Duration of cochlear implant use in children with prelingual single-sided deafness is a predictor of word perception in the CI ear.

As part of a longitudinal study regarding the benefit of early cochlear implantation for children with single-sided deafness, the current work explored the children's daily device use, potential barriers to full-time device use, and the children's ability to understand speech with the cochlear implant (CI). Data were collected from 20 children with prelingual SSD who received a CI before the age of 2.5 years, from the initial activation of the sound processor until the children were 4.8 to 11.0 years old. Daily device use was extracted from the CI's data logging, while word perception in quiet was assessed using direct audio input to the children's sound processor. The children's caregivers completed a questionnaire about habits, motivations, and barriers to device use. The children with SSD and a CI used their device on average 8.3 h per day, corresponding to 63 % of their time spent awake. All children except one could understand speech through the CI, with an average score of 59 % on a closed-set test and 73 % on an open-set test. More device use was associated with higher speech perception scores. Parents were happy with their decision to pursue a CI for their child. Certain habits, like taking off the sound processor during illness, were associated with lower device use. Providing timely counselling to the children's parents, focused on SSD-specific challenges, may be helpful to improve daily device use in these children.

Effects of thinning and understory removal on soil phosphorus fractions in subtropical pine plantations.

Forest management changes the physical environments and nutrient dynamics and then regulates the forest productivity. Soil phosphorus (P) availability is critical for productivity in tropical and subtropical forests. However, it was still poorly understood how soil P content and fraction respond to various forest management practices in these regions. Here, we measured the soil total P, available P, and Hedley's P fractions, including inorganic and organic P (Pi and Po), in subtropical pine plantations treated with understory removal (UR), non-dominant species thinning (NDST) and dominant species thinning (DST) after nine years. Compared to plantations without management (CK), treatments such as UR, NDST, and DST decreased soil total P at 0-10 cm and soil available P at 0-10 cm and 10-20 cm. Increases in resin-Pi, NaOH-Pi, and C.HCl-Pi resulted in a higher total Pi in 0-10 cm (p < 0.05) in treated plots (UR, NDST, and DST) than in CK plots. UR, NDST, and DST treatments increased NaHCO3-Po and NaOH-Po (p < 0.05) but decreased C.HCl-Po at a depth of 0-10 cm. Regardless of management treatments, soil total P, available P, and P fractions in 0-10 cm showed higher contents than those in 10-20 cm. There were positive relationships between total P and total Po (p < 0.01) and between available P and total Pi. There were also positive relationships between total P, available P, NaHCO3-Pi, and NaOH-Pi (p < 0.05). In conclusion, forest management such as UR, NDST, and DST decreased soil total P and available P, and transforming soil P fractions to available P will meet the P demand following management in the pine plantations of subtropical China.

Variation in Nitrogen Utilization and Nutrient Composition across Various Organs under Different Strip Logging Management Models in Moso Bamboo (Phyllostachys edulis) Forest.

The rapid restoration and renewal of the moso bamboo logging zone after strip logging has emerged as a key research area, particularly regarding whether nutrient accumulation and utilization in reserve zones can aid in the restoration and regeneration of the logging zone. In this study, a dynamic 15N isotope tracking experiment was conducted by injecting labeled urea fertilizer into bamboo culms. Logging zones and reserve zones of 6 m, 8 m, and 10 m widths were established. The conventional selective logging treatment served as a control (Con). Measurements were taken in May and October to assess the differences in nitrogen accumulation ability, utilization rates, and nutrient content across different organs in bamboo forests at different growth stages and under different treatments. Principal component analysis was conducted to evaluate and determine the importance of each indicator and strip logging treatment comprehensively. The results showed that various bamboo organs exhibited higher nitrogen accumulation and utilization rates during the peak growth period compared to the late growth period. Leaves had the highest nitrogen accumulation and utilization rates than the other organs. The average C content in various bamboo organs under different logging treatments exhibited subtle differences, irrespective of variation in logging width treatments. Bamboo culm exhibited the highest carbon accumulation. The C content in various bamboo organs was higher during the peak growth period than in the late growth period. The nitrogen content peaked in the leaves during the two growth stages and was significantly higher compared to the other organs. Most bamboo organs in the logging zones exhibited relatively higher nitrogen content than in the reserve zone and Con group. The P content was highest in bamboo leaves compared with other organs across the different strip logging treatments. Principal component analysis revealed relatively high absolute values of the coefficients for the C content, bamboo stump C content, and culm Ndff%. Log8 and Res10 zones had the highest comprehensive evaluation scores, indicating that Log8 and Res10 had the best effect on the promotion of nitrogen utilization and nutrient accumulation in various organs of moso bamboo.

Advanced Monitoring of H2S Injection through the Coupling of Reactive Transport Models and Geophysical Responses.

Hydrogen sulfide (H2S), an environmentally harmful pollutant, is a byproduct of geothermal energy production. To reduce the H2S emissions, H2S-charged water is injected into the basaltic subsurface, where it mineralizes to iron sulfides. Here, we couple geophysical induced polarization (IP) measurements in H2S injection wells and geochemical reactive transport models (RTM) to monitor the H2S storage efforts in the subsurface of Nesjavellir, one of Iceland's most productive geothermal fields. An increase in the IP response after 40 days of injection indicates iron-sulfide formation near the injection well. Likewise, the RTM shows that iron sulfides readily form at circumneutral to alkaline pH conditions, and the iron supply from basalt dissolution limits its formation. Agreement in the trends of the magnitude and distribution of iron-sulfide formation between IP and RTM suggests that coupling the methods can improve the monitoring of H2S mineralization by providing insight into the parameters influencing iron-sulfide formation. In particular, accurate fluid flow parameters in RTMs are critical to validate the predictions of the spatial distribution of subsurface iron-sulfide formation over time obtained through IP observations. This work establishes a foundation for expanding H2S sequestration monitoring efforts and a framework for coupling geophysical and geochemical site evaluations in environmental studies.

Numerical Simulation Study on the Influence of Fracture on Borehole Wave Modes: Insights from Fracture Width, Filling Condition, and Acoustic Frequency.

Unconventional reservoirs, such as shale and tight formations, have become increasingly vital contributors to oil and gas production. In these reservoirs, fractures serve as crucial spaces for fluid migration and storage, making their precise assessment essential. Array acoustic logging stands out as a pivotal method for evaluating fractures. To investigate the impact of fracture width, fracture-filling conditions, and acoustic frequency on compressional and shear waves, a three-dimensional variable mesh finite difference program was employed for acoustic logging numerical simulation. Firstly, numerical models representing fractured formations with varying fracture widths and distinct fluid-filling conditions were established, and array acoustic logging numerical simulations were conducted at different frequencies. Subsequently, the waveform data were processed to extract acoustic characteristic parameters, such as velocities and amplitude attenuations of compressional and shear waves. Finally, a quantitative analysis was conducted to examine the variation patterns of characteristic parameters of refracted compressional and shear waves in relation to fracture properties. The research results indicate that amplitude attenuation information derived from borehole wave modes is particularly sensitive to the changes in fracture properties. As fracture width increased, we observed a significant amplitude attenuation in both compressional and shear waves, proportional to the logarithm of the attenuation coefficients. Furthermore, when the fracture width was constant, gas-filled fractures exhibited more prominent amplitude attenuation than water-filled fractures, with shear wave attenuation being more sensitive to the filling material. Moreover, from a quantitative perspective, the analysis revealed that the attenuation coefficients of refracted compressional and shear waves exhibited an exponential variation with gas saturation. Notably, once fracture width and filling conditions were established, the amplitudes of compressional and shear waves at the dominant frequency of 40 kHz were significantly reduced compared to those at 8 kHz, accompanied by increased attenuation. Subsequent quantitative analysis revealed that, when the product of fracture width and dominant frequency remains constant, the corresponding attenuation coefficient ratios approach 1. This indicates that the attenuation process of acoustic propagation in fractured media follows the principle of acoustic similarity. The findings of this study provide reference for further research on fracture property evaluation methods based on array acoustic logging data.

A Data Compression Method for Wellbore Stability Monitoring Based on Deep Autoencoder.

The compression method for wellbore trajectory data is crucial for monitoring wellbore stability. However, classical methods like methods based on Huffman coding, compressed sensing, and Differential Pulse Code Modulation (DPCM) suffer from low real-time performance, low compression ratios, and large errors between the reconstructed data and the source data. To address these issues, a new compression method is proposed, leveraging a deep autoencoder for the first time to significantly improve the compression ratio. Additionally, the method reduces error by compressing and transmitting residual data from the feature extraction process using quantization coding and Huffman coding. Furthermore, a mean filter based on the optimal standard deviation threshold is applied to further minimize error. Experimental results show that the proposed method achieves an average compression ratio of 4.05 for inclination and azimuth data; compared to the DPCM method, it is improved by 118.54%. Meanwhile, the average mean square error of the proposed method is 76.88, which is decreased by 82.46% when compared to the DPCM method. Ablation studies confirm the effectiveness of the proposed improvements. These findings highlight the efficacy of the proposed method in enhancing wellbore stability monitoring performance.

Sustainable extraction and conservation of soil resources: New insights through Natural Gamma-ray Spectrometry based Proximal Sensing Method.

Soil is one the most extracted natural raw materials. The vast expanses of fertile alluvial soils of the Indo Gangetic Plains have long remained as abundant soil resource pool for brick manufacturing and construction sectors. Unmonitored continuous removal of soil is reported to cause depletion of soil reserves, loss of soil fertility and affect crop yield. Excavation and removal of soil from isolated patches of land creates low lying and elevated degraded areas which disrupts normal crop cultivation pattern. Natural gamma-ray spectrometry (NGS) can be used as a non-destructive and rapid geophysical sensing method, for identification and delineation of areas with suitable soils. During this work brick kiln areas were visited to understand soil's availability and extraction pattern. NGS measurements of samples from soil profiles were carried out to find if gamma-ray intensities varied with soil clay content. Soil texture and plasticity of the same samples were obtained following standard testing procedures. Winkler and Plasticity charts were used to assess suitability of the soils. A strong linear relationship between gamma-ray potassium (K) intensity and clay contents of soil profile samples (R2 = 0.88) was observed. NGS based devices can be used to scan soil samples rapidly and log shallow depth boreholes in grid sampling design. The gathered spectral gamma-ray data can be then used to predict and generate high resolution 3D models of soil properties, based on which resource areas of suitable soils can be delineated for long term soil extraction without affecting cultivated areas. This will help in delineating areas restricted for soil extraction, which will not only make soil mining sustainable but also address soil conservation by setting aside large cultivated fertile soil areas untouched. Adopting NGS methods will prevent unsystematic removal of fertile soil and creation of degraded lands. This will ultimately result in efficient soil resource management.

How to treat mixed behavior segments in supervised machine learning of behavioural modes from inertial measurement data.

The application of supervised machine learning methods to identify behavioural modes from inertial measurements of bio-loggers has become a standard tool in behavioural ecology. Several design choices can affect the accuracy of identifying the behavioural modes. One such choice is the inclusion or exclusion of segments consisting of more than a single behaviour (mixed segments) in the machine learning model training data. Currently, the common practice is to ignore such segments during model training. In this paper we tested the hypothesis that including mixed segments in model training will improve accuracy, as the model would perform better in identifying them in the test data. We test this hypothesis using a series of data simulations on four datasets of accelerometer data coupled with behaviour observations, obtained from four study species (Damaraland mole-rats, meerkats, olive baboons, polar bears). Results show that when a substantial proportion of the test data are mixed behaviour segments (above ~ 10%), including mixed segments in machine learning model training improves the accuracy of classification. These results were consistent across the four study species, and robust to changes in segment length, sample size, and degree of mixture within the mixed segments. However, we also find that in some cases (particularly in baboons) models trained with mixed segments show reduced accuracy in classifying test data containing only single behaviour (pure) segments, compared to models trained without mixed segments. Based on these results, we recommend that when the classification model is expected to deal with a substantial proportion of mixed behaviour segments (> 10%), it is beneficial to include them in model training, otherwise, it is unnecessary but also not harmful. The exception is when there is a basis to assume that the training data contains a higher rate of mixed segments than the actual (unobserved) data to be classified-such a situation may occur particularly when training data are collected in captivity and used to classify data from the wild. In this case, excess inclusion of mixed segments in training data should probably be avoided.

Detecting changes in seafloor elevation in sandy coastal environments using low-cost opensource tooling.

Knowledge of sediment erosion and deposition can be useful for a variety of engineering, marine science, and environmental applications, but collecting detailed time-series measurements of the sediment-water interface can be challenging, particularly in coastal marine environments. We developed economical and open-source sediment level loggers to record sediment-water interface time-series data with accuracy up to 1 cm. The logger is composed of a programmable Circuit-Python (or Arduino) microcontroller and "breakout boards" that attach to a specially designed printed circuit board (PCB) and an array of evenly spaced photoresistors enclosed in a robust waterproof housing. These instruments were paired with temperature sensors in a study off the coast of Charleston, SC in the South Atlantic Bight where heat was used as a tracer to detect the flow of porewater in the permeable coastal sediments. This approach requires accurate knowledge of the depth of temperature sensors relative to the sediment-water interface. In this application, improved knowledge of the elevation of the sediment-water interface elevation data from the sediment level loggers reduced average root mean squared errors in modeling submarine groundwater discharge by as much as 25 %. The sediment level loggers can be easily installed, withstand long deployment times, and provide long-term recording abilities suitable for a range of environments.

Geophysical characterization of Saraswati River palaeochannel in parts of Yamuna Nagar and Kurukshetra districts of Haryana, India.

Palaeochannels are remnants of rivers or stream channels filled with younger sediments over the period of time. In ancient times, these rivers/channels were thriving in phenomenal conditions, but due to frequent tectonic activities, they lost the direction of their original path and were gradually either lost or buried under thick beds of younger alluvium. Palaeochannels act as reservoirs for fresh groundwater since they are made up of coarser sediments and were formerly flowing rivers. Depending on the groundwater regime and local topography, these could either be saturated or dry. The palaeochannels have high groundwater potential if saturated. These are ideal sites for artificial groundwater recharge, if dry. The identification of palaeochannels becomes quite challenging if they are buried under thick deposits of finer younger sediments. In the present study, an attempt has been made to characterize the Saraswati River Palaeochannel in parts of Yamuna Nagar and Kurukshetra districts of Haryana by using surface and subsurface geophysical methods. Till date, the palaeochannels in this area were mainly discerned on the basis of remote sensing only; therefore, geophysical characterization of these palaeochannels has been attempted in this study. In surface geophysical methods, electrical resistivity surveys, especially gradient resistivity profiling (GRP) and vertical electrical sounding (VES), were conducted in the study area, while electrical and natural gamma logging was used as subsurface geophysical approaches to identify the coarser sands of buried palaeochannels. The main objective of the study was to characterize the Saraswati River palaeochannel and analyze the quality of the groundwater stored in the palaeochannel in the study area. The findings were compared with the well-log data and were found in good agreement.

Design and performance of an epithermal neutron detector based on PFN.

In this paper, an epithermal neutron detector suitable for the Prompt Fission Neutron (PFN) uranium logging method is designed by Monte Carlo simulation. According to the simulation results, the epithermal neutron detector composed of a 1 mm cadmium (Cd) layer, a 5 mm high-density polyethylene (HDPE) layer, and a 3He tube is sensitive to epithermal neutrons. Through the simulation test of Monte Carlo in formations with different uranium content, the results show that the uranium content in the formation has an obvious linear relationship with E/T, and the detection limit can meet the minimum standard for uranium ore detection. It meets the design expectation and provides a basis for the optimal design of an epithermal neutron detector.

An inversion method for calculating formation and borehole parameters in X-ray lithology density logging.

The use of X-ray sources in place of the 137Cs sources used in traditional lithology density logging methods has become a new trend in the development of nuclear logging techniques. How to eliminate the effects of drilling fluids or mudcake in the measurement process is a key question that determines the accuracy of measurement. In order to reduce the effects of mudcake and improve the accuracy of measurement of formation parameters, this paper presents an inversion method that can accurately calculate formation and borehole parameters and is suitable for X-ray lithology density logging. The general process of this inversion method is described below. First, a response model for broad-beam attenuation during X-ray lithology density logging is derived. Subsequently, the responses of four detectors under various formation and borehole conditions are studied by means of Monte Carlo simulation, and the energy spectra measured by each detector are divided into four energy windows (ranges) depending on the correlation with formation parameters. Finally, accurate values of formation and borehole parameters are obtained through iterative inversion using the Levenberg-Marquardt (LM) algorithm. The results of this study show that compared with previously established analysis methods, the inversion method based on forward modeling can effectively improve the accuracy of measurement of formation density and lithology index during X-ray lithology density logging, reduce the influence of the borehole environment, and overcome the deficiencies of data processing techniques based on the spine and ribs plot.

Cumulative Effects of Watershed Disturbances and Run-of-river Dams on Mercury Cycling: Case Study and Recommendations for Environmental Managers.

Run-of-river power plants (ROR) represent the majority of hydroelectric plants worldwide. Their environmental impacts are not well documented and are believed to be limited, particularly regarding the contamination of food webs by methylmercury (MeHg), a neurotoxin. RORs are typically installed in small rivers where combined effects of watershed disturbances with dam construction can complicate environmental management. We report a multi-year case study on the Saint-Maurice River (Canada) where an unpredicted temporary increase in MeHg accumulation in predator fish was observed after the construction of two ROR plants. The associated pondages acted as sedimentation basins for mercury (Hg) and organic matter from a watershed disturbed by a forest fire and by logging. This fresh organic carbon likely fueled microbial MeHg production. Hg methylation was more associated with environmental conditions than to the presence of Hg, and main methylating microbial groups were identified. A constructed wetland was a site of significant Hg methylation but was not the main source of the fish Hg increase. Organic carbon degradation was the main driver of MeHg accumulation at the base of the food chain whereas trophic levels explained the variations at the top of the food chain. Overall, carbon cycling was a key driver of Hg dynamics in this system, and ROR plants can cause temporary (ca. 12 years) Hg increase in food webs when developed in disturbed watersheds, although this increase is smaller than for large reservoirs. Recommendations for future ROR construction are to establish a good environmental monitoring plan with initial high temporal resolution and to consider recent and potential watershed disturbances in the plan.

Research on trajectory control technology for L-shaped horizontal exploration wells in coalbed methane.

Horizontal wells have significant advantages in coal bed methane exploration and development blocks. However, its application in new exploration and development blocks could be challenging. Limited geological data, uncertain geological conditions, and the emergence of micro-faults in pre-drilled target coal seams make it hard to accurately control the well trajectory. The well trajectory prior to drilling needs to be optimized to ensure that the drilling trajectory is within the target coal seam and to prevent any reduction in drilling ratio (defined here as the percentage of the drilling trajectory in the entire horizontal section of the well located in the target coal seam) caused by faults. In this study, the well trajectory optimization is achieved by implementing the following process to drill pilot hole, acquire 2D resonance, and azimuthal gamma logging while drilling. The pilot hole drilling can obtain the characteristic parameters of the target coal seam and the top and bottom rock layers in advance, which can provide judgment values for the landing site design and real-time monitoring of whether the wellbore trajectory extends along the target coal seam; 2D resonance exploration can obtain the construction of set orientation before drilling and the development of small faults and formation fluctuations in the horizontal section, which can optimize the well trajectory in advance; the azimuth gamma logging while drilling technology can monitor the layers drilled by the current drill bit in real time, and can provide timely and accurate well trajectory adjustment methods.The horizontal well-Q in the Block-W of the Qinshui Basin was taken as a case study and underwent technical mechanism research and applicability analysis. The implementation of this new innovative process resulted in a successful drilling of a 711 m horizontal section, with a target coal seam drilling rate of 80%. Compared to previous L-type wells, the drilling rate increased by about 20%, and the drilling cycle shortened by 25%. The technical experience gained from this successful case provides valuable insight for low-cost exploration and development of new coalbed methane blocks.

Chronic anthropogenic disturbance mediates the bottom-up influence of plant diversity on arthropods in tropical forests.

Understanding how primary productivity and diversity affect secondary productivity is an important debate in ecology with implications for biodiversity conservation. Particularly, how plant diversity influences arthropod diversity contributes to our understanding of trophic cascades and species coexistence. Previous studies show a positive correlation between plant and arthropod diversity. The theory of associational resistance suggests that plant herbivory rate will decrease with increasing plant diversity indicating feedbacks between primary diversity, productivity, and secondary productivity rates. However, our understanding of how these relations are mediated by anthropogenic disturbance is still limited. We surveyed 10 forest sites, half of which are disturbed by fire, logging, and tree pruning, distributed in two climatic zones in Benin, West Africa. We established 100 transects to record plant species and sampled arthropods using pitfall traps, ceramic plates with bait, and sweeping nets. We developed a structural equation model to test the mediating effect of chronic anthropogenic disturbance on plant diversity and how it influences arthropod diversity and abundance. Arthropod diversity increased but arthropod abundance decreased with increasing intensity of disturbance. We found no significant bottom-up influence of the plant diversity on arthropod diversity but a significant plant diversity-arthropod abundance relationship. Some arthropod guilds were significantly affected by plant diversity. Finally, herbivory rates were positively associated with arthropod diversity. Synthesis. Our results highlight how chronic anthropogenic disturbance can mediate the functional links between trophic levels in terms of diversity and productivity. Our study demonstrated a decoupled response of arthropod diversity and abundance to disturbance. The direct positive influence of plant diversity on herbivory rates we found in our study provides counter-support for the theory of associational resistance.

How will climate change and forest harvesting influence the habitat quality of two culturally salient species?

Boreal landscapes face increasing disturbances which can affect cultural keystone species, i.e. culturally salient species that shape in a major way the cultural identity of a people. Given their importance, the fate of such species should be assessed to be able to act to ensure their perennity. We assessed how climate change and forest harvesting will affect the habitat quality of Rhododendron groenlandicum and Vaccinium angustifolium, two cultural keystone species for many Indigenous peoples in eastern Canada. We used the forest landscape model LANDIS-II in combination with species distribution models to simulate the habitat quality of these two species on the territories of three Indigenous communities according to different climate change and forest harvesting scenarios. Climate-sensitive parameters included wildfire regimes as well as tree growth. Moderate climate change scenarios were associated with an increased proportion of R. groenlandicum and V. angustifolium in the landscape, the latter species also responding positively to severe climate change scenarios. Harvesting had a minimal effect, but slightly decreased the probability of presence of both species where it occurred. According to the modeling results, neither species is at risk under moderate climate change scenarios. However, under severe climate change, R. groenlandicum could decline as the proportion of deciduous trees would increase in the landscape. Climate change mitigation strategies, such as prescribed fires, may be necessary to limit this increase. This would prevent the decrease of R. groenlandicum, as well as contribute to preserve biodiversity and harvestable volumes.

Threats to reptiles at global and regional scales.

Reptiles are an important, yet often understudied, taxon in nature conservation. They play a significant role in ecosystems1 and can serve as indicators of environmental health, often responding more rapidly to human pressures than other vertebrate groups.2 At least 21% of reptiles are currently assessed as threatened with extinction by the IUCN.3 However, due to the lack of comprehensive global assessments until recently, they have been omitted from spatial studies addressing conservation or spatial prioritization (e.g., Rosauer et al.,4,5,6,7,8 Fritz and Rahbek,4,5,6,7,8 Farooq et al.,4,5,6,7,8 Meyer et al., 4,5,6,7,8 and Farooq et al.4,5,6,7,8). One important knowledge gap in conservation is the lack of spatially explicit information on the main threats to biodiversity,9 which significantly hampers our ability to respond effectively to the current biodiversity crisis.10,11 In this study, we calculate the probability of a reptile species in a specific location being affected by one of seven biodiversity threats-agriculture, climate change, hunting, invasive species, logging, pollution, and urbanization. We conducted the analysis at a global scale, using a 50 km × 50 km grid, and evaluated the impact of these threats by studying their relationship with the risk of extinction. We find that climate change, logging, pollution, and invasive species are most linked to extinction risk. However, we also show that there is considerable geographical variation in these results. Our study highlights the importance of going beyond measuring the intensity of threats to measuring the impact of these separately for various biogeographical regions of the world, with different historical contingencies, as opposed to a single global analysis treating all regions the same.

Logging response alters trajectories of reorganization after loss of a foundation tree species.

Forest insect outbreaks cause large changes in ecosystem structure, composition, and function. Humans often respond to insect outbreaks by conducting salvage logging, which can amplify the immediate effects, but it is unclear whether logging will result in lasting differences in forest structure and dynamics when compared with forests affected only by insect outbreaks. We used 15 years of data from an experimental removal of Tsuga canadensis (L.) Carr. (Eastern hemlock), a foundation tree species within eastern North American forests, and contrasted the rate, magnitude, and persistence of response trajectories between girdling (emulating mortality from insect outbreak) and timber harvest treatments. Girdling and logging were equally likely to lead to large changes in forest structure and dynamics, but logging resulted in faster rates of change. Understory light increases and community composition changes were larger and more rapid in the logged plots. Tree seedling and understory vegetation abundance increased more in the girdled plots; this likely occurred because seedlings grew rapidly into the sapling- and tree-size classes after logging and quickly shaded out plants on the forest floor. Downed deadwood pools increased more after logging but standing deadwood pools increased dramatically after girdling. Understory light levels remained elevated for a longer time after girdling. Perhaps because the window of opportunity for understory species to establish was longer in the girdled plots, total species richness increased more in the girdled than logged plots. Despite the potential for greater diversity in the girdled plots, Betula lenta L. (black birch) was the most abundant tree species recruited into the sapling- and tree-size classes in both the girdled and logged plots and is poised to dominate the new forest canopy. The largest difference between the girdling and logging treatments-deadwood structure and quantity-will persist and continue to bolster aboveground carbon storage and structural and habitat diversity in the girdled plots. Human responses to insect outbreaks hasten forest reorganization and remove structural resources that may further alter forest response to ongoing climate stress and future disturbances.

Quantifying the impact of key factors on the carbon mitigation potential of managed temperate forests.

BACKGROUND: Forests mitigate climate change by reducing atmospheric CO 2 -concentrations through the carbon sink in the forest and in wood products, and substitution effects when wood products replace carbon-intensive materials and fuels. Quantifying the carbon mitigation potential of forests is highly challenging due to the influence of multiple important factors such as forest age and type, climate change and associated natural disturbances, harvest intensities, wood usage patterns, salvage logging practices, and the carbon-intensity of substituted products. Here, we developed a framework to quantify the impact of these factors through factorial simulation experiments with an ecosystem model at the example of central European (Bavarian) forests. RESULTS: Our simulations showed higher mitigation potentials of young forests compared to mature forests, and similar ones in broad-leaved and needle-leaved forests. Long-lived wood products significantly contributed to mitigation, particularly in needle-leaved forests due to their wood product portfolio, and increased material usage of wood showed considerable climate benefits. Consequently, the ongoing conversion of needle-leaved to more broad-leaved forests should be accompanied by the promotion of long-lived products from broad-leaved species to maintain the product sink. Climate change (especially increasing disturbances) and decarbonization were among the most critical factors influencing mitigation potentials and introduced substantial uncertainty. Nevertheless, until 2050 this uncertainty was narrow enough to derive robust findings. For instance, reducing harvest intensities enhanced the carbon sink in our simulations, but diminished substitution effects, leading to a decreased total mitigation potential until 2050. However, when considering longer time horizons (i.e. until 2100), substitution effects became low enough in our simulations due to expected decarbonization such that decreasing harvests often seemed the more favorable solution. CONCLUSION: Our results underscore the need to tailor mitigation strategies to the specific conditions of different forest sites. Furthermore, considering substitution effects, and thoroughly assessing the amount of avoided emissions by using wood products, is critical to determine mitigation potentials. While short-term recommendations are possible, we suggest risk diversification and methodologies like robust optimization to address increasing uncertainties from climate change and decarbonization paces past 2050. Finally, curbing emissions reduces the threat of climate change on forests, safeguarding their carbon sink and ecosystem services.

Bornean tropical forests recovering from logging at risk of regeneration failure.

Active restoration through silvicultural treatments (enrichment planting, cutting climbers and liberation thinning) is considered an important intervention in logged forests. However, its ability to enhance regeneration is key for long-term recovery of logged forests, which remains poorly understood, particularly for the production and survival of seedlings in subsequent generations. To understand the long-term impacts of logging and restoration we tracked the diversity, survival and traits of seedlings that germinated immediately after a mast fruiting in North Borneo in unlogged and logged forests 30-35 years after logging. We monitored 5119 seedlings from germination for ~1.5 years across a mixed landscape of unlogged forests (ULs), naturally regenerating logged forests (NR) and actively restored logged forests via rehabilitative silvicultural treatments (AR), 15-27 years after restoration. We measured 14 leaf, root and biomass allocation traits on 399 seedlings from 15 species. Soon after fruiting, UL and AR forests had higher seedling densities than NR forest, but survival was the lowest in AR forests in the first 6 months. Community composition differed among forest types; AR and NR forests had lower species richness and lower evenness than UL forests by 5-6 months post-mast but did not differ between them. Differences in community composition altered community-weighted mean trait values across forest types, with higher root biomass allocation in NR relative to UL forest. Traits influenced mortality ~3 months post-mast, with more acquisitive traits and relative aboveground investment favoured in AR forests relative to UL forests. Our findings of reduced seedling survival and diversity suggest long time lags in post-logging recruitment, particularly for some taxa. Active restoration of logged forests recovers initial seedling production, but elevated mortality in AR forests lowers the efficacy of active restoration to enhance recruitment or diversity of seedling communities. This suggests current active restoration practices may fail to overcome barriers to regeneration in logged forests, which may drive long-term changes in future forest plant communities.

A restauração ativa por meio de tratamentos silviculturais (plantio de enriquecimento, corte de trepadeiras e desbaste) é considerada uma intervenção importante em florestas com exploração de madeira. No entanto, sua capacidade de melhorar a regeneração, essencial para a recuperação de longo prazo das florestas exploradas, permanece pouco compreendida, especialmente no que diz respeito à produção e sobrevivência de mudas em gerações subsequentes. Para compreender os impactos de longo prazo da exploração madeireira e da restauração, acompanhamos a diversidade, sobrevivência e características de plântulas que germinaram imediatamente após uma frutificação em massa no norte de Bornéu, em florestas com e sem exploração de madeira, 30-35 anos após o fim da extração. Monitoramos 5119 mudas desde a germinação por aproximadamente 1,5 anos em uma paisagem mista de florestas não exploradas (UL), florestas exploradas em regeneração natural (NR) e florestas exploradas restauradas ativamente por meio de tratamentos silviculturais de reabilitação (AR), 15-27 anos após a restauração. Medimos 14 traços funcionais de folhas, raízes e alocação de biomassa em 399 mudas de 15 espécies. Logo após a frutificação, as florestas UL e AR apresentaram densidades de mudas mais altas do que as florestas NR, mas a sobrevivência foi mais baixa nas florestas AR nos primeiros seis meses. A composição da comunidade diferiu entre os tipos de floresta; as florestas AR e NR teviram menor riqueza de espécies e menor equidade do que as florestas UL 5-6 meses após a frutificação, mas não diferiram entre si. As diferenças na composição da comunidade alteraram os valores de média ponderada pela comunidade das características entre os tipos de floresta com maior alocação de biomassa radicular nas florestas NR em relação às florestas UL. As características influenciaram a mortalidade aproximadamente 3 meses após a frutificação, com traços mais aquisitivos maior investimento em biomassa relativa acima do solo nas florestas AR em relação às florestas UL. Nossas descobertas de redução na sobrevivência e diversidade de plântulas sugerem que há longos retardos no recrutamento após o fim da exploração de madeira, particularmente para alguns táxons. A restauração ativa de florestas exploradas recupera a produção inicial de plântulas, mas a mortalidade elevada nas florestas AR diminui a eficácia da restauração ativa no melhorio do recrutamento e da diversidade das comunidades de mudas. Isso sugere que as práticas atuais de restauração ativa podem não superar as barreiras à regeneração em florestas exploradas, o que pode levar a mudanças de longo prazo nas comunidades florestais no futuro.