes war vergleichbar mit den Angaben des LFI. Beim direkten Vergleich mit den LFI-Luftbildinterpretationspunkten wurden grossere Abweichungen festgestellt. Der Hauptgrund dafur ist der unterschiedliche raumliche Detaillierungsgrad. LFI-Flachen mit einem hohen Strauchanteil wurden jedoch zuverlassig als Gebuschwald klassifiziert. Die hier vorgestellte Methode unterstreicht das Potenzial von schweizweit verfugbaren Fernerkundungsdaten fur eine weitgehend objektive, kosteneffiziente und grossflachige Kartierung von Gebuschwaldern in einer fur die Praxis genugenden Genauigkeit. Large-scale classification of shrub forest with remote sensing data: Information on shrub forest distribution and development is important for a range of forestry- and ecologically-related questions, but current and area-wide datasets have been characterized by limited availability. In this study, the mapping of shrub forests dominated by green alder, mountain pine and hazel for the canton of Grison was investigated, based on available nationwide remote sensing data. Satellite data from Sentinel-1 and Sentinel-2, as well as a vegetation height and an elevation model were used. Training areas provided by the canton and supplemented by aerial imagery interpretation were used for a supervised classification with Random Forest, a decision tree-based machine learning algorithm. Independent validation of the results was carried out with data from the National Forest Inventory (NFI). Green alder and mountain pine forests were classified with high accuracy of 92.1% respectively 86.7%, whereas for hazel shrub forests, the internal model accuracy was only 66.7%. The resulting area expansion of the shrub forest was comparable with findings based on the NFI. A direct comparison with the NFI aerial imagery interpretation points revealed major discrepancies. The main reason for this is the different degree of spatial detail. However, NFI areas with a high percentage of shrubs were reliably classified as shrub forest. The method presented here underscores the potential of remote sensing data available throughout Switzerland for an essentially objective, costefficient and large-scale mapping of shrub forests with an accuracy applicable in practice.

Journal of Geophysical Research: Earth Surface, 123 (6), ISSN:0148-0227, ISSN:2169-9003, ISSN:2169-9011

The importance of perception through all the senses has been recognized in previous studies on landscape preference, but data on aural perception, as opposed to the visual, remains rare. We seek to bridge this gap by analyzing texts that describe more than 3.5 million georeferenced images, created by more than 12000 volunteers in the Geograph project. Our analysis commences by extracting and automatically disambiguating descriptions that potentially contain verbs and nouns of sound (e.g. rustle, bellow, echo, noise) and adjectives of sound intensity (e.g. deafening, quiet, vociferous). Using random forests we classify more than 8000 descriptions based on the type of sound emitter into geophony (e.g. rustling wind, bubbling waterfall), biophony (e.g. gulls calling, bellowing stag), anthrophony (e.g. roaring jets, rumbling traffic) and perceived absence of sound (e.g. not a sound can be heard) with a precision of 0.81. Further, we additionally classify these descriptions as negative, neutral and positive using an Opinion Lexicon and GloVe word embeddings. Our results show that sentiment classification gives an additional level of understanding of descriptions classified into different types of sound emitters. We see that geophony, biophony and anthrophony cannot be uniquely classified as positive or negative. Our results demonstrate how text can provide a valuable, complementary to field-based studies, source of spatially-referenced information about aural landscape perception.

AGAP : équipe CONSYT; International audience; Whilst the benefits of agroforestry are widely recognised in tropical latitudes few studies have assessed how agroforestry is perceived in temperate latitudes. This study evaluates how stakeholders and key actors including farmers, landowners, agricultural advisors, researchers and environmentalists perceive the implementation and expansion of agroforestry in Europe. Meetings were held with 30 stakeholder groups covering different agroforestry systems in 2014 in eleven EU countries (Denmark, France, Germany, Greece, Hungary, Italy, Netherlands, Portugal, Spain, Sweden and the United Kingdom). In total 344 valid responses were received to a questionnaire where stakeholders were asked to rank the positive and negative aspects of implementing agroforestry in their region. Improved biodiversity and wildlife habitats, animal health and welfare, and landscape aesthetics were seen as the main positive aspects of agroforestry. By contrast, increased labour, complexity of work, management costs and administrative burden were seen as the most important negative aspects. Overall, improving the environmental value of agriculture was seen as the main benefit of agroforestry, whilst management and socio-economic issues were seen as the greatest barriers. The great variability in the opportunities and barriers of the systems suggests enhanced adoption of agroforestry across Europe will be most likely to occur with specific initiatives for each type of system.

The central role played by deforestation in the increase in global CO2 emissions has recently justified the development of new schemes which offer compensation in exchange for reductions in emissions from deforestation (Reducing Emissions from Deforestation and Forest Degradation, REDD). The design of REDD projects can be based on market prices to set how deforesters are compensated for avoiding deforestation. With limited experiments involving a true market integration of REDD, it remains however difficult to assess the potential impact market price uncertainties may have on the targets of the protective scheme. The goal of this article is to assess the optimal choices of a forest owner, in terms of his combined decision of choosing when to protect his forest, and the deforestation rate prior to it, given his option to enter an irreversible REDD scheme that provides him with uncertain cash flows under different risk aversion scenarios.

Ungulate browsing is a major factor influencing tree regeneration. However, it is unclear if the observed increase in ungulate abundance in Central Europe implies increased browsing, and which other factors influence the incidence of browsing. We investigated the impact of forty variables (site, climate, forest and ungulates) on the probability of leader shoot browsing of six tree species which are frequent in Switzerland. The analysis was based on a large dataset including 49 monitoring areas, each containing 25&ndash, 64 circular plots, in which 10 to 130 cm tall seedlings were repeatedly assessed. Browsing probability was estimated for each plot and year by mixed effects logistic regression and used as a response in random forests to disentangle the influence of the explanatory variables. Browsing probability was positively correlated with ungulate density measures (number culled by hunting or found dead) for all six tree species. Where beyond roe deer, some red deer and/or chamois were present, the browsing probability was higher. Small timber tree stands had less browsing than young growth and thicket stands. Seedlings tended to be more frequently browsed in stands with &gt, 80% canopy shading. Browsing increased with increasing understory cover, independent of vegetation category. In conclusion, browsing is a multifactorial phenomenon and ungulate density estimates alone do not explain the whole browsing probability.

Natural floodplains are characterized by a complex habitat mosaic. However, damming, water storage, and hydropower production affect many floodplains by altering their natural habitat diversity. Field sampling data and imaging spectroscopy are used in combination with statistical models to assess resource allocation strategies of willow stands in perialpine floodplains. Three contrasting floodplain reaches located along two rivers in Switzerland serve as test beds: The Sarine River is partitioned into an upstream and downstream segment under the influence of a dam and a hydropower plant, while the Sense River represents an undisturbed, natural floodplain. Airborne imaging spectrometer data allow mapping of spatially distributed Competitor/Stress tolerator/Ruderal (CSR) strategies using a partial least square modeling approach. Using cross validation, we demonstrate that a statistical modeling approach can reveal variations in CSR scores based on the StrateFy model. Such intraspecific variation of CSR scores cannot be captured by a strategy categorization based solely on the species. Results reveal that willows shifted toward more competition and less stress tolerance along hydrologically altered reaches compared to the willows strategy along the natural control. Moreover, the overall distribution of strategies indicates that stress factors (i.e., limiting growth factors), rather than disturbance (i.e., events leading to partial or total destruction), shape the plant traits of alluvial willow trees. Detailed assessments of resource allocation strategies contribute to a more complete understanding of the continuous and reciprocal shaping between flow regimes, landforms, and alluvial vegetation.

Despite the economic importance of Theobroma cacao, surprisingly little is known about its pollination ecology. Ceratopogonid midges are considered to be the main pollinators, but the limited available evidence on the sexual reproduction is based almost exclusively on cultivated cacao and knowledge is nonexistent for wild populations. We documented flower visitors in wild and cultivated plants by applying glue on 2237 flowers of wild and cultivated cacao trees in Bolivia to trap floral visitors. We caught 631 insects belonging to seven orders, corresponding to a mean capture rate of 0.3 insects per flower. The most abundant and diverse insect order on both cacao types was Hymenoptera, represented mainly by small parasitoids. Hymenoptera were more abundant on wild cacao, whereas species richness was higher on cultivated cacao. The abundance and species richness of Diptera were not significantly different between wild and cultivated cacao. However, species composition and proportion of Diptera species differed between both wild and cultivated cacao. Ceratopogonidae were only represented by 13 individuals belonging to seven species. Cacao pollen was carried by only a single specimen of Encyrtidae. We were thus unable to identify actual pollinators. We found significant differences among the visitor assemblages between wild and cultivated cacao, which suggest that midges alone were probably too rare to act as main or even sole pollinators of cacao in our study region. Potential additional pollinators would be small Diptera (e.g., Chloropidae and Phoridae) and Hymenoptera (e.g., Eulophidae and Platygastridae).

Background The production and subsequent turnover of aboveground litter is an important process in the ecosystem carbon (C) cycle. Litterfall links above- and belowground processes by transferring organic material to the soil where it becomes available to heterotrophs, fueling nutrient cycling. Little is known about how litter fluxes respond to experimental manipulation of tree species richness. Methods We sampled litterfall in a large-scale forest biodiversity experiment in subtropical China. Litter was collected at monthly intervals during peak senescing season for two years and throughout the whole year in 2016, using 0.75 m × 0.75 m litter traps, in plots with a tree species richness of 1, 2, 4, 8 and 16 species. Results Cumulated annual litter production increased with tree species richness from an average of 1.96 ± 0.25 Mg∙ha− 1∙yr.− 1 in monocultures to 4.39 ± 1.15 Mg∙ha− 1∙yr.− 1 in 16-species mixtures. At site B, the doubling of species richness resulted in a positive effect with peak litter production increasing from 0.09 Mg∙ha− 1 when trees were 5 years old in 2015, to 0.14 Mg∙ha− 1 in 2016. The intra-annual distribution of litter production varied strongly among species, leading to a larger community niche for seasonal distribution of litter in species-rich than in species-poor plots. Community-niche size was positively correlated with litter production, thus providing an explanation for the species richness effects. Conclusions Different species had complementary temporal dynamics of litterfall, which led to a more or less constant litter supply in species-rich stands over the whole year. This caused positive richness effects on litter production which in turn may positively affect mineralization and subsequent tree growth.

There is a direct relation between the composition of a host star and that of the planets orbiting around it. As such, the recent discovery of stars with unusual chemical composition, notably enriched in carbon instead of oxygen, support the existence of exoplanets with a chemistry dominated by carbides instead of oxides. Accordingly several studies have been recently conducted on the Si C binary system at high pressure and temperature. Nonetheless, the properties of carbides at the P T conditions of exoplanets interiors are still inadequately constrained, effectively hampering reliable planetary modeling. Here we present an in situ X ray diffraction study of the Si C binary system up to 200 GPa and 3500 K, significantly enlarging the pressure range explored by previous experimental studies. The large amount of collected data allows us to properly investigate the phase diagram and to refine the Clapeyron slope of the transition line from the zinc blende to the rock salt structure. Furthermore the pressure volume temperature equation of state are provided for the high pressure phase, characterized by low compressibility and thermal expansion. Our results are used to model idealized C rich exoplanets of end members composition. In particular, we derived mass radius relations and performed numerical simulations defining rheological parameters and initial conditions which lead to onset of convection in such SiC planets. We demonstrate that if restrained to silicate rich mantle compositions, the interpretation of mass radius relations may underestimate the interior diversity of exoplanets., 30 Pages, 8 Figures

We present physics-based snowpack simulations for four snow seasons with detailed wet snow avalanche activity records. The distributed, spatially explicit simulations using the Alpine3D and SNOWPACK model show that the simulated snowpack in the release areas of documented wet snow avalanches often exhibits its first wetting of the season on the release day. This first wetting is accompanied in the simulations by liquid water accumulating on capillary barriers, often formed by depth hoar layers. The strongest water accumulations and largest increases in percolation depth are found on the day of avalanche release. For individual avalanche paths, however, this only holds in 25%-30% of the cases. Assuming that the depth of the strongest water accumulation corresponds to the avalanche fracture depth, the avalanche dynamics model RAMMS-Extended was run using simulated snowpack properties as initial conditions in the release area and boundary conditions along the avalanche path. On average, the simulated affected area by the avalanche and runout distance for the release day are statistically significant in closer agreement with the observations than two days before the release. This does not hold for the simulations of 1day before and 1 and 2days after the release. This suggests that fracture depths and the temporal evolution of percolation depths are adequately simulated within a 1-day period. The results show a large potential for distributed snow cover and avalanche dynamics simulations to assess wet snow avalanche hazards, although predictions for individual avalanche paths remain challenging., Plain Language Summary Recent years have shown an increasing interest in methods to forecast wet snow avalanches. Wet snow avalanche activity is closely related to water flow processes in snow. It is often considered that water accumulating on layer transitions inside the snowpack (e.g., layers with fine grains on top of coarse grains), may locally reduce snow strength and trigger an avalanche. We show results from detailed simulations of liquid water flow in snow in a mountainous area surrounding Davos, Switzerland, for which also detailed avalanche records are available. We find that periods with strong local water accumulations inside the snowpack correspond well with periods of avalanche activity. On average, the strongest water accumulations and the strongest increases in percolations depth in the simulations occur within 1day of the observed avalanche activity. Assuming that the depth of the water accumulation is the fracture depth, avalanche simulations were carried out to assess the resulting avalanche size. Also, here a good correspondence was found between the average simulated and observed runout distances, suggesting that fracture depths are on average adequately simulated. However, for individual avalanche paths, errors in runout distance were regularly considerable, indicating that predictions for individual avalanche paths remain challenging.

While deforestation and fragmentation can cause massive species loss in forest ecosystems, forest regeneration can also drive successional changes in species composition. Although studies have sometimes documented the effects of these compositional changes on interspecific interactions, few studies have investigated changes in the structure of plant-animal networks. We investigated how interaction networks of assemblages of rodents and tree seeds changed with forest fragmentation and succession in a subtropical region. We compared seed-rodent interactions between 14 secondary forest patches that ranged in area from 2 to 58 ha, and from 10 to at least 100 years old, representing a successional gradient. We expected that deforestation and fragmentation would reduce seed production and diversify rodent communities, resulting in higher interaction strengths and connectivity, but weak nestedness (i.e., specialists interact with subsets of the species interaction of generalists). We measured the frequency of rodents eating and removing seeds (interaction strength) in each patch during 3 successive years, using seed tagging and infrared camera trapping, and calculated the properties of the seed-rodent networks. We found that the relative abundances of seeds and rodents changed with stand age not patch size, as did seed-rodent interactions: older patches produced more seeds, contained fewer individuals and species of rodents, and had seed-rodent networks with lower connectance and interaction strength, but higher nestedness. Connectance and interaction strength decreased with metabolic per capita seed availability (as measured by seed energy value); nestedness increased with seed richness, but decreased with rodent abundance. At species level, we found stand age and patch size showed significant effects on seed or rodent abundance of a few species. We also found seed coat thickness and starch contents had significant effects on network metrics. Our results suggest that during succession after deforestation, seed-rodent interactions in these sub-tropical forests change from a state dominated by high seed removal and highly connected seed-rodent networks to a state with more seeds and highly nested networks. From a management perspective of our study region, succession age, not fragment size, and network structure should be paid more attention so as to facilitate the restoration processes of degraded forests. Rodent management should be applied to protect native forest species and exclude incursive ones from farmlands and human residences at early succession stage.

Terrestrial herbs are important ecological components in tropical agroforests, but little is known about how they are affected by agricultural management. In cacao agroforests of Central Sulawesi, Indonesia, we studied the change in herb species richness, cover, and biomass over 3 years in 86 subplots subjected to high and low weeding frequency as well as fertilized and non-fertilized treatments. We recorded 111 species with rapid changes in species composition between the 3 years. Species richness increased sharply in the 2nd year, presumably as a result of changes in the management with the experimental regimes, and decreased in the 3rd, probably due to competitive exclusion. Species richness, cover, and biomass were all significantly higher in the infrequently weeded plots than in the frequently weeded ones, but there were only slight responses to the fertilization treatment. An indicator species analysis recovered 45 species that were typical for a given year and a further eight that were typical for certain treatments, but these species showed no clear patterns relative to their ecology or biogeography. We conclude that the herb assemblages in cacao agroforests are quite resilient against weeding, but that the cover of species shifts rapidly in response to management.

Trees, 21 (3), ISSN:0931-1890, ISSN:1432-2285

Forest canopy structure influences and partitions the energy fluxes between the atmosphere and vegetation. It serves as an indicator of a variety of biophysical variables and ecosystem goods and services. Airborne laser scanning (ALS) can simultaneously provide horizontal and vertical information on canopy structure. Existing approaches to assess canopy structure often focus on in situ collected structural variables and require a substantial set of prior information about stand characteristics. They also rely on pre-defined spatial units and are usually dependent on site-specific model calibrations. We propose a method to provide quantitative canopy-structure descriptors on different scales, retrieved from ALS data. The approach includes (i) a sensitivity assessment and a quantification of ALS-derived canopy-structure information dependent on ALS data properties, (ii) an automatic determination of the most feasible spatial unit for canopy-structure characterization, and (iii) the derivation of canopy-structure types (CSTs) using a hierarchical, multi-scale classification approach based on Bayesian robust mixture models (BRMM), satisfying structurally homogenous criteria without the use of in situ calibration information. The CSTs resulted in retrievals of canopy layering (single-, two-, and multi-layered canopies) and canopy types (deciduous or evergreen canopies). Retrievals classified seven CSTs with accuracies ranging from 52% to 82% user accuracy (canopy layering) and 89–99% user accuracy (canopy type). The method supports a data-driven approach, allowing for an efficient monitoring of canopy structure.

Canopy layers form essential structural components, affecting stand productivity and wildlife habitats. Airborne laser scanning (ALS) provides horizontal and vertical information on canopy structure simultaneously. Existing approaches to assess canopy layering often require prior information about stand characteristics or rely on pre-defined height thresholds. We developed a multi-scale method using ALS data with point densities &gt, 10 pts/m2 to determine the number and vertical extent of canopy layers (canopylayer, canopylength), seasonal variations in the topmost canopy layer (canopytype), as well as small-scale heterogeneities in the canopy (canopyheterogeneity). We first tested and developed the method on a small forest patch (800 ha) and afterwards tested transferability and robustness of the method on a larger patch (180,000 ha). We validated the approach using an extensive set of ground data, achieving overall accuracies &gt, 77% for canopytype and canopyheterogeneity, and &gt, 62% for canopylayer and canopylength. We conclude that our method provides a robust characterization of canopy layering supporting automated canopy structure monitoring.

Timing and accumulation of snow are among the most important phenomena influencing land surface phenology in mountainous ecosystems. However, our knowledge on their influence on alpine land surface phenology is still limited, and much remains unclear as to which snow metrics are most relevant for studying this interaction. In this study, we analyzed five snow and phenology metrics, namely, timing (snow cover duration (SCD) and last snow day), accumulation of snow (mean snow water equivalent, SWEm), and mountain land surface phenology (start of season and length of season) in the Swiss Alps during the period 2003–2014. We examined elevational and regional variations in the relationships between snow and alpine land surface phenology metrics using multiple linear regression and relative weight analyses and subsequently identified the snow metrics that showed strongest associations with variations in alpine land surface phenology of natural vegetation types.We found that the relationships between snow and phenology metrics were pronounced in high-elevational regions and alpine natural grassland and sparsely vegetated areas. Start of season was influenced primarily by SCD, secondarily by SWEm, while length of season was equally affected by SCD and SWEm across different elevational bands. We conclude that SCD plays the most significant role compared to other snow metrics. Future variations of snow cover and accumulation are likely to influence alpine ecosystems, for instance, their species composition due to changes in the potential growing season. Also, their spatial distribution may change as a response to the new environmental conditions if these prove persistent.

Mass population displacements put additional stress on the ecosystems and often lead to conflicts with the host communities, especially in the case of large refugee or Internally Displaced Person (IDP) camps. Therefore, there is need for the assessment of environmental impacts and, based on this, the sustainable management of natural resources between host and refugee communities. We propose a method based on high (Landsat 5,7 and 8) and very high (WorldView-2) resolution Earth Observation data to establish forest inventories combining the analysis of remote sensing satellite data along with ground-based observations in South Sudan. The resulting forest inventory mapping comprises map products on vegetation cover, tree species, and vegetation changes. We distinguished between the vegetation types grassland, shrub/tree savanna, savanna woodland, and woodland. For savanna woodland and woodland, we furthermore applied a tree species classification, differentiating between Red acacia, Desert date tree, Silak, and Doum palm. The tree species classification yielded in mean accuracies of about 61.0% for both the Landsat and WorldView based classifications, with the best results achieved for Desert palm tree and red acacia with average accuracies of 88% and 53%, respectively. The product about vegetation changes indicates a decrease of vegetation up to 50% within and in the surroundings of the refugee camps/settlement. The resulting maps can serve to estimate accessible wood resources and to identify potential harvest areas. In addition, they can support the definition of a sustainable use of wood for construction and cooking purposes for the refugee and host communities based on a community forest management.

The patchy distribution of high-Andean treeline forests has provoked discussion about the relative importance of anthropogenic and climatic causes of this pattern, both of which vary with topography. We aimed to understand the topographic controls on the distribution of Polylepis subsericans treeline forests in the Andes of southern Peru, and the changes in these controls along an elevational gradient. We mapped Polylepis forests in the Cordillera Urubamba, Cusco, using high-resolution aerial images and related forest cover to topographic variables extracted from a digital terrain model (30-m resolution). The variables were selected based on their expected biological relevance for tree growth at high elevations. We constructed logistic regression models of forest cover, separately for each of five 100-m elevational belts. To deal with spatial autocorrelation, models were based on randomized 10% subsampling of the data with 1000 repetitions. The results suggest a consistent shift in topographic preference with elevation, with forests at lower elevations showing a preference for topographically protected sites near rivers and forests at higher elevations being increasingly restricted to north-facing and well-drained sites. Our study offers the first indication of the ability of Andean treeline forests to benefit from the topographic heterogeneity of the high-Andes. Providing that dispersal and establishment are possible, local relocation between microsites could help these forests to persist regionally in spite of changing climatic conditions.

Forests contribute to the sequestration of organic carbon (C). A key role in forest C cycling is played by deadwood. While a broad range of literature on deadwood decay (above-ground) exists, the mechanisms occurring in the transition zone from deadwood to the humus are poorly understood. In particular, scarce information is available on the temporal patterns of wood compounds (such as lignin and cellulose) during decay processes. Our objective was to provide a deeper understanding on deadwood decay in a Mediterranean montane environment by focussing on semi-natural forests of Fagus sylvatica L. (beech). The decay process was studied in a field experiment (in the Majella mountains, Apennine Mountains, Italy) among an altitudinal transect at different climatic conditions. Beech wood blocks (mass, cellulose, lignin) having all an equal in size (5 cm × 5 cm × 2 cm) were placed in soil mesocosms to investigate over one year changes in the overall mass, cellulose and lignin content. The sites were along an altitudinal gradient, reflecting different climatic conditions. The effect of exposure (north- vs. south-facing slopes) was also considered. Deadwood, cellulose and lignin dynamics were related to soil parameters (pH, grain size, moisture, temperature) and climate data. Deadwood decayed very fast and followed an exponential trend. The decay rate constants of the deadwood mass significantly (positively) correlated with air temperature and soil moisture: the lower the temperature, the lower the evapotranspiration, the higher the moisture availability, and the higher the decay rates. Lignin decayed more slowly than cellulose, resulting in average decay rate constants (k) between 0.368 and 0.382 y−1. Soil properties and topographic traits (slope and exposure) strongly influenced the decay processes. At south-facing sites (having an altitude

The current global wave of land acquisition – variously debated as land grabbing or investment in land – is promoted by the World Bank and the FAO as creating win–win-situations for local populations and investors alike. Common policy recommendations suggest expanding the production of export crops, by making use of marginal or unused land. Considerable potentials for such an expansion are assumed. Taking Tanzania as a case study, the evidence for such types of land is assessed by using a broad range of statistics. We will argue firstly, that the terms marginal and unused land serve as a manipulative terminology for the benefit of attempts to commercially valorize and commodify African landscapes, from biofuel to large-scale food production and tourism. However, they relate to different rationalities of domination. Unused land refers to a state-bureaucratic narrative, which excludes user groups deemed irrelevant for national development, while marginal land refers to a capitalist-economic narrative that excludes what is not profitable. Secondly, the terms are analyzed as categories central for state simplification of social relations attached to land. Modelling of these land use categories based on remote sensing is an attempt to compensate weak state capacities to enhance the legibility of the landscape by constructing it as a landscape of commercial value.

A set of 57 novel canopy metrics of potential value for snow modeling were created from airborne LiDAR data. The metrics were meant to estimate size and relative location of gap openings around a point within forested areas, allowing for measures of the spatial arrangement of surrounding canopy elements. These new metrics were correlated with snow interception measured in the field (8488 manually measured snow interception points). The results were further compared to the correlation values between effective interception and traditionally used forest parameters (CC and LAI). The correspondence between all metrics was also analyzed in order to understand the potential cross correlation between each variable. LAI (average R: 0.57) demonstrated low correlations when directly compared to snow interception and further showed a large cross correlation with canopy closure (average R: 0.72). A new metric, ‘mean distance to canopy’ had the highest correlation (average R: 0.78) over all storm events to the effective interception. But in contrast to LAI, this metric did not show any cross correlation with canopy closure (CC). Likewise, ‘total gap area,’ an indirect measurement of apparent gap fraction (another new metric), also showed a high correlation to effective interception (average R: 0.72) without demonstrating a significant cross correlation to CC or to mean distance to canopy. These findings suggest that modeling forest snow processes with both CC and LAI may not be the best option due to both the low correlation of LAI as well as high cross correlation between these parameters. However, the pairing of mean distance to canopy and/or total gap area with canopy closure could give more robust estimations of snow interception within heterogeneous terrain.

This is a post-peer-review, pre-copyedit version of an article published in Agroforestry Systems. The final authenticated version is available online at: http://dx.doi.org/10.1007/s10457-017-0132-3 Agroforestry systems are known to provide ecosystem services which differ in quantity and quality from conventional agricultural practices and could enhance rural landscapes. In this study we compared ecosystem services provision of agroforestry and non-agroforestry landscapes in case study regions from three European biogeographical regions: Mediterranean (montado and dehesa), Continental (orchards and wooded pasture) and Atlantic agroforestry systems (chestnut soutos and hedgerows systems). Seven ecosystem service indicators (two provisioning and five regulating services) were mapped, modelled and assessed. Clear variations in amount and provision of ecosystem services were found between different types of agroforestry systems. Nonetheless regulating ecosystems services were improved in all agroforestry landscapes, with reduced nitrate losses, higher carbon sequestration, reduced soil losses, higher functional biodiversity focussed on pollination and greater habitat diversity reflected in a high proportion of semi-natural habitats. The results for provisioning services were inconsistent. While the annual biomass yield and the groundwater recharge rate tended to be higher in agricultural landscapes without agroforestry systems, the total biomass stock was reduced. These broad relationships were observed within and across the case study regions regardless of the agroforestry type or biogeographical region. Overall our study underlines the positive influence of agroforestry systems on the supply of regulating services and their role to enhance landscape structure We acknowledge funding through Grant 613520 from the European Commission (Project AGFORWARD, 7th Framework Program), the Xunta de Galicia, Consellería de Cultura, Educación e Ordenación Universitaria (“Programa de axudas á etapa posdoutoral DOG no. 122, 29/06/2016 p.27443, exp: ED481B 2016/071-0”), the Forest Research Center strategic project (PEst OE/AGR/UI0239/2014) and the Portuguese Foundation for Science and Technology through the contract SFRH/BD/52691/2014 SI

Forest canopy structure and associated solar radiation fluxes greatly influence snow accumulation and melt and have large implications for water availability from forested areas. The ability to efficiently and explicitly infer canopy parameters at high resolution is crucial to improve the success of large scale applications of snow water resources modeling within these areas. In this paper, the utility of estimating leaf area index (LAI), canopy closure (CC) and below canopy potential incoming solar radiation (PISR) from synthetic hemispheric photos derived from airborne LiDAR data was evaluated. LAI and CC estimates from the synthetic LiDAR images were directly compared to actual hemispherical photos taken at 16 points at 7 field areas with heterogeneous canopy stand characteristics for a total of 112 photo comparison points. The synthetic data was further analyzed against LAI and CC derived from more traditional aerial LiDAR methods using a Cartesian space which integrates values over an area rather than a point based angular viewpoint. Furthermore, the PISR estimates were directly compared to in-situ radiometer measurements taken at 30 different locations during clear sky conditions with heterogeneous canopy stand properties. When compared to the actual hemispherical photos, the CC and LAI metrics from synthetic images showed higher correlations and lower biases for all canopy coverage classes (r: 0.93 for CC and r: 0.83 for LAI) than the metrics from the Cartesian approach which displayed decreased correlations and higher biases with increasing canopy closure. Using a clear sky partitioning scheme for the direct and diffuse portions of the incoming shortwave radiation, the PISR was also accurately estimated from the synthetic images with average site correlations ranging from 0.90 to 0.94 where the timing and peak trends of both the diffuse and direct radiation components were well represented. Finally, a basic methodology for the steps toward automation of the process was presented in order to explicitly derive these metrics within similar LiDAR datasets.

Solar radiation is the primary source of energy for the Earth's climate system. Although the incoming and outgoing solar fluxes at the top of atmosphere can be quantified with high accuracy, large uncertainties still exist in the partitioning of solar absorption between surface and atmosphere. To compute best estimates of absorbed solar radiation at the surface and within the atmosphere representative for Europe during 2000–2010, we combine temporally homogeneous and spatially representative ground-based observations of surface downwelling solar radiation with collocated satellite-retrieved surface albedo and top-of-atmosphere net irradiance. We find best estimates of Europe land annual mean surface and atmospheric absorption of 117.3 ± 6 W m−2 (41.6 ± 2% of top-of-atmosphere incident irradiance) and 65.0 ± 3 W m−2 (23.0 ± 1%). The fractional atmospheric absorption of 23% represents a robust estimate largely unaffected by variations in latitude and season, thus, making it a potentially useful quantity for first-order validation of regional climate models. Uncertainties of the individual absorption estimates arise mostly from the measurements themselves. In this context, the surface albedo and the ground-based solar radiation data are the most critical variables. Other sources of uncertainty, like the multiplicative combination of spatially averaged surface solar radiation and surface albedo estimates, and the spatial representativeness of the point observations, are either negligibly small or can be corrected for.

Better decisions in forest management with the SorSim bucking simulator To be able to estimate the commercial wood assortment of forests at all times is an important requirement of economical wood production. This makes it possible to improve management decisions by quantifying the revenues of alternative silvicultural and bucking strategies. So far a functional simulaton instrument for bucking single trees and whole stands was missing in forestry and in forest science in Switzerland. The SorSim bucking simulator of the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) fills this gap. SorSim is implemented in Java and is platform-independent. An overview is given how the simulator works. Two examples show applications in practice and science. Of particular value is the possibility of estimating wood assortments of planned harvesting operations based on simple timber marking protocols. Especially in science and in strategic planning, SorSim allows the analysis of the long-term development of revenues of forest stands given different silvicultural methods. Combining SorSim with IT-based harvesting productivity models provides greater insight. Further development of SorSim entails testing different optimization approaches, e.g. single tree bucking to value and whole stand bucking to order.

[1] Discharge from marine-terminating outlet glaciers represents a key component of the Greenland Ice Sheet mass budget and observations suggest that mass loss from northwest Greenland has recently accelerated. Despite this, the factors controlling outlet glacier dynamics within this region have been comparatively poorly studied. Here we use remotely sensed data to investigate the influence of atmospheric, oceanic, and glacier-specific controls on the frontal position of Alison Glacier (AG), northwest Greenland, and nine surrounding outlet glaciers. AG retreated by 9.7 km between 2001 and 2005, following at least 25 years of minimal change. Results suggest that sea ice and air temperatures influence glacier frontal position at seasonal and interannual timescales. However, the response of individual outlet glaciers to forcing was strongly modified by factors specific to each glacier, specifically variations in fjord width and terminus type. Overall, our results underscore the need to consider these factors in order to interpret recent rapid changes and predict the dynamic response of marine-terminating outlet glaciers to atmospheric and oceanic forcing.

This study aimed to answer the question how cartography can help decision makers visualize the problem of contamination by explosive remnants of war (ERW). We thus explored a set of six cartographic visualization methods and systematically evaluated their usefulness with respect to four categories of stakeholders in the humanitarian demining process (i.e., database administrators, operations officers, directors of national mine action authorities, and donors) at four geographical scales, ranging from municipal to global. The main application of our work is for stakeholders involved in humanitarian demining. We provide them with a comprehensive framework for visualizing ERW hazards at the geographical scale at which they have to make decisions, as well as customized cartographic visualization tools and recommendations to help them make informed decisions. For example, we provide potential donors with a method for obtaining a global overview of ERW contamination while remaining aware of regional variation and hot spots. We also enhance cartographic visualization capabilities using traditional kernel density estimation by customizing key parameters. Specifically, we propose a method for adjusting kernel bandwidth for datasets with highly heterogeneous spatial distributions and a method for generating kernel surfaces from polygon data that consists of infilling the polygons with points before using them as inputs in the kernel density estimation.

Along with air temperatures, the freezing level height (FLH) has risen over the last decades. The mass balance of tropical glaciers in Peru is highly sensitive to a rise in the FLH, mainly due to a decrease in accumulation and increase of energy for ablation caused by reduced albedo. Knowledge of future changes in the FLH is thus crucial to estimating changes in glacier extents. Since in situ data are scarce at altitudes where glaciers exist (above ~4800 m above sea level (asl)), reliable FLH estimates must be derived from multiple data types. Here we assessed the FLHs and their spatiotemporal variability, as well as the related snow/rain transition in the two largest glacier-covered regions in Peru by combining data from two climate reanalysis products, Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar Bright Band data, Micro Rain Radar data, and meteorological ground station measurements. The mean annual FLH lies at 4900 and 5010 m asl, for the Cordillera Blanca and Vilcanota, respectively. During the wet season, the FLH in the Cordillera Vilcanota lies ~150 m higher compared to the Cordillera Blanca, which is in line with the higher glacier terminus elevations. Coupled Model Intercomparison Project version 5 (CMIP5) climate model projections reveal that by the end of the 21st century, the FLH will rise by 230 m (±190 m) for Representative Concentration Pathway (RCP) 2.6 and 850 m (±390 m) for RCP8.5. Even under the most optimistic scenario, glaciers may continue shrinking considerably, assuming a close relation between FLH and glacier extents. Under the most pessimistic scenario, glaciers may only remain at the highest summits above approximately 5800 m asl. © 2017. American Geophysical Union. Por pares