Forest Values Research Articles

On the unique value of forests for water: Hydrologic impacts of forest disturbances, conversion, and restoration

AbstractWe need empirical evidence on the impacts of land‐use change on hydrological processes to guide policies and land management decisions. Based on a global meta‐analysis of 287 primary studies covering 1049 data points in 58 countries and across 12 biomes, we review hydrologic process changes resulting from native forest disturbances and conversions to other land‐use types. Infiltration rates consistently fell over 50%, overland flow increased and evapotranspiration as a share of rainfall declined when native forests were disturbed or converted. Changes in total evapotranspiration, interception, and streamflow were less consistent in direction, while restored native forests returned infiltration function rates to pre‐conversion levels. Forests, and perhaps especially native forests, have a unique value in supporting and regulating hydrologic processes, as they can reduce erosion, improve water infiltration, and potentially enhance water supply, including in downwind locations. We thus underscore global calls for increasing the proportion of reforested areas with native species in landscape restoration planned for this decade.

Potential Application of Natural Fibres for the Reinforcement of Unpaved Forest Roads—Response after RL-CBR Tests

Unpaved roads are essential as transportation infrastructure. These roads are traditionally built utilizing local soils and aggregates. The application of different materials to improve the strength and the overall performance of these road solutions has been investigated. This study focuses on the assessment of the suitability of reinforcing a fine soil using natural fibres from the forest value chain—specifically, pine needles—for unpaved forest roads. The resilient response of both unreinforced and reinforced soils was assessed with RL-CBR tests (California Bearing tests with repeated load) for different percentages of natural fibres incorporated into the soil. The force–penetration response, CBR value, recoverable and permanent displacements, and equivalent modulus were estimated. The effect of different load stages on the elastic response of both unreinforced and reinforced soils was also evaluated. The CBR values improved with the addition of pine needles; the best response was observed for specimens reinforced with 1% (mass) of these natural fibres (the CBR value increased by 45%). The equivalent modulus also was improved, showing that the stiffness of the soil increased with the inclusion of reinforcement. The findings imply that RL-CBR studies offer a promising method for obtaining important design parameters, especially for unpaved forest roads where investments in soil characterization are frequently limited.

Story of Conservation: Integrating Ethnobotanical Knowledge, Healer, and Sacred Area in Daulu–Karonese, North Sumatera

This article aims to explain the conservation mechanisms of a community to protect village forests; and how actors can create communities that maintain the value of forests as spaces for life's needs. This article focuses on ethnobotanical knowledge (especially medicines), transmission, healing practices, and forest protection mechanisms. The relationship between these four things is a story of sustainable conservation, both in-situ and ex-situ. This mechanism turns out to be related to mythology, sacredness, and sacred areas. This phenomenon was found in Karonese, Daulu Village, North Sumatra, Indonesia. The cognitive anthropology approach with the concept of culture in mind becomes an important tool for analyzing how knowledge is constructed and transmitted. Ethnographic research methods with an emic approach, participant observation, in-depth interviews with key informants, and completeness of filed notes are one way to capture the native point of view. Data analysis was carried out qualitatively through ongoing analysis. The conclusion of the study found that the capacity of actors, especially healers, and the transmission of ethnobotanical knowledge, especially medicines, and the survival of mythological stories and values about sacred areas have consequences for the sustainability of conservation of what they call the kerangen kuta or village forest.

Enhancing stakeholder engagement in sustainable forest management: A multi‐domain comparative analysis of forest‐related beliefs, values, and behaviors of Canadian Aboriginal and non‐Aboriginal groups

AbstractThe study aims to understand the variations in the domain‐specific pro‐sustainable‐forest‐management behavior (PSFMBs) and their explanatory factors across ecological, economic, recreational, and Aboriginal domains and between Aboriginal and non‐Aboriginal groups. A hybrid model of PSFMB, which integrates environmental psychology and resource economics perspectives, is conceptualized and estimated using multi‐group path analysis and data from three Aboriginal and three non‐Aboriginal communities in Ontario, Canada. Results show that both groups make substantial pro‐SFM contributions, but the contributions and their influencing factors differ across domains and groups. For Aboriginals, environmental worldviews and assigned forest values are the only influencing factors, while for non‐Aboriginals, income and forest environmental conditions play dominant roles. The findings confirm the fundamental differences in the roles of beliefs, values, and situational factors in influencing the PSFMB of Aboriginal and non‐Aboriginal groups, highlight the need for theoretical lenses that account for cultural differences, and contribute to the development of inclusive policies that respect the unique values of different social groups.

Comparison and Optimization of Water Conservation Function in Natural Forests and Tea Plantations in a Headwater Catchment, Taihu Lake Basin

The rapid expansion of tea plantations (Camellia sinensis), which replace local natural forests, decreases the water conservation function in the headwater region and threatens regional water security. However, studies focusing on the comprehensive evaluation and improvement of the water conservation function of natural forests and tea plantations are lacking. In this study, we developed a comprehensive evaluation method for the water conservation function by investigating, monitoring, and conducting process model simulations of 221 tea plantation and natural forest (bamboo forest) samples obtained in the field. We also quantified the trade-off between water conservation and carbon sequestration. The results showed that the tea plantations had lower annual water conservation than the bamboo forests. Slope was the most critical influential variable affecting water conservation in tea plantations. Strict control should be exercised in the development of steep slopes above 20° for tea plantations, to enhance the regional water conservation capacity. Water conservation in bamboo forests increased to the maximum level at a planting density (SD) of approximately 2500–2700 tree/ha and then decreased quickly. The optimal SD values of bamboo forests were 2500, 2600, and 2650 trees/ha at slopes of 10°, 15°, and 20°, respectively, which can maintain higher water conservation and adequate carbon sequestration. Overall, water conservation and carbon sequestration increased by approximately 22.6% and 13.7%, respectively, compared with the average values for bamboo forests. However, at slopes >20°, a strong trade-off was observed between water conservation and carbon sequestration, and competing ecosystem services accompanied those, which were hard to balance and which resulted here in disproportionate water conservation at the cost of carbon sequestration loss.

Clinical study of different prediction models in predicting diabetic nephropathy in patients with type 2 diabetes mellitus.

Among older adults, type 2 diabetes mellitus (T2DM) is widely recognized as one of the most prevalent diseases. Diabetic nephropathy (DN) is a frequent complication of DM, mainly characterized by renal microvascular damage. Early detection, aggressive prevention, and cure of DN are key to improving prognosis. Establishing a diagnostic and predictive model for DN is crucial in auxiliary diagnosis. To investigate the factors that impact T2DM complicated with DN and utilize this information to develop a predictive model. The clinical data of 210 patients diagnosed with T2DM and admitted to the First People's Hospital of Wenling between August 2019 and August 2022 were retrospectively analyzed. According to whether the patients had DN, they were divided into the DN group (complicated with DN) and the non-DN group (without DN). Multivariate logistic regression analysis was used to explore factors affecting DN in patients with T2DM. The data were randomly split into a training set (n = 147) and a test set (n = 63) in a 7:3 ratio using a random function. The training set was used to construct the nomogram, decision tree, and random forest models, and the test set was used to evaluate the prediction performance of the model by comparing the sensitivity, specificity, accuracy, recall, precision, and area under the receiver operating characteristic curve. Among the 210 patients with T2DM, 74 (35.34%) had DN. The validation dataset showed that the accuracies of the nomogram, decision tree, and random forest models in predicting DN in patients with T2DM were 0.746, 0.714, and 0.730, respectively. The sensitivities were 0.710, 0.710, and 0.806, respectively; the specificities were 0.844, 0.875, and 0.844, respectively; the area under the receiver operating characteristic curve (AUC) of the patients were 0.811, 0.735, and 0.850, respectively. The Delong test results revealed that the AUC values of the decision tree model were lower than those of the random forest and nomogram models (P < 0.05), whereas the difference in AUC values of the random forest and column-line graph models was not statistically significant (P > 0.05). Among the three prediction models, random forest performs best and can help identify patients with T2DM at high risk of DN.

Outlier detection using conditional information entropy and rough set theory

Outlier detection is critically important in the field of data mining. Real-world data have the impreciseness and ambiguity which can be handled by means of rough set theory. Information entropy is an effective way to measure the uncertainty in an information system. Most outlier detection methods may be called unsupervised outlier detection because they are only dealt with unlabeled data. When sufficient labeled data are available, these methods are used in a decision information system, which means that the decision attribute is discarded. Thus, these methods maybe not right for outlier detection in a a decision information system. This paper proposes supervised outlier detection using conditional information entropy and rough set theory. Firstly, conditional information entropy in a decision information system based on rough set theory is calculated, which provides a more comprehensive measure of uncertainty. Then, the relative entropy and relative cardinality are put forward. Next, the degree of outlierness and weight function are presented to find outlier factors. Finally, a conditional information entropy-based outlier detection algorithm is given. The performance of the given algorithm is evaluated and compared with the existing outlier detection algorithms such as LOF, KNN, Forest, SVM, IE, and ECOD. Twelve data sets have been taken from UCI to prove its efficiency and performance. For example, the AUC value of CIE algorithm in the Hayes data set is 0.949, and the AUC values of LOF, KNN, SVM, Forest, IE and ECOD algorithms in the Hayes data set are 0.647, 0.572, 0.680, 0.676, 0.928 and 0.667, respectively. The advantage of the proposed outlier detection method is that it fully utilizes the decision information.

Machine learning analysis with population data for the associations of preterm birth with temporomandibular disorder and gastrointestinal diseases.

This study employs machine learning analysis with population data for the associations of preterm birth (PTB) with temporomandibular disorder (TMD) and gastrointestinal diseases. The source of the population-based retrospective cohort was Korea National Health Insurance claims for 489,893 primiparous women with delivery at the age of 25-40 in 2017. The dependent variable was PTB in 2017. Twenty-one predictors were included, i.e., demographic, socioeconomic, disease and medication information during 2002-2016. Random forest variable importance was derived for finding important predictors of PTB and evaluating its associations with the predictors including TMD and gastroesophageal reflux disease (GERD). Shapley Additive Explanation (SHAP) values were calculated to analyze the directions of these associations. The random forest with oversampling registered a much higher area under the receiver-operating-characteristic curve compared to logistic regression with oversampling, i.e., 79.3% vs. 53.1%. According to random forest variable importance values and rankings, PTB has strong associations with low socioeconomic status, GERD, age, infertility, irritable bowel syndrome, diabetes, TMD, salivary gland disease, hypertension, tricyclic antidepressant and benzodiazepine. In terms of max SHAP values, these associations were positive, e.g., low socioeconomic status (0.29), age (0.21), GERD (0.27) and TMD (0.23). The inclusion of low socioeconomic status, age, GERD or TMD into the random forest will increase the probability of PTB by 0.29, 0.21, 0.27 or 0.23. A cutting-edge approach of explainable artificial intelligence highlights the strong associations of preterm birth with temporomandibular disorder, gastrointestinal diseases and antidepressant medication. Close surveillance is needed for pregnant women regarding these multiple risks at the same time.

Long-term dynamics of forests with Pinus sibirica in the upper reaches of the River Kolva (Northern Pre-Urals, Russia) from 1938 to 2023

Forest ecosystems have been impacted by human activity over several millennia in a variety of ways. Previous land use activity has not only changed the ratio of various terrestrial ecosystems, but also influenced the distribution of tree species. The insight into the forest species composition, dynamics and revealing how it differs from the modern one should be of decisive importance for the identification and conservation of the most valuable forests, as well as the restoration of ones previously disturbed. The density and distribution of some species continues to decline rapidly due to the anthropogenic activity. This problem is most urgent in boreal forests, formed by a limited set of tree species. Studies of the long-lived tree species dynamics and their ability to restore after various types of disturbances deserve special attention. Based on analysis of forest management materials from 1938 and 2023, this paper was aimed to analyse the dynamics of forests with the participation of Pinus sibirica in the Northern Pre-Urals (Permsky Krai, Russia), on the western border of the species' natural range. In 1938, the forests with Pinus sibirica occupied 16.6% of all forests in the research area. In 1938, most forests with Pinus sibirica (64%) were forests, in which P. sibirica was represented by only 1–5% of the stock. Pinus sibirica-dominated forests were almost absent, with only one site with 60% dominance of P. sibirica, and five sites with 40% dominance of P. sibirica. Over the next 85 years, the area of forests with Pinus sibirica participation in the research area has decreased by 2.5 times due to the impact of clear cuttings and forest fires. By 2023, the ratio of forest areas with various proportions of Pinus sibirica participation had changed considerably. The highest changes were found in forests with Pinus sibirica participation of 1%, 5% and 20% of the stock. Analysis of the typological structure of forests showed that at present Pinus sibirica has survived only in natural dark-coniferous forests, which have not been affected previously by forestry activities and fires. Due to the exceptionally slow regeneration following fires and logging activities, Pinus sibirica is absent in the forests formed over the studied period. The current federal legal restrictions prove ineffective as they target the preservation of forest stands containing over 30% of Pinus sibirica, while the majority of forests in the study area contain less proportion of this species. We believe that it is necessary to develop uniform measures to preserve existing and restore the lost Pinus sibirica populations in the Komi Republic and the Permsky Krai, including the prohibitions on the logging of forests with any proportion of Pinus sibirica as well as the creation of P. sibirica forest plantations.

Risk Prediction Model for Non-Suicidal Self-Injury in Chinese Adolescents with Major Depressive Disorder Based on Machine Learning.

Non-suicidal self-injury (NSSI) is a significant social issue, especially among adolescents with major depressive disorder (MDD). This study aimed to construct a risk prediction model using machine learning (ML) algorithms, such as XGBoost and random forest, to identify interventions for healthcare professionals working with adolescents with MDD. This study investigated 488 adolescents with MDD. Adolescents was randomly divided into 75% training set and 25% test set to testify the predictive value of risk prediction model. The prediction model was constructed using XGBoost and random forest algorithms. We evaluated the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, recall, F Score of the two models for comparing the performance of the two models. There were 161 (33.00%) participants having NSSI. Compared without NSSI, there were statistically significant differences in gender (P=0.035), age (P=0.036), depressive symptoms (P=0.042), sleep quality (P=0.030), dysfunctional attitudes (P=0.048), childhood trauma (P=0.046), interpersonal problems (P=0.047), psychoticism (P) (P=0.049), neuroticism (N) (P=0.044), punishing and Severe (F2) (P=0.045) and Overly-intervening and Protecting (M2) (P=0.047) with NSSI. The AUC values for random forest and XGBoost were 0.780 and 0.807, respectively. The top five most important risk predictors identified by both machine learning methods were dysfunctional attitude, childhood trauma, depressive symptoms, F2 and M2. The study demonstrates the suitability of prediction models for predicting NSSI behavior in Chinese adolescents with MDD based on ML. This model improves the assessment of NSSI in adolescents with MDD by health care professionals working. This provides a foundation for focused prevention and interventions by health care professionals working with these adolescents.

Integrating wind disturbances into forest planning: a stochastic programming approach

Forest disturbances challenge our ability to carefully plan for sustainable use of forest resources. As forest disturbances are stochastic, we cannot plan for the disturbance at any specific time or location. However, we can prepare for the possibility of a disturbance by integrating its potential intensity range and frequency when developing forest management plans. This study uses stochastic programming to integrate wind intensity (wind speed) and wind event frequency (number of occurrences) into the forest planning process on a small coastal Finnish forest landscape. We used a mechanistic model to quantify the critical wind speed for tree felling, with a Monte Carlo approach to include wind damage and salvage logging into forest management alternatives. We apply a stochastic programming model to explore two objectives: maximizing the expected forest net present value or maximizing the even-flow of income. To assess the effects of improper wind risk assumptions in planning, we compare the results when optimizing for correct versus incorrect wind intensity and frequency assumptions. When maximizing for net present value, the impacts of misidentifying wind intensity and frequency are minor, likely due to harvests planned immediately as trees reach maturity. For the case when maximizing even-flow of income, incorrectly identifying wind intensity and frequency severely impacts the ability to meet the required harvest targets and reduces the expected net present value. The specific utility of risk mitigation therefore depends on the planning problem. Overall, we show that incorporating wind disturbances into forest planning can inform forest owners about how they can manage wind risk based on their specific risk preferences.

Study on Improving the Mechanism for Assessing and Realizing the Value of Forest Ecological Products in Fujian Province

Abstract The key to grasping and practicing the important concept of “green mountains are golden mountains” is to internalize the construction of ecological civilization into the operation mechanism of the market economy and to stimulate the endogenous motivation of the whole society to engage in the construction of ecological civilization. The study focuses on the value of forest ecological products in Fujian Province and evaluates these products from four perspectives: support services, regulating services, supply services, and cultural services. Subsequently, we constructed the suitability evaluation index system for the realization mode of forest ecological product value in Fujian Province. We weighted the indexes by combining the entropy value method and the expert scoring method, and evaluated the suitability of the realization mode using the structural equation model. The suitability assessment results show that Zhouning County, Ningde City - ecological compensation &gt; Shunchang County, Nanping City - ecological tenure trading &gt; Changting County, Longyan City - ecological restoration &gt; Jiangle County, Sanming City - ecological industrialization model. The regression estimates of ecological product production potential factor (β=0.221, p&lt;0.001), ecological environment constraints (β=0.145, p&lt;0.05), social environment constraints (β=0.178, p&lt;0.001), and regression estimation of the realization of the value of the ecological products of forests in Fujian Province are significant. The mechanism for integrating synergy and coordination, localization, and differentiation for the realization of sustainable forest ecological product value has been improved.

Response to: Exploring evolving spiritual values of forests in Europe and Asia: a transition hypothesis toward re-spiritualizing forests

Response to: Exploring evolving spiritual values of forests in Europe and Asia: a transition hypothesis toward re-spiritualizing forests

Challenging the concept of active forest ownership: the perspective of women forest owners in Finland

In Finland, women comprise 41% of private forest owners. However, studies examining forest ownership from the gender perspective are scarce. Forestry and forest ownership is a field dominated by masculine and techno-economic values. For example, this is manifested in the ideal of ‘active forest owner’ in forest policy documents. Therefore, this dissertation studied the concept of ‘active forest ownership’ from the perspective of women forest owners. Different conceptual lenses were used, such as the gender theory and service-dominant logic. Specifically, the thesis focused on four questions: 1. Are women less active than men when a variety of forestry related activities are studied? (Article I); 2. How do women forest owners understand the concept of active forest owner, how does it differ from the one from Finnish forest policy and what kind of attributes impact women forest ownership? (Article II); 3. Do women forest owners have differing objective structure compared with men? (Article III); and 4. Is the relationship between objectives and activity different between women and men? (Article IV). Both quantitative (Articles I, III and IV) and qualitative (Article II) methods were applied. Articles I and III employ exploratory factor analysis and Article IV confirmatory factor analysis. Two sets of data were used: a questionnaire of the Finnish Forest Owner 2020 research project (n=6558) and 22 semistructured interviews. In this thesis, women were found to be less active than men when a selection of forestry related activities were studied (Article I). Women forest owners also had more diverse objective structure compared with men (Article III). In addition, the relationship between forest owner objectives and activity differed between genders (Article IV). Women also defined the concept of ‘active forest owner’ as a much wider concept than Finnish policies. (Article II). These findings suggest that forest ownership is a gendered performance and that there is a lack of service-dominant logic, that is, value cocreation corresponding to the objectives of women. More specifically, the results indicate that women owners need support, especially when forest ownership is something new. Furthermore, gendering and the prevailing forest values impact the whole forest owner population, their behaviour and forest owner research. Understanding this can enable the design of more equal and inclusive forest policies and services.

Economic Valuation of Mangrove Forest Ecosystem in Zamboanga City, Philippines

Mangrove forests are considered one of the most productive and biologically diverse ecosystems in the world. The purpose of conducting this economic valuation study of the mangrove forest ecosystem is to ensure the effective use of mangrove resources by raising the public and decision-maker's awareness of the potential use and benefits of mangroves to the community and the environment. This study assessed the total economic value of the mangrove forest ecosystem in Zamboanga City, Philippines by taking into account the direct use values of mangroves (for example; shrimp value, crab value, and mollusks value), indirect use values of mangroves (for example, the fish value obtained from the nursery and breeding grounds potential of mangroves, coastal protection value of mangroves which include sediment trap for erosion prevention and mangrove protection from strong waves and flooding, and sequestering carbon in the atmosphere), and the people’s willingness-to-pay and willingness-to-work for the option value of the mangrove forest (for example; future potential direct use and indirect use of mangroves). A research survey was conducted to the mangrove beneficiaries (for example, fisherman, crab and shrimp seeker, shellfish/mollusks picker) of Barangay Mampang, and Barangay Talon-Talon, Zamboanga City. Data was collected in April 2022. The market price method was used to calculate the direct use value of mangroves. Replacement cost and Benefit transfer methods were used to assess the indirect use value of mangroves. While the Contingent valuation method was used to determine the option value of mangroves by assessing the willingness-to-pay and willingness-to-work of the respondents for the mangrove conservation and protection program. The total economic value of mangroves in Barangay Mampang and Barangay Talon-Talon, Zamboanga City amounts to 1,559,918.88 United States Dollars/year. The direct use value of mangroves reached 661,703.47 United States Dollars/year from the operational costs and market prices of the various fishery resources provided by the mangrove forest. While the Indirect use value of mangroves reached 881,524.30 United States Dollars/year obtained from the potential of mangroves to provide nursery, feeding, and breeding grounds for fish, protect the coast from flooding and storm surges, and sequester carbon dioxide in the atmosphere. The average willingness-to-pay of the respondents for the mangrove conservation and protection program is 8.16 United States Dollars/household/year. Their mean willingness-to-work is 6 labor days/month, equivalent to 184.86 United States Dollars/year in monetary terms at the local wage rate. The total option value of mangroves obtained by adding the amount willing-to-pay and amount willing-to-work of the respondents reached 22,296.11 United States Dollars/year. Mangrove Forest benefits the coastal communities by providing nursery, feeding, and breeding grounds for fishery resources, protecting coastal communities from strong waves, and flooding, and sequestering carbon in the atmosphere. To sustainably maintain the provision of goods and services provided by the mangroves, participation in cash or in kind of the beneficiaries are essential as part of the mangrove conservation initiatives in Zamboanga City. The researchers of the study recommend the policymakers, and the local government unit of Zamboanga to use this economic valuation study as a reference in implementing mangrove conservation programs and developing policies concerning the effective use and management of mangrove resources.

Determination of Potential Forest Areas in the Altınapa Dam Lake Basin

In this study, a suitability analysis has been conducted to assess the suitability of forest land use within the Altınapa Dam Lake basin, considering natural and cultural potentials, ecological structure, and forest resource values. Suitability analysis is recognized as a crucial tool for the conservation and sustainable utilization of natural and cultural resources. This analysis was carried out using Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP). The result of this analysis is a suitability map, which indicates that approximately half of the basin is considered suitable for forest areas. This finding highlights the importance of forested areas in preserving and enhancing the ecological balance of the basin.

Identifying driving factors of soil heavy metal at the mining area scale: Methods and practice

Identifying driving factors is of great significance for understanding the mechanisms of soil pollution. In this study, a data processing method for driving factors was analyzed to explore the genesis of Arsenic (As) pollution in mining areas. The wind field that affects the atmospheric diffusion of pollutants was simulated using the standard k−ε model. Machine learning and GeoDetector methods were used to identify the primary driving factors. The results showed that the prediction performances of the three machine learning models were improved after data processing. The R2 values of random forest (RF), support vector machine, and artificial neural network increased from 0.45, 0.69, and 0.24 to 0.55, 0.76, and 0.52, respectively. The importance of wind increased from 20.85% to 26.22%. The importance of distance to the smelter plant decreased from 43.26% to 33.19% in the RF model. The wind's driving force (q value) increased from 0.057 to 0.235 in GeoDetector. The average value of historical atmospheric dust reached 534.98 mg/kg, indicating that atmospheric deposition was an important pathway for As pollution. The outcome of this study can provide a direction to clarify the mechanisms responsible for soil pollution at the mining area scale.

Estimation of Water Consumption of Haloxylon ammodendron Sand-Fixing Forest in Minqin Oasis-Desert Ecotone of China Based on Leaf Index, China

In order to accurately estimate the water consumption of a Minqin desert Haloxylon ammodendron sand fixation forest, we used thermal equilibrium stem flow measurement to monitor the stem flow dynamics of Minqin desert H. ammodendron (5, 10, 15, and 20 years old, respectively, denoted as H5, H10, H15, and H20). In this study, we chose the growth index of assimilated branches (expressed as Ab in the following text) as the scalar quantity for expansion, and then estimated the water consumption of the H. ammodendron sand fixation forest by fitting the correlation between the water consumption of single H. ammodendron plants and the surface area and dry weight of single Ab. The results showed that the growth of assimilated H. ammodendron branches and the plant’s monthly water consumption were synchronized, and that the growth of Ab and water consumption were significantly higher during the fast-growth period of H. ammodendron (July) compared to during the leaf-expanding (May) and leaf-falling periods (October). After correlation analysis, it was determined that there was a linear function between the surface area and dry weight of Ab and water consumption in H. ammodendron. The simulated water consumption values (kg) of H. ammodendron sand fixation forests were greatly affected by stand density and branching configuration, and the simulated values of H. ammodendron assimilated branch growth (cm) were slightly smaller than the measured values for forests of different ages, while the simulated values of assimilated branch surface area (cm2) had a much smaller relative error (8.92%) on average. Therefore, it is feasible to use the surface area and dry weight of Ab to calculate the water consumption of H. ammodendron sand fixation forests. This can enable the reliable estimation of the water consumption of H. ammodendron forests and provide a reference for desert vegetation sand fixation afforestation and its ecological water management.

Canopy reduction and fire seasonality effects on deer and turkey habitat in upland hardwoods

Understory conditions strongly influence the value of upland hardwood forests for white-tailed deer (Odocoileus virginianus) and wild turkey (Meleagris gallopavo). Canopy reduction can be paired with low-intensity prescribed fire to increase forage and cover. Most fire in these systems is applied during the dormant season, but there may be benefits to burning during different seasons to provide different resources throughout the year. We implemented a shelterwood harvest with reserves in four upland hardwood stands in east Tennessee in 2010, then applied fire during the early-growing season (EGS) and late-growing season (LGS) to different treatment units on approximately a 2.2-year return interval from 2012–2023. We recorded vegetation composition, measured vegetation structure, calculated deer forage availability, and tallied wildlife detections via camera traps in summer 2023 to evaluate our treatments relative to an unharvested and unburned control. We found canopy reduction and fire during either season resulted in greater understory coverage of plants, with tree and bramble coverage greatest following LGS fire, which was lower intensity on average than EGS fire. Vegetation structure following EGS fire was more open, which is typically selected by brooding turkeys. The taller structure following LGS fire provided conditions typically selected for bedding or fawning by deer and nesting for turkeys. Deer forage biomass in July was increased by both EGS and LGS relative to control, but forage of sufficient quality to support a lactating doe was increased only in EGS because of increased nutrition of recently resprouting vegetation. Deer and turkey detections were greater in EGS than control or LGS during May–June. Turkey detections remained greater in EGS during July–August, but deer use was similar between EGS and LGS during July–August. Our results indicate burning during different seasons following canopy reduction can promote different food and cover resources which are important for deer and turkeys during different times of the year.

Sensitivities of Vegetation Gross Primary Production to Precipitation Frequency in the Northern Hemisphere from 1982 to 2015

Vegetation of the Northern Hemisphere plays a vital role in global ecosystems and the carbon cycle. Variations in precipitation profoundly affect vegetation productivity, plant growth, and species communities. Precipitation frequency directly controls soil moisture availability, which has an impact on the vegetation carbon sink. However, it is unclear how precipitation frequency affects the vegetation productivity of different land cover types in different seasons. In this study, the sensitivities of the gross primary production (GPP) of six vegetation types (forest, cropland, grassland, shrubland, tundra and barren land) in response to the frequency of five categories of precipitation (trace: 0.1–5 mm/day, small: 5–10 mm/day, moderate: 10–15 mm/day, heavy: 15–20 mm/day, and very heavy: &gt;20 mm/day) were analyzed based on the XGBoost model. The results showed that, between 1982 and 2015, precipitation frequency declined in most land cover types but increased significantly in the pan-Arctic. Differences in the sensitivity to precipitation frequency were observed between seasons and precipitation categories in northern latitudes. The GPP values of forest and barren land vegetation were less sensitive to precipitation frequency than grassland, shrubland and tundra. This may be related to different vegetation community structures and underlying surfaces and gradually increasing drought resistance capability. The sensitivity to precipitation frequency declined for moderate and heavy precipitation in cropland, but it increased in winter. As the frequency of trace precipitation diminishes in winter, the sensitivity of each vegetation type reduces by an average of 0.03%/decade. Conversely, the sensitivities to small and moderate rain increase by 0.01%/decade and 0.02%/decade, respectively, for ecosystems such as cultivated land, forests, and shrubs. However, shrubs and tundra exhibit distinct behaviors, where shifts in precipitation frequency align directly with trends in sensitivity. These results show that the frequency of precipitation significantly affects vegetation productivity and has different sensitivities, and vegetation shows different feedback mechanisms in the face of environmental changes.