Leveraging Artificial Intelligence (AI) in Strengthening the Legal Framework for Regulation of Wildlife and Forest Crimes in Nigeria

1Introduction

AI, traditionally a computer science domain, refers to machines’ ability to display intelligence distinct from the innate intelligence found in humans and other living beings.¹ Wang and Srinivasan defined the term as science and engineering concerned with creating machines exhibiting human-like intelligence.²Z. Thus, to effectively accomplish activities begun by humans, AI robots must first learn from experience to adapt to new inputs and overcome problems that arise in daily life.³

John McCarthy introduced AI in 1956 as a field of science and engineering focused on developing intelligent machines.⁴ AI is primarily concerned with the replication of human intelligence within computer systems. Its main goal is to develop computer systems that mimic human thinking and decision-making processes. Today, AI is making significant strides and finding applications across various industries, including gaming, finance, retail, business, and government. This technology is not limited to a single field but is profoundly impacting diverse sectors. As 21st-century environmental concerns escalate, AI is essential to tackle many of these sustainability issues. Research has suggested that AI can help direct public attention to common environmental problems, making them easier to manage.⁵ Over the last 50 years, emphasis on AI’s robustness has emphasised the necessity of environmental sustainability during the development and application of technology, according to Jha.⁶ The employment of AI-related technology in lowering the prevalence of wildlife trafficking and forest crimes in many developed countries is one such indicator of environmental sustainability that has profited from its practical use in recent years.⁷ According to Rusch and Arora, the fight against the illicit wildlife poaching industry remains daunting given its high profit and low exponentials.⁸ However, AI-based approaches can reverse the narrative and turn it into a high-risk enterprise.⁹

Nigeria has become a significant source and transit country for illegally traded wildlife products in the last ten years. The United Nations Office on Drugs and Crime UNODC’s World Wildlife Crime Report (WWCR) 2020 reported that in 2019 in Nigerian ports, the amount of confiscated pangolin scales surged to 51 tons, a significant increase from the 2 tons seized in 2015.¹⁰ Data shows that Nigeria plays an increasingly important part in the illegal ivory trade, with approximately 25% of all confiscated ivory worldwide being transported through Nigerian ports.¹¹ Despite efforts by the government at both the federal and state levels through the machinery of law and the establishment of agencies to stem the trend of wildlife and forest crimes, Nigeria faces a daunting task in boosting its capacity to combat wildlife trafficking crossing its borders. Therefore, there is a need for focused and strategic measures to strengthen the nation’s ability to mount a forceful and effective legal retort to the issue of wildlife and forest types of crimes.¹²

This paper thus explores the gap as to how the Nigerian government can leverage on AI to achieve enhanced compliance with the existing legal framework on biodiversity conservation and reduce the incidents of crimes against its wildlife and forests. The use of AI for environmental sustainability in Nigeria has not been discussed much. To bridge this gap, this paper finds how AI techniques and options can best be used to strengthen the challenges in compliance with the extant laws on wildlife and forest crimes in Nigeria. The paper will be structured into six parts, the first being the introduction. The second part examines the levels and domains of AI for environmental sustainability. The third part is an exposés on the preponderance of wildlife and forest crimes as a significant drawback for Nigeria’s biodiversity conservation and environmental sustainability. The fourth part discusses the extant legal responses of the government to this problem. At the same time, the fifth section proposes the infusion of AI-related technologies as a solution for strengthening the capacity of these laws to achieve their objectives, whilst the last section is the concluding paragraph.

2Levels and Realms of AI for Environmental Sustainability

In the contemporary digital era, the term “AI” denotes the capacity of a computer-controlled robot to perform tasks based on the cognitive abilities of intelligent humans.¹³ This concept finds extensive application in developing systems endowed with mental faculties akin to human beings, including the capacity for reasoning, generalisation, learning from past experiences, and seeking meaning.¹⁴ In simpler terms, AI research centres on harnessing language, logic, perception, and learning to analyse and address complex problems.s many. AI systems are now present in many areas of our life.¹⁵ Various data-driven, networked, and automated applications help us communicate, trade, and acquire information daily. Today, all facets of business, research, and policy-making already utilise technology to advance knowledge, manage processes more effectively, and ultimately control and influence our environment.¹⁶ This has also been extended to the field of environmental sustainability.¹⁷

In their research on the contribution of AI to achieving the Sustainable Development Goals (SDG), Vinuesa. highlighted that AI’s advantages could arise from its ability to analyse extensive, interconnected databases to devise collaborative efforts toward environmental conservation.¹⁸ The study indicates that AI development can help comprehend climate change, compute its potential effects, and foster low-carbon energy systems that rely heavily on renewable energy and energy efficiency –all essential for dealing with climate change. In a related study, Akshara also explained that AI can help protect local ecosystems by assisting environmental agencies in making informed decisions to reduce air pollution and protect public health.¹⁹ Mohammadi,²⁰ found that AI tools, including neural networks and objective-oriented methods, can rapidly and efficiently classify vegetation cover types in satellite images. This data can inform environmental decision-making and management, leading to the prevention or reversal of desertification trends. Furthermore, Vinuesa argued that AI can help tackle SDG 14’s goal of reducing marine pollution by using algorithms to detect oil spills quickly.²¹

Similarly, Cowls J. ’s research explained that the potential of AI and other technologies will allow us to understand better and tackle environmental challenges by increasing our knowledge base through the results provided by analysing large amounts of data on the environment.²² For instance, biodiversity research can benefit from developing machine learning (MLE) processing solutions that can be used to predict ecosystem services.²³ AI applications and MLE models are now being used more often for predicting and improving water conservation.²⁴ In the same vein, area neural networks, expert systems, pattern recognition, and fuzzy logic models are helping to provide more knowledge in the energy sector with a focus on renewable energy,²⁵ and Computer Vision and Decision Support are now used in transportation.²⁶

In addition to the above, AI enables firms to autonomously tackle environmental challenges, such as waste removal, for improved sustainability.²⁷ Cheng, Lefeng, and Tao Yu believe that AI involves Machine Learning (ML), which allows machines to use past data and experiences for problem-solving.²⁸ Thus, ML can be used to anticipate environmental issues, such as stream flow and water quality metrics.

Sustainable agriculture is another aspect of environmental sustainability that has benefited from AI and its technologies. Through robotics, which combines cognitive behaviour from humans, such as emotions and thinking, AI robots can now execute tasks using human actions and other manipulations.²⁹ This has simplified farm tasks such as seeding, planting, fertilising, weeding, spraying, irrigating, harvesting, and shepherding, which would typically require more human labour. AI also allows for water resource variables, crop nutrition levels, and weed/crop differentiation predictions.³⁰

AI has also addressed the challenge of managing large amounts of constantly changing environmental data when determining environmental protection tactics. For example, AI has been implemented in the design of wastewater treatment plants to improve their effectiveness and capacity. Additionally, AI has led to innovative waste management approaches, such as developing intelligent trash cans and waste-sorting robots at landfills.³¹ Artificial Neural Networks (ANN) have offered several solutions for detecting and warning of oil spills in marine life conservation and pollution prevention. AI-based Autonomous Underwater Vehicles (AUVs) and underwater robots have enabled the forecasting of the propagation of invasive species, tracing marine debris, observing ocean currents, identifying “dead zones,” and gauging pollution levels. These tools can also create an open living database of aquatic health and fish populations, carry out deep sea assessments, and provide real-time monitoring of sea pollution.³²

Therefore, no doubt, utilising AI-related technologies has the potential to help in achieving the vision of environmental sustainability.

3Wildlife and Forest Crimes: A Legal Challenge

The nation of Nigeria abounds in natural resources.³³ Its varied climatic conditions and physical features contribute to the abundance of its wildlife and forests, creating one of the richest biodiversities in Africa.³⁴ These resources have economic and nutritional values and ecological, medicinal, educational, scientific, recreational, and socio-cultural importance.³⁵ Nigeria’s natural environments vary greatly, spanning from semi-arid savannas to mountainous forests and encompassing fertile seasonal floodplains, rainforests, expansive forests of freshwater swamps and a varied assortment of coastal vegetation.³⁶ Nigeria’s Niger Delta is home to Africa’s most significant mangrove habitats.³⁷

Nigeria is home to an estimated 4,715 vascular plant species, 285 mammal species, 117 amphibian species, over 775 fish species and, potentially, many more undocumented species.³⁸ Nonetheless, Nigeria’s wildlife reserves are rapidly declining due to human activities, especially modifications in land use and overexploitation through practices like fishing, logging, and hunting.³⁹ Of particular importance to this study is the impact of wildlife and forest crimes as a significant driver of this overexploitation, a dilemma for wildlife conservation in the country.

On September 8 2022, the Nigeria Customs Service at Murtala Mohammed Airport seized 7,000 pieces of donkey genitals with a declared value of more than N216 million that were intended for export to Hong Kong.⁴⁰ Although, according to the Customs Area Controller, Sambo Dangaladima, this was the first time they were seizing such an item, the Organised Crime and Corruption Project (OCCRP) reported that in July of the same year, 2,820 donkey hides valued at $116,000 was being prepared for illegal export from the country were seized by the Nigerian Customs Service.⁴¹ This is coming a month after the Leadership Newspaper reported that Muhammad Umar, Controller of the Kano/Jigawa Command of the same unit, verified that the command had handed over 3,712 confiscated donkey skins and three bags of donkey penises weighing 100 kg each.⁴² Despite the Nigerian government’s endeavours, the situation above exemplifies the country’s current state and pervasiveness of wildlife crimes.

Studies conducted over the years have demonstrated that these crimes against nature have been on the rise for a considerable amount of time and have persisted despite government efforts to stop them, providing a significant barrier to wildlife conservation in Nigeria. In a study by Olateru and Egonmwan on the challenges of wildlife conservation in Nigeria’s Okomu National Park,⁴³ wildlife loss is increasing in the park due to wildlife and forest crimes despite being a designated protected area for the country. According to the study, despite efforts to prevent it, Okomu National Park is subject to poaching, farming, logging, and non-timber product collection, albeit its adverse impacts on wildlife conservation. This was mainly due to the community’s view that nature provided wildlife for commercial and subsistence purposes rather than for preservation. In a related study by Jacob Daniel, a Cross River National Park case study was conducted to examine wildlife poaching in Nigerian national parks. The author found that the economic incentive behind wildlife and forest crimes poses a significant threat to the future of Nigeria’s diverse ecosystems.⁴⁴ The study’s data revealed that even though most respondents were aware of the park’s restrictions on animal poaching and the consequences for violators, they continued to break these laws without consequence. The dynamics and socioeconomic drivers of the illegal hunting of wildlife for consumption in Oba Hills Forest Reserve, located in Southwest Nigeria, were investigated by Akinsorotan. The study concluded that controlling wildlife and forest crimes remains extremely difficult in Nigeria, leaving the future of wildlife conservation bleak.⁴⁵ Using illegal bushmeat hunting as a case study, the authors found that poverty and people’s perception remains the primary driver of wildlife and forest crimes in Nigeria, and the resultant effect is a decline in wildlife conservation. These crimes continue to persist owing to the demand from wealthier communities. Many of those involved in these crimes are in it either for luxury, to meet market demands for ivory at local and international levels, or meat for subsistence or commercial uses.

Similarly, Beekman’s book explains that Lake Chad has dramatically decreased in size, losing more than 90% due to water overutilisation and climate change.⁴⁶ This has led to the destruction of fisheries, agriculture, and pastures, resulting in an estimated 49 million people who depend on its resources, mainly in Nigeria, to be in a precarious situation. The jeopardy faced by the sustenance of local communities and the preservation of natural ecosystems and biodiversity cannot be understated. These factors are fundamental for a just and sustainable society, a robust economy, and a secure future. Consequently, curbing overexploitation, which includes wildlife crime, is a significant obstacle to conserving the flora and fauna in and around the lake. A study conducted by Omifolaji⁴⁷ revealed that Nigeria boasts the presence of three out of the four pangolin species found in the Afro-tropical forests of Sub-Saharan Africa. The research shed light on the fact that these remarkable creatures are frequently hunted for various purposes, including as a source of bushmeat, for ethno-medicinal remedies, and even as a game. Over the last five years, the escalation of demand from global markets has led to a surge in poaching incidents and seizures. This has resulted in the depletion of local pangolin populations and the destruction of their habitats in West and Central African countries, including Nigeria.

Mahi and Usman’s study⁴⁸ showed that community members often rationalise and justify hunting as part of their heritage and felt the establishment of Kainji National Park was intruding on this. This became a significant catalyst for illegal hunting, with poachers employing various tactics. These tactics included resorting to mystical powers, targeting vultures, offering bribes, utilising community members as informants, predicting the movements of park rangers, selling hunted animals to familiar and new customers, and leveraging their expertise in navigating the forest environment. The persistence of poaching can be attributed to the rich diversity of available wildlife and the unfortunate presence of corruption among park rangers. This paints a concerning picture of the challenges faced in combating illegal hunting.

According to the World Wildlife Crime Report 2020 by the UNODC, the illegal trade of ivory is estimated to be worth anywhere between $310 to $570 million, while the trade in rhino horn is valued at $170 to $280 million.⁴⁹ In July 2021, three suspects were arrested, and 196 sacks containing 4.6 Kgs. of pangolin claws, 888.5 kgs of ivory and 7,167 Kgs. of pangolin scales were seized by the Nigerian Customs Service during a search at a residence in Lagos.⁵⁰ Similarly, in September 2021, two suspects were arrested, and 15 sacks with over 1 tonne of pangolin scales, representing more than 2,500 dead pangolins, and 5 kgs of pangolin claws were seized.⁵¹ This illegal wildlife trade has devastatingly affected wildlife conservation in Nigeria. For example, Yankari National Park, the stronghold of Nigerian savanna elephants (L. Africana), experienced a population decline from 350 in 2006 to only 100 in 2015 due to poaching and ivory trafficking.⁵² There are also reports of endangered hooded vultures being openly traded in Nigerian markets.⁵³

Wildlife and forest crimes severely threaten nations’ resources, with their most profound impact felt by vulnerable individuals and communities.⁵⁴ Unfortunately, the consequences of conservation efforts are often overlooked. These crimes persist due to their low-risk nature and minimal sanctions, rendering them an attractive option for criminals. Several factors drive wildlife and forest crimes in Nigeria, and addressing these issues is vital to reducing the nation’s vulnerability.⁵⁵ Foremost among the drivers of such crimes are porous borders, enabling illicit trade in wildlife and forest products to flourish.⁵⁶

Additionally, corruption at various levels of governance further exacerbates the problem, fostering an environment where criminal activities can thrive with relative impunity.⁵⁷ Political apathy and enforcement challenges compound these issues, making it imperative to devise effective strategies for combating these crimes. The following section will examine the frameworks to combat these drivers and reduce Nigeria’s vulnerability.

4Policy, Legal and Institutional Responses

Nigeria faces massive challenges in preventing wildlife and forest crimes. Laws exist to confront these crimes, particularly those associated with vulnerable and endangered species, to create a unified response to the prevalence of these offences. This analysis will examine existing legislation tackling wildlife crimes in Nigeria.

5Artificial Intelligence as an Algorithm for Strengthening Legal Framework for Wildlife and Forest Crime Prevention

Advances in computation, technology and AI-related research have increased their application in environmental conservation.⁹⁴ Recently, the social media space was awash with the story of a Nigerian man who was to be deported from Canada for unknowingly killing a rare parrot species. The parrot at the time it was killed was fitted with a Global Positioning System (GPS) tracker,⁹⁵ an AI-related technology initially created to help soldiers and military ships, planes, and vehicles locate themselves correctly anywhere in the world. It is now used to track wildlife. The arrest was made primarily due to GPS monitoring, which allows conservationists to attach a radio receiver to an animal and use that information to determine its whereabouts and the direction in which it is going.

There is no doubt that enforcing wildlife protection laws is a difficult task, but using technology can make it easier. Technology, such as data science and big data, can help address various wildlife monitoring and forest management issues. These objectives involve safeguarding, rejuvenating, and encouraging the sustainable utilisation of land-based ecosystems, promoting sustainable management of forests, combating desertification, halting and reversing soil degradation, and preventing biodiversity decline. Recent advances in wildlife conservation have been made by applying AI, which could be adopted in Nigeria to strengthen the enforcement of wildlife crime prevention laws. Some of such advantages of AI for wildlife crime prevention include;

Classification, Study, and Protection of Wildlife Species

Today, scientists use artificial intelligence to gain insights into the factors that threaten endangered species worldwide.⁹⁶; Ai, Z., Ishihama, F. and Hanasaki, N. ‘Mapping current and future seawater desalination plants globally using species distribution models’. (2022) Water Resources Research 58.7 e2021WR031156. This involves using AI to provide data on various aspects of the species’ lives, such as their birthplaces, survival rates, migration patterns, and distance travelled.⁹⁷ AI has allowed wildlife researchers to study wild animal species together and develop protective strategies by tracking their behaviours and predicting the possible extinction of endangered animals. Applying AI in Nigeria, where there is a diverse range of animal species, to legal efforts at wildlife crime prevention will make it easier to determine the location of animals, their sighting dates, migration patterns, and social groups. This will enable conservationists and law enforcement agents to more effectively monitor and protect animals in their natural habitats. For example, DeepMind, a UK-based company, has deployed an AI-based model in Tanzania’s Serengeti National Park to identify animal species and count their numbers. This effort aims to recognise wild animals and protect endangered species before it becomes too late.⁹⁸ Microsoft’s Species Classification API Demo also employs a machine-learning model to identify more than 5000 animal and plant species. Additionally, the World Wildlife Fund and Intel are collaborating with researchers on a project that uses artificial intelligence to monitor and safeguard Siberian tigers in China. By utilising AI, the project can analyse vast amounts of data collected through advanced camera traps to observe Siberian tigers. Deploying a similar approach in Nigeria’s national parks would improve the identification, study, and protection of animal species and strengthen the enforcement of the country’s wildlife crime prevention laws, particularly the National Parks Act and the NESREA Act.

Data Collection, Analysis, and Dissemination

AI enables the quick collection and analysis of extensive datasets, providing detailed data on natural activity. This data reveals the path to preserving animal species and gives a comprehensive view of the planet’s biodiversity. AI further helps experts by providing complete data and analysis reports to make informed decisions, aiding in developing conservation policies. For instance, Katharina Schmidt, the founder of apic.ai, and her team created a beehive monitor to collect data using Tensor Flow, Google’s open-source machine learning platform, to save the world’s bee population.⁹⁹ The information has helped observe different bee behaviours, such as bee counts, migratory patterns, or whether they carry pollen.¹⁰⁰ Protection Assistant for Wildlife Security (PAWS is another AI-powered application that leverages predictive analysis and resource optimisation to aid rangers in their duties. By analysing data, PAWS provides information about the terrain, animal populations, natural pathways, and foot traffic, among other factors.¹⁰¹ Similarly, Wildlife Insight is a cloud-based platform that utilises AI to enable multiple organisations to upload, store, manage, and share their data. The platform allows efficient and rapid processing of data collected from the field and seamlessly integrates with the Google Cloud for easy analysis and mapping.¹⁰²

By leveraging the capabilities of AI, it is possible to address the gap in enforcing existing wildlife crime prevention laws in Nigeria, which is currently limited by a lack of capacity for a comprehensive strategic response. The information derived from analysed data can be shared among agencies for wildlife crime prevention, improving critical areas of expertise, such as species assessment and intelligence-led investigations.

Nigeria’s enforcement agencies, which include police, customs, judiciary, and wildlife officials, have a limited understanding of CITES, which can also be remedied through data gathered from AI technologies. Additionally, this data would be relevant in the development of a national strategy to combat wildlife crime, as well as the formulation of standard procedures for inter-agency collaborations.

Detection and Control of Wildlife and Forest Resources Poaching

One major challenge with wildlife conservation in Nigeria is the high rate of wildlife crimes- the illegal practice of the intensive slaughter of animals, which reduces the number of these species and forest resources poaching. AI tools can now assist in managing illicit activities related to poaching by utilising a human-free monitoring system. AI-enabled drones and night vision cameras can facilitate the swift detection of poachers on the ground and alert forest rangers to take preventive measures before any harm is caused to wildlife. Cameras equipped with AI and rapid alert systems can also quickly identify humans carrying weapons or engaging in suspicious activities. This will aid wildlife crime prevention agencies such as NESREA and officials of the National Park Service to detect and stop wildlife crimes before they occur. For example, The Protection Assistant for Wildlife Security (PAWS),¹⁰³ an AI system created by the University of Southern California, uses past poaching records to anticipate future locations. It factors location, timing, and ranger patrols to make its predictions. With the algorithm generated from this data, park rangers in the Nigerian National Parks will be able to accurately predict which areas to patrol and identify the most vulnerable areas of the parks, thus taking appropriate and proactive actions toward wildlife crime prevention. In the same vein, using The Rainforest Connection, an AI system developed by a San Francisco-based NGO,¹⁰⁴ park rangers can effectively identify the optimal route for patrolling, search for traps and snares, and quickly detect wildlife crimes.

Similarly, using The Elephant Listening Project, developed by Cornell University researcher Peter Wrege and his team,¹⁰⁵ wildlife conservationists could collect and categorise information about savanna elephants living in Nigeria’s dense rainforests. By placing audio recorders in the forest to observe jungle sound, this AI technology could help Nigeria’s wildlife crime prevention agencies separate noises locate elephants, and trace poachers’ movements. In addition to the aforementioned, Project SEEKER, a groundbreaking multi-species artificial intelligence (AI) tool developed utilising Microsoft Azure Machine Learning Services, represents a significant leap forward in the fight against illegal wildlife trafficking.¹⁰⁶ This innovative AI model is designed to identify illegally trafficked wildlife concealed within luggage and cargo autonomously, and it has recently undergone successful trials at Heathrow Airport, where it processed a remarkable volume of up to 250,000 bags daily.¹⁰⁷ The results showed a detection rate exceeding 70%, particularly excelling in identifying ivory items, including tusks and horns.¹⁰⁸ What sets Project SEEKER apart is its potential to revolutionise the way airports and security systems address the critical issue of illegal wildlife trafficking. Its successful deployment at Heathrow Airport underscores its effectiveness in rapidly and accurately identifying prohibited wildlife products, bolstering global efforts to combat this illicit trade. Nigeria’s airport security systems cannot detect illegal wildlife items concealed in baggage and cargo. Project SEEKER has the potential to fill this significant gap, fortifying Nigeria’s defences against wildlife trafficking. This integration could mark a pivotal moment in the country’s environmental conservation and sustainability commitment.The illegal timber trade is often regarded as lucrative as the illegal wildlife trade. This is because the forest provides a home for the animals to thrive; as such, the illicit timber trade also affects wildlife conservation. AI and MLE algorithms are now used with spatial analysis to accurately forecast and monitor deforestation worldwide and keep track of global deforestation rates using monitoring systems.¹⁰⁹ For instance, Rainforest Connection utilises old, discarded cell phones equipped with solar power to detect illegal timber felling in forests. The cell phones are mounted on treetops and record chainsaw sounds. The data is then sent to cell phone towers, where Google’s AI and MLE library distinguishes chainsaw noise from other sounds. Using this data and the sensor’s location, forest managers are informed to prevent illegal tree felling.¹¹⁰ Tools like Outland Analytics, Terramonitor, Global Forest Watch, and Future Forest Map are also being used to create maps and continuously monitor deforestation in real time using open-source satellite data.¹¹¹ To successfully combat wildlife crime, Outland Analytic employs AI-based audio recognition algorithms to identify the sounds of chainsaws and unlicensed vehicles and instantly sends email alerts to the concerned authorities.¹¹²

AI has the potential to revolutionise the fight against wildlife trafficking in Nigeria. Using object recognition and machine learning, AI can identify species, verify shipping contents, detect online sales, and recognise trafficking patterns. Additionally, AI-powered scanning equipment can detect contraband in luggage and cargo, prompting manual inspection.¹¹³ Finally, AI algorithms can bolster existing laws to reduce the rate of wildlife crimes over time. AI could have the most significant potential to identify contraband, trafficking routes, and patterns while reducing personnel and investigation needs.

Control of Illegal Animal Trade on Social Media

Online illegal wildlife trafficking has significantly increased due to the growth of social media and e-commerce platforms, making it extremely difficult to identify and stop such criminal activity. These online marketplaces have allowed traders to trade illegally in wildlife worldwide, making it challenging to track supply chains. AI technology is being developed to automatically scan and explore massive amounts of online data to stop this trade and address this rising problem. The “Coalition to End Wildlife Trafficking Online” (CEWTO), which unites 34 e-commerce, search, and social media technology companies to work with wildlife organisations to stop this illegal trade, was established in 2018 by the World Wildlife Fund (WWF) and the International Fund for Animal Welfare (IFAW). One such enterprise is Baidu, a well-known Chinese multinational tech company with a speciality in AI and the internet, which is collaborating with the CEWTO to develop AI tools for identifying wildlife for sale listings online.

Analysing the Effect of Climate Change on Wildlife Species

When obtaining data on how climate change affects animals and minimising its effects through strategic planning, AI technology has shown to be a beneficial tool. The tremendous data issues associated with climate change make deploying AI extremely helpful. Scientists have been monitoring greenhouse gases and their sources for a long time, but evaluating and using the data¹¹⁴ effectively has been challenging. Improving climate modelling and predictions is one of the most essential advantages of AI technology in the context of climate change. Models for forecasting the weather are becoming more accurate thanks to recent developments in machine learning. AI is also increasingly used to analyse model results and contrast them with observations from the outside world. With AI, it is now easier to monitor temperature increases that directly affect many species’ chances of surviving, leading to a lack of food, fewer possibilities for reproduction, and changes to the environment for local fauna. AI techniques are also included in species recognition systems, remote sensing tools, and animal monitoring sensors to assess ecological changes using visual or auditory data.¹¹⁵

6Conclusion

The government has enacted laws and policies in Nigeria to prevent wildlife and forest crimes. However, these laws are not always effective, as offenders frequently go unpunished due to insufficient resource allocation by environmental compliance authorities. AI-related technologies have the potential to address this ongoing issue by managing and monitoring ecosystems. New data-gathering technologies such as UAS, satellites, and camera traps generating large amounts of data have significantly impacted ecology and conservation sciences. By using technology to reduce poaching and preserve marine life, among other things, AI techniques can help Nigeria achieve its environmental protection goals and contribute to its Sustainable Development Goals. It is essential to strengthen the existing legal framework on wildlife crime prevention in light of AI’s potential to unlock benefits far beyond this century. Failing to do so may result in a future that could leave conservation efforts in limbo for years to come.