Boosted Regression Tree Analysis Research Articles

Carbon sequestration potential and its main drivers in soils under alfalfa (Medicago sativa L.)

As a perennial forage crop, alfalfa (Medicago sativa L.) has been extensively utilized for the vegetation restoration of degraded soil and provides feedstock for forage. Its high usage can be attributed to its high yield potential and the increasing soil organic carbon (SOC) sequestration of alfalfa cultivation. However, the impact of land conversion to alfalfa on SOC content and its underlying drivers remain unclear. We performed a meta-analysis at the global scale to explore the quantified effects of alfalfa cultivation on SOC content and identify its controlling factors. We employed 1699 pairwise data points from 90 publications based on cropland/abandoned land conversion to alfalfa. Globally, cropland (cropland-alfalfa) and abandoned land (abandoned land-alfalfa) conversion to alfalfa enhanced SOC content by 12.1 % and 13.7 %, respectively. Alfalfa exhibited greater SOC content benefits in the surface soils (0–20 cm) with a lower level of initial SOC (<16 g kg−1), regardless of the land conversion type. Cropland-alfalfa was observed to increase SOC content with fertilization, irrigation, and conventional tillage in the long term (>5 years). Furthermore, abandoned land-alfalfa enhanced SOC content in the absence of alfalfa biomass removal and for longer cultivation durations (>5 years). Boosted regression tree analyses indicated variations in soil properties (75 % for cropland-alfalfa and 65 % for abandoned land-alfalfa) as the primary factors driving changes in SOC content. The dominant drivers were determined as the soil layer (51.6 %), cultivation duration (13.1 %), and initial SOC (12.9 %) for cropland-alfalfa, and initial SOC (43.7 %), soil layer (24.6 %) and cultivation duration (17.1 %) for abandoned land-alfalfa. Land conversion to alfalfa has great potential for SOC sequestration, particularly in low-fertility soils. Therefore, alfalfa cultivation is highly recommended for degraded lands due to its SOC sequestration benefits in vegetation restoration.

The Use of Boosted Regression Trees to Predict the Occurrence and Quantity of Staphylococcus aureus in Recreational Marine Waterways

Microbial monitoring in marine recreational waterways often overlooks environmental variables associated with pathogen occurrence. This study employs a predictive boosted regression trees (BRT) model to predict Staphylococcus aureus abundance in the Tampa Bay estuary and identify related environmental variables associated with the microbial pathogen’s occurrence. We provide evidence that the BRT model’s adaptability and ability to capture complex interactions among predictors make it invaluable for research on microbial indicator research. Over 18 months, water samples from 7 recreational sites underwent microbial quantitation and S. aureus isolation, followed by genetic validation. BRT analysis of S. aureus occurrence and environmental variables revealed month, precipitation, salinity, site, temperature, and year as relevant predictors. In addition, the BRT model accurately predicted S. aureus occurrence, setting a precedent for pathogen–environment research. The approach described here is novel and informs proactive management strategies and community health initiatives in marine recreational waterways.

Coupling and decoupling of soil carbon and nutrients cycles at different salinity levels in a mangrove wetland: Insights from CUE and enzymatic stoichiometry

Soil carbon (C), nitrogen (N), and phosphorus (P) cycling, in conjunction with microbial metabolism, varies significantly with salinity in coastal areas. However, microbial metabolism limitation on salinity levels has received limited attention. Based on soil microbial carbon use efficiency and enzymatic stoichiometry, microbial nutrient limitation characteristics of soil microbial communities in different salinity levels (4.45 mS·cm−1 - 17.25 mS·cm−1) in a subtropical mangrove wetland were investigated. Compared to low-salinity levels, the activity of soil C-acquiring enzyme activities, enzymatic C:N ratios and enzymatic C:P ratios decreased with medium salinity levels and high salinity levels. Soil microbial metabolism was primarily constrained by C and N at different salinity levels. Boosted regression tree analysis revealed that abiotic factors had the greatest influence on C and N limitation of microbial metabolism at different salinity levels. This study underscores the significance of salinity in microbial metabolic processes and enhances our understanding of how future salinity changes induced by rising sea levels will affect soil carbon and nutrient cycling in coastal wetlands.

Characteristics of dew/hoar frost from Artemisia ordosica and bare soil based on weighing lysimeters in a semi-arid region

Dew and hoar frost are important water resources in arid and semi-arid regions. However, knowledge of the characteristics of dew/hoar frost formation in the typical shrub canopy of Northwestern China and its importance for vegetation survival is still not clear as it is difficult to observe. In this study, we investigated dew/hoar frost formation characteristics under both Artemisia ordosica and bare soil conditions based on weighing lysimeters in Mu Us Sandy Land, Northwest of China. The results show that dew and hoar frost occurred 214 days for Artemisia ordosica and 162 days for bare soil. The hoar frost formation mainly occurs from October to March, while dew formation occurs every month. The amount of hoar frost was 19.6 mm under Artemisia ordosica condition and 17.4 mm under bare soil condition, and the amount of dew was 27.5 mm of Artemisia ordosica and 18.4 mm of bare soil. The most common daily amount of dew/hoar frost is between 0 and 0.2 mm, which accounts for 60.7 % and 52.5 % of dew/hoar frost formation days for the Artemisia ordosica and bare soil conditions, respectively. The results from boosted regression tree analysis indicated that relative humidity had the greatest influence on dew/hoar frost formation. During soil drought periods (July 15 to August 18, 2021), the soil water content of Artemisia ordosica kept constant at 0.061 cm3/cm3, while the soil water content of bare soil was dropped at the rate of 0.00135 (cm3/cm3)/d. The ratio of dew amount of Artemisia ordosica to rainfall amount was 42.1 %. Despite the small amount of dew, it serves as a frequent and important supplementary water source for the ecosystem. This study provided valuable insights into dew/hoar frost formation, especially its importance for vegetation survival.

Gafftopsail Catfish in Texas estuaries: Population trends and ecosystem implications

AbstractObjectiveGiven the limited information on population dynamics of Gafftopsail Catfish Bagre marinus in the western Gulf of Mexico, the objectives of this study were to determine the status of this species in Texas estuaries by assessing trends in relative abundance, length, and habitat preferences from fishery‐independent trawl (juvenile) and gill‐net (adult) data, as well as angler harvest trends from fishery‐dependent creel surveys collected in all Texas estuaries.MethodsFishery‐independent and ‐dependent monitoring data were collected by the Texas Parks and Wildlife Department in all major bay systems of the Texas coast from 1983 to 2022. Linear trend analysis was used to assess trends across the full time series and all major bay systems for both juvenile and adult specimens and for total recreational harvest. Boosted regression tree analysis was used to assess habitat preference for both juveniles and adults.ResultBoth juvenile and adult catch rates consistently increased in most Texas estuaries, with the most extreme increases occurring in central Texas coast estuaries beginning in the early 2000s. During the same time frame, mean lengths of adult specimens significantly decreased in many of the same estuaries. Habitat suitability analysis suggested that Gafftopsail Catfish were primarily influenced by salinity, though they still exist across a very broad range of salinity conditions. Angler catch rates showed some localized patterns of increasing or decreasing trends, though they generally did not follow fishery‐independent trends for most estuaries.ConclusionThese trends interpreted in the context of the known trophic role of Gafftopsail Catfish imply the potential for larger ecosystem‐level effects on both prey organisms and competitors. A more thorough awareness of these trends and potential interactions should help fisheries managers operate in an ecosystem‐based context when investigating population dynamics and recommending management strategies.

Investigation of the evolved pyrolytic products and energy potential of Bagasse: experimental, kinetic, thermodynamic and boosted regression trees analysis

This study explored bagasse's energy potential grown using treated industrial wastewater through various analyses, experimental, kinetic, thermodynamic, and machine learning boosted regression tree methods. Thermogravimetry was employed to determine thermal degradation characteristics, varying the heating rate from 10 to 30 °C/min. The primary pyrolysis products from bagasse are H2, CH4, H2O, CO2, and hydrocarbons. Kinetic parameters were estimated using three model-free methods, yielding activation energies of approximately 245.98 kJ mol−1, 247.58 kJ mol−1, and 244.69 kJ mol−1. Thermodynamic parameters demonstrated the feasibility and reactivity of pyrolysis with ΔH ≈ 240.72 kJ mol−1, ΔG ≈ 162.87 kJ mol−1, and ΔS ≈ 165.35 J mol−1 K-1. The distribution of activation energy was analyzed using the multiple distributed activation energy model. Lastly, boosted regression trees predicted thermal degradation successfully, with an R2 of 0.9943. Therefore, bagasse's potential as an eco-friendly alternative to fossil fuels promotes waste utilization and carbon footprint reduction.

Occurrence, multiphase partitioning, drivers, and ecological risks of current-use herbicides in a river basin dominated by rice–vegetable rotations in tropical China

Rice–vegetable rotation practices prevail in subtropical and tropical agriculture worldwide, with applications of current-use herbicides (CUHs) vital for nontarget plant control. After application, CUHs migrate to environmental compartments, where the occurrence, fate, and ecological risks have not been well characterized. To further understand the occurrence and multiphase partitioning, as well as to evaluate potential drivers and mixture risks in environmental compartments, we analyzed 11 CUHs in 576 samples from 36 rice–vegetable rotations in Nandu River basin, Hainan, China. Samples included soil, water, suspended particulate matter, and sediment collected during both rice and vegetable planting periods. The CUH concentrations varied across environmental compartments, but with high levels of glyphosate and aminomethylphosphonic acid organophosphorus herbicides (OPHs) frequently detected, accounting for 82.3 % to 99.0 % in environmental compartments. Phenoxy acid (PAA) and chloroacetanilide (ANH) herbicides were detected at lower frequencies. Spatiotemporal variation was significantly different among OPHs, ANHs, and PAAs, with geographic and crop-related patterns most evident for CUHs rather than OPHs. Structural equation model, redundancy, and boosted regression tree analyses indicated environmental compartment properties (pH, organic matter, and Fe/Al oxides), crop type, and wet/dry climate were important drivers of spatiotemporal patterns. Fugacity ratios indicated multiphase partitioning and transport of CUHs differed in rice and vegetable planting periods. A new assessment framework based on species-sensitive distributions and environmental compartment weight index indicated unacceptable risks of CUHs (risk quotient >1 in >50 % of sites), with most risks from OPHs (10.5 % to 98.0 %) and butachlor, acetochlor, and 2,4-dichlorophenoxyacetic acid. Risk hot spots were identified as the soil, the central region, and the vegetable planting period, potentially threatening nontarget organisms (e.g., Lemna minor, Glomus intraradices, and Apis mellifera). This study provides a new risk assessment framework and demonstrates the domination of OPHs in CUH contamination and risks in the tropics, thus helping guide policymakers and stakeholders on herbicide management.

Temporal population genetic structure of Phormia regina (Diptera: Calliphoridae).

The genetic structure of forensically important blow fly (Brauer & Bergenstamm) (Diptera: Calliphoridae) populations has remained elusive despite high relatedness within wild-caught samples. This research aimed to determine if the implementation of a high-resolution spatiotemporal sampling design would reveal latent genetic structure among blow fly populations and to elucidate any environmental impacts on observed patterns of genetic structure. Adult females of the black blow fly, Phormia regina (Meigen) (Diptera: Calliphoridae), were collected from 9 urban parks in Indiana, USA over 3 yr and genotyped at 6 polymorphic microsatellite loci. The data analysis involved 3 clustering methods: principal coordinate analysis (PCoA), discriminant analysis of principal components (DAPC), and STRUCTURE. While the PCoA did not uncover any discernible clustering patterns, the DAPC and STRUCTURE analyses yielded significant results, with 9 and 4 genetic clusters, respectively. Visualization of the STRUCTURE bar plot revealed N = 11 temporal demarcations indicating barriers to gene flow. An analysis of molecular variance of these STRUCTURE-inferred populations supported strong temporally driven genetic differentiation (FST = 0.048, F'ST = 0.664) relative to geographic differentiation (FST = 0.009, F'ST = 0.241). Integrated Nested Laplace Approximation and Boosted Regression Tree analyses revealed that collection timepoint and 4 main abiotic factors (temperature, humidity, precipitation, and wind speed) were associated with the genetic subdivisions observed for P. regina. A complex interplay between environmental conditions, the unique reproductive strategies of the blow fly, and the extensive dispersal abilities of these organisms likely drives the strong genetic structure of P. regina in the Midwestern US.

Ecosystem and soil respiration radiocarbon detects old carbon release as a fingerprint of warming and permafrost destabilization with climate change.

The permafrost region has accumulated organic carbon in cold and waterlogged soils over thousands of years and now contains three times as much carbon as the atmosphere. Global warming is degrading permafrost with the potential to accelerate climate change as increased microbial decomposition releases soil carbon as greenhouse gases. A 19-year time series of soil and ecosystem respiration radiocarbon from Alaska provides long-term insight into changing permafrost soil carbon dynamics in a warmer world. Nine per cent of ecosystem respiration and 23% of soil respiration observations had radiocarbon values more than 50‰ lower than the atmospheric value. Furthermore, the overall trend of ecosystem and soil respiration radiocarbon values through time decreased more than atmospheric radiocarbon values did, indicating that old carbon degradation was enhanced. Boosted regression tree analyses showed that temperature and moisture environmental variables had the largest relative influence on lower radiocarbon values. This suggested that old carbon degradation was controlled by warming/permafrost thaw and soil drying together, as waterlogged soil conditions could protect soil carbon from microbial decomposition even when thawed. Overall, changing conditions increasingly favoured the release of old carbon, which is a definitive fingerprint of an accelerating feedback to climate change as a consequence of warming and permafrost destabilization. This article is part of the Theo Murphy meeting issue 'Radiocarbon in the Anthropocene'.

Temporal and spatial characteristics of paddy soil potassium in China and its response to organic amendments: A systematic analysis

Understanding the role of organic amendments on soil potassium (K) distribution characteristics in Chinese paddy fields, we conduct a meta-analysis to explore the effect of organic amendment under different climatic and management practices. The meta-analysis consisted of 376 published papers from which 1294 paired observations were collected to evaluate the response of exchangeable K (EK) to different organic amendments in Chinese paddy soils. The results showed that EK concentration presented great variations (coefficient of variation: 44.5 %) and followed a decreasing trend from North to South and West to East, while higher EK concentration was detected in Northeast China, in 2020 s. Compared to the 2000s, the soil EK concentration in the 2020s significantly increased for the Northeast, Southwest, and East China. The highest EK concentrations were observed in Northeast (164 mg kg−1) and lowest values were observed in South China (71 mg kg−1). In case of organic amendments soil EK significantly increased compared to chemical fertilizers (CF), whereas the total K showed no significant differences in CF plus manure (CFM). The effects of organic amendments on soil K concentration revealed significant difference under various soil textures, cropping systems, and organic material types. The boosted regression trees analysis confirmed that the difference in K input for CF and CFM, and available phosphorus (AP) for straw combined with CF were the most influential variables on the variation of soil EK concentration. The structural equation modeling illustrated that organic amendments can directly and indirectly affect soil EK variation through increased K input and the regulation of crop K uptake and soil properties (total nitrogen and AP), respectively. These findings indicate that the organic amendments presented great potential for solving paddy soil K deficiency, as well as the types of organic material and soil properties should be carefully considered for greatest K use efficiency and lowest resource waste.

Soil potassium regulation by initial K level and acidification degree when subjected to liming: A meta-analysis and long-term field experiment

Potassium (K) is the most commonly neglected macronutrient in global change, especially in acidified areas. Lime is a typical management to eliminate soil acidification in agroecosystem soils; however, its impact on soil K dynamics remains inconsistent under different acidic environments. Here, we combine a meta-analysis based on 407 observations from 89 papers and a long-term experiment to investigate the effect and main driving factors of liming on soil K change. The meta-analysis showed that lime application significantly reduced topsoil exchangeable K (EK) content by an average of 4.8% globally. The decrease in topsoil EK content due to liming depended on various soil properties, crop types, fertilizer regimes, and experiment types. Boosted regression tree analysis showed that initial soil exchangeable K (IEK) and pH were the main factors affecting soil EK change under the lime application. The field experiment results further evidence that the decrease of soil EK after the lime application was mainly due to increased K uptake by the crop, and EK transformed to non-exchangeable K (NEK). The application of lime has a greater impact on reducing subsoil EK content at a higher IEK thresholds. Soil EK showed a significant negative relationship with exchangeable calcium (Ca) and a significant positive relationship with exchangeable aluminum (Al). Redundancy analysis revealed that K input (KI), IEK, lime, Ca, Al, pH, and exchangeable magnesium significantly affected the K in soil and crops. The partial least squares path model showed that lime application and IEK levels combined indirectly influence soil K (EK and NEK) by directly affecting soil Ca and Al, K uptake, and K balances. The findings highlight the importance of the lime effect on K management in globally adverse environmental agroecosystems and indicate the key role of initial soil EK levels and acidification degree for regulating crops to excavate the subsoil potassium when subjected to liming.

Tree species growth response to climate warming varies by forest canopy position in boreal and temperate forests.

Reports of forest sensitivity to climate change are based largely on the study of overstory trees, which contribute significantly to forest growth and wood supply. However, juveniles in the understory are also critical to predict future forest dynamics and demographics, but their sensitivity to climate remains less known. In this study, we applied boosted regression tree analysis to compare the sensitivity of understory and overstory trees for the 10 most common tree species in eastern North America using growth information from an unprecedented network of nearly 1.5 million tree records from 20,174 widely distributed, permanent sample plots across Canada and the United States. Fitted models were then used to project the near-term (2041-2070) growth for each canopy and tree species. We observed an overall positive effect of warming on tree growth for both canopies and most species, leading to an average of 7.8%-12.2% projected growth gains with climate change under RCP 4.5 and 8.5. The magnitude of these gains peaked in colder, northern areas for both canopies, while growth declines are projected for overstory trees in warmer, southern regions. Relative to overstory trees, understory tree growth was less positively affected by warming in northern regions, while displaying more positive responses in southern areas, likely driven by the buffering effect of the canopy from warming and climate extremes. Observed differences in climatic sensitivity between canopy positions underscore the importance of accounting for differential growth responses to climate between forest strata in future studies to improve ecological forecasts. Furthermore, latitudinal variation in the differential sensitivity of forest strata to climate reported here may help refine our comprehension of species range shift and changes in suitable habitat under climate change.

Cumulative effects of dams on migratory fishes across the conterminous United States: Regional patterns in fish responses to river network fragmentation

AbstractGlobally, dams fragment river networks, threatening migratory fishes which require access to distinct habitats to complete their life cycles. Efforts to understand how cumulative effects of multiple dams affect migratory fishes across large regions, such as a country or continent, could help to identify locations for connectivity‐enhancing actions to conserve migratory fishes. To address this, we evaluated cumulative effects of dams on migratory fishes in rivers across nine ecoregions of the conterminous USA. First, using fish data from thousands of sites (N = 45,989), we summarized ecoregional patterns in assemblages, quantifying the number of migratory species comprising assemblages, showing the prominence of potamodromous species across the large region as well as differences in migratory life history traits among ecoregions. Next, we compared the importance of a set of river network fragmentation metrics that captured influences of multiple dams in networks versus other anthropogenic landscape stressors and natural landscape factors that impact migratory fishes by ecoregion. We found that migratory fishes were more sensitive to cumulative dam effects than other stressors including urbanization and agriculture in the eastern USA. To further identify specific effects of environmental variables on potamodromous fishes, we conducted Boosted Regression Trees analysis in the eastern ecoregions. Our results suggested that the key natural influences on river fishes included catchment area as well as river baseflow and air temperature, suggesting that migratory fishes may be affected by changing climate. Additionally, we found that downstream dams were more influential than other human stressors to potamodromous fishes, underscoring the importance of enhancing connectivity within river networks to conserve migratory fishes. Collectively, our results provide new insights in identifying threats to migratory fish species across the USA, providing information that can aid in conserving this vulnerable but ecologically and socioeconomically important group of fishes.

Socio-ecological drivers of demersal fishing activity in the North Sea: The case of three German fleets

Worldwide, fisheries face the consequences of climate change and compete with expanding human activities at sea, which may trigger unforeseen reactions of fishers. Hence, knowledge on drivers of fishing behavior is crucial for management and needs to be integrated in resource management policies. In this study, we identify factors influencing fishing activity of North Sea demersal fleets. First, we explore drivers of the North Sea demersal fisheries in scientific literature. Subsequently, we study the effects of identified drivers on the spatio-temporal dynamics of German demersal fisheries using boosted regression trees (BRT), a supervised machine learning technique. An exploratory literature review revealed a lack of studies incorporating biophysical, economic and socio-cultural fishing drivers in a single quantitative analysis. Our BRT analysis contributed to filling this research gap and highlighted the importance of biophysical drivers such as temperature, salinity, and bathymetry for fishing behavior. Contrary to findings of previous studies, our empirical analysis identified quotas and market prices to be irrelevant, except for low brown shrimp prices, which counter-intuitively increased fishing effort. Moreover, economic and socio-cultural variables influencing brown shrimp fishing effort differed from the other fleets, especially determined by increased effort on workdays and reduced effort when fuel prices were high. Our findings provide key information for marine spatial planning and supports the integration of fishing fleet behavior into policies.

Assessment of Indoor Air Quality in Small and Medium Food Industries and Effects towards Perceived IAQ Symptoms

Background: Cooking activities generate pollutants that can cause adverse health effects to occupants. This study aims to characterize the indoor air environment in small and medium food enterprises (SMEs), as studies in this area are scarce. Methods: A series of field measurements were conducted to investigate the IAQ at 14 SMEs selected in Pulau Pinang for three different cooking methods (frying, boiling, and baking). Data on environmental perception and health symptoms were obtained from 76 workers by using a validated questionnaire. Boosted regression tree (BRT) analysis and parametric tests were performed to evaluate the impact of the IAQ on the prevalence of disease symptoms. Results: The results showed that CO2, temperature, and relative humidity were higher than the standard limits, while PM2.5 and TVOC were below the standard limits. Using BRT analysis, CO2 was indicated as the highest pollutant to cause complaints by workers (41.55%), followed by CO (21.93%), relative humidity (11.81%), temperature (10.66%), PM2.5 (7.07%), and TVOC (6.99%). This study indicated that workers in SMEs food industries are affected by the indoor air quality at their workplace in which CO2 was the main parameter influencing their health. This study suggests that future research focuses on boiling and frying SMEs with CO2, CO, temperature, and relative humidity to be afforded emphasis.

Identification of Key Antioxidants of Free, Esterified, and Bound Phenolics in Walnut Kernel and Skin.

Walnut is a natural source of antioxidants. Its antioxidant capacity is determined by the distribution and composition of phenolics. The key phenolic antioxidants in various forms (free, esterified, and bound) in walnut kernel (particularly seed skin) are unknown. The phenolic compounds in twelve walnut cultivars were analyzed using ultra-performance liquid chromatography coupled with a triple quadrupole mass spectrometer in this study. A boosted regression tree analysis was used to identify the key antioxidants. Ellagic acid, gallic acid, catechin, ferulic acid, and epicatechin were abundant in the kernel and skin. The majority of phenolic acids were widely distributed in the free, esterified, and bound forms in the kernel but more concentrated in bound phenolics in the skin. The total phenolic levels of the three forms were positively correlated with antioxidant activities (R = 0.76-0.94, p < 0.05). Ellagic acid was the most important antioxidant in the kernel, accounting for more than 20%, 40%, and 15% of antioxidants, respectively. Caffeic acid was responsible for up to 25% of free phenolics and 40% of esterified phenolics in the skin. The differences in the antioxidant activity between the cultivars were explained by the total phenolics and key antioxidants. The identification of key antioxidants is critical for new walnut industrial applications and functional food design in food chemistry.

Unravelling the influence of landscape alteration from flow alteration on benthic macroinvertebrate assemblage response in the Delaware River Basin

Quantifying the effects of streamflow alteration on assemblage response is central to understanding the role humans play in shaping aquatic environments. These changes represent a level of complexity that impedes developing quantitative links between flow and ecological response because stream hydrology is strongly intertwined with natural and anthropogenic factors. Better management outcomes require disentangling these linkages. Benthic macroinvertebrate data were combined with GIS-derived natural and anthropogenic basin characteristics to identify factors associated with changes in flow and assemblage characteristics. Models linking streamflow metrics and macroinvertebrate response at basin- and subregion-scales were developed using boosted regression tree (BRT) analysis. Basin-scale BRT analyses revealed that links between macroinvertebrate response and streamflow metrics were often obscured, whereas more homogeneous subregions were better able to discern relations with flow. Urban land cover was the primary factor accounting for changes in flow characteristics. Elevation, land cover and high flow frequency were the principal variables driving changes in assemblage structure within subregions. Assemblage metrics and traits were equally useful for building response models and were affected similarly by flow alteration. Our results indicate that response models based on upland and lowland subregions performed better than basin-scale models. However, when defining subregions, care should be taken to maintain data sufficiency. Developing practical flow-protection standards that support a balance between human water requirements and ecological integrity requires models that reduce uncertainty and identify management-relevant drivers. However, effective management often differs by location and models developed at the subregion level may be more applicable to management and stakeholder interests.

Association of Leopard Cat Occurrence with Environmental Factors in Chungnam Province, South Korea.

This study was conducted to investigate the association of leopard cat (Prionailurus bengalensis) occurrences and environmental factors in Chungnam Province, South Korea, using two different analytical approaches for binomial responses: boosted regression trees and logistic regression. The extensive field survey data collected through the Chungnam Biotope Project were used to model construction and analysis. Five major influential factors identified by the boosted regression tree analysis were elevation, distance to road, distance to water channel/body, slope and population density. Logistic regression analysis indicated that distance to forest, population density, distance to water, and diameter class of the forest were the significant explanatory variables. The results showed that the leopard cats prefer the areas with higher accessibility of food resources (e.g., abundance and catchability) and avoid the areas adjacent to human-populated areas. The results also implied that boosted regression and logistic regression models could be used in a complementary manner for evaluating wildlife distribution and management.

Rainfall partitioning by vegetation in China: A quantitative synthesis

Rainfall partitioning into stemflow, throughfall, and interception loss by vegetation alters hydrological and biogeochemical fluxes between vegetation and soil. Here, we compiled a comprehensive dataset of rainfall partitioning by forests, shrublands, croplands, and grasslands in China from 287 peer reviewed papers (71 in English and 216 in Chinese). Based on this dataset, we summarized the best-fit functions reported for rainfall partitioning (in both mm and %) as a function of rainfall amount, as well as the rainfall thresholds for throughfall and stemflow initiation. We explored the pattern of the proportions of stemflow, throughfall, and interception loss of vegetation in China, and performed boosted regression trees (BRT) analysis to model the relative effects of cross-site biotic and abiotic predictors on each of the rainfall partitioning fluxes (%). Our results identified the scarcity of rainfall partitioning data, particularly for grasslands. A substantial variability of each rainfall partitioning flux (mm) could be explained solely by rainfall amount, with median R2 values of 0.91, 0.99, and 0.82 for stemflow, throughfall, and interception loss, respectively, and with linear functions most often reported as the best-fit functions. Significant differences (p < 0.0001) were detected in rainfall thresholds for initiating stemflow (median: 3.3 mm; interquartile range, IQR: 1.8–5.4 mm) and throughfall (median: 1.2 mm; IQR: 0.8–2.2 mm). Stemflow (%) had a median (IQR) of 2.7 % (1.2–6.0 %), and that value was 74.3 % (66.7–80.3 %) for throughfall (%) and 21.6 % (16.3–28.5 %) for interception loss (%), respectively. Significant differences were detected in the proportion of stemflow (p < 0.001) and throughfall (p < 0.01) between forests and shrublands, respectively; whereas no significant differences in the proportion of interception loss were found among vegetation types. BRT analysis indicated that of the eleven biotic and abiotic predictors examined, six were classified as significant predictors in determining stemflow (%) and interception loss (%), respectively, whereas throughfall (%) had four significant predictors. Non-linear partial effects of predictors on rainfall partitioning fluxes were prevalent. This study avails a global readership to the findings of a large cache of Chinese studies that have been inaccessible hitherto, providing a mechanistic understanding of the effects of cross-site biotic and abiotic predictors on rainfall partitioning fluxes.

Structure and heterogeneity of habitat determine diet of predators despite prey abundance: Similar response in Long-eared, Short-eared Owls and Common Kestrels

According to one of the theses of optimal foraging theory, main prey species abundance in the hunting area is the main factor determining the diet and habitat choices of birds of prey. However other factors can also be important. The habitat structure influences the predators' diets as well. In this study we examined the influence of habitat structure on diet compositions of three species of birds: Long-eared Owl (Asio otus), Short-eared Owl (A. flammeus) and Common Kestrel (Falco tinnunculus). The study was carried out from 2007 to 2019 in a 48 ​km2 area of the Crane's Homeland Reserve, Moscow Region, Russia. The habitat structures of model species' hunting territories (ratio of different types of landscape elements) were classified in module “Semi-Automatic Classification Plugin” based on the QGIS. A boosted regression tree analysis identified that the share of the main prey species in the diet is primarily determined by the landscape structure of hunting territories. The largest share of Common Vole (Microtus arvalis) in birds' diet was determined by the shrubs area (15% of hunting area), the meadow area (75%), the habitat heterogeneity (70%) and the arable land area (5%). The same predictors determined the largest share of Root Vole (Microtus oeconomus): the shrubs area 25%, the meadow area 70%, and the arable land area 3%. The annual mean abundance of prey species did not determine their importance in the diet of birds of prey. Thus, the main prey abundance in the hunting area is not a determining factor for the formation of diet composition of birds of prey.