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Tropical forests dominate terrestrial photosynthesis, yet there are major contradictions in our understanding due to a lack of field studies, especially outside the tropical Americas. A recent field study indicated that West African forests have among the highest forests gross primary productivity (GPP) yet observed, contradicting models that rank them lower than Amazonian forests. Here, we show possible reasons for this data-model mismatch. We found that biometric GPP measurements are on average 56.3% higher than multiple global GPP products at the study sites. The underestimation of GPP largely disappears when a standard photosynthesis model is informed by local field-measured values of (a) fractional absorbed photosynthetic radiation (fAPAR), and (b) photosynthetic traits. Remote sensing products systematically underestimate fAPAR (33.9% on average at study sites) due to cloud contamination issues. The study highlights the potential widespread underestimation of tropical forests GPP and carbon cycling and hints at the ways forward for model and input data improvement. This study finds that vegetation models commonly underestimate the productivity of West African forests, owing to bias in fractional absorbed photosynthetic radiation (fAPAR) and leaf level photosynthetic capacities. [ABSTRACT FROM AUTHOR]

Comfort and safety in automobiles can be enhanced with predictive maintenance by means of early problem detection and isolation, collectively referred to as fault diagnosis. To maintain a lead position in automotive industry, fleet managers are turning to predictive analysis. In this study, an attempt was made involving feature fusion to determine most significant features required to determine the suspension faults using vibration signals and machine learning approach. Three different features extraction techniques such as statistical, histogram and autoregressive moving average model (ARMA) were extracted from the acquired vibration signals for different fault conditions at the three different loads by means of a specially fabricated experimental setup. Feature selection was done for individual features using J48 decision tree algorithm. The performance of tree-based classifiers was assessed on the chosen individual features. Additionally, each individual feature was paired with others in four distinct combinations: statistical-histogram, statistical-ARMA, ARMA-histogram and ARMA-histogram-statistical, across three different loads. These combined features were then input into tree-based algorithms to identify the optimal classification algorithm, regardless of the load conditions. The results obtained in this study indicate that the combination of the ARMA-histogram-statistical feature with a random forest classifier yields optimal classification accuracy, regardless of load conditions, with values of 98.125%, 99.375% and 96.250%, respectively, and an average computational time of 0.10 s. [ABSTRACT FROM AUTHOR]

Realistic representations of plant carbon exchange processes are necessary to understand the growth and productivity of forests and to understand how plants will behave in future climate change scenarios. These processes are known to vary over depending on environmental and genetic factors. Here, we used the model by Farquhar et al. (Plant 149:78–90, 1980) to obtain the parameters Vcmax, Jmax and Jmax/Vcmax, and we analyzed the influence of growth temperature and precipitation variables and climatic groups on these parameters for the two functional groups (pine and eucalypt). Our results show that the photosynthetic capacity of forests has a difference between the functional groups, the variables growth temperature and precipitation at 10 and 30 days before physiological measurements influenced photosynthetic parameters, indicated a tendency to increase in photosynthetic capacity, suggesting its acclimatization to the environment. There were no differences between the subtropical and tropical climatic groups, demonstrating an adaptation of the genotypes to the environmental conditions of Brazil. The values of Vcmax, Jmax and Jmax/Vcmax parameters provided in this study expand the database of photosynthetic parameters and can be widely used in modeling studies of planted forests in Brazil. However, they should be interpreted with caution, we recommend specific field studies to fit models and further studies comparing species groups in Brazil. [ABSTRACT FROM AUTHOR]

Late spring frosts, occurring after spring phenological events, pose a dire threat to tree growth and forest productivity. With climate warming, earlier spring phenological events have become increasingly common and led to plants experiencing more frequent and severe frost damage. However, the effect of late spring frosts after leaf-out on subsequent flowering phenology in woody species remains unknown. Utilizing 572,734 phenological records of 640 species at 5024 sites from four long-term and large-scale in situ phenological networks across the Northern Hemisphere, we show that late spring frosts following leaf-out significantly delay the onset of the subsequent flowering by approximately 6.0 days. Late-leafing species exhibit greater sensitivity to the frosts than early-leafing species, resulting in a longer delay of 2.5 days in flowering. Trees in warm regions and periods exhibit a more pronounced frost-induced flowering delay compared to those in cold regions and periods. A significant increase in the frequency of late spring frost occurrence is observed in recent decades. Our findings elucidate the intricate relationships among leaf-out, frost, and flowering but also emphasize that the sequential progression of phenological events, rather than individual phenological stages, should be considered when assessing the phenological responses to climate change. Climate warming causes earlier spring phenological events and higher risk of late spring frost damage. Here, the authors investigate the impact of late spring frosts on phenological events, finding that they delayed flowering by an average of 6 days across 640 species. [ABSTRACT FROM AUTHOR]

The use of intensive silviculture to increase forest productivity in commercial plantations will undoubtedly persist into the future. This review synthesizes and analyses studies that have investigated the influence of fertilization on density, microfibril angle (MFA), and modulus of elasticity (MOE) of different Pinus species under intensive management. It was found that in general, ring width or growth rate demonstrated a negative correlation with density, and a positive relationship with MFA. Also, the relationship between growth rate and density and MFA were age specific and often non-significant at the whole stem level. Earlywood and latewood were influenced differently by fertilization: Earlywood width and density increased while in latewood, width stayed constant but density decreased. This resulted in a decrease in within-ring heterogeneity of density and density-related properties. Since latewood generally contributed more to whole-ring density, the net effect was that whole-ring wood density of pines mostly decreased with fertilization. Given that fertilization often resulted in a decrease in wood density and an increase in MFA, MOE decreased with fertilization. Most fertilization-wood-property studies on Pinus involved nitrogen and phosphorus fertilizers with differing quantity and ratios. Results suggest that nitrogen may cause the greatest change in wood growth and properties. An important question that was often unanswered in research, was whether the effect of specific fertilization treatments on wood properties were purely based on the influence of increased growth or whether there were direct influences not explained by growth. Also, despite potassium being an important elemental component of many fertilizers, relatively little work has been done to determine its effect on wood properties. [ABSTRACT FROM AUTHOR]

Growth and yield (G&Y) of forest plantations can be significantly impacted by maladaptation resulting from climate change, and assisted migration has been proposed to mitigate these impacts by restoring populations to their historic climates. However, genecology models currently used for guiding assisted migration do not account for impacts of climate change on cumulative growth and assume that responses of forest population to climate do not change with age. Using provenance trial data for interior lodgepole pine (Pinus contorta subsp. latifolia Douglas) and white spruce (Picea glauca (Moench) Voss) in western Canada, we integrated Universal Response Functions, representing the relationship of population performance with their provenance and site climates, into top height curves in a G&Y model (Growth and Yield Projection System, GYPSY) to develop population-specific climate sensitive top height curves for both species. These new models can estimate the impact of climate change on top height of local populations and populations from a range of provenances to help guide assisted migration. Our findings reveal that climate change is expected to have varying effects on forest productivity across the landscape, with some areas projected to experience a slight increase in productivity by the 2050s, while the remainder are projected to face a significant decline in productivity for both species. Adoption of assisted migration, however, with the optimal populations selected was projected to maintain and even improve productivity at the provincial scale. The findings of this study provide a novel approach to incorporating assisted migration approaches into forest management to mitigate the negative impacts of climate change. [ABSTRACT FROM AUTHOR]

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Slot structure is the equilibrium result of market demand side and slot resource supply side, while slot parameters reflect the operational support capacity of the aviation system. Time parameters reflect the operational support capability of the aviation system. Time structure should not only reflect changes in market demand, but also meet the constraints of operational efficiency. Constructing a reasonable 18–24 h timetable profile for busy airports that meets normal expectations for declared capacity and seasonal scheduling is a challenge in civil aviation slot management. This study utilizes historical data on airport flights and weather conditions to establish a regression prediction model for the time structure using K-means clustering and partial least squares regression. Additionally, ensemble learning is employed to forecast flight delay levels. The findings demonstrate that random forest yields favorable results in regression and prediction tasks, allowing for the integration of upper (good weather) and lower (severse weather) limits of the time profile with delay predictions as time parameter intervals. Consequently, the flights falling within these intervals achieve an average delay level of less than 15 min which meets the expectations of normal flight. [ABSTRACT FROM AUTHOR]

Neonatal medical data holds critical information within the healthcare industry, and it is important to analyze this data effectively. Machine learning algorithms offer powerful tools for extracting meaningful insights from the medical data of neonates and improving treatment processes. Knowing the length of hospital stay in advance is very important for managing hospital resources, healthcare personnel, and costs. Thus, this study aims to estimate the length of stay for infants treated in the Neonatal Intensive Care Unit (NICU) using machine learning algorithms. Our study conducted a two-class prediction for long and short-term lengths of stay utilizing a unique dataset. Adopting a hybrid approach called Classifier Fusion-LoS, the study involved two stages. In the initial stage, various classifiers were employed including classical models such as Logistic Regression, ExtraTrees, Random Forest, KNN, Support Vector Classifier, as well as ensemble models like AdaBoost, GradientBoosting, XGBoost, and CatBoost. Random Forest yielded the highest validation accuracy at 0.94. In the subsequent stage, the Voting Classifier—an ensemble method—was applied, resulting in accuracy increasing to 0.96. Our method outperformed existing studies in terms of accuracy, including both neonatal-specific length of stay prediction studies and other general length of stay prediction research. While the length of stay estimation offers insights into the potential suitability of the incubators in the NICUs, which are not universally available in every city, for patient admission, it plays a pivotal role in delineating the treatment protocols of patients. Additionally, the research provides crucial information to the hospital management for planning such as beds, equipment, personnel, and costs. [ABSTRACT FROM AUTHOR]

On 12 sample plots established in the ecotone of the northern forest boundary in the Khadyta-Yakha River valley on the Yamal Peninsula, time of emergence and death, as well as productivity of about 1000 Siberian larch (Larix sibirica Ledeb.) and Siberian spruce (Picea obovata Ledeb.) trees were analyzed. Over the last 140 years, there has been a sharp increase in the stocks and annual growth of stem phytomass of woody plants within the studied ecotone. Since the 1970s, the average annual growth of phytomass has been increased by 1.2–39 times, which was facilitated by a 0.9°C increase in average June–July air temperature. However, this effect is insignificant in areas of mixed open forests subjected to periodic logging. [ABSTRACT FROM AUTHOR]

Quantifying nitrogen uptake rates across different forest types is critical for a range of ecological questions, including the parameterization of global climate change models. However, few measurements of forest nitrogen uptake rates are available due to the intensive labor required to collect in situ data. Here, we seek to optimize data collection efforts by identifying measurements that must be made in situ and those that can be omitted or approximated from databases. We estimated nitrogen uptake rates in 18 mature monodominant forest stands comprising 13 species of diverse taxonomy at the Morton Arboretum in Lisle, IL, USA. We measured all nitrogen concentrations, foliage allocation, and fine root biomass in situ. We estimated wood biomass increments by in situ stem diameter and stem core measurements combined with allometric equations. We estimated fine root turnover rates from database values. We analyzed similar published data from monodominant forest FACE sites. At least in monodominant forests, accurate estimates of forest nitrogen uptake rates appear to require in situ measurements of fine root productivity and are appreciably better paired with in situ measurements of foliage productivity. Generally, wood productivity and tissue nitrogen concentrations may be taken from trait databases at higher taxonomic levels. Careful sorting of foliage or fine roots to species is time consuming but has little effect on estimates of nitrogen uptake rate. By directing research efforts to critical in situ measurements only, future studies can maximize research effort to identify the drivers of varied nitrogen uptake patterns across gradients. [ABSTRACT FROM AUTHOR]

Fertilizer input is one of the effective forest management practices, which improves soil nutrients and microbial community compositions and promotes forest productivity. However, few studies have explored the response of rhizosphere soil microbial communities to various fertilization regimes across seasonal dynamics. Here, we collected the rhizosphere soil samples from Phoebe bournei plantations to investigate the response of community assemblages and microbial interactions of the soil microbiome to the short-term application of four typical fertilizer practices (including chemical fertilizer (CF), organic fertilizer (OF), compound microbial fertilizer (CMF), and no fertilizer control (CK)). The amendments of organic fertilizer and compound microbial fertilizer altered the composition of rhizosphere soil bacterial and fungal communities, respectively. The fertilization regime significantly affected bacterial diversity rather than fungal diversity, and rhizosphere fungi responded more sensitively than bacteria to season. Fertilization-induced fungal networks were more complex than bacterial networks. Stochastic processes governed both rhizosphere soil bacterial and fungal communities, and drift and dispersal limitation dominated soil fungal and bacterial communities, respectively. Collectively, these findings demonstrate contrasting responses to community assemblages and interactions of rhizosphere bacteria and fungi to fertilizer practices. The application of organic fertilization strengthens microbial interactions and changes the succession of key taxa in the rhizosphere habitat. Key points: • Fertilization altered the key taxa and microbial interaction • Organic fertilizer facilitated the turnover of rhizosphere microbial communities • Stochasticity governed soil fungal and bacterial community assembly [ABSTRACT FROM AUTHOR]

The essential biodiversity variables (EBV) framework has been proposed as a monitoring system of standardized, comparable variables that represents a minimum set of biological information to monitor biodiversity change at large spatial extents. Six classes of EBVs (genetic composition, species populations, species traits, community composition, ecosystem structure and ecosystem function) are defined, a number of which are ideally suited to observation and monitoring by remote sensing systems. We used moderate-resolution remotely sensed indicators representing two ecosystem-level EBV classes (ecosystem structure and function) to assess their complementarity and redundancy across a range of ecosystems encompassing significant environmental gradients. Redundancy analyses found that remote sensing indicators of forest structure were not strongly related to indicators of ecosystem productivity (represented by the Dynamic Habitat Indices; DHIs), with the structural information only explaining 15.7% of the variation in the DHIs. Complex metrics of forest structure, such as aboveground biomass, did not contribute additional information over simpler height-based attributes that can be directly estimated with light detection and ranging (LIDAR) observations. With respect to ecosystem conditions, we found that forest types and ecosystems dominated by coniferous trees had less redundancy between the remote sensing indicators when compared to broadleaf or mixed forest types. Likewise, higher productivity environments exhibited the least redundancy between indicators, in contrast to more environmentally stressed regions. We suggest that biodiversity researchers continue to exploit multiple dimensions of remote sensing data given the complementary information they provide on structure and function focused EBVs, which makes them jointly suitable for monitoring forest ecosystems. [ABSTRACT FROM AUTHOR]

Riparian buffer zones (RBZs) are an important instrument for environmental policies for water and biodiversity protection in managed forests. We investigate the variation of the cost of implementing RBZs within different property size classes across the size range of non-industrial forest owner properties in Southern Sweden. Using the Heureka PlanWise decision support system, we quantified the cost of setting aside RBZs or applying alternative management in them, as the relative loss of harvest volume and of net present value per property. We did this for multiple simulated as well as real-world property distributions. The variation of cost distribution among small properties was 4.2–6.9 times higher than among large properties. The interproperty cost inequality decreased non-linearly with increasing property size and levelled off from around 200 ha. We conclude that RBZs, due to the irregular distribution of streams, cause highly unequal financial consequences for owners, with some small property owners bearing a disproportionally high cost. This adds to previous studies showing how environmental considerations differentially affect property owners. We recommend decision makers to stimulate the uptake of RBZs by alleviating these inequalities between forest owners by including appropriate cost sharing or compensation mechanisms in their design. [ABSTRACT FROM AUTHOR]

The spatial divergence of climatic changes necessitates the creation of predictive models of the state of vegetation cover. Our proposed solution for the spatial modeling of the biological productivity of natural ecosystems creates the basis for a further quantitative assessment of the potential absorption of CO2, which is currently considered one of the most urgent environmental issues. In the proposed work, using the methods of geoanalysis of growing conditions, an original technology for modeling the potential spread of biocenoses and their productivity has been developed, reflecting the internal attractor of the development of biocenoses under the influence of local hydrological and climatic conditions of their growth. The methodology was implemented for the southeast of Western Siberia within the framework of publicly available GIS Saga based on a digital terrain model and data from the WorldClim 2.0 climate reanalysis. To forecast data for the period of the third decade of the 21st century, V.V. Paromov's regional climate forecast was used on the basis of an adaptive model—the exponential smoothing method. The verification of the simulation results was carried out on the basis of the Productivity of Ecosystems of Northern Eurasia database. As a result, spatially distributed data were obtained in the form of rasters with high spatial resolution for the average long-term potential bioproductivity according to reanalysis data for 1970–2000 and predicted data for 2021–2030. Both positive and negative trends of potential bioproductivity for various natural zones of the southeast of Western Siberia due to the spatial divergence of changes in heat and energy resources and precipitation over the territory have been revealed. In general, warming in sufficiently drained areas contributes to an increase in the biological productivity of agro and biocenoses and, in hydromorphic areas, to a decrease. [ABSTRACT FROM AUTHOR]

In the Mediterranean region, inner rural and mountain areas suffered abandonment and land marginalization. Extensive conifer afforestations were established in these areas, which are particularly vulnerable to climate change and its associated risks. To identify critical areas where climate change could negatively impact forest vitality, we need to understand how the temporal variability of tree growth and its vulnerability to climate and drought have arisen and what their possible causes are. We used dendrochronological techniques to examine the effects of stand structure, physiography, and local climate variations in determining the growth dynamics of Aleppo pine plantations and temporal shifts in their susceptibility to hydroclimate and drought in semi-arid northeastern Spain. We found that structural traits strongly modulated growth dynamics and forest productivity. Young and small trees showed more synchronized growth and greater inter-annual ring width variability, and widely spaced trees in better quality stands had higher productivity. In contrast, temporal shifts in growth susceptibility to hydroclimate and drought were dependent on local physiography and climatic variability. Trees in low-elevation eastern stands with less continental conditions and milder winters showed decreasing dependence on water availability and increasing growth resistance and resilience to severe droughts. However, in high-elevation sites with wetter climates and cold winters, increasing growth response to water availability and decreasing resistance and resilience to drought were found. Our results highlight that adaptation to local physiographic and climatic conditions is a better strategy to mitigate the impacts of climate warming on Aleppo pine plantations in the semi-arid Mediterranean region. [ABSTRACT FROM AUTHOR]

Background: The Rio de la Plata grassland region is dominated by temperate grasslands, with the scarce natural forests, influenced floristically by adjacent biogeographical provinces. Uruguay represents the southern limit for many tree species of the Paranaense Province, several of which inhabit the hillside forests. With many species shifting poleward due to climate change, we do not yet know how current environmental factors, particularly climatic ones, are linked to the tree diversity of this flora nowadays. The aim of this study is to understand the geographic pattern of tree richness in the hillside forests of Uruguay, evaluating the water–energy and the environmental heterogeneity hypotheses. The distribution of the hillside forest trees was obtained by compiling and updating the herbaria database and distribution maps of woody plants of Uruguay. The presence/absence of each species, and then the species richness, were georeferenced over a grid that covers Uruguay with 302 cells (660 km2). Over the same grid were compiled environmental variables associated with climate and environmental heterogeneity. The relationship between richness and environmental variables was studied by applying general linear models (GLM). As a strong autocorrelation was detected, a residuals auto-covariate term was incorporated into the GLM, to take into account the species richness spatial structure. Results: The tree flora of the hillside forest was composed mainly by Paranaense species that show a latitudinal gradient, with two high richness cores, in the east and northeast of Uruguay. The final model including the environmental variables and the spatial term explained 84% of the variability of tree richness. Species richness showed a positive relationship with precipitation, forest cover, potential evapotranspiration and productivity, while a negative effect of temperature variation was found. The spatial component was the primary predictor, accounting for a 30% of spatial pattern of tree richness. Conclusions: This study accounts for a large proportion of the environmental and spatial variations of the tree richness pattern of the Paranense flora in its southernmost portion. It brings support to both water–energy and environmental heterogeneity hypotheses, emphasizing the role of climate and its variation and the habitat availability on the hillside forest diversity. [ABSTRACT FROM AUTHOR]

Background: Deciduous forests in eastern North America experienced a widespread and intense spongy moth (Lymantria dispar) infestation in 2021. This study quantified the impact of this spongy moth infestation on carbon (C) cycle in forests across the Great Lakes region in Canada, utilizing high-resolution (10 × 10 m2) Sentinel-2 satellite remote sensing images and eddy covariance (EC) flux data. Study results showed a significant reduction in leaf area index (LAI) and gross primary productivity (GPP) values in deciduous and mixed forests in the region in 2021. Results: Remote sensing derived, growing season mean LAI values of deciduous (mixed) forests were 3.66 (3.18), 2.74 (2.64), and 3.53 (2.94) m2 m−2 in 2020, 2021 and 2022, respectively, indicating about 24 (14)% reduction in LAI, as compared to pre- and post-infestation years. Similarly, growing season GPP values in deciduous (mixed) forests were 1338 (1208), 868 (932), and 1367 (1175) g C m−2, respectively in 2020, 2021 and 2022, showing about 35 (22)% reduction in GPP in 2021 as compared to pre- and post-infestation years. This infestation induced reduction in GPP of deciduous and mixed forests, when upscaled to whole study area (178,000 km2), resulted in 21.1 (21.4) Mt of C loss as compared to 2020 (2022), respectively. It shows the large scale of C losses caused by this infestation in Canadian Great Lakes region. Conclusions: The methods developed in this study offer valuable tools to assess and quantify natural disturbance impacts on the regional C balance of forest ecosystems by integrating field observations, high-resolution remote sensing data and models. Study results will also help in developing sustainable forest management practices to achieve net-zero C emission goals through nature-based climate change solutions. [ABSTRACT FROM AUTHOR]

Forest growth varies across landscapes due to the intricate relationships between various environmental drivers and forest management. In this study, we analysed the variation of tree growth potential across a landscape scale and its relation to soil moisture. We hypothesised that soil moisture conditions drive landscape-level variation in site quality and that intermediate soil moisture conditions demonstrate the highest potential forest production. We used an age-independent difference model to estimate site quality in terms of maximum achievable tree height by measuring the relative change in Lorey's mean height for a five year period across 337 plots within a 68 km2 boreal landscape. We achieved wall-to-wall estimates of site quality by extrapolating the modelled relationship using repeated airborne laser scanning data collected in connection to the field surveys. We found a clear decrease in site quality under the highest soil moisture conditions. However, intermediate soil moisture conditions did not demonstrate clear site quality differences; this is most likely a result of the nature of the modelled soil moisture conditions and limitations connected to the site quality estimation. There was considerable unexplained variation in the modelled site quality both on the plot and landscape levels. We successfully demonstrated that there is a significant relationship between soil moisture conditions and site quality despite limitations associated with a short study period in a low productive region and the precision of airborne laser scanning measurements of mean height. [ABSTRACT FROM AUTHOR]

In forests, the amount and diversity of structural features with high value for biodiversity, such as large trees and dead wood, are affected by productivity, stand age, and forest management. For efficient conservation of forest biodiversity, it is essential to understand the combined effects of these drivers. We used data from the Swedish National Forest Inventory to study the combined effects of productivity, stand age, and management for wood production on structures with high value for biodiversity: tree species richness, large living trees, dead wood volume, and specific dead wood types. Forest management changed the relationship between productivity and amount or diversity of some of the structures. Most structures increased with productivity and stand age, but decreased due to management. The negative effect of management was greatest for structures occurring mainly in high-productivity forests, such as deciduous dead wood. Thus, biodiversity conservation should target high-productivity forests to preserve these structures. [ABSTRACT FROM AUTHOR]

Preplaced aggregate concrete (PAC) also known as two-stage concrete (TSC) is widely used in construction engineering for various applications. To produce PAC, a mixture of Portland cement, sand, and admixtures is injected into a mold subsequent to the deposition of coarse aggregate. This process complicates the prediction of compressive strength (CS), demanding thorough investigation. Consequently, the emphasis of this study is on enhancing the comprehension of PAC compressive strength using machine learning models. Thirteen models are evaluated with 261 data points and eleven input variables. The result depicts that xgboost demonstrates exceptional accuracy with a correlation coefficient of 0.9791 and a normalized coefficient of determination (R2) of 0.9583. Moreover, Gradient boosting (GB) and Cat boost (CB) also perform well due to its robust performance. In addition, Adaboost, Voting regressor, and Random forest yield precise predictions with low mean absolute error (MAE) and root mean square error (RMSE) values. The sensitivity analysis (SA) reveals the significant impact of key input parameters on overall model sensitivity. Notably, gravel takes the lead with a substantial 44.7% contribution, followed by sand at 19.5%, cement at 15.6%, and Fly ash and GGBS at 5.9% and 5.1%, respectively. The best fit model i.e., XG-Boost model, was employed for SHAP analysis to assess the relative importance of contributing attributes and optimize input variables. The SHAP analysis unveiled the water-to-binder (W/B) ratio, superplasticizer, and gravel as the most significant factors influencing the CS of PAC. Furthermore, graphical user interface (GUI) have been developed for practical applications in predicting concrete strength. This simplifies the process and offers a valuable tool for leveraging the model's potential in the field of civil engineering. This comprehensive evaluation provides valuable insights to researchers and practitioners, empowering them to make informed choices in predicting PAC compressive strength in construction projects. By enhancing the reliability and applicability of predictive models, this study contributes to the field of preplaced aggregate concrete strength prediction. [ABSTRACT FROM AUTHOR]

Agroecology is identified as an important solution to increase the sustainability of agricultural and food systems. Despite the increasing number of publications assessing the socio-economic outcomes of agroecology, very few studies have consolidated the scattered results obtained on various case studies. This paper provides new insights by consolidating evidence on the varied socio-economic effects of agroecology across a large number of cases at a global level. To this purpose, we used a rapid review methodology, screening more than 13,000 publications to retrieve evidence on the socio-economic outcomes of the implementation of agroecological practices. The results of the review indicate that (1) agroecological practices are associated more often with positive socio-economic outcomes across the broad range of evaluated metrics (51% positive, 30% negative, 10% neutral, and 9% inconclusive outcomes); (2) the socio-economic metrics associated with financial capital represent the vast majority of evaluated metrics (83% of total) and are affected positively in a large share of cases (53%), due to favourable outcomes on income, revenues, productivity and efficiency; (3) human capital metrics (16%) are associated with a larger number of negative outcomes (46% versus 38% positive), due to higher labour requirements and costs that are however partly compensated by an overall greater number of positive outcomes on labour productivity (55%); and (4) the results vary depending on the agroecological practice assessed; e.g. for agroforestry, we identify 53% positive outcomes while for cropping system diversification 35%. These results indicate an overall favourable potential for farms to benefit from a positive socio-economic performance with the use of agroecological practices. Yet, the magnitude, temporal aspects, and success factors related to these outcomes, as well as the trade-offs between them, and the system-level effects of an agroecological transition are to be further assessed, since they can have an important influence on the performance of individual farms. [ABSTRACT FROM AUTHOR]

The steppes on the Mongolian Plateau cover a large land area of Mongolia (MG) and Inner Mongolia of China (IM). They share similar biophysical conditions, but have experienced divergent land use systems over the past several decades. However, no systematic field study has been done across different climate-vegetation zones for a comparison of the patterns of these steppes subject to different land use systems. We performed a field survey on 65 sites along four climatic transects, two in MG and two in IM, across desert steppe, typical steppe and meadow steppe zones, and investigated plant species composition, diversity and productivity. We compared these vegetation features between two regions, and attributed their variation patterns to climate and human activities. The results showed that plant species or plant functional group composition were similar between the two regions. However, plant productivity was significantly higher, whereas plant diversity indices were lower, in IM than MG. Aridity is the primary factor driving the spatial variation in plant diversity and productivity of the steppes across the Mongolian Plateau, while land use also has profound effects. The contrast vegetation pattern between MG and IM may be related with their difference in overgrazing history and grassland management strategies. These results suggest that overgrazing induced decline in plant productivity and its recovery is faster than the species diversity loss and recovery. Our results indicate that land use policies are urgently needed to promote destocking for preventing biodiversity loss in Mongolia, and that practical measures need to be developed to facilitate the recovery of species diversity in Inner Mongolia. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are expected to be vital in transitioning to a low-carbon energy system. However, integrating EVs into the power grid poses significant challenges for grid operators and energy suppliers, especially regarding the uncertainty and variability of EV charging demand. Accurate forecasting of EV charging demand is essential for optimal power system integration, yet previous studies have often only considered point predictions that are inadequate for risk assessment. Therefore, this paper compares different probabilistic forecasting models for the short-term prediction of EV charging demand at various aggregation levels, using a large and novel dataset of over 350,000 charging processes at more than 500 locations across Germany. The performance of both machine learning and deep learning methods is evaluated against a naïve benchmark model, and the impact of data availability on the forecasting models is investigated. Further, the paper examines the effects of forecast accuracy on energy procurement, which has so far received minor attention in the literature. The results show that machine learning methods such as Ada Boosting and Random Forest yield robust results with a normalized root mean square error of 0.42 and 0.41 and a mean absolute scaled error of 0.36 and 0.34 at the highest aggregation level. Furthermore, the results show the influence of different site compositions on the forecast quality and how many charging points are likely to yield a robust forecast. Energy and fleet managers can use the described method to reliably predict the required energy quantities for fleets of sufficient size and procure them at low risk. [ABSTRACT FROM AUTHOR]

In tree species, inbreeding due to selfing or biparental mating may decrease offspring adaptation and growth due to inbreeding depression (ID). Degenerative effects of ID, mainly reduction in productivity and survival, are undesirable for ex-situ conservation, improvement, and environmental and commercial reforestation of tree species. The effects of ID resulting from self-fertilization and biparental inbreeding were assessed for the traits cylindrical volume and survival in juvenile individuals of Hymenaea stigonocarpa in a progeny test (0.83 ha) at 4 and 7 years of age. The progeny test was established for ex situ conservation in the state of Mato Grosso, Brazil, and was based on seeds collected from a wild population. Nine microsatellite loci were used to genotype 48 adult (plot = 4.3 ha) and 612 juvenile samples to determine spatial genetic structure (for adults), inbreeding, mating system, and pollen dispersal pattern. Spatial genetic structure was observed up to 82 m. Reproduction occurred mainly by outcrossing, with low rates of selfing (7.5%) and biparental inbreeding (13.2%). Mating was not random due to the fat-tail pollen dispersal pattern, resulting in high pollen immigration (70.1%) and low mean pollen dispersal distance (105 m) within the sample area. Inbreeding was observed only in juveniles, indicating selection against inbred individuals between juvenile and adult stages. The volume trait showed higher ID for biparental inbreeding (41.5–44.0%) than for self-fertilization (29.1–42.6%). Volume also showed greater ID than survival. Our results show that even low rates of selfing and biparental inbreeding can decrease the productivity of H. stigonocarpa plantations. [ABSTRACT FROM AUTHOR]

Climate change adaptation and mitigation strategies (CCAMS) are changes to the management of production forests motivated by the need to mitigate climate change, or adapt production forests to climate change risks. Sweden is employing CCAMS with unclear implications for biodiversity and forest ecosystem services (ES). Here, we synthesized evidence from 51 published scientific reviews, to evaluate the potential implications for biodiversity and a range of provisioning, regulating, and cultural ES, from the adoption of CCAMS relative to standard forestry practice. The CCAMS assessed were the adoption of (i) mixed-species stands, (ii) continuous cover forestry, (iii) altered rotation lengths, (iv) conversion to introduced tree species, (v) logging residue extraction, (vi) stand fertilization, and (vii) altered ditching/draining practices. We highlight the complexity of biodiversity and ES outcomes, identify knowledge gaps, and emphasize the importance of evidence-based decision making and landscape-scale planning when navigating choices involving the widespread adoption of CCAMS. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to quantify the environmental impacts of Sitka spruce timber products harvested from the forestry sector in Ireland. This data is typically country-specific and is required to accurately quantify the environmental impacts associated with its production to better understand the impacts on the environment. Methods: A representative model utilising the ReCiPe midpoint approach is developed for the forest sector and the production of log products in Ireland from primary data collected from the national forestry agencies, boardmill and sawmills over a 12-month period, where the last two represent 100% and 67% of the national production volume, respectively. The model was analysed using Life Cycle Assessment (LCA) and the resulting environmental impacts of log production are presented for two different boundary conditions, namely 'cradle-to-forest road' and 'cradle-to-factory gate' which considers the transport of the logs for further processing. Results and discussion: The results are presented for the reference functional unit of 1 m3 of Sitka spruce log product but the results are also shown for 1 rotation of 1 ha of forest area, which allows comparisons with existing studies that utilise similar metrics such as a given area of forest. The results show that typically, clearfell operations are the most significant contributor to all impact categories. The contribution of the remaining operations in descending order of magnitude are thinning operations, forest road construction and maintenance, site preparation options, seedling production and finally forest maintenance operations. The extended model ('cradle-to-factory gate' model), which includes transport or delivery, has demonstrated a significant contribution due to transport alone where it was found to be responsible for, on average, 50% of each impact category presented (excluding land occupation) highlighting its significance. Conclusions: The underlying Life Cycle Inventory (LCI) data, which quantifies the total outputs of emissions and substances to air, land and water, is presented. It can be seen that the contribution of different operations varies significantly dependent on the log type which provides important data which can be further incorporated into future studies for downstream products utilised in the construction industry. [ABSTRACT FROM AUTHOR]

Determining the patterns of changes in the productivity of agricultural land in different growing areas in the zone of influence of State Protective Forest Belts (SPFB) is relevant due to the need to assess the future crop yield in fields with differences in geomorphological, soil, and climatic conditions in the research area. The object was to study the sowing of winter grain crops in fields mixed within the influence of State Protective Forest Belts. Materials and methods involved a research methodology based on the geoinformation analysis of the results of the decryption of actual satellite images, both to identify the distribution of cultivated fields located in the zone of influence of SPFB, and the state of crops on them. At the same time, the soil zonality of the research area was taken into account in view of the considerable length of forest strips. The assessment of the condition of winter grain crops as they move away from the planting was carried out using the NDVI vegetation index calculated from the high-resolution spectral channels of satellite images. Results and conclusions: based on the results of the research, a database of spatial data of the processed fields has been compiled. The grouping of fields was carried out both according to the similarity of the conditions of the places of cultivation of crops and by agricultural crops. Their placement and geomorphological parameters have been established. With the use of geoinformation technologies for groups of fields using statistical processing tools, the average values of the width and area of the selected zones of influence, as well as terrain parameters, were determined. During geoinformation mapping, data on the state of crops at the end of May were obtained based on the change in the NDVI index by field groupings in the zone of SPFB impact. These data are the basis for the forecast of crop yields, taking into account the spatial location of fields. [ABSTRACT FROM AUTHOR]

Peculiarities of the compositionally pure larch stand formation following forest fires have been studied in the northern (Evenkia, middle course of the Nizhnyaya Tunguska River, 64°03′ N, 101°10′ E) and southern (Yermakovsky District, 52°23′ N, 93°33 ′ E) regions of Krasnoyarsk Krai. The structure, growth, and biological productivity of the forest restoration successions have been analyzed based on the materials from the sample plots. The highest phytomass value (in terms of total productivity) in larch stands is 1055.5 t abs. dry substances/ha at the age of 93 years. The structural ratio of the forest stands phytomass fractions naturally changes with an increase in their average age and density. An increase in the average age of a stand is associated with an increase in its above-ground and root phytomasses. At the same time, the relative proportion of the crown wood mass and needle mass in the total above-ground phytomass of a stand decreases. In 38-year-old larch forests, the proportion of crown mass is 18% and the share of stems is 82%. In 60-year-old forest stands, the total biomass of the crown wood and needles accounts for 14%, and the other 86% accounts for the stem weight. In the 93-year-old larch forest, the proportion of stem phytomass increases to 89%, and the proportion of combined crown wood and needles biomasses fall up to a minimum value of 11%. The maximum growth potential of the 56-year-old larch stands, according to the current increase in phytomass (in terms of total productivity), is realized at about 14.69 t abs. dry substances/ha per year. The young and middle-aged larch forests formed on the burnt areas have higher rates of growth and phytomass accumulation; in terms of the amount of fixed atmospheric carbon, they exceed the mature and overmature stands by more than two times. [ABSTRACT FROM AUTHOR]

Context: The forestry industry provides important goods, services and economic benefits, but timber harvest can adversely impact ecosystem services, including wildlife habitat. Timber harvest planning can integrate wildlife habitat quality through multi-objective optimization for timber harvest and wildlife habitat suitability. Objectives: Our objective was to develop a method to find optimal solutions for timber harvest and wildlife habitat suitability individually and concurrently, then apply the method to Roosevelt elk (Cervus elaphus roosevelti) on Afognak Island, Alaska. Methods: We developed three seasonal habitat suitability models using elk locations and landscape variables including historical timber harvest on Afognak Island, Alaska. We used threshold-accepting optimization over a 50-year planning horizon to maximize timber harvest yield and habitat suitability in each season, then used multi-objective goal-deviation optimization to simultaneously maximize timber harvest volume and seasonal habitat suitability. Results: The optimal solution for timber yield decreased seasonal average habitat suitability by 5.7%. Elk habitat suitability and corresponding optimal solutions varied seasonally; elk generally selected open landcovers and early- to mid-successional timber stands over late-successional and mature stands. Therefore, in the optimal solutions, stands were harvested before they reached maximum volume and few stands were harvested in early planning periods, resulting in a seasonal average loss of 17.5% yield. Multi-objective optimization decreased seasonal average suitability by 3.9% and yield by 1.4% compared to single-objective optimization. Conclusions: Our multi-objective optimization approach that incorporates data-driven habitat suitability models using open-source software can enable managers to achieve desired quantity and quality of wildlife habitat while providing for resource extraction. [ABSTRACT FROM AUTHOR]

Seasonal drought limits the growth of plantations. Functional traits are effective indicators to clarify the controlling factors of plantation productivity. In this study, four treatments were carried out for the juvenile Eucalyptus urophylla × E.grandis plantations as (1) no dry-season irrigation or conventional fertilization (C); (2) only dry-season irrigation (W); (3) only conventional fertilization (F); (4) dry-season irrigation and conventional fertilization (WF). During the two years of treatment, growth traits, gas exchange characteristics, and structural properties were measured. The results showed that both dry-season irrigation and conventional fertilization could promote the growth of E. urophylla × E. grandis plantations. The effect of fertilization on increasing biomass of E. urophylla × E. grandis (3 times that of C) was greater than that of dry-season irrigation (only 1.5 times that of C). The biomass of WF was significantly higher than that of F. Dry-season irrigation could play the greatest role in promoting growth only when soil nutrients were sufficient. E. urophylla × E. grandis increased the total leaf area per tree but not the single leaf photosynthetic capacity, indicating the increased growth reflected greater canopy light interception. Fertilization increased the growth of E. urophylla × E. grandis plantations more than irrigation alone, but combining fertilization and dry-season irrigation further improved biomass yields of the juvenile plantations. Therefore, suitable dry-season irrigation management should be considered in seasonally arid areas to further improve the productivity of conventional plantations with only fertilization. This study elucidated the mechanism of dry-season irrigation to enhance the productivity of Eucalyptus plantations by functional traits, which provided strong data support for enhancing the productivity of plantation forests in seasonal arid areas. [ABSTRACT FROM AUTHOR]

Coppice forests are socio-ecological systems especially rich in biodiversity. They have been transformed into high forest and abandoned across large areas of Europe over the past 200 years. Coppice loss is likely an important driver of insect declines. It is currently unclear whether habitat quality or decreasing connectivity of the remaining fragments is more important for the survival of insect populations. We related the abundance of two coppice-associated butterflies of conservation concern, Satyrium ilicis and Melitaea athalia, to indicators of habitat quality and habitat connectivity. We estimated butterfly densities using Distance Sampling along a successional gradient (time since last cut: 1–9 years; N = 130 plots) across one of the largest remaining simple oak-birch coppice landscapes in Central Europe. Both species reached abundance peaks within four to six years after the last cut, declining rapidly in abundance with subsequent succession. We found no evidence that coupe size, coppice availability and patch (= coupe) connectivity were related to the density of the species. Besides stand age, the cover of larval foodplants explained predicted butterfly densities well. Only Satyrium ilicis benefitted from high Red Deer densities. Implications for insect conservation: Our results suggest that habitat quality and sufficient availability of coppice of suitable age matters more than coupe size and fragmentation within a traditional managed coppice landscape. Coppice restoration aiming at the study species should ensure a shifting mosaic of successional habitat to provide a large availability of resprouting oak stools and bilberry vegetation that holds dense Melampyrum pratense stands. [ABSTRACT FROM AUTHOR]

Farmer Managed Natural Regeneration (FMNR) is a simple and inexpensive practice for restoring vegetation cover on degraded land, unlike reforestation. Current knowledge on the socioeconomic factors that may influence its adoption is limited. The objective of this study is to analyze the socioeconomic determinants of FMNR adoption by communities. 197 households were surveyed. The probit model was used to identify the socioeconomic determinants of adoption. The results show that ethnicity, access to external support, receptivity to technological innovations, mode of land acquisition and the importance of production are determining factors in the adoption of FMNR. According to farmers, FMNR contributes to improving soil fertility and soil moisture conservation (21% and 17% of farmers, respectively). According to them, the FMNR improves the supply of wood (18 %) and non-timber forest products (13 %). The main constraints to the scaling up of this practice are, respectively, illegal logging (42%), animal roaming (29%), and the difficulties of using animal traction in a farm having many trees/shrubs (12 %). These results provide an overview of the considerations to be integrated for the success of FMNR as a strategy to strengthen the resilience of communities and ecosystems to climate disturbances. [ABSTRACT FROM AUTHOR]

Context: In northern Europe, changes in forest ecosystem structures are commonly attributed to the ubiquitous impact of modern forestry. However, the starting point for modern forestry was not a pristine forest, but landscapes influenced for centuries by diverse human activities. Objectives: Our aims were to (1) describe spatial patterns of forest structure and species compositions over large scales in 1920s Finland, and to (2) analyze how these characteristics were influenced by human population and past land-uses. Methods: We mapped ca. 3000 systematic sample plots measured in the first Finnish National Forest Inventory (1921–1924) and produced a series of maps of large-scale variation in forest characteristics in upland forests. We analyzed forest age and size structures, and species compositions relative to human population and land-use data. Results: We found strong geographical and regional gradients in forest age and size structures, and tree species composition. Depending on the variable, these characteristics were at the stand-level best explained by human population density, reflecting the long history of various forest uses. Tree species composition was clearly associated with site productivity, but also with the history of slash-and-burn agriculture and forest grazing. Conclusions: Forest landscapes in the early twentieth century Finland exhibited a strong human fingerprint, visible as the abundance of young forests in populated areas, while in remote areas forest characteristics typical of natural forests prevailed. These gradients in human impact a century ago are still reflected as legacies in forest structure, a situation that needs consideration in management and restoration. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Climate change adaptation and mitigation strategies for production forests: Trade-offs, synergies, and uncertainties in biodiversity and ecosystem services delivery in Northern Europe." The correction addresses an error in the formatting of Table 1 in the original publication. The corrected version of Table 1, which outlines the expected implications of climate change adaptation and mitigation strategies for biodiversity and ecosystem services, is provided in the correction. The original article has been corrected. [Extracted from the article]

Context: Planted pine forests are highly abundant communities in the Mediterranean Basin. Being the result of past reforestation, these forests show high species and structural homogeneity. Diversification to conifer-broadleaved mixed forests is recommended to promote adaptation to climate change and increase their resilience to perturbations. Objectives: This study aims at evaluating how these planted pine forests will develop in the future as a result of the combined impacts of management and climate. Methods: We applied a forest landscape model (LANDIS-II) to simulate different climate scenarios and management strategies designed in cooperation with forest managers to assess their effects on the performance of planted pine forests and their change in terms of forest composition. Results: Climate change scenarios caused a shift in the phenological growth pattern of planted pine forests by reducing forest growth during summer and increasing photosynthetic productivity in spring and fall, particularly under high emission scenarios. Biomass increased through time and more strongly under climate change, but this increase differs among species, resulting in changes of forest types across the landscape. Our results portray natural succession as the main driver of forest change, but intensive management accelerated this process by limiting pine growth and promoting growth of oak species. Conclusions: Our results highlight the importance of active management on planted pine forests to favour mixed and climate-adapted ecosystems in shorter time scales than offered by succession alone. Moreover, our spatially explicit modelling approach helps to identify areas where lack of seed dispersal and/or competitive exclusion prevent natural diversification, providing useful recommendations for interventions. However, the modelling approach has some limitations since it does not consider natural disturbances. [ABSTRACT FROM AUTHOR]

Genomic selection (GS) is currently being used in the New Zealand radiata pine (Pinus radiata D. Don) breeding program to accelerate genetic gain. GS also has the potential to accelerate the deployment of genetic gain to the production forest through early selection. The increased rate of genetic gain in the breeding cycle will need to be transferred more quickly to realise that gain in the deployment population. GS selections will have lower accuracies than selections based on phenotypic data as currently practised; however, it is unknown how this will affect the genetic gain from GS-based deployment. Moreover, census size and turnover rate need to be optimised to cope with the influx of new marker-based selected material into a commercial orchard. We utilised a stochastic simulation approach to investigate these concepts, comparing three deployment scenarios: half-sib open-pollinated orchards (OP), full-sib control-pollinated orchards (CP) and clonal deployment through somatic embryogenesis. When accounting for time, genomic selection in OP, CP and clonal deployment pathways increased genetic gain by 9.5%, 15.9% and 44.6% respectively compared to phenotypic selection. The optimal orchard scenario would be genomic-selected control-pollination with a low census size (n = 40, males and females combined), low female turnover (5%) and a high male turnover (15–25%). This scheme balances high genetic gain with high seed yield while moderating the rate of inbreeding. [ABSTRACT FROM AUTHOR]

Empirical evidence of Taungya agroforestry program in Sudan was generated. The objectives were to examine the association between socio-economic characteristics of farmers and Tuangya practice, assess the program's contribution to farmers' income, and highlight farmers' major incentives and constraints. The purposive sampling technique was applied targeting 200 Taungya farmers. Data were collected using questionnaires, focus group discussions, key informant interviews, direct field observations, and document reviews. Descriptive statistics, the chi-square test, and a paired sample t-test were used to analyze the data. Study results showed that 77% of farmers were male, with an average age of 41 years. About 77% of farmers cultivate an average land area of 3.5 hectares. The chi-square result showed that socio-economic characteristics such as marital status, age, family size, year of participation, and educational level had a significant association with Taungya practice, while gender, main occupation, and land size had no significant association. The study revealed that Taungya agroforestry program contributed significantly to farmers' income. Evidence of that was the sharp reduction in mean annual costs from SDG 32,851.75 to SDG 25,107.50, and a substantial increase in the mean annual net incomes of the farmers from SDG 35,298.52 to SDG 91,839.50 before and after participation, respectively. Farmers' participation was encouraged by the high productivity within the forest and access to free fertile land. Contrary, lack of extension services and supervision from Forest National Corporation, overgrazing and crop destruction, land size limitation, and crop species restrictions were identified as major challenges. The study suggests that prioritizing extension services, providing live fencing, and reconsidering farmers' interest in having intercropping sorghum on their farms to improve their sustenance will overcome the constraints and further boost farmers' productivity. [ABSTRACT FROM AUTHOR]

Measurement of the recovery of wood stocks in logging areas in the Amazon helps to understand the efficiency of policies for the use and conservation of native forests. This work evaluated the effects of logging on the dynamics and production of commercial species in the short and medium term in a conservation unit in the state of Rondônia. Structural patterns of the species as a function of mortality and recruitment rates, patterns of average increment in diameter, and estimates of forest production in the short and medium term were analyzed. The study was carried out in an area designated as Annual Production Unit 2 of Forest Management Unit III of Jamari National Forest. In addition to legalized harvesting, there are reports of illegal logging in the area as of 2015. Inventory data from 2011, 2015, and 2018 were used, considering trees of commercial value with a diameter at breast height (DBH) greater than 10 cm. Mortality rate, recruitment, periodic annual increment, absolute tree density, basal area, and commercial volume, by species and DBH classes, as well as the similarity of the species regarding the growth pattern. The population structure of species over the years was affected by tree mortality, mainly due to damage caused by illegal logging. Mean increment values varied by species and diameter classes, and six species represented 72% of the total volume of wood stock. It is important to review the criteria for sustainable forest production in the long term. Thus, it is necessary to promote species diversity and improve public authorities' capacity to enforce and of the private sector to comply with legislation. This, in turn, will enable the development of strategies to make the consumption of legal wood more rational. [ABSTRACT FROM AUTHOR]

Causal effects of biodiversity on ecosystem functions can be estimated using experimental or observational designs — designs that pose a tradeoff between drawing credible causal inferences from correlations and drawing generalizable inferences. Here, we develop a design that reduces this tradeoff and revisits the question of how plant species diversity affects productivity. Our design leverages longitudinal data from 43 grasslands in 11 countries and approaches borrowed from fields outside of ecology to draw causal inferences from observational data. Contrary to many prior studies, we estimate that increases in plot-level species richness caused productivity to decline: a 10% increase in richness decreased productivity by 2.4%, 95% CI [−4.1, −0.74]. This contradiction stems from two sources. First, prior observational studies incompletely control for confounding factors. Second, most experiments plant fewer rare and non-native species than exist in nature. Although increases in native, dominant species increased productivity, increases in rare and non-native species decreased productivity, making the average effect negative in our study. By reducing the tradeoff between experimental and observational designs, our study demonstrates how observational studies can complement prior ecological experiments and inform future ones. Isolating the relationships between biodiversity and ecosystem functioning in natural ecosystems is challenging. Here, the authors apply a causal inference approach to observational data from grasslands and find a negative effect of biodiversity on productivity driven by non-native and rare species. [ABSTRACT FROM AUTHOR]

Forests play a major role in the global carbon cycle, and droughts have been shown to explain much of the interannual variability in the terrestrial carbon sink capacity. The quantification of drought legacy effects on ecosystem carbon fluxes is a challenging task, and research on the ecosystem scale remains sparse. In this study we investigate the delayed response of an extreme drought event on the carbon cycle in the mixed deciduous forest site 'Hohes Holz' (DE-HoH) located in Central Germany, using the measurements taken between 2015 and 2020. Our analysis demonstrates that the extreme drought and heat event in 2018 had strong legacy effects on the carbon cycle in 2019, but not in 2020. On an annual basis, net ecosystem productivity was ∼ 16 % higher in 2018 ( ∼ 424 g C m - 2 ) and ∼ 25 % lower in 2019 ( ∼ 274 g C m - 2 ) compared to pre-drought years ( ∼ 367 g C m - 2 ). Using spline regression, we show that while current hydrometeorological conditions can explain forest productivity in 2020, they do not fully explain the decrease in productivity in 2019. Including long-term drought information in the statistical model reduces overestimation error of productivity in 2019 by nearly 50 % . We also found that short-term drought events have positive impacts on the carbon cycle at the beginning of the vegetation season, but negative impacts in later summer, while long-term drought events have generally negative impacts throughout the growing season. Overall, our findings highlight the importance of considering the diverse and complex impacts of extreme events on ecosystem fluxes, including the timing, temporal scale, and magnitude of the events, and the need to use consistent definitions of drought to clearly convey immediate and delayed responses. [ABSTRACT FROM AUTHOR]

Background and aims: Soil phosphorus (P) availability is a key factor determining primary productivity in forest ecosystems in arid and semiarid regions. Under P deficient conditions, phoD-harboring microorganisms secrete alkaline phosphatase, improving P bioavailability. However, their roles in aging plantations of leguminous trees is still unclear. Methods: Soil samples were collected from 8-, 18-, and 30-year-old stands of a Robinia pseudoacacia afforestation of degraded agricultural land. Soil P fractions, alkaline phosphatase activity, phoD gene abundance, and bacterial community structure were determined. An experiment with P addition in pots with tree seedlings was set up to check for short-term P transformation processes. Results: Soil inorganic P (Pi) and organic P (Po) in R. pseudoacacia afforestation stands mainly existed as stable Pi (NaOH-Pi) and moderately easily available Po (HCl-Po). The contents of all these soil P fractions except for HCl-Pi decreased with stand age, while alkaline phosphatase activity increased. Structural equation modelling (SEM) revealed that soil organic carbon (SOC), available phosphorus (AP) and labile-Po contents mediated the community composition, α diversity or abundance of phoD genes, thereby affecting alkaline phosphatase activity. SOC showed the strongest positive effect on alkaline phosphatase activity. The P addition experiment suggests that alkaline phosphatase activity was mainly regulated via soil C:P stoichiometry. Conclusion: SOC appears to be an important regulator of Po turnover in P deficient soils via phoD gene-harboring microbes. [ABSTRACT FROM AUTHOR]

Aims: Conversion from pure plantations to mixed plantations can significantly increase forest productivity and provide better ecosystem services, yet there is still a lack effective of assessment methods to determine how this conversion affects belowground biodiversity and ecological functions. Methods: We conducted an in-situ experiment to investigate the impacts of forest conversion (Cunninghamia lanceolata pure plantations vs. C. lanceolata-Betula luminifera mixed plantations) on soil multifunctionality, bacterial composition, network patterns and assembly mechanisms in southern subtropical China. Results: The results showed that compared with monoculture plantations, most soil physicochemical properties and enzyme activities were higher in mixed plantations. The mixed plantations increased bacterial α-diversity, and community structure differed between the two forest types. Network analysis showed that the network structure of the mixed plantation was more complex and stable, and contained more keystone taxa. Furthermore, stochastic processes primarily governed the assembly of bacterial communities. Forest conversion increased habitat niche breadth and the importance of stochastic processes. Based on PICRUSt2, the mixed plantations significantly increased soil multifunctionality and bacterial functions (e.g., carbohydrate metabolism and energy metabolism). Moreover, variations in the bacterial community and functionality were highly correlated with soil pH and nutrients. Conclusions: Our study showed that the conversion of monoculture plantations into mixed plantations enhances soil fertility and has more positive benefits. The changes in soil bacterial composition and function were mainly mediated by soil pH and nutrient increases caused by forest conversion, which contributes to assessing the eco-environmental effects of mixed planting in reforestation. [ABSTRACT FROM AUTHOR]

Emerald ash borer (Agrilus planipennis; EAB) has devastated populations of ash (Fraxinus spp.) trees in dozens of U.S. states and Canada over the past few decades. The continued survival of scattered ash trees known as "lingering ash" in heavily infested natural stands, however, offers evidence of genetic resistance or tolerance to EAB. These surviving or "lingering" ash individuals may form the basis for reforestation programs in EAB-impacted areas, and clonal mass-propagation of these genotypes can help accelerate these efforts. Between 2013 and 2018, we initiated embryogenic cultures by culturing immature zygotic embryos from open-pollinated (OP) seeds collected from several surviving white ash and green ash trees in Michigan and Pennsylvania. In addition, in 2018, we initiated cultures from crosses made between lingering green ash parents from the USDA Forest Service ash breeding program in Ohio. Somatic embryos were produced by growing cultures in liquid suspension, followed by fractionation and plating on semisolid medium to produce developmentally synchronous populations of somatic embryos. Somatic embryo germination and conversion were enhanced by a combination of pre-germination cold treatment and inclusion of activated charcoal and gibberellic acid in the germination medium. Ash somatic seedlings derived from OP explants grew rapidly following transfer to potting mix and somatic seedlings representing nine ash clones were acclimatized, grown in the greenhouse and planted in a preliminary field test, along with EAB-resistant Manchurian ash (F. mandshurica) and EAB-susceptible control seedlings. Somatic seedlings have now been produced from cultures that originated from seeds derived from the progeny of lingering green ash parents and an ex vitro germination protocol has shown some promise for accelerating early somatic seedling growth. Results of this research could provide the basis for scaled-up production of EAB-resistant ash varieties for seed orchard production for forest restoration and cultivar development for urban tree restoration. [ABSTRACT FROM AUTHOR]

Covering 35% of Europe's land area, forest ecosystems play a crucial role in safeguarding biodiversity and mitigating climate change. Yet, forest degradation continues to undermine key ecosystem services that forests deliver to society. Here we provide a spatially explicit assessment of the condition of forest ecosystems in Europe following a United Nations global statistical standard on ecosystem accounting, adopted in March 2021. We measure forest condition on a scale from 0 to 1, where 0 represents a degraded ecosystem and 1 represents a reference condition based on primary or protected forests. We show that the condition across 44 forest types averaged 0.566 in 2000 and increased to 0.585 in 2018. Forest productivity and connectivity are comparable to levels observed in undisturbed or least disturbed forests. One third of the forest area was subject to declining condition, signalled by a reduction in soil organic carbon, tree cover density and species richness of threatened birds. Our findings suggest that forest ecosystems will need further restoration, improvements in management and an extended period of recovery to approach natural conditions. Monitoring ecosystem conditions in quantitative and standardized ways could facilitate transnational coordination of conservation and land management policies. Here, the authors use a spatially explicit ecosystem accounting approach to assess the state of European forests and recent trends. [ABSTRACT FROM AUTHOR]

Nutrient limitation of tree growth can intensify when nutrients are lost to forest harvest, creating challenges for forest growth and sustainability. Forest harvest accelerates nutrient loss by removing nutrient-containing biomass and by increasing nutrient leaching, shaping patterns of nutrient depletion that cause long-term shifts in nutrient limitation. Nitrogen most frequently limits tree growth, but where nitrogen is abundant, nutrient limitation often shifts to phosphorus and base cations, depending on soil mineralogy. We used the process-based biogeochemical model NutsFor to evaluate how multiple elements can limit long-term forest growth via interactions between soil nitrogen (low vs. high nitrogen) and soil mineralogy (sedimentary vs. basaltic bedrock). Simulations were run for 525 years with 40-year harvest intervals for managed Douglas-fir forests of the Oregon Coast Range. In low nitrogen sites, nutrient limitation switched after several centuries from nitrogen to phosphorus, as cycles of forest growth and harvest depleted soil organic phosphorus pools. In contrast, high nitrogen sites displayed severe base cation depletion and reduced tree growth within only one to two rotations, with sedimentary bedrock sites limited by calcium and basaltic sites by both calcium and potassium. Harvesting stimulated the largest fractional losses of nitrogen and potassium across all simulations, and additionally of calcium in high nitrogen sites. These multi-element simulations of interactions among harvesting, soil nitrogen, and bedrock type provide a set of testable predictions to guide monitoring and changes in management aimed at sustaining long-term forest productivity across a wide range of soil biogeochemical conditions. [ABSTRACT FROM AUTHOR]

Thinning is an important forest management practice to mitigate the adverse effects of increased drought on tree growth and productivity. However, the responses of the soil microbial community and its functions to thinning and drought have received little attention in planted forests. In this study, we assessed the combined effects of thinning (30% and 45% of trees removed) and precipitation reduction (− 30%) on soil fungal and bacterial communities and the multifunctionality associated with carbon, nitrogen, and phosphorus cycling during one growing season (from April to September) in a 16-year-old larch plantation. We found that 45% thinning, but not 30%, significantly increased soil multifunctionality during the growing season (except for April and May) and fungal diversity in June. In contrast, precipitation reduction significantly decreased soil multifunctionality during the growing season and fungal diversity in June. Thinning also considerably suppressed the relative abundance of ectomycorrhizal (ECM) fungi during the growing season, whereas precipitation reduction significantly increased the relative abundance of ECM fungi in June and July. Furthermore, soil multifunctionality was more related to ECM and saprotrophic fungal communities than to bacterial communities. Our results suggest that a high thinning level can mitigate the negative effect of precipitation reduction on soil multifunctionality and fungal diversity, and this effect depends on the sampling month. Therefore, thinning is recommended as a tool to mitigate the impact of precipitation reduction on soil multifunctionality and the microbial community in larch plantations. [ABSTRACT FROM AUTHOR]

While forest productivity and biodiversity are expected to be correlated, prioritizing either forest productivity or biodiversity can result in different management. Spatial quantification of the congruence between areas suitable for either one can inform planning. Here we quantify the relationship between net primary productivity of European forests and biodiversity of mammals, birds, reptiles, amphibians, and butterflies both separately and in combination, and map their spatial congruence. We used richness maps obtained by stacking species distribution models for these animal species, and average net primary production from 2000 to 2012 using moderate resolution imaging spectroradiometer (MODIS) data. We tested how biodiversity and primary productivity are correlated and quantified the spatial congruence of these two sources. We show the areas where high or low productivity co-occur with high or low biodiversity using a quantile-based overlay analysis. Productivity was positively correlated to overall biodiversity and mammal, herptile and butterfly biodiversity, but biodiversity of birds showed a weak negative correlation. There were no significant differences in the strength of relationship across species groups, while herptiles had stronger relationships with productivity compared to other groups. Overlap analysis revealed significant spatial overlap between productivity and biodiversity in all species groups, except for birds. High value areas for both productivity and biodiversity in all species groups, except birds, co-occurred in the Mediterranean and temperate regions. The areas with high biodiversity of birds are mainly found in the boreal areas of Europe, while for all other species groups these areas are mostly located on the Iberian Peninsula and the Balkan ranges. Based on the presented maps, areas where regulating wood production activities to conserve species can be identified. But the maps also help to identify areas where either biodiversity or productivity is high and focusing on just one aspect is more straightforward. [ABSTRACT FROM AUTHOR]

Artificial intelligence has deeply revolutionized the field of medicinal chemistry with many impressive applications, but the success of these applications requires a massive amount of training samples with high-quality annotations, which seriously limits the wide usage of data-driven methods. In this paper, we focus on the reaction yield prediction problem, which assists chemists in selecting high-yield reactions in a new chemical space only with a few experimental trials. To attack this challenge, we first put forth MetaRF, an attention-based random forest model specially designed for the few-shot yield prediction, where the attention weight of a random forest is automatically optimized by the meta-learning framework and can be quickly adapted to predict the performance of new reagents while given a few additional samples. To improve the few-shot learning performance, we further introduce a dimension-reduction based sampling method to determine valuable samples to be experimentally tested and then learned. Our methodology is evaluated on three different datasets and acquires satisfactory performance on few-shot prediction. In high-throughput experimentation (HTE) datasets, the average yield of our methodology's top 10 high-yield reactions is relatively close to the results of ideal yield selection. [ABSTRACT FROM AUTHOR]

The question of whether biodiversity conservation and carbon conservation can be synergistic hinges on the form of the biodiversity–productivity relationship (BPR), a fundamental ecological pattern. The stakes are particularly high when it comes to forests, which at a global level comprises a large fraction of both biodiversity and carbon. And yet, in forests, the BPR is relatively poorly understood. In this review, we critically evaluate research on forest BPRs, focussing on the experimental and observational studies of the last 2 decades. We find general support for a positive forest BPR, suggesting that biodiversity and carbon conservation are synergistic to a degree. However, we identify several major caveats: (i) although, on average, productivity may increase with biodiversity, the highest-yielding forests are often monocultures of very productive species; (ii) productivity typically saturates at fewer than ten species; (iii) positive BPRs can be driven by some third variable, in particular stem density, instead of a causal arrow from biodiversity to productivity; (iv) the BPR's sign and magnitude varies across spatial grains and extents, and it may be weak at scales relevant to conservation; and (v) most productivity estimates in forests are associated with large errors. We conclude by explaining the importance of these caveats for both conservation programmes focussed on protection of existing forests and conservation programmes focussed on restoring or replanting forests. [ABSTRACT FROM AUTHOR]