Artificial Intelligence Technologies as Smart Solutions for Sustainable Protected Areas Management
Abstract
1. Introduction
2. Materials and Methods
- Sample Group
- Data Collection Tool
- What are the main problems and challenges in achieving sustainability in protected areas management?
- What do you think about the applicability and current use of AI technologies in protected areas management? Which AI applications could be particularly effective?
- What is the potential of AI in achieving sustainable protected areas management goals in your country? How can these technologies contribute to environmental sustainability?
- What are the main legal challenges related to the application of artificial intelligence in protected areas management? What legal measures can encourage the implementation of AI in sustainable forest management?
- Does the use of AI technologies in forest management create any challenges in terms of legal frameworks and ethical standards in Morocco? How is regulation and oversight applied in this?
- What collaboration models or strategies would you suggest for public institutions to adopt AI technologies in forest management? What is the status and future of such collaborations?
- How do you see the role of AI technologies in protected areas management evolving in the future? What strategic plans do in your country have to implement these technologies on a larger scale?
- Analysis of Interview Data
3. Results
In the context of the emerging theme “Economic and Social Activities Conflicting with Conservation”, FMM-4 highlights the relationship between financial development and environmental conservation in the country, emphasizing that economic activities may be disrupted if the natural environment deteriorates (AT-2). Under the heading “Climate Change and Natural Threats”, it is emphasized that global climate change increases risks in protected areas and negatively affects the conservation strategies of local managers (NGOEL-3). Another threat identified is under the theme “Biodiversity and Illegal Activities”, where it is pointed out that illegal hunting activities pose a significant risk to biodiversity. Illegal hunting represents a major threat to our country, with people hunting certain species despite the risk of extinction. This is highlighted as a significant issue for biodiversity (LM-6). Another concern is the “Local Community Participation” theme, where the lack of local community involvement in the sustainable management of protected areas is considered one of the biggest obstacles. The sustainable management of protected areas is only possible when the local population feels a sense of ownership over the region. Social participation is essential and must be effective (FML-4).
Sustainability in protected areas requires the effective implementation of legal frameworks. However, in many cases, existing laws are not sufficiently robust, and local authorities fail to enforce regulatory mechanisms effectively (LT3-TNGOE1). Conflicting legislation and regulatory inconsistencies create legal uncertainty, limiting sustainable conservation efforts and complicating collaboration among relevant stakeholders. These legal inconsistencies hinder the effective implementation of conservation policies (LL7-LA4). Another major challenge in achieving sustainable management of protected areas is the reluctance of local communities to adopt and implement conservation practices (FMT6). Sustainable management practices in protected areas face many obstacles. The most important of these is that the people living in that area contribute little to the conservation of these areas and hinder this process. Therefore, the sustainable management approach is sometimes disrupted (FML9).
The limited availability of financial resources and the slow pace of technological advancements disrupt effective monitoring processes in protected areas, thus hindering sustainable management. The lack of technological infrastructure negatively impacts data collection and analysis, preventing the timely detection of environmental changes and the implementation of appropriate measures (LM4, FEM5-LM3).
AI can be particularly beneficial for monitoring natural disasters (e.g., wildfires) and enabling rapid response mechanisms. However, the successful implementation of these technologies requires collaboration at both local and national levels as well as investment in infrastructure. Ensuring the sustainability of AI-based technologies also necessitates regular maintenance and technical support (FMT4-6). In Lithuania, AI has the potential to make significant contributions to nature conservation, but this would require investments in data collection, adaptation of AI models to local conditions, and ensuring that institutions and experts are adequately prepared to utilize these technologies (FML2-AL3-7). Strengthening data collection mechanisms, enhancing technological infrastructure, and developing localized solutions can enable the effective use of AI and other advanced technologies, thereby generating both environmental and economic benefits (FEM5).
Today, artificial intelligence technologies are an increasingly widespread and powerful tool in the sustainable management of protected areas. It is an important tool for the protection and sustainability of biodiversity and combating forest fires, which have recently increased, and it also makes significant contributions to the protection of environmental health (FMT5-FET6.8). It also contributes significantly to the detection and reduction of environmental crimes. Facilitating management processes and effective management is a very important process (LT1-7).
Although the use of AI in the management processes of protected areas in Morocco is not yet widespread enough, there are initiatives to apply AI, especially in the identification and monitoring of different species and, of course, in the fight against forest fires (FEM3-4-5). AI is quite popular for biodiversity conservation and sustainable management of natural areas, but yes, it is not yet very widespread. We need to overcome this situation and increase the use of AI in management processes. In the process, AI infrastructure investments should be increased, and we should build a strong technology infrastructure for the future (NGOEM2-9).
Lithuania. No, the use of AI in the management of protected areas is not yet at the desired level, there is actually a huge potential, but as I said, there is not yet widespread use, unfortunately (NGOEL5). There is a huge transformation, and it is necessary to support the use of AI in the management of protected areas. The use of AI is inevitable, especially for monitoring and protecting environmental health, tracking and reducing environmental crimes, and harmonizing tourism activities in these areas with the environment (FEL5).
There are, of course, legal regulations on the environment in the country, but I think the effectiveness of these laws will increase with the widespread use of AI. The objectives targeted in the laws can be concretized with AI and can be used as an important tool for managers (LT3-4-9). One of the most important problems is environmental crimes. With the use of AI, detection and prevention of crimes can become easier and contribute to the fight against crime. Therefore, it can contribute to the sustainable management of protected areas (AT4-5). In Morocco, there is no specific legal framework for the use of AI in environmental management, which presents a challenge for the effective regulation and implementation of AI technologies in this field (LM7-9, FEM1-8). Who is responsible for decision-making errors made by AI? If an AI system incorrectly detects an infringement in the natural environment or misses a significant event (e.g., illegal logging), it is necessary to clearly define the boundaries of responsibility (FML5-6, LL2-8).
There are uncertainties regarding the legal compliance of AI usage. In Turkey, there is a lack of concrete legal regulations for AI usage, and ethical standards are generally based on general technology laws (LT1-2-9). Legal regulations regarding the use of AI technologies have yet to be sufficiently developed. Ethical standards are still in the development phase. The absence of comprehensive legislation in this field complicates supervision and regulation (NGOET4-7-8).
The lack of legal arrangements and policies on AI is a major concern in Morocco. This is because it is often argued that data policies and data privacy may be violated. I think this is the most important obstacle to the use of AI (FEM7-8-9). The use of AI in the management of protected areas is inevitable once legal gaps are addressed. However, very serious regulations are required for this (FMM4-6).
In Lithuania, the use of AI in the nature conservation sector is not yet strictly regulated. However, the Lithuanian Environmental Protection Law provides a framework for AI usage in nature conservation measures and monitoring, offering a workable framework in this field (FML2, AL4-6).
In Morocco, the government prioritizes the Public-Private Partnerships (PPPs) model to encourage collaboration between public institutions and AI companies (FEM5-FEM2-8). Additionally, universities are encouraged to take leadership in AI-based environmental research projects, which can advance the integration of AI technologies in protected area management and environmental protection (FMM4-6).
In Lithuania, it appears that the country is working on establishing open data platforms to support the integration of AI technologies into protected area management strategies, while also incentivizing the private sector and academia through tax reductions and innovation funds. Furthermore, Lithuania values participation in European Union projects for international experience sharing. The Lithuanian government can promote the implementation of AI in forestry through clear strategies, financial support, and open data initiatives. By collaborating with business and academia, it can develop innovative solutions for sustainable forest management (FEL4-5-9).
In Turkey, the government aims to establish stronger collaborations with the private sector and academic institutions. Turkey believes that legal frameworks need to be developed for AI technologies, while also focusing on sector-specific training and raising awareness. Governments should collaborate with academia and the private sector to encourage the effective use of AI technologies in the forestry sector and implement regulations to ensure the applicability of these technologies (NGOET7-FET8). For AI to be used effectively in protected area management, governments should create a strong legal infrastructure and encourage closer collaboration between the private sector and academia. Education and awareness-building are also important steps (LT1-2-7).
There is significant potential for AI technologies to be used in forest management. Turkey’s strategic plans in this area should focus particularly on monitoring forest fires and protecting biodiversity (FMT7-9, LT1-3). Academia can provide guidance in the implementation of these technologies. The integration of AI technologies into forest management could revolutionize data collection and analysis. For the successful implementation of these technologies in Turkey, local governments and the state need to establish strategic partnerships (NGOET4-FET9). AI tools can be highly effective in the management of protected areas as they work with real-time data, but the correct needs must be identified (AT-7). In Turkey, the use of AI technologies should be increased, particularly in combating forest fires, and their proper application for early detection should be widely promoted (NGOET-4).
Morocco’s future for AI in forest management focus on integrating AI into national environmental policies, increasing investment in AI-driven research and monitoring systems, and developing decision-making frameworks for conservation (AM7-8). The country aims to scale AI by expanding pilot projects to national parks and strengthening partnerships with academia and technology firms (LM4). Additionally, Morocco is working on encouraging AI-based policymaking to support sustainability goals, fostering a collaborative approach to enhance forest management (NGOEM5).
Lithuania, meanwhile, aims to use AI technologies in areas such as data collection and forest health monitoring, having developed an AI action plan for 2023–2026, and is working to strengthen academic collaborations through innovative projects like Forest 4.0.
The Forest 4.0 project aims to create a center of excellence for forest-related AI and Internet of Things (IoT) technologies, involving Vytautas Magnus University, Linnaeus University (Sweden), Kaunas University of Technology, and companies Art21 and Agrifood (FEL5). The Ministry of Environment emphasizes the need to improve the efficiency of forest information collection, automate data collection and monitoring, and implement AI solutions (AL5-7).
4. Discussion
- (a)
- Legal Challenges
- (b) Technological Barriers
- (c) Collaboration Strategies
5. Conclusions
- ✓ In Turkey and Lithuania, the main issues faced in protected areas are the inadequacy of legal regulations, resistance from local communities toward legal processes, and lack of participation, whereas in Morocco, infrastructure deficiencies and illegal activities are the primary challenges;
- ✓ In the management of protected areas, similar themes emerged regarding the use of AI in all three countries. The most significant barrier to AI use was the lack of legal regulations. However, it was also noted that increasing infrastructure investments and enhancing collaboration at the local level would promote the wider adoption of AI;
- ✓ When evaluating the impact of AI use on the sustainable management of protected areas, similar themes emerged in all three countries. Particularly, forest fire detection and suppression, biodiversity conservation, prevention of illegal activities, and early detection systems were identified as areas where AI could significantly improve the management of protected areas;
- ✓ A key finding highlighted that for the widespread adoption of AI in the sustainable management of protected areas, public–private sector collaborations should be enhanced in all three countries. Additionally, governments should provide tax reductions and develop incentives for innovative applications, and academia should offer scientific data support in this field.
- ✓ In the fight against forest fires, prevention of illegal activities, environmental sustainability, conservation of natural resources and combating climate change, it is inevitable to integrate technology transfer into the sustainable management of protected areas. For this, governments in all three countries are expected to support and encourage managers through tax breaks and incentive policies.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Country | Experts | Codes |
---|---|---|
Turkey | Lawyer | LT (1-2-3-4-5-6-7-8-9) |
Academics | AT (1-2-3-4-5-6-7-8-9) | |
Forest Managers | FMT (1-2-3-4-5-6-7-8-9) | |
Forest Expert from Government | FET (1-2-3-4-5-6-7-8-9) | |
Non-governmental organization Expert (NGO) | NGOET (1-2-3-4-5-6-7-8-9) | |
Lithuania | Lawyer | LL (1-2-3-4-5-6-7-8-9) |
Academics | AL (1-2-3-4-5-6-7-8-9) | |
Forest Managers | FML (1-2-3-4-5-6-7-8-9) | |
Forest Expert from Government | FEL (1-2-3-4-5-6-7-8-9) | |
Non-governmental organization Expert (NGO) | NGOEL (1-2-3-4-5-6-7-8-9) | |
Morocco | Lawyer | LM (1-2-3-4-5-6-7-8-9) |
Academics | AM (1-2-3-4-5-6-7-8-9) | |
Forest Managers | FMM (1-2-3-4-5-6-7-8-9) | |
Forest Expert from Government | FEM (1-2-3-4-5-6-7-8-9) | |
Non-governmental organization Expert (NGO) | NGOEM (1-2-3-4-5-6-7-8-9) |
Challenge Area | Turkey | Lithuania | Morocco |
---|---|---|---|
Economic and Social Activities Conflicting with Conservation | Local communities resistant to sustainable management; dependence on forest products. | Agriculture; forestry conflict with nature protection. | Tourism, agriculture, and conservation clash; land use conflicts. |
Climate Change and Natural Threats | Forest fires; climate change, over-exploitation. | Climate change impacts species habitats. | Climate change affecting forest regeneration. |
Limited Resources and Infrastructure | Limited budgets; lack of scientific data collection resources. | Limited budgets for protected area management; infrastructure difficulties. | Limited technological infrastructure; insufficient funding for monitoring. |
Tourism and Human Activities Environmental Impacts | Excessive tourism; recreational activities causing ecosystem damage. | Increased visitor traffic causing littering, noise, and ecosystem damage. | Tourism and environmental degradation; conflicting demands. |
Biodiversity and Illegal Activities | Illegal hunting; logging; weak deterrent penalties. | Monoculture forestry reducing biodiversity; invasive species. | Deforestation; illegal logging; impact on biodiversity. |
Inadequate Legal Frameworks and Conflicting Laws | Inadequate local laws; insufficient enforcement of regulations. | Conflicting regulations; lack of cooperation between institutions. | Conflicting land use demands; lack of real-time data for decision making. |
Local Community Participation | Insufficient local community involvement in conservation. | Limited involvement of local communities; insufficient education programs. | Lack of community involvement in sustainable management. |
Country | Current State of AI Applications | Effective AI Applications | Infrastructure and Legal Barriers | Education and Local Involvement |
---|---|---|---|---|
Turkey | AI applications have started to develop in Turkey, but there are infrastructure gaps and legal barriers. | Smart monitoring systems Forest fire detection Monitoring illegal activities | Infrastructure deficiencies Data security and legal regulations Legal barriers to monitoring illegal activities | Education of local communities and authorities is required Collaboration between public and private sectors is essential |
Lithuania | AI applications are not widely utilized, but early steps have been taken. | Satellite data and GIS technologies Drone use Smart sensor networks chatbots and visitor flow management | Infrastructure gaps and legal regulations Need for local authorities to adapt to the technology | Training for local authorities and raising awareness in communities is necessary |
Morocco | AI technologies are in the early stages of adoption, with limited use in forest management. | Remote sensing (satellite imagery) Drone use and IoT sensor networks Predictive modeling (forest fire risk prediction) | Lack of infrastructure investment Insufficient training at the local level | Training is necessary Encouraging collaboration between government bodies and the private sector |
AI Application Areas | Turkey | Morocco | Lithuania |
---|---|---|---|
Species Identification | Monitoring biodiversity and environmental crimes | Track wildlife in protected areas | Automatic animal species recognition |
Forest Ecosystem Monitoring | Forest health, fire detection, and ecosystem monitoring | Drones and IoT sensors for ecosystem health tracking | Drones and sensors for monitoring forest health and animal populations |
Illegal Activity Detection | AI used for detecting illegal logging, poaching, and other environmental crimes | AI used in surveillance to combat illegal activities | PAWS AI for predicting poaching locations; TrailGuard AI for real-time monitoring |
Climate Change Analysis | AI supports monitoring climate effects on forests and biodiversity | AI helps mitigate environmental impacts through climate adaptation strategies | AI for climate change adaptation and ecosystem monitoring |
Resource Management | Data-driven decision making for sustainable forest management | AI in water and soil management for better land-use planning | GIS and satellite data for monitoring protected areas (not fully integrated with AI) |
AI Technologies Used | Satellite imagery, drones, sensors, and data analysis | Remote sensing, drones, and predictive modeling | GIS, drones, sensors, satellite imagery, and mobile guides |
Level of AI Development | Advanced use, particularly in forest and biodiversity management | Early-stage AI applications | Emerging AI use with significant growth potential |
Category | Morocco | Lithuania | Turkey |
---|---|---|---|
Legal Arrangements | Inadequate legal arrangements for AI | Update existing AI regulations | AI integration into environmental laws |
Data Privacy and Ethical Issues | Ethical concerns; data policies and concerns about changing jobs | GDPR compliance in data use; legal framework in privacy and audit | AI trustworthiness; ethical concerns and verification |
Legal Measures | AI governance policies | Public–private partnership; current legal framework for AI | Legal promotion of AI use |
Country | Legal Challenges | Ethical Concerns | Oversight and Arrangements |
---|---|---|---|
Turkey | Lack of legal arrangements for AI | Data privacy and ethical concerns for AI | Lack of legal arrangements for AI and ethical concerns |
Morocco | Lack of legal arrangements for AI Data privacy for AI | Questioning AI decision-making processes; data privacy and oversight | Lack of legal arrangements for AI Current Legal Arrangements |
Lithuania | Lack of legal arrangements for AI Reliability of data generated by AI | AI validity and reliability Reliability of data generated by AI | Eligibility for EU Current Legal Arrangements |
Strategy Areas | Morocco | Lithuania | Turkey |
---|---|---|---|
Public–Private Partnerships | Encouraging collaboration with the private sector. | AI pilot projects and incubators for collaboration. | Stronger partnerships with the private sector. |
Academic Research | Universities should lead AI-based environmental research. | Funding research centers for AI solutions. | Funding for academic research is provided. |
International Cooperation | Partnerships with global organizations. | Participation in EU AI projects and experience exchange. | International collaborations and tech sharing. |
Data Availability | Access to data for AI implementation. | Open data platforms for AI systems. | Open data policies should be developed. |
Financial Support | ------------- | Tax breaks and innovation funds for AI projects. | Tax incentives and financial support are necessary. |
Themes | Morocco | Lithuania | Turkey |
---|---|---|---|
Future AI Implementation Plans | Updating environmental policies for AI. Supporting the use of AI in research. | AI Action Plan 2023–2026. Forest 4.0 project. Academic initiatives for AI. | Legal regulations for AI technologies. Investment in AI research. |
Scaling AI in Protected Areas Management | Expanding AI in national parks. Partnerships with academia and tech firms. Policy-making support for sustainability. | Forest data management systems. Collaborations between academia and government. Expansion of AI applications. | Stronger AI integration with local authorities. Collaboration between government, local authorities, and academia. Strengthening digital infrastructure. |
Strategic Plans | Investment and government policies for AI. Enhancing monitoring and fire prevention. | AI-driven forest management solutions. Integration of AI into national forest management policies. Innovations in AI for forest sustainability. | Inadequate legal arrangements for AI. Government policies for AI. AI-powered research. |
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Share and Cite
Atalay, A.; Perkumienė, D.; Safaa, L.; Škėma, M.; Aleinikovas, M. Artificial Intelligence Technologies as Smart Solutions for Sustainable Protected Areas Management. Sustainability 2025, 17, 5006. https://doi.org/10.3390/su17115006
Atalay A, Perkumienė D, Safaa L, Škėma M, Aleinikovas M. Artificial Intelligence Technologies as Smart Solutions for Sustainable Protected Areas Management. Sustainability. 2025; 17(11):5006. https://doi.org/10.3390/su17115006
Chicago/Turabian StyleAtalay, Ahmet, Dalia Perkumienė, Larbi Safaa, Mindaugas Škėma, and Marius Aleinikovas. 2025. "Artificial Intelligence Technologies as Smart Solutions for Sustainable Protected Areas Management" Sustainability 17, no. 11: 5006. https://doi.org/10.3390/su17115006
APA StyleAtalay, A., Perkumienė, D., Safaa, L., Škėma, M., & Aleinikovas, M. (2025). Artificial Intelligence Technologies as Smart Solutions for Sustainable Protected Areas Management. Sustainability, 17(11), 5006. https://doi.org/10.3390/su17115006