Assessment of challenges and strategies for driving energy transitions in emerging markets:A socio-technological systems perspective

The pursuit of improved quality of life standards has significantly influenced the contemporary mining model in the 21st century.This era is witnessing an unprecedented transformation driven by pressing concerns related to sustainability,climate change,the just energy transition,dynamic operating environments,and complex social challenges.Such transitions present both opportunities and obstacles.The aim of this study is to provide an extensive literature review on energy transition to identify the challenges and strategies associated with navigating transformations in energy systems.Understanding these transformations is particularly critical in the face of the severe consequences of global warming,where an accelerated energy transition is viewed as a universal remedy.Adopting a socio-technological systems perspective,specifically through the application of Actor Network Theory(ANT),this research provides a theoretical foundation while categorising challenges into five distinct domains and outlining strategies across these different dimensions.These insights are specifically tailored for emerging market countries to effectively navigate energy transition while fostering the development of resilient societies.Furthermore,our findings highlight that energy transition encompasses more than a mere technological shift;it entails fundamental changes in various systemic socio-economic imperatives.Through focusing on the role of social structures in transitions,this study makes a significant and innovative contribution to ANT,which has historically been criticised for its limited acknowledgement of social structures.Consequently,we propose an emerging market energy transition framework,which not only addresses technological aspects,but also integrates social considerations.This framework paves the way for future research and exploration of energy transition dynamics.The outcomes of this study offer valuable insights to policymakers,researchers,and practitioners engaged in the mining industry,enabling them to comprehend the multifaceted challenges involved and providing practical strategies for effective resolution.Through incorporating the social dimension into the analysis,we enhance the understanding of the complex nature of energy system transformations,facilitating a more holistic approach towards achieving sustainable and resilient energy transitions in emerging markets and beyond.

Female zebra finches are more vulnerable to social isolation stress than males:Involvement of the nonapeptide system

In group-living animals,chronic juvenile social isolation stress(SIS)can profoundly affect behavior and neuroendocrine regulation.However,its impact on social behavior in avian species,particularly regarding sexspecific neural circuit differences,remains underexplored.This study focused on zebra finches,a species known for its social clustering and cognitive abilities,to elucidate these influences.Results indicated that SIS significantly increased plasma corticosterone levels in females but not in males,suggesting a heightened stress response and susceptibility in females.Additionally,SIS disrupted sociality and flocking behavior in both sexes,with more severe impairments in social recognition observed in females.Mesotocin(MT)levels in the lateral septum of both sexes and in the ventromedial hypothalamus of females were found to mediate the SIS effect,while vasotocin(VT)levels within the social behavior network remained unchanged.Pharmacological interventions confirmed the critical role of MT in reversing SIS-induced impairments in sociality,flocking behavior,and social recognition,particularly in females.These findings highlight unique nucleus-and sex-dependent variations in MT and VT regulation,providing novel insights into the mechanisms governing avian social behavior.This study advances our understanding of the independent evolutionary pathways of neural circuits and neuroendocrine systems that modulate social behaviors across different taxonomic groups.

Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic outbreaks.This review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their performance.Since,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by SM.This paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic outbreaks.DL has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation results.In recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM analysis.This paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM analysis.Finally,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

Analysis and Modeling of Mobile Phone Activity Data Using Interactive Cyber-Physical Social System

Mobile networks possess significant information and thus are considered a gold mine for the researcher’s community.The call detail records(CDR)of a mobile network are used to identify the network’s efficacy and the mobile user’s behavior.It is evident from the recent literature that cyber-physical systems(CPS)were used in the analytics and modeling of telecom data.In addition,CPS is used to provide valuable services in smart cities.In general,a typical telecom company hasmillions of subscribers and thus generatesmassive amounts of data.From this aspect,data storage,analysis,and processing are the key concerns.To solve these issues,herein we propose a multilevel cyber-physical social system(CPSS)for the analysis and modeling of large internet data.Our proposed multilevel system has three levels and each level has a specific functionality.Initially,raw Call Detail Data(CDR)was collected at the first level.Herein,the data preprocessing,cleaning,and error removal operations were performed.In the second level,data processing,cleaning,reduction,integration,processing,and storage were performed.Herein,suggested internet activity record measures were applied.Our proposed system initially constructs a graph and then performs network analysis.Thus proposed CPSS system accurately identifies different areas of internet peak usage in a city(Milan city).Our research is helpful for the network operators to plan effective network configuration,management,and optimization of resources.

Effectiveness of sensory integration therapy in children,focusing on Korean children:A systematic review and meta-analysis

BACKGROUND Sensory integration intervention is highly related to the child's effective interaction with the environment and the child's development.Currently,various sensory integration interventions are being applied,but research methodological problems are arising due to unsystematic protocols.This study aims to present the optimal intervention protocol by presenting scientific standards for sensory integration intervention through meta-analysis.AIM To prove the effectiveness of sensory integration therapy,examine the latest trend of sensory integration studies in Korea,and provide clinical evidence for sensory integration therapies.METHODS The database of Korean search engines,including RISS,KISS,and DBpia,was used to search for related literature published from 2001 to October 2020.The keywords,“Children”,“Sensory integration”,“Integrated sensory”,“Sensorymotor”,and“Sensory stimulation”were used in this search.Then,a meta-analysis was conducted on 24 selected studiesRISS,KISS,and DBpia,was used to search for related literature published from 2001 to October 2020.The keywords,“Children”,“Sensory integration”,“Integrated sensory”,“Sensorymotor”,and“Sensory stimulation”were used in this search.Then,a meta-analysis was conducted on 24 selected studies.RESULTS Sensory integration intervention has been proven effective in children with cerebral palsy,autism spectrum disorder,attention deficit/hyperactivity disorder,developmental disorder,and intellectual disability in relation to the diagnosis of children.Regarding sensory integration therapies,1:1 individual treatment with a therapist or a therapy session lasting for 40 min was most effective.In terms of dependent variables,sensory integration therapy effectively promoted social skills,adaptive behavior,sensory processing,and gross motor and fine motor skills.CONCLUSION The results of this study may be used as therapeutic evidence for sensory integration intervention in the clinical field of occupational therapy for children,and can help to present standards for sensory integration intervention protocols.

Does Parental Migration Affect Left-Behind Children’s Social Anxiety?A Systematic Review and Meta-Analysis

Social anxiety is a common psychological problem among left-behind children(LBC)and has been a popular issue in recent years.Children with higher levels of social anxiety have more emotional and behavioral problems and are prone to negative life events.Although several studies have explored the differences in social anxiety between LBC and non-left-behind children(N-LBC),the findings have not been consistent.In this study,a systematic review and meta-analysis method was used,with 411 papers retrieved on October 01,2023,from Pubmed,Embase,Web of Science,and Chinese databases(CNKI,VIP,and Wanfang)(PROSPERO registry number:CRD42023472463).Twenty-one studies met the research criteria and included 11,254 LBC and 13,096 N-LBC.LBC scored significantly higher for social anxiety([WMD(95%CI):0.35[0.23,0.48],p<0.001])and social avoidance and distress([WMD(95%CI):0.35[0.23,0.48],p<0.001]).Subgroup analyses showed significant differences in effect sizes for the overall proportion of children left behind(p=0.02).In addition,different types of parental migration may influence the social anxiety of LBC,double-parent migration was associated higher social anxiety than father migration(p<0.001).Future research should focus on treatments to decrease social anxiety of left-behind children.These findings suggest that due to the long-term absence of parental migration,LBC are more vulnerable to negative emotional experiences and behaviours such as anxiety,distress,and avoidance during social interaction,especially for those with both parents absent from the home.Future research should focus on treatments to reduce social anxiety in LBC.

An Expert System to Detect Political Arabic Articles Orientation Using CatBoost Classifier Boosted by Multi-Level Features

The number of blogs and other forms of opinionated online content has increased dramatically in recent years.Many fields,including academia and national security,place an emphasis on automated political article orientation detection.Political articles(especially in the Arab world)are different from other articles due to their subjectivity,in which the author’s beliefs and political affiliation might have a significant influence on a political article.With categories representing the main political ideologies,this problem may be thought of as a subset of the text categorization(classification).In general,the performance of machine learning models for text classification is sensitive to hyperparameter settings.Furthermore,the feature vector used to represent a document must capture,to some extent,the complex semantics of natural language.To this end,this paper presents an intelligent system to detect political Arabic article orientation that adapts the categorical boosting(CatBoost)method combined with a multi-level feature concept.Extracting features at multiple levels can enhance the model’s ability to discriminate between different classes or patterns.Each level may capture different aspects of the input data,contributing to a more comprehensive representation.CatBoost,a robust and efficient gradient-boosting algorithm,is utilized to effectively learn and predict the complex relationships between these features and the political orientation labels associated with the articles.A dataset of political Arabic texts collected from diverse sources,including postings and articles,is used to assess the suggested technique.Conservative,reform,and revolutionary are the three subcategories of these opinions.The results of this study demonstrate that compared to other frequently used machine learning models for text classification,the CatBoost method using multi-level features performs better with an accuracy of 98.14%.

Socialization Development of ESG Business Models in Representative Asia-Pacific Countries:A State-of-the-Art Review and Recommendation

The integration of environmental,social,and governance(ESG)principles has become a pivotal factor in shaping sustainable and responsible corporate practices.The present study investigates the integration of ESG principles within corporate governance models in Asia-Pacific countries,focusing on socialization.By examining the governance culture,legal frameworks,and corporate practices in these representative countries,the paper delineates a strategic framework for embedding social governance into corporate strategies.The study introduces a Cultural,Economic,Legal,and Political(CELP)framework to assess corporate social governance,investigating the correlation between business practices and social changes.Through a systematic literature review and detailed thematic analysis,this paper aims to offer actionable insights and recommendations,guiding corporations in their transition towards more sustainable and socially responsible business practices.

Enhancing User Security on Instagram: A Multifaceted AI System for Filtering Abusive Comments

Social media platforms like Instagram have increasingly become venues for online abuse and offensive comments. This study aimed to enhance user security to create a safe online environment by eliminating hate speech and abusive language. The proposed system employed a multifaceted approach to comment filtering, incorporating the multi-level filter theory. This involved developing a comprehensive list of words representing various types of offensive language, from slang to explicit abuse. Machine learning models were trained to identify abusive messages through sentiment analysis and contextual understanding. The system categorized comments as positive, negative, or abusive using sentiment analysis algorithms. Employing AI technology, it created a dynamic filtering mechanism that adapted to evolving online language and abusive behavior. Integrated with Instagram while adhering to ethical data collection principles, the platform sought to promote a clean and positive user experience, encouraging users to focus on non-abusive communication. Our machine-learned models, trained on a cleaned Arabic language dataset, demonstrated promising accuracy (75.8%) in classifying Arabic comments, potentially reducing abusive content significantly. This advancement aimed to provide users with a clean and positive online experience.

Digital Human Rights from the Perspective of System Theory——Concept Definition, Social Function, and Constitutional Basis

The three core issues in the“digital human rights”debate are whether“digital human rights”are possible,necessary,and feasible.Both sides of the debate focus on discovering the value of“digital human rights”to individuals from a semantic level,but ignore the significance of“digital human rights”to the whole society and its subsystems at the level of social structure.By introducing Niklas Luhmann's System Theory,this observation blind spot can be eliminated.Fundamental rights are devoted to directly shaping not a physiological-psychological“individual”as a social environment but a social“person”that can be included by social systems.It is clear that digital human rights are the right to participate in digital communication of a“human”as a“person”,so they are possible in terms of conceptual definition.Digital human rights can help“people”lower the threshold for participation in digital communication,limit the excessive expansion of social systems,and promote the free and complete expression of body and mind,so they are necessary for social functions.There are limitations in the existing two ideas of“incorporating digital human rights into the constitution”.Based on the new construction idea of System Theory of Law,digital human rights as the right to participate in digital communication can be typified into digital communication in social sub-fields such as politics,economy,science,and art.The right to participate constructs a complete digital human rights system,making it feasible on the basis of the constitution.

Construction of an Evaluation Indicator System for Civic and Political Applications in Professional Practice Courses Based on CIPP:Taking the VBSE Practical Training Course as an Example

This study takes the virtual business society environment(VBSE)practical training course as a case study and applies the theoretical framework of the context,input,process,product(CIPP)model to construct an evaluation indicator system for the application of civic and politics in professional practice courses.The context evaluation is measured from the support of the VBSE practical training course into course civic and politics,teachers’cognition,and the integration of course objectives;the input evaluation is measured from the matching degree of teachers’civic and political competence,and the matching degree of teaching resources;the process evaluation is measured from the degree of implementation of civic and politics teaching and the degree of students’acceptance;and the product evaluation is measured from the degree of impact of civic and politics teaching.

Polygynous Mating System and Behavioural Reason of Black Crested Gibbon (Nomascus concolor jingdongensis) at Dazhaizi,Mt.Wuliang, Yunnan,China

The field research on five black crested gibbon groups, recently performed at Dazhaizi, Mr. Wuliang, Central Yunnan, China, showed that all groups in the local population consisted of one adult male, two adult females and 2 - 5 sub-adults, juveniles and itfants. The mean group size was 6.2 in August 2003 and 6.4 in August 2005. Two subadult males disappeared from their natal home range and three newborns were given birth in Group 3 （G3） and G4 during this study. The two adult females in G1, G2 and G3 gave births and/or carried babies but at different times. There was no aggressive or dominating behaviour observed between the two adult females. One floating female was first seen in G3＇s territory on April 15, 2005. The two resident females interrupted her duet with adult male and chased her. We did not observe adult male chased this floating female and she left G3＇s territory 10 days later. Sub-adult males often kept distance with the family, and they often sang solo bouts in their natal territory before they dispersed. The sub-adult males and females dispersed from natal territory and two adult resident females rejected the third one, which might were the reasons why the black gibbon groups were polygyny in Dazhaizi.

Brain region-specific roles of brain-derived neurotrophic factor in social stress-induced depressive-like behavior

Brain-derived neurotrophic factor is a key factor in stress adaptation and avoidance of a social stress behavioral response.Recent studies have shown that brain-derived neurotrophic factor expression in stressed mice is brain region–specific,particularly involving the corticolimbic system,including the ventral tegmental area,nucleus accumbens,prefrontal cortex,amygdala,and hippocampus.Determining how brain-derived neurotrophic factor participates in stress processing in different brain regions will deepen our understanding of social stress psychopathology.In this review,we discuss the expression and regulation of brain-derived neurotrophic factor in stress-sensitive brain regions closely related to the pathophysiology of depression.We focused on associated molecular pathways and neural circuits,with special attention to the brain-derived neurotrophic factor–tropomyosin receptor kinase B signaling pathway and the ventral tegmental area–nucleus accumbens dopamine circuit.We determined that stress-induced alterations in brain-derived neurotrophic factor levels are likely related to the nature,severity,and duration of stress,especially in the above-mentioned brain regions of the corticolimbic system.Therefore,BDNF might be a biological indicator regulating stress-related processes in various brain regions.

Way to Push Ahead Corporate Social Responsibility Report System in China

According to the analysis and statistics of relevant institution, it is a prominent problem that CSR reports generally become a mere formality. Through the analysis on the causes, it finds that it is inevitable for the phenomenon. Thus, we proposed to improve the cultivation mechanism of corporate responsibility by ex- panding and advancing the subject and the object, as well as the contents, of fi- nancial analysis in order to push ahead with CSR report in China.

Correlation between anxiety, depression, and social stress in young patients with thoracolumbar spine fractures

BACKGROUND Traumatic injuries,such as falling,car accidents,and crushing mostly cause spinal fractures in young and middle-aged people,and>50%of them are thoracolumbar fractures.This kind of fracture is easily combined with serious injuries to peripheral nerves and soft tissues,which causes paralysis of the lower limbs if there is no timely rehabilitation treatment.Young patients with thoracolumbar fractures find it difficult to recover after the operation,and they are prone to depression,low self-esteem,and other negative emotions.AIM To investigate the association between anxiety,depression,and social stress in young patients with thoracolumbar spine fractures and the effect on rehabilitation outcomes.METHODS This study retrospectively analyzed 100 patients admitted to the orthopedic department of Honghui Hospital,Xi’an Jiaotong University who underwent thoracolumbar spine fracture surgery from January 2022 to June 2023.The general data of the patients were assessed with the Hamilton anxiety scale(HAMA),Hamilton depression scale(HAMD),life events scale,and social support rating scale(SSRS)to identify the correlation between anxiety,depression scores,and social stress and social support.The Japanese Orthopedic Association(JOA)was utilized to evaluate the rehabilitation outcomes of the patients and to analyze the effects of anxiety and depression scores on rehabilitation.RESULTS According to the scores of HAMD and HAMA in all patients,the prevalence of depression in patients was 39%(39/100),and the prevalence of anxiety was 49%(49/100).Patients were categorized into non-depression(n=61)and depression(n=39),non-anxiety(n=51),and anxiety(n=49)groups.Statistically significant differences in gender,occupation,Pittsburgh Sleep Quality Index(PSQI)score,and monthly family income were observed between the non-depression and depression groups(P<0.05).A significant difference in occupation and PSQI score was found between the non-anxiety and anxiety groups.Both depression(r=0.207,P=0.038)and anxiety scores(r=0.473,P<0.001)were significantly and positively correlated with negative life events.The difference in negative life event scores as well as SSRS total and item scores was statist-ically significant between patients in the non-depression and depression groups(P<0.05).The difference between the non-anxiety and anxiety groups was statistically significant(P<0.05)in the negative life event scores as well as the total SSRS scores.Additionally,JOA scores were significantly lower in both anxious and depressed patients.CONCLUSION Young patients with thoracolumbar fractures are prone to anxiety and depression.Patients’anxiety and depression are closely associated with social pressure,which reduces the life pressure of young patients with thoracolumbar fractures,enhances social support,and improves the psychology of anxiety and depression.,which affects patients’recovery.

Mediating role of health literacy in the relationship between social isolation and psychological distress among pre-frail older adults

BACKGROUND Frailty has become a significant public health issue.The recent increase in the number of frail older adults has led to increased attention being paid to psycho-logical care services in communities.The social isolation of pre-frail older adults can impact their psychological distress.AIM To explore the mediating effect of health literacy between social isolation and psychological distress among communitydwelling older adults with pre-frailty.METHODS This descriptive cross-sectional study was conducted with 254 pre-frail older individuals aged 60 years and over.Social isolation,health literacy,and psycholo-gical distress were comprehensively measured using the Lubben Social Network Scale-6,12-item Short-Form Health Literacy Questionnaire,and the Kessler Psy-chological Distress Scale-10.Data were evaluated using the SPSS 27.0 package program and the PROCESS macro tool.Descriptive statistical analyses,correlation analyses,and bootstrap mediation tests were used to assess associations between the variables.RESULTS The results showed that social isolation had an effect on health literacy among pre-frail older adults(β=0.240,P<0.001),social isolation impact on psycho-logical distress pre-frail older adults(β=-0.415,P<0.001);health literacy was identified effect on psychological distress among pre-frail older persons(β=-0.307,P<0.001).Health literacy partially mediated the relationship between social isolation and psychological distress among community-dwelling older adults with pre-frailty,with a mediation effect of-0.074,accounting for 17.83%of the total effect.

Social function scores and influencing factors in patients with residual depressive symptoms

BACKGROUND At present,the influencing factors of social function in patients with residual depressive symptoms are still unclear.Residual depressive symptoms are highly harmful,leading to low mood in patients,affecting work and interpersonal communication,increasing the risk of recurrence,and adding to the burden on families.Studying the influencing factors of their social function is of great significance.AIM To explore the social function score and its influencing factors in patients with residual depressive symptoms.METHODS This observational study surveyed patients with residual depressive symptoms(case group)and healthy patients undergoing physical examinations(control group).Participants were admitted between January 2022 and December 2023.Social functioning was assessed using the Sheehan Disability Scale(SDS),and scores were compared between groups.Factors influencing SDS scores in patients with residual depressive symptoms were analyzed by applying multiple linear regression while using the receiver operating characteristic curve,and these RESULTS The SDS scores of the 158 patients with depressive symptoms were 11.48±3.26.Compared with the control group,the SDS scores and all items in the case group were higher.SDS scores were higher in patients with relapse,discon-tinuous medication,drug therapy alone,severe somatic symptoms,obvious residual symptoms,and anxiety scores≥8.Disease history,medication compliance,therapy method,and residual symptoms correlated positively with SDS scores(r=0.354,0.414,0.602,and 0.456,respectively).Independent influencing factors included disease history,medication compliance,therapy method,somatic symptoms,residual symptoms,and anxiety scores(P<0.05).The areas under the curve for predicting social functional impairment using these factors were 0.713,0.559,0.684,0.729,0.668,and 0.628,respectively,with sensitivities of 79.2%,61.8%,76.8%,81.7%,63.6%,and 65.5%and specificities of 83.3%,87.5%,82.6%,83.3%,86.7%,and 92.1%,respectively.CONCLUSION The social function scores of patients with residual symptoms of depression are high.They are affected by disease history,medication compliance,therapy method,degree of somatic symptoms,residual symptoms,and anxiety.

Ecology and social system of northern gibbons living in cold seasonal forests

Gibbons in China represent the northernmost margin of present day gibbon species distribution （around N25°）. Compared to tropical habitats, northern gibbon habitats are characterized by low temperatures and remarkable seasonal variation in fruit abundance How gibbons adapt to their cold and seasonal habitats and what ecological factors affect their sociality are key questions for understanding their ecology and social system evolution, the elucidation of which will contribute to the conservation of these special populations/species. According to preliminary short-term studies, northern gibbons consume more leaves and use larger home ranges than tropical gibbons. Interestingly, some Nomascus groups consist of more than one adult female. However, these preliminary results are not well understood or incorporated into current socio-ecological theories regarding gibbon species. To better understand northern gibbons, our team has systematically studied three habituated groups of Nomascus concolor, three groups of N. nasutus, and two habituated groups of Hoolock tianxing since 2002. In this paper, we stress the challenges facing gibbons living in northern habitats and summarize their behavioral adaptations to their harsh environments. We also describe the northern gibbon social system and discuss the potential relationships between their ecology and sociality. Finally, we highlight future research questions related to northern gibbons in China.

Impact of social isolation on behavioral health in elderly: Systematic review

AIM: To examine and compare the effects of subjective and objective social isolation on behavioral health in elderly adults.METHODS: A systematic search of Pub Med was performed for original research articles from peerreviewed journals examining one of the following topics: "Social isolation and sleep disturbance", "social isolation and depression", or "social isolation and fatigue in older adults". Studies were selected following the criteria established based on the aim of this review. Data were extracted from the articles by two independent reviewers. Due to the heterogeneity in study designs and outcome measures of the included studies, qualitative and narrative analyses were conducted.RESULTS: The set criteria were used to select a total of 16 studies for the review. Of the 16, 13 were crosssectional studies. The characteristics of study populations were identified as follows. A total of 12 studies randomly selected subjects irrespective of pre-existing health conditions. Consequently, an unspecified number of the study subjects had chronic diseases in the studies compared. In addition, cultural and ethnic backgrounds of studies in this review were diverse, and included subjects living in North America, South America, Asia, Europe, and Oceania. Both subjective and objective types of social isolation increased behavioral symptoms, such as sleep disturbance, depressive symptoms, and fatigue in older adults. Furthermore, a few recent studies reported stronger effects of subjective social isolation than objective social isolation on sleep disturbance and depressive symptoms.CONCLUSION: Social isolation affects behavioral health in older adults. Compared to the objective social isolation, subjective social isolation contributes more significantly to sleep disturbance and depression.

Land cover changes and fragmentation in mountain neotropical ecosystems of Oaxaca, Mexico under community forest management

Changes in land cover have a direct impact on forest ecosystem goods and services. In this study, changes in land cover in Sierra de Juarez–Oaxaca ecosystems were estimated using a consistent processing of Landsat images and OBIA methodology. Additionally, landscape analyses using FRAGSTAT were conducted. In 2014, Sierra de Juarez–Oaxaca was covered by approximately 84% of forests, mainly pine-oak and cloud forests. After extensive deforestation until 2001, this trend was reversed and the forest cover surface area in 2014 was slightly higher than in 1979. The comparison of the landscape structure of the forested and agricultural lands suggests an increase in habitat heterogeneity. However, interspersion and juxtaposition indices, showing the patch shape by patch area and perimeter, were similar throughout the study period(1979–2014). Social and economic drivers can explain this situation: namely, community organization, forest enterprises, payment for ecosystem services programs, and changes of agricultural activity. Communities in the Sierra of Oaxaca have reforested degraded lands, created community forest enterprises, and preserved the forest under conservation schemes like those proposed by the Mexican payment for ecosystem services programs. However, their sustainable management faces internal challenges and has become highly dependent on political and institutional decisions beyond their control.