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1.
Sci Data ; 11(1): 218, 2024 Feb 17.
Artigo em Inglês | MEDLINE | ID: mdl-38368451

RESUMO

As an important forestry pest, Coronaproctus castanopsis (Monophlebidae) has caused serious damage to the globally valuable Gutianshan ecosystem, China. In this study, we assembled the first chromosome-level genome of the female specimen of C. castanopsis by merging BGI reads, HiFi long reads and Hi-C data. The assembled genome size is 700.81 Mb, with a scaffold N50 size of 273.84 Mb and a contig N50 size of 12.37 Mb. Hi-C scaffolding assigned 98.32% (689.03 Mb) of C. Castanopsis genome to three chromosomes. The BUSCO analysis (n = 1,367) showed a completeness of 91.2%, comprising 89.2% of single-copy BUSCOs and 2.0% of multicopy BUSCOs. The mapping ratio of BGI, second-generation RNA, third-generation RNA and HiFi reads are 97.84%, 96.15%, 97.96%, and 99.33%, respectively. We also identified 64.97% (455.3 Mb) repetitive elements, 1,373 non-coding RNAs and 10,542 protein-coding genes. This study assembled a high-quality genome of C. castanopsis, which accumulated valuable molecular data for scale insects.


Assuntos
Ecossistema , Agricultura Florestal , Feminino , Humanos , Genoma , Cromossomos , RNA , Filogenia
2.
Sci Rep ; 14(1): 3973, 2024 02 17.
Artigo em Inglês | MEDLINE | ID: mdl-38368502

RESUMO

The Zagros oak forests in Iran are facing a concerning decline due to prolonged and severe drought conditions over several decades, compounded by the simultaneous impact of temperature on oak populations. This study in oak woodlands of central Zagros forests in Lorestan province analyzed abiotic factors such as climate properties, topographic features, land use, and soil properties from 1958 to 2022. We found that higher elevation areas with steeper slopes and diverse topography show significant potential for enhancing oak tree resilience in the face of climate change. Additionally, traditional land use practices like livestock keeping and dryland farming contribute to a widespread decline in oak populations. Preserving forest biodiversity and ensuring ecological sustainability requires immediate attention. Implementing effective land-use management strategies, such as protecting and regulating human-forest interaction, and considering meteorological factors to address this issue is crucial. Collaborative efforts from stakeholders, policymakers, and local communities are essential to oppose destructive suburban sprawl and other developments. Sustainable forestry practices should be implemented to improve the living standards of local communities that rely on forests and traditional livestock keeping, offer forestry-related jobs, and ensure social security. Such efforts are necessary to promote conservation awareness and sustainable practices, safeguarding this unique and vital ecosystem for future generations.


Assuntos
Ecossistema , Quercus , Humanos , Irã (Geográfico) , Florestas , Agricultura Florestal , Árvores
3.
Sci Rep ; 14(1): 4052, 2024 02 19.
Artigo em Inglês | MEDLINE | ID: mdl-38374339

RESUMO

The objective of this study is to promptly and accurately allocate resources, scientifically guide grain distribution, and enhance the precision of crop yield prediction (CYP), particularly for corn, along with ensuring application stability. The digital camera is selected to capture the digital image of a 60 m × 10 m experimental cornfield. Subsequently, the obtained data on corn yield and statistical growth serve as inputs for the multi-source information fusion (MSIF). The study proposes an MSIF-based CYP Random Forest model by amalgamating the fluctuating corn yield dataset. In relation to the spatial variability of the experimental cornfield, the fitting degree and prediction ability of the proposed MSIF-based CYP Random Forest are analyzed, with statistics collected from 1-hectare, 10-hectare, 20-hectare, 30-hectare, and 50-hectare experimental cornfields. Results indicate that the proposed MSIF-based CYP Random Forest model outperforms control models such as support vector machine (SVM) and Long Short-Term Memory (LSTM), achieving the highest prediction accuracy of 89.30%, surpassing SVM and LSTM by approximately 13.44%. Meanwhile, as the experimental field size increases, the proposed model demonstrates higher prediction accuracy, reaching a maximum of 98.71%. This study is anticipated to offer early warnings of potential factors affecting crop yields and to further advocate for the adoption of MSIF-based CYP. These findings hold significant research implications for personnel involved in Agricultural and Forestry Economic Management within the context of developing agricultural economy.


Assuntos
Agricultura Florestal , Zea mays , Algoritmo Florestas Aleatórias , Agricultura , Grão Comestível
4.
Sensors (Basel) ; 24(3)2024 Jan 25.
Artigo em Inglês | MEDLINE | ID: mdl-38339515

RESUMO

Smart forestry, an innovative approach leveraging artificial intelligence (AI), aims to enhance forest management while minimizing the environmental impact. The efficacy of AI in this domain is contingent upon the availability of extensive, high-quality data, underscoring the pivotal role of sensor-based data acquisition in the digital transformation of forestry. However, the complexity and challenging conditions of forest environments often impede data collection efforts. Achieving the full potential of smart forestry necessitates a comprehensive integration of sensor technologies throughout the process chain, ensuring the production of standardized, high-quality data essential for AI applications. This paper highlights the symbiotic relationship between human expertise and the digital transformation in forestry, particularly under challenging conditions. We emphasize the human-in-the-loop approach, which allows experts to directly influence data generation, enhancing adaptability and effectiveness in diverse scenarios. A critical aspect of this integration is the deployment of autonomous robotic systems in forests, functioning both as data collectors and processing hubs. These systems are instrumental in facilitating sensor integration and generating substantial volumes of quality data. We present our universal sensor platform, detailing our experiences and the critical importance of the initial phase in digital transformation-the generation of comprehensive, high-quality data. The selection of appropriate sensors is a key factor in this process, and our findings underscore its significance in advancing smart forestry.


Assuntos
Inteligência Artificial , Agricultura Florestal , Humanos , Agricultura Florestal/métodos , Conservação dos Recursos Naturais/métodos , Florestas , Tecnologia
5.
PLoS One ; 19(2): e0297873, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38412162

RESUMO

BACKGROUND: The relationship of serum 25(OH)D levels and hyperlipidemia has not been explored in the Agriculture, Forestry, and Fishing (AFF) occupation. We aimed to explore the impact of serum 25(OH)D levels on lipid profiles in AFF workers, traffic drivers, and miners. METHODS: Data from 3937 adults aged 18-65 years old with completed information were obtained from the National Health and Examination Survey from 2001 to 2014. Multivariate linear regression models were used to examine the associations between serum 25(OH)D concentrations and triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and HDL-C/LDL-C ratio. Subgroup analyses for AFF workers considered age, sex, BMI, work activity, months worked, and alcohol consumption. Non-linear relationships were explored using curve fitting. RESULTS: Serum 25(OH)D levels differed between groups (AFF: 60.0 ± 21.3 nmol/L, drivers: 56.6 ± 22.2 nmol/L, miners: 62.8 ± 22.3 nmol/L). Subgroup analysis of the AFF group showed that participants with serum 25(OH)D ≥50 nmol/L, females, and BMI <30 kg/m2 demonstrated improved HDL-C levels correlating with higher serum 25(OH)D. Serum 25(OH)D in AFF workers had a reversed U-shaped relationship with TG and TC, and a U-shaped relationship with HDL-C, with HDL-C, with inflection points at 49.5 nmol/L for TG and TC, and 32.6 nmol/L for HDL-C. CONCLUSIONS: Serum 25(OH)D levels are associated with lipid profiles, and the relationship varies among occupational groups. AFF workers, facing unique occupational challenges, may benefit from maintaining adequate serum 25(OH)D levels to mitigate adverse lipid profiles and reduce cardiovascular risk.


Assuntos
Agricultura Florestal , Caça , Vitamina D/análogos & derivados , Adulto , Feminino , Humanos , Adolescente , Adulto Jovem , Pessoa de Meia-Idade , Idoso , LDL-Colesterol , Inquéritos Nutricionais , Calcifediol , Lipídeos , Triglicerídeos , HDL-Colesterol , Ocupações , Agricultura
6.
PLoS One ; 19(2): e0297439, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38306349

RESUMO

The impacts of the Anthropocene on climate and biodiversity pose societal and ecological problems that may only be solved by ecosystem restoration. Local to regional actions are required, which need to consider the prevailing present and future conditions of a certain landscape extent. Modeling approaches can be of help to support management efforts and to provide advice to policy making. We present stage one of the LaForeT-PLUC-BE model (Landscape Forestry in the Tropics-PCRaster Land Use Change-Biogeographic & Economic model; in short: LPB) and its thematic expansion module RAP (Restoration Areas Potentials). LPB-RAP is a high-resolution pixel-based scenario tool that relies on a range of explicit land use types (LUTs) to describe various forest types and the environment. It simulates and analyzes future landscape configurations under consideration of climate, population and land use change long-term. Simulated Land Use Land Cover Change (LULCC) builds on dynamic, probabilistic modeling incorporating climatic and anthropogenic determinants as well as restriction parameters to depict a sub-national regional smallholder-dominated forest landscape. The model delivers results for contrasting scenario settings by simulating without and with potential Forest and Landscape Restoration (FLR) measures. FLR potentials are depicted by up to five RAP-LUTs. The model builds on user-defined scenario inputs, such as the Shared Socioeconomic Pathways (SSP) and Representative Concentration Pathways (RCP). Model application is here exemplified for the SSP2-RCP4.5 scenario in the time frame 2018-2100 on the hectare scale in annual resolution using Esmeraldas province, Ecuador, as a case study area. The LPB-RAP model is a novel, heuristic Spatial Decision Support System (SDSS) tool for smallholder-dominated forest landscapes, supporting near-time top-down planning measures with long-term bottom-up modeling. Its application should be followed up by FLR on-site investigations and stakeholder participation across all involved scales.


Assuntos
Conservação dos Recursos Naturais , Ecossistema , Conservação dos Recursos Naturais/métodos , Florestas , Biodiversidade , Agricultura Florestal/métodos
7.
Nature ; 626(7998): 327-334, 2024 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-38109939

RESUMO

The pulp and paper industry is an important contributor to global greenhouse gas emissions1,2. Country-specific strategies are essential for the industry to achieve net-zero emissions by 2050, given its vast heterogeneities across countries3,4. Here we develop a comprehensive bottom-up assessment of net greenhouse gas emissions of the domestic paper-related sectors for 30 major countries from 1961 to 2019-about 3.2% of global anthropogenic greenhouse gas emissions from the same period5-and explore mitigation strategies through 2,160 scenarios covering key factors. Our results show substantial differences across countries in terms of historical emissions evolution trends and structure. All countries can achieve net-zero emissions for their pulp and paper industry by 2050, with a single measure for most developed countries and several measures for most developing countries. Except for energy-efficiency improvement and energy-system decarbonization, tropical developing countries with abundant forest resources should give priority to sustainable forest management, whereas other developing countries should pay more attention to enhancing methane capture rate and reducing recycling. These insights are crucial for developing net-zero strategies tailored to each country and achieving net-zero emissions by 2050 for the pulp and paper industry.


Assuntos
Agricultura Florestal , Efeito Estufa , Gases de Efeito Estufa , Indústrias , Internacionalidade , Papel , Desenvolvimento Sustentável , Madeira , Efeito Estufa/prevenção & controle , Efeito Estufa/estatística & dados numéricos , Gases de Efeito Estufa/análise , Gases de Efeito Estufa/isolamento & purificação , Indústrias/legislação & jurisprudência , Indústrias/estatística & dados numéricos , Metano/análise , Metano/isolamento & purificação , Reciclagem/estatística & dados numéricos , Reciclagem/tendências , Países Desenvolvidos , Países em Desenvolvimento , Florestas , Agricultura Florestal/métodos , Agricultura Florestal/tendências , Desenvolvimento Sustentável/tendências , Clima Tropical
8.
Environ Pollut ; 343: 123272, 2024 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-38160777

RESUMO

Mycobacterium avium subsp. paratuberculosis (MAP) is the etiological agent of paratuberculosis, a chronic infection affecting ruminants and other species worldwide. Information on the ecological factors that increase infection risk at the livestock-wildlife-environment interface remains scarce. Thus, this work aimed at determining which factors modulate the exposure of a mammal community within a Mediterranean agro-forestry farmstead to MAP. Through field, molecular and ecological modeling approaches, MAP prevalence, distribution and spatial risk at the livestock-wildlife-environment was estimated in the study area by screening 436 samples (cattle, n = 150; wildlife, n = 206; soil, n = 80). Using molecular detection of IS900 as proxy, MAP was identified in ten wild mammal species. Being a central prey of mesocarnivores in Portugal, the high prevalence of MAP in the wild rabbit (19%) may be related with red fox's (22%). MAP was also detected in cattle managed in the farmstead (animal and herd prevalence, 54% and 100%) and in soil (44%), which may perpetuate intraspecies and interspecies transmission. Wildlife diversity showed a positive influence on MAP presence in wild mammals, while wildlife abundance showed a negative effect. Land use variables exerted distinct degrees of impact upon MAP detection in specific groups of mammals: mixed forest cover showed positive influence on carnivores, and shrubland showed positive effect on wild rabbits. The prevalence of MAP in cattle showed a negative influence on the detection of MAP in lagomorph, which may stem from wild rabbit lower density and avoidance of cattle areas. Based on explanatory variables, the spatial prediction of MAP occurrence in wildlife indicated two hotspots with increased exposure risk but future studies are needed to confirm this projection. This work represents the most comprehensive molecular survey of MAP occurrence and determinants in Mediterranean agroecosystems leveraging the principles and tools of community ecology, debating potential biological and ecological effects underlying MAP transmission.


Assuntos
Mycobacterium avium subsp. paratuberculosis , Paratuberculose , Animais , Bovinos , Coelhos , Animais Selvagens , Gado , Agricultura Florestal , Paratuberculose/epidemiologia , Paratuberculose/microbiologia , Mamíferos , Solo , Fezes/microbiologia
9.
J Environ Manage ; 350: 119593, 2024 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-38016237

RESUMO

The Amazon has a range of species with high potential for sustainable timber harvesting, but for them to be utilized globally, the merchantable wood volume must be accurately quantified. However, since the 1950s, inadequate methods for estimating merchantable timber volumes have been employed in the Amazon, and Brazilian Government agencies still require some of them. The natural variability of the Amazon Forest provides an abundance of species of different sizes and shapes, conferring several peculiarities, which makes it necessary to use up-to-date and precise methods for timber quantification in Amazon Forest management. Given the employment of insufficient estimation methods for wood volume, this study scrutinizes the disparities between the actual harvested merchantable wood volume and the volume estimated by the forest inventory during the harvesting phase across five distinct public forest areas operating under sustainable forest management concessions. We used mixed-effect models to evaluate the relationships between inventory and harvested volume for genera and forest regions. We performed an equivalence test to assess the similarity between the volumes obtained during the pre-and post-harvest phases. We calculated root mean square error and percentage bias for merchantable volume as accuracy metrics. There was a strong tendency for the 100% forest inventory to overestimate merchantable wood volume, regardless of genus and managed area. There was a significant discrepancy between the volumes inventoried and harvested in different regions intended for sustainable forest management, in which only 22% of the groups evaluated were equivalent. The methods currently practiced by forest companies for determining pre-harvest merchantable volume are inaccurate enough to support sustainable forest management in the Amazon. They may even facilitate the region's illegal timber extraction and organized crime.


Assuntos
Árvores , Madeira , Agricultura Florestal/métodos , Brasil , Conservação dos Recursos Naturais/métodos , Florestas
12.
Sci Rep ; 13(1): 19437, 2023 11 09.
Artigo em Inglês | MEDLINE | ID: mdl-37945639

RESUMO

The bundle of forest landowners' rights largely varies from one jurisdiction to another. On a global scale, the diversity of forest management regime and property rights systems is such that finding comprehensive and standardised approaches for governance analysis purposes is a challenging task. This paper explores the use of the Property Rights Index for Forestry (PRIF) as an analytical tool based on five rights domains (access, withdrawal, management, exclusion, and alienation) to assess how regulatory frameworks impact the owners' forest property rights. We show that PRIF is a reliable index for various governance arrangements, considering its ability to score forest owners' freedom to decide in case studies that range from the Amazon area (Brazil), Misiones province (Argentina) and Quebec (Canada) to community-managed Nepalese and Mexican forests. PRIF scores obtained in these diverse governance arrangements confirm that the governance of forests held by entities other than the state is driven by two factors: the owner's ability to exclude the public from the use of his/her own resource and the owner's freedom to decide on the forest management goals. These factors explained 66.44% of the variance in our sample and should be considered as the main potential drivers while implementing any new international or national policy. Despite having a few limitations, the PRIF is a promising governance indicator and has been proven to perform well for various socioeconomic and legal contexts.


Assuntos
Conservação dos Recursos Naturais , Propriedade , Feminino , Masculino , Humanos , Florestas , Agricultura Florestal , Canadá
13.
Environ Monit Assess ; 195(12): 1460, 2023 Nov 11.
Artigo em Inglês | MEDLINE | ID: mdl-37950805

RESUMO

Air pollution is one of the killers of our age especially for the urban areas. Urban forestry which involves planting more trees has been considered as one of the prominent strategies to mitigate air pollution. Identification of trees tolerant to air pollution is important for plantation drives being organized across the country. The present study aimed to compare the air pollution tolerance potential of 46 tree species growing in Guru Nanak Dev University (GNDU) campus, Amritsar, using two indices, viz., Air Pollution Tolerance Index (APTI) and Anticipated Performance Index (API). APTI is based on four biochemical parameters, viz., relative water content, leaf extract pH, total chlorophyll, and ascorbic acid contents of leaf samples, whereas API takes into consideration morphological and socioeconomic values of plant species along with their APTI. Based on APTI values calculated for 46 tree species, only 2 tree species, viz., Psidium guajava (46.26) and Cassia fistula (41.83), were found to be tolerant to air pollution, while 25 species showed intermediate tolerance. API scores revealed one tree species, namely, P. guajava, as an excellent performer, 8 species as very good performers, and 28 species as moderate to good performers against air pollution. In conclusion, tree species like Alstonia scholaris, C. fistula, Ficus tsjakela, Grevillea robusta, Kigelia africana, Mangifera indica, Melia azedarach, P. guajava, Pongamia pinnata, Pterospermum acerifolium, Putranjiva roxburghii, Syzygium cumini, Terminalia arjuna, and Toona ciliata can be considered as most desirable for plantations in areas around GNDU campus.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Humanos , Árvores , Poluentes Atmosféricos/toxicidade , Poluentes Atmosféricos/análise , Agricultura Florestal , Monitoramento Ambiental , Poluição do Ar/análise
14.
PLoS One ; 18(11): e0294650, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37976263

RESUMO

For political and administrative governance of land-use decisions, high-resolution and reliable spatial models are required over large areas and for various time horizons. We present a process-centered simulation model 'NextStand' (a forest landscape model, FLM) and its R-script, which predicts regional forest characteristics at a forest stand resolution. The model uses whole area stand data and is optimized for realistic iterative timber harvesting decisions, based on stand compositions (developing over time) and locations. We used the model for simulating spatial predictions of the Estonian forests in North Europe (2.3 Mha, about 2 M stands); the decisions were parameterized by land ownership, protection regimes, and rules of clear-cut harvesting. We illustrate the model application as a potential broad-scale Decision Support Tool by predicting how the forest age composition, placement of clear-cut areas, and connectivity of old stands will develop until the year 2050 under future scenarios. The country-scale outputs had a generally low within-scenario variance, which enabled to estimate some main land-use effects and uncertainties at small computing efforts. In forestry terms, we show that a continuation of recent intensive forest management trends will produce a decline of the national timber supplies in Estonia, which greatly varies among ownership types. In a conservation perspective, the current level of 13% forest area strictly protected can maintain an overall area of old forests by 2050, but their isolation is a problem for biodiversity conservation. The behavior of low-intensity forest management units (owners) and strict governance of clear-cut harvesting rules emerged as key questions for regional forest sustainability. Our study confirms that high-resolution modeling of future spatial composition of forest land is feasible when one can (i) delineate predictable spatial units of transformation (including management) and (ii) capture their variability of temporal change with simple ecological and socioeconomic (including human decision-making) variables.


Assuntos
Conservação dos Recursos Naturais , Árvores , Humanos , Estônia , Florestas , Agricultura Florestal , Biodiversidade , Fatores Socioeconômicos , Ecossistema
15.
Ying Yong Sheng Tai Xue Bao ; 34(11): 2907-2918, 2023 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-37997401

RESUMO

We constructed base model, dummy variable model, and mixture model with three variables including knot diameter, loose knot length, and sound knot length with three typical coniferous species, Pinus koraiensis, Larix olgensis, and Pinus sylvestris var. mongolica, from the Linkou Forestry Bureau and Mengjiagang forest farm in Heilongjiang Province in 2020. We analyzed the differences in knot properties among different tree species and simplified the modeling work. Firstly, we collected relevant knot property data through the sectioning method based on relevant literature, transformation of the model form and substitution of related variables to conduct a base model. We transformed the species into dummy variables as qualitative factors, and introduced the dummy variable model of the relevant attributes into the base model. We introduced the random effects of sample trees and sample plots when constructing the mixture model. By comparing evaluation indicators, such as Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), the mixture model with the best fitting effect was selected. We selected the optimal universal equation by comparing the fitting accuracy of the base model, dummy variable model and mixture model. The fitting accuracy of the dummy variable model and mixture model was higher than that of the basic model. The evaluation indicators (AIC and BIC) showed that the mixture model had a better fitting effect on knot properties than the dummy variable model. In the model comparison results, R2 of mixture models for sound knot length, the loose knot length, and knot diameter increased by 13.2%, 84.8% and 40.3%, respectively. The predictive accuracy of the three base models for different tree species' knot attributes was above 90%, and both the prediction accuracy of the dummy variable model and mixture model were above 94%, indicating that the constructed models could well predict knot-related properties. From the perspective of tree species, the sound knot length, knot diameter, and loose knot length was in order of P. sylvestris var. mongolica > P. koraiensis > L. olgensis. Fitted results of the dummy variable model and the mixture model were superior to the basic model, with higher accuracy.


Assuntos
Larix , Pinus , Teorema de Bayes , Florestas , Agricultura Florestal , China
17.
Molecules ; 28(20)2023 Oct 14.
Artigo em Inglês | MEDLINE | ID: mdl-37894564

RESUMO

Sustainable development goals require a reduction in the existing heavy reliance on fossil resources. Forestry can be considered a key resource for the bioeconomy, providing timber, energy, chemicals (including fine chemicals), and various other products. Besides the main product, timber, forestry generates significant amounts of different biomass side streams. Considering the unique and highly complex chemical composition of coniferous needle/greenery biomass, biorefinery strategies can be considered as prospective possibilities to address top segments of the bio-based value pyramid, addressing coniferous biomass side streams as a source of diverse chemical substances with applications as the replacement of fossil material-based chemicals, building blocks, food, and feed and applications as fine chemicals. This study reviews biorefinery methods for coniferous tree forestry biomass side streams, exploring the production of value-added products. Additionally, it discusses the potential for developing further biorefinery strategies to obtain products with enhanced value.


Assuntos
Agricultura Florestal , Rios , Estudos Prospectivos , Biocombustíveis , Alimentos , Biomassa
18.
Ying Yong Sheng Tai Xue Bao ; 34(9): 2355-2362, 2023 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-37899100

RESUMO

Based on data collected from 2054 saplings of Larix gmelinii forest in 55 fixed plots in 2018-2019 in Cuigang Forestry Station, Daxing'anling area, we classified the stand density index (SDI) into four classes, i.e., Class Ⅰ (SDI1<1863 plants·hm-2), Class Ⅱ (1863 plants·hm-2≤SDI2<2155 plants·hm-2), Class Ⅲ (2155 plants·hm-2≤SDI3<2459 plants·hm-2) and Class Ⅳ (SDI4≥2459 plants·hm-2) by using the quartile method. We constructed a dummy variable model and quantile regression model for the height-breast diameter of saplings of L. gmelinii with dummy variable method introduced SDI. The results showed that among the five selected representative non-linear tree height curve models, the Richards model fitted the best, with Ra2, RMSE and MAE of 0.7637, 0.8250 m and 0.5696 m. The dummy variable model including the SDI constructed based on the Richards model showed a 1.3% increase in Ra2 compared with the base model, while RMSE, MAE, and AIC decreased by 2.1%, 1.5%, and 11.2%, respectively. When the quantile τ was 0.5, Ra2 of quantile regression model was the maximum, and RMSE, MAE, AIC was the minimum, being 0.7612, 0.8294 m, 0.5657 m, and -767.19, respectively. Compared with SDI1, sapling height in SDI2-SDI4 was increased by 5.6%, 5.6%, and 11.3%, suggesting reasonable that regulation of stand density was conducive to increase the height growth of saplings in regeneration.


Assuntos
Larix , Florestas , Árvores , Agricultura Florestal , China
19.
Environ Monit Assess ; 195(10): 1236, 2023 Sep 21.
Artigo em Inglês | MEDLINE | ID: mdl-37730944

RESUMO

Land use, land use change, and forestry (LULUCF) are critical in climate change mitigation. Producing or collecting activity data for LULUCF is essential in developing national greenhouse gas inventories, national communications, biennial update reports, and nationally determined contributions to meet international commitments under climate change. Collect Earth is a free, publicly accessible software for monitoring dynamics between all land use classes: forestlands, croplands, grasslands, wetlands, settlements, and other lands. Collect Earth supports countries in monitoring the trends in land use and land cover over time by applying a sample-based approach and generating reliable, high-quality, consistent, accurate, transparent, robust, comparable, and complete activity data through augmented visual interpretation for climate change reporting. This article reports forest extent estimates in Azerbaijan, analyzing 7782 0.5-ha sampling units through an augmented visual interpretation of very high spatial and temporal resolution images on the Google Earth platform. The results revealed that in 2016, tree cover existed in 31.9% of total land, equal to 2,751,167 ha and 1,301,188 ha or 15.1% of the total land, with a 5.4% sampling error covered by forests. The estimate is 15 to 25% higher than the previous estimates, equal to 169,418 to 260,888 ha of forest that was never reported in previous studies.


Assuntos
Mudança Climática , Agricultura Florestal , Azerbaijão , Tecnologia de Sensoriamento Remoto , Monitoramento Ambiental
20.
J Safety Res ; 86: 21-29, 2023 09.
Artigo em Inglês | MEDLINE | ID: mdl-37718049

RESUMO

PROBLEM: Fatal injuries in the agriculture, forestry, and fishing sector (AgFF) outweigh those across all sectors in the United States. Transportation-related injuries are among the top contributors to these fatal events. However, traditional occupational injury surveillance systems may not completely capture crashes involving farm vehicles and logging trucks, specifically nonfatal events. METHODS: The study aimed to develop an integrated database of AgFF-related motor-vehicle crashes for the southwest (Arkansas, Louisiana, New Mexico, Oklahoma, and Texas) and to use these data to conduct surveillance and research. Lessons learned during the pursuit of these aims were cataloged. Activities centered around the conduct of traditional statistical and geospatial analyses of structured data fields and natural language processing of free-text crash narratives. RESULTS: The structured crash data in each state include fields that allowed farm vehicles or equipment and logging trucks to be identified. The variable definitions and coding were not consistent across states but could be harmonized. All states recorded data fields pertaining to person, vehicle, and crash/environmental factors. Structured data supported the construction of crash severity models and geospatial analyses. Law enforcement provided additional details on crash causation in free-text narratives. Crash narratives contained sufficient text to support viable machine learning models for farm vehicle or equipment crashes, but not for logging truck narratives. DISCUSSION: Crash records can help to fill research and surveillance gaps in AgFF in the southwest region. This supports traffic safety's evolution to the current Safe System paradigm. There is a conceptual linkage between the Safe System and Total Worker Health approaches, providing a bridge between traffic safety and occupational health. PRACTICAL APPLICATIONS: Despite limitations, crash records can be an important component of injury surveillance for events involving AgFF vehicles. They also can be used to inform the selection and evaluation of traffic countermeasures and behavioral interventions.


Assuntos
Acidentes de Trânsito , Agricultura Florestal , Humanos , Agricultura , Meios de Transporte , Bases de Dados Factuais
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