Evaluation of Mountain Ecosystems Response to Global Climate Change

#### **Chapter 3**

## Forest Degradation in Dryland Ecosystems of Sudan: Review of the Causes, Consequences, Assessment Methods, and Potential Solutions

*Emad H.E. Yasin, Ahmed A.H. Siddig, Eiman E. Deiab, Czimber Kornel, Ahmed Hasoba and Abubakr Osman*

#### **Abstract**

Dryland forests are ecologically and socioeconomically important. They contribute to livelihood diversification, food security, animal feed and shelter, and environmental conservation in sub-Saharan Africa, particularly Sudan. Despite their importance, current findings show that multiple ecological, human, socio-economic, and policy factors have damaged these resources. As a result, undesirable consequences have been observed, such as food famine, land and water resource degradation, decline/loss of biodiversity, and contribution to global warming that affect the welfare of humans, plants, animals, and micro-organisms. This chapter briefly reviews the forest degradation in drylands Sudan with emphasis on its common causes, impacts, assessment methods, management intervention efforts, and potential future solutions. Given the current situation, there must be urgent combating efforts to manage Sudan's dryland forest resources properly. On the one hand, following prevention measures to essentially deal with the current causes thus prevent any further degradation of forest resources in dryland Sudan. On the other hand, there is an urgent need to address current degradation following appropriate and timely rehabilitation interventions. We also recommend adopting a serious monitoring and evaluation system within these combating efforts by applying the five common indicators for measuring forest degradation: biodiversity, productive functions, carbon storage, forest health, and protective functions.

**Keywords:** forest degradation, dryland ecosystems, causes of degradation, assessment methods & indicators, management interventions

#### **1. Introduction**

Forest resources in drylands hold significant socio-economic and ecological value, especially in sub-Saharan countries like Sudan. Here, they play vital roles in livelihood diversification, food security, animal feed, shelter, and environmental conservation. Despite their importance, recent studies reveal that these resources are undergoing severe degradation due to a complex interplay of natural, anthropogenic, socioeconomic, and policy-related factors [1–3]. Forest degradation is a global issue that contributes to deforestation, desertification, and loss of biodiversity, particularly in drylands [4, 5]. Estimates suggest that approximately 850 million hectares of forests and forest lands are degraded [6, 7]. Drylands, which occupy 41% of Earth's land area, have already seen 10–20% degradation, with 1–6% of their populations living in desertified areas [8, 9]. Dry forests constitute more than 40% of all tropical forests [10, 11]. In Africa and tropical islands worldwide, dry forests account for 70–80% of forested areas. These ecosystems are characterized by their seasonality, differing significantly from rainforests, which remain stable year-round [12]. Due to their accessibility and fertility, dry forest zones have historically been preferred for human settlement over wetter forest zones [10–13]. However, this has led to extensive exploitation of these forests for thousands of years, including for fuelwood and charcoal production [14, 15]. In Sudan, forest resources are inversely proportional to population density. A staggering 68% of Sudan's forests are located in the south, where only 15% of the population resides. In contrast, the more populated northern states hold just 32% of the forests [16–19]. The 2015 National Biodiversity Strategy and Action Plan (NBSAP) showed that forest cover accounts for a mere 11.9% of the country, with an annual deforestation rate exceeding 2.4%. The dry tropics are characterized by shifting cultivation systems with both long cultivation and short fallow periods, which hamper the natural recovery of vegetation [20, 21]. Despite their long history of exploitation and the associated degradation, dry forests have received scant attention compared to rain forests. Knowledge gaps make the management and restoration of these forests a challenge, with little data available on forestry activities, stock assessment, and the economic contributions of these resources [20, 21]. In this review, we shed light on the issue of forest degradation in Sudan's drylands. We focus on internationally recognized indicators of forest degradation, its causes, and its socio-economic and environmental consequences. We also propose a set of recommendations for preventing, controlling, and reversing forest degradation as a direction for future research and policy.

#### **2. Concept and signs of forest degradation**

Teketay [22] defines forest degradation as alterations within a forest that negatively impact its structure and function, thereby reducing its ability to supply products and/or services. In practical terms, however, the concept of degradation is far more subjective, as perceptions can vary widely regarding the same landscape. Various definitions of forest degradation have been examined through literature reviews, and these are summarized below. The criteria used to define forest degradation differ among authors and international bodies, as highlighted by [23]. This divergence in definitions further emphasizes the subjectivity inherent in understanding and assessing forest degradation, making it a complex and nuanced issue that requires comprehensive, multi-dimensional approaches for effective management and mitigation (**Table 1**).

Overall, a common thread in most definitions of forest degradation found in the literature is the emphasis on reduced crown cover and loss of biodiversity as key indicators. These two elements often serve as crucial signs pointing to the declining health and function of a forest, thus making them vital parameters for evaluating the extent and severity of forest degradation. This consensus provides a starting point for *Forest Degradation in Dryland Ecosystems of Sudan: Review of the Causes, Consequences… DOI: http://dx.doi.org/10.5772/intechopen.113222*


**Table 1.**

*Parameters covered by different definitions of forest degradation from the literature review.*

a more unified approach to monitoring and mitigating the issue, despite the various nuances and subjectivities involved in defining forest degradation.

#### **3. Causes of drylands' forest degradation**

Despite the immense value and services that forest ecosystems offer in drylands, these vital resources face numerous threats that contribute to their degradation. The literature has extensively discussed the types and categories of factors leading to forest degradation. Generally, there seems to be a consensus to classify these factors into natural and anthropogenic categories [38].

Additionally, the causes of dryland forest degradation (DFD) span multiple dimensions, including economic, social, ecological, policy, and governance factors. These causes can further be categorized under natural influences as well as humaninduced (anthropogenic) and social and policy-related factors. This multi-faceted nature of the drivers behind DFD underscores the need for an integrated approach that addresses each of these dimensions to effectively manage and mitigate the degradation of these critical ecosystems.

#### **3.1 Natural factors of forest degradation**

Natural factors contributing to dryland forest degradation (DFD) can be further subdivided into:


Each of these categories poses unique challenges for the preservation and restoration of dryland forests, and understanding them is crucial for the formulation of effective management and mitigation strategies.

### **3.2 Anthropogenic factors of forest degradation**

Major anthropogenic factors contributing to dryland forest degradation include:


Each of these anthropogenic factors poses its own set of challenges to the health and sustainability of dryland forests. Addressing them will require multi-faceted and tailored approaches that take into account the complexity and interconnectedness of these contributing elements.

*Forest Degradation in Dryland Ecosystems of Sudan: Review of the Causes, Consequences… DOI: http://dx.doi.org/10.5772/intechopen.113222*

#### **4. Socio-economic and policy-related factors**

According to Teketay [22], several socio-economic and policy-related factors contribute either directly or indirectly to the degradation of dryland forests. The major factors among these include:


Understanding and addressing these socio-economic and policy-related factors is crucial for developing multi-pronged strategies to manage and mitigate dryland forest degradation effectively.

#### **5. Consequences of dryland forest degradation**

The impacts of dryland forest degradation are multi-dimensional and significantly detrimental to both the environment and human livelihoods. Here are some key consequences:

#### 1.**Environmental consequences:**


#### 2.**Socio-economic consequences:**


To address these challenges, a multi-faceted approach is needed that combines sustainable forest management practices, socio-economic interventions, and policy changes. This should also involve the active participation of local communities and be guided by comprehensive research and monitoring (**Figure 1**) [45].

This diagram illustrates the complex interplay of processes contributing to forest degradation in the Brazilian Amazon. The framework begins with pristine forests that *Forest Degradation in Dryland Ecosystems of Sudan: Review of the Causes, Consequences… DOI: http://dx.doi.org/10.5772/intechopen.113222*

**Figure 1.** *Dynamics and interactions of forest degradation [45].*

become vulnerable through several stages that are mentioned in the diagram and seeks to encapsulate the chain reactions and feedback loops involved in forest degradation, emphasizing the multifaceted nature of the issue.

**Figure 2** presents a detailed look at the far-reaching implications of forest cover loss. At its core, the loss of forest cover serves as a catalyst for a cascade of negative environmental, social, and economic consequences. The environmental impacts are immediate and devastating, affecting biodiversity, soil quality, and the water cycle. This leads to a decrease in carbon sequestration capabilities, which further exacerbates climate change. On a social level, forest cover loss adversely affects indigenous communities and local populations that rely on forests for their livelihoods, leading to displacement and poverty. The economic repercussions are equally severe, with the loss of valuable resources like timber, nontimber forest products, and ecosystem services that have both local and global economic value. The figure also illustrates how these different domains are interlinked, emphasizing that the implications of forest cover loss are not isolated but are interconnected in complex ways. Therefore, forest cover loss represents a multidimensional issue that requires integrated solutions.

**Figure 2.** *Implication of forest cover loss [17].*

#### **6. Methods of assessing forest degradation and common indicators**

There are two common methods for assessing forest conditions which are briefly stated in the following:

#### **6.1 Remote sensing-based multi-temporal analysis**

Advancements in modern technology have been a boon to the field of environmental science, particularly in the realm of forest conservation and management. Among these technologies, remote sensing stands out as a particularly effective method for long-term monitoring of forest conditions. Developed over the years through various studies [44, 46, 47], remote sensing technologies now allow for sophisticated multi-temporal analyses that can reveal subtle but significant changes in forest ecosystems.

In the multi-temporal analysis approach, satellite images of the same geographical location are captured at different times and are then aligned or 'co-registered' with one another. This enables scientists to directly compare these images, paying particular attention to changes in spectral values, which are indicative of shifts in vegetation condition and health. Spectral values are measures of how different wavelengths of light are absorbed or reflected by the Earth's surface, providing a sort of 'fingerprint' of its current state. For instance, healthy vegetation reflects a lot of green light but absorbs red and blue light, which is why it appears green to the human eye. By studying these spectral "signatures," experts can glean intricate details about soil moisture levels, plant health, and even species composition.

The utility of this approach has been demonstrated in various settings, including the ability to monitor specific types of environmental stress. For example, the analysis

#### *Forest Degradation in Dryland Ecosystems of Sudan: Review of the Causes, Consequences… DOI: http://dx.doi.org/10.5772/intechopen.113222*

of multi-temporal imagery has proven to be particularly effective for tracking defoliation events caused by insect infestations [48]. Such defoliation would show up as changes in the spectral values, allowing researchers to not only identify affected areas quickly but also estimate the extent of foliage loss. This is invaluable information for forest management teams who can then take targeted action, whether it be through the introduction of natural insect predators or other integrated pest management strategies.

Moreover, multi-temporal remote sensing offers the advantage of continuous, automated monitoring, enabling timely interventions. It's an approach that makes it possible to identify patterns and trends over time, from seasonal variations to the long-term impacts of climate change. This not only facilitates proactive management practices but also aids in policy formulation for sustainable forest management.

While remote sensing provides a bird's-eye view of large forested areas and can quickly detect large-scale changes, it's important to combine this method with ground assessments for a more comprehensive understanding. On-the-ground assessments can validate satellite imagery findings while adding context, especially when it comes to local biodiversity, soil conditions, and human activity. Therefore, the integration of both remote sensing and ground-based methods offers the most thorough, accurate, and actionable insights for forest conservation efforts.

#### **6.2 Ground assessment of vegetation conversion and change**

In addition to the technological advances of remote sensing, direct field or ground assessments serve as another crucial method for monitoring and evaluating forest conditions. Unlike remote sensing, which offers a macroscopic, overhead perspective, ground assessments provide a microscopic, detailed view that is indispensable for a comprehensive understanding of forest ecosystems.

Ground assessments typically involve systematic vegetation sampling to evaluate key metrics such as species composition, abundance, distribution, and structural attributes of the forest. Essentially, researchers collect baseline data for these parameters and then periodically revisit the site to identify any changes. This approach is cited as particularly effective for assessing forest degradation, offering nuanced insights that remote sensing sometimes misses [45, 49, 50].

During these ground assessments, various indicators can be meticulously examined. For instance, vegetation composition can be assessed through species identification and counts, helping to determine if invasive species are encroaching upon native vegetation. Abundance and distribution metrics can indicate whether certain species are becoming more dominant or rare, possibly signaling ecological imbalance. Structural attributes, such as tree height, canopy density, and undergrowth conditions, can provide clues to the forest's overall health and its ability to support various forms of wildlife.

Importantly, ground assessments also allow for the study of soil conditions, local hydrology, and even microclimatic variables, offering a holistic perspective on the forest ecosystem. Soil samples can reveal nutrient deficiencies, contamination, or changes in microbial communities, all of which have far-reaching implications for vegetation health. Examination of local water sources can also identify any changes in water quality or quantity, which again impacts the entire ecosystem.

Additionally, ground assessments can be designed to be adaptive, allowing researchers to adjust their monitoring strategies based on preliminary findings or

**Figure 3.** *Conceptual framework of the image processing procedures: a) pre-processing, b) software [45].*

emerging environmental threats. This adaptability ensures that the assessment remains relevant and continues to generate actionable data over time.

While ground assessments are generally more labor-intensive and time-consuming than remote sensing methods, they offer an unparalleled level of detail. Therefore, the most effective forest monitoring programs often employ a multi-faceted approach, combining the broad overview provided by satellite imagery with the granular detail captured through ground assessments. This integrated methodology ensures a more accurate and nuanced understanding, which in turn facilitates better decision-making for conservation and management efforts (**Figure 3**).

#### **6.3 Common indicators of forest degradation in dryland ecosystem**

Forest degradation has been succinctly defined as a reduction in the ability of a given forest ecosystem to provide goods and services [51]. A comprehensive framework was first established in 2009 and has been globally adopted to measure forest degradation, including in dryland areas. This framework consists of five major categories of indicators:


additional measures like changes in leaf area index, which can provide insights into the forest's ability to sequester carbon.

4.*Forest health indicators*: This category addresses the forest's vulnerability to both biotic (living) and abiotic (non-living) agents, such as fires, diseases, invasive species, storms, and snowfall. Sub-indicators include:

#### *6.3.1 Crown condition*

The crown indicator serves as a comprehensive measure to evaluate the health and vitality of individual trees within a forest ecosystem. It specifically focuses on three main components: the amount of foliage, the condition of that foliage along with branches, and the distribution of growing tips on the trees. By assessing these components, one can derive valuable insights into not only the health of individual trees but also the overall health and resilience of the forest.


Together, these aspects offer a nuanced picture of trees and, by extension, forest health. They can be invaluable for early detection of forest degradation factors such as disease outbreaks or the impact of environmental stressors. Given their significance, crown indicators have been elaborated extensively in academic and practical literature, serving as a cornerstone in the study and monitoring of forest ecosystems [52].

#### *6.3.2 Lichen communities*

Lichens, the symbiotic organisms resulting from the partnership between fungi and algae, are a remarkable component of many forest ecosystems. They colonize various surfaces, including the bark of trees, rocks, and even soil, thereby playing multiple crucial roles within these ecosystems.

1.*Nutrient cycling*: Lichens are particularly effective at breaking down rocks and other hard substrates, contributing to the formation of soil and the cycling of essential nutrients. This process is critical for the ongoing productivity and health of forest ecosystems.


Given their multi-faceted contributions and sensitivity to environmental conditions, lichens serve as an invaluable bio-indicator for forest health and vitality. Monitoring the diversity, abundance, and condition of lichens can provide a wealth of information about the forest's current state and its resilience to future changes or threats. This concept of using lichens as an indicator has been described extensively, providing a foundational tool for ecologists, conservationists, and researchers interested in forest health and sustainability [53].

#### *6.3.3 Down woody debris*

Down Woody Debris (DWD) serves as an often-overlooked yet invaluable metric for assessing the health, complexity, and functionality of a forest ecosystem. This indicator involves the meticulous cataloging and analysis of various forms of woody material that have fallen to the forest floor, ranging from smaller twigs to entire tree trunks.


*Forest Degradation in Dryland Ecosystems of Sudan: Review of the Causes, Consequences… DOI: http://dx.doi.org/10.5772/intechopen.113222*


By meticulously examining and cataloging Down Woody Debris, researchers and forest managers can glean a multitude of insights about the ecosystem's health, its history, and its capacity to support various forms of life. These aspects of the DWD indicator have been discussed in great depth, offering a nuanced tool for understanding and managing forest ecosystems [54].

#### *6.3.4 Tree damage*

The Damage Indicator serves as a comprehensive gauge for evaluating the various impacts affecting the health and vitality of a forest ecosystem. This measure delves into the nuances of forest health by meticulously recording different types of injuries and their causative agents. By doing so, it allows for a more granular understanding of forest health, thereby aiding in targeted conservation and management efforts.


By methodically recording and interpreting these aspects of tree damage, this indicator furnishes a multi-faceted lens through which forest health can be evaluated and managed [55].

#### *6.3.5 Tree mortality*

The Tree Mortality Indicator is a crucial metric that offers insights into the overall health and sustainability of a forest ecosystem. It meticulously quantifies the number, size, and volume of trees that have died, thereby furnishing critical data that can illuminate the underlying causes of forest decline. In doing so, it allows for nuanced approaches to forest management and conservation.


*Forest Degradation in Dryland Ecosystems of Sudan: Review of the Causes, Consequences… DOI: http://dx.doi.org/10.5772/intechopen.113222*


Overall, the Tree Mortality Indicator serves as a robust diagnostic tool that helps stakeholders better understand forest dynamics, thereby allowing for more effective and targeted conservation initiatives [56].

#### *6.3.6 Vegetation diversity and structure*

The vegetation diversity indicator provides a comprehensive evaluation of forest ecosystems by quantifying the variety, abundance, and spatial arrangement of vascular plant species. This tool serves multiple purposes, including inventory assessment and long-term monitoring. By keeping track of changes in species richness, their relative abundances, and the layering or vertical structure within the forest, it helps researchers and conservationists gauge the health and resilience of the forest over time. This indicator is particularly useful for capturing nuanced shifts in forest composition, which can result from various factors like climate change, habitat fragmentation, or human activity. Additionally, changes in the vertical stratification of vegetation—such as the understory, midstory, and canopy—can indicate the forest's capacity to support a diverse array of wildlife and maintain its ecological functions. This comprehensive approach to understanding vegetation diversity is invaluable for adaptive management strategies, providing a more complete picture of forest health and functioning. For a more in-depth discussion and methodology of this indicator [57].

#### *6.3.7 Soil condition*

Soil serves as the foundational component in forest ecosystems, supplying the essential environmental elements upon which all vegetation relies: nutrients for

growth, water for sustenance, air for respiration, heat for temperature regulation, and mechanical support for stability. Beyond these basic functions, soil health is intricately linked to a range of forest processes and services, thereby making it a crucial indicator for forest management and conservation. The soil condition indicator provides both chemical and physical data, offering critical insights into the soil's fertility status and its physical characteristics such as texture, structure, and water-holding capacity. These metrics are instrumental in a variety of ecological models, which operate at diverse spatial scales within the forest ecosystem. For instance, accurate soil data can help estimate the forest's carbon budget, thereby assessing its role in carbon sequestration and climate change mitigation. By comprehensively understanding the condition of the soil, researchers and forest managers can make more informed decisions about sustainable land use, reforestation initiatives, and the mitigation of environmental impacts such as soil erosion and nutrient depletion. This deep-dive into soil indicators and their significant role in forest ecology is elaborated upon in the study detailed by [58].

#### *6.3.8 Ozone injury*

A subset of plant species serve as particularly sensitive bioindicators of ozone exposure levels that exceed typical background concentrations. These plants display distinct symptoms of foliar injury on the upper surface of their leaves, which sets them apart from other types of foliage damage. Such easily identifiable and quantifiable signs of ozone-induced stress make them invaluable for monitoring air quality and its potential impact on forest ecosystems. By focusing on these bioindicator species, researchers can more precisely gauge the levels of ozone pollution in a given area and understand its ecological implications. This information is especially critical for assessing the health of forest ecosystems that may be affected by rising ozone levels due to industrial activities or other environmental stressors. The presence or absence of these symptoms can serve as a red flag for policymakers and forest managers, enabling them to take timely action to mitigate harmful effects. The intricate dynamics of how ozone levels influence plant health, and by extension, the overall well-being of forest ecosystems, is explored comprehensively in the research elaborated upon by [59].

#### *6.3.9 Protective function indicator which is indicated by the rate of soil erosion (or area affected)*

The Protective Function Indicator focuses on assessing the forest's role in soil conservation, particularly by monitoring the rate of soil erosion or the extent of areas affected by it. Soil erosion can lead to the loss of fertile topsoil and decrease the forest's ability to store water and nutrients, adversely impacting its overall health and resilience.

This indicator is crucial because forests often serve as natural barriers against soil erosion, thereby preserving water quality and reducing the risk of landslides and other natural disasters. High rates of soil erosion could signify that the forest's protective functions are compromised, possibly due to factors such as deforestation, uncontrolled logging, or the presence of invasive species that destabilize soil structures.

By closely monitoring the rate of soil erosion and the extent of affected areas, forest managers can take targeted conservation measures, such as reforestation or implementing erosion control structures like terraces or sediment traps.

#### *Forest Degradation in Dryland Ecosystems of Sudan: Review of the Causes, Consequences… DOI: http://dx.doi.org/10.5772/intechopen.113222*

Understanding the forest's ability or inability to perform this protective function can be pivotal for land-use planning and natural resource management strategies.

The methodology and metrics for assessing the Protective Function Indicator in the context of soil erosion are discussed in detail in the relevant scientific literature, serving as a guideline for both researchers and policymakers in the evaluation of forest degradation and conservation efforts.

#### **7. Prevention and control measures of forest degradation in drylands**

Addressing the pervasive issue of forest degradation in drylands necessitates an intensive, multi-faceted approach, given the magnitude and far-reaching implications of the problem. However, merely dealing with the degradation after it occurs is insufficient; it's vital to take into account the intricate web of contributing factors—be they climatic, anthropogenic, or ecological—that feed into this environmental calamity. This involves not just identifying its root causes, but also establishing a comprehensive set of assessment indicators that can measure the degradation's scope, rate, and ultimate impact on both the local ecosystem and broader environmental health.

Beyond immediate control and rehabilitation methods, a proactive, preventive strategy must also be part of the solution. Simply put, measures to halt degradation are not enough; preemptive actions that thwart its onset in the first place are just as crucial. This calls for a shift in perspective, from a reactive to a proactive stance in combating forest degradation.

With this in mind, we propose two key interventions aimed at both effectively halting and preventing forest degradation in drylands:


#### **7.1 Prevention/mitigation measures:**

Addressing the root causes of forest degradation is an intricate task that involves a multi-pronged approach, taking into account not just the environmental aspects but also forest governance, community involvement, and economic factors. This complexity demands a multi-layered solution tailored to specific concerns.

#### 1.**Forest governance:**

• *Establishing a professional body for foresters*: A dedicated organization can provide guidelines, share best practices, and set ethical standards. This body can serve as a liaison between governmental agencies and local communities.


#### 2.**Community involvement**:


#### 3.**Economic factors**:


By focusing on these pillars—governance, community involvement, and economic factors—tailored interventions can be developed to tackle the root causes of forest degradation. Doing so involves not just policy changes but also active collaboration among governments, professionals, communities, and NGOs.

#### **7.2 Control/adaptation measures**

To holistically address the challenges of forest degradation in drylands, a multifaceted approach is necessary. Here are some expanded guidelines grouped under specific topics that could pave the way for more sustainable forest management:

#### 1.**National forest programs and eco-agriculture**:


#### 2.**Market exploration and price regulation**:


#### 3.**Alternative energy sources**:

• *Promote non-wood energy*: Encourage the use of energy alternatives like solar, wind, and biogas to reduce dependency on wood, charcoal, and other forest resources.

#### 4.**Integrated and multidisciplinary approach**:

• *Comprehensive solutions*: Given the complexity of dryland forest degradation, an integrated approach that combines sectoral development with targeted interventions is vital.

#### 5.**Information dissemination and research**:


By methodically tackling each of these areas, it is possible to build a comprehensive strategy that not only mitigates the ongoing degradation but also sets a foundation for the sustainable development of dryland forests [60].

**Figure 4** presents a comprehensive conceptual framework that delineates the intricate relationship between the causes and consequences of land degradation, as

#### **Figure 4.**

*Conceptual framework linking land degradation causes and consequences, restoration responses (both indirect and direct), and response outcomes and evaluation [60].*

**Figure 5.** *Framework for Sudan forest landscape restoration [17].*

*Forest Degradation in Dryland Ecosystems of Sudan: Review of the Causes, Consequences… DOI: http://dx.doi.org/10.5772/intechopen.113222*

well as potential restoration responses and their outcomes. The framework begins by identifying the root causes of degradation, which can be both natural and anthropogenic, and traces these to their immediate and long-term ecological and socio-economic consequences. It then outlines various restoration responses that could be applied, categorizing them into indirect approaches, such as policy changes or community engagement, and direct interventions like reforestation or soil stabilization. Finally, the framework emphasizes the necessity for robust monitoring and evaluation strategies to assess the effectiveness of these restoration efforts. This multidimensional approach aims to guide practitioners, policymakers, and researchers in the quest to address land degradation in a holistic manner.

**Figure 5** outlines an Agroforestry System Framework tailored for the restoration of forest landscapes in Sudan. This comprehensive framework integrates agriculture, forestry, and local community needs to create a sustainable land management strategy. It begins with an assessment phase that gauges the current conditions of both agriculture and forestry sectors, identifying key issues such as soil degradation, deforestation, and community livelihood needs.

#### **8. Conclusion**

The urgent degradation of forest resources in Sudan's arid landscapes presents a complex, multi-layered crisis demanding swift and comprehensive action. This detailed review illustrates that the drivers of this degradation are varied and farreaching, incorporating natural influences as well as human activities and policyrelated decisions. The fallout of such degradation has ramifications beyond forest borders, impacting crucial areas like food security, biodiversity, land and water conservation, and also contributing to overarching global issues like climate change. To tackle this pressing dilemma, a dual-faceted strategy is indispensable. On one hand, immediate proactive steps must be taken to prevent the further decline of these vulnerable dryland forests. This includes a deep dive into the root causes, which span from unsustainable land management to policy shortfalls. Equally important is advocating for sustainable alternatives that carefully balance human developmental needs with ecological conservation. On the other hand, there's an urgent necessity for targeted efforts to rehabilitate already degraded forest landscapes and offset the consequent negative impacts. To ensure the efficacy of these interventions, it's critical to have a robust monitoring and evaluation mechanism in place. This system should be based on the five globally recognized indicators for assessing forest degradation, namely, biodiversity levels, productive functions, carbon storage capacities, overall forest health, and the forests' protective functions against erosion and other environmental stresses. With diligent, data-driven assessment and adaptive management, it's possible to turn the tide on these degrading trends and set Sudan's arid forests on a path toward resilience and sustainability. Given the monumental nature of the challenges at hand, collaboration emerges as a linchpin for success. It's essential to establish partnerships across local, national, and international platforms, where stakeholders can pool their collective knowledge, resources, and expertise. By working together, we can hope to not only preserve but also rejuvenate these invaluable dryland ecosystems. In doing so, we secure their essential contributions to human livelihoods, biodiversity, and overall environmental equilibrium, both within Sudan and on a global scale.

#### **Author details**

Emad H.E. Yasin1,2\*, Ahmed A.H. Siddig1,3, Eiman E. Deiab4 , Czimber Kornel<sup>2</sup> , Ahmed Hasoba2,5 and Abubakr Osman1,2

1 Faculty of Forestry, University of Khartoum, Khartoum North, Sudan

2 Faculty of Forestry, University of Sopron, Sopron, Hungary

3 Department of Environmental Conservation, University of Massachusetts, Amherst, MA, USA

4 Institute of the Environment, National Centre for Research, Khartoum, Sudan

5 Faculty of Forest Sciences and Technology, University of Gezira Madani, Sudan

\*Address all correspondence to: emadysin513@gmail.com; emad.hassanelawadyasin@phd.uni-sopron.hu

© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Forest Degradation in Dryland Ecosystems of Sudan: Review of the Causes, Consequences… DOI: http://dx.doi.org/10.5772/intechopen.113222*

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#### **Chapter 4**

## Assessment and Mapping of Forest Cover Change in Dryland, Sudan Using Remote Sensing

*Emad H.E. Yasin, Czimber Kornel and Mohamed Hemida*

#### **Abstract**

Forest resources in the arid and semi-arid of Sudan are experiencing significant fluctuations in tree cover and ecological functionality. This study aims to bridge this gap by utilizing multi-temporal Landsat imagery and mapping forest cover change in the Nabag Forest Reserve (NFR) in South Kordofan State, Sudan. For this assessment, two cloud-free images (TM from 2011 and OLI from 2021) were downloaded and analyzed using ArcMap 10.7 and ERDAS 2014 software. Supervised classification techniques were applied, corroborated by GPS point verification and field surveys, to quantify changes in forest cover over the decade. The results revealed that dense forest cover increased from 9% in 2011 to 38.9% in 2021, while light forest cover decreased from 34.4% in 2011 to 30.9% in 2021. Additionally, the area occupied by agriculture and barren land declined from 37.2% and 19.4% in 2011 to 18.7% and 11.5% in 2021, respectively. Rapid shifts were observed in all LULC categories during the study period. The primary causes of deforestation and forest degradation were tree felling, unsustainable grazing practices, and construction activities. These findings are crucial for guiding future forest rehabilitation and creating targeted management plans for the local communities reliant on these forests.

**Keywords:** remote sensing, land use and land cover (LULC), forest degradation, Landsat imagery, forest rehabilitation, Nabag forest, South Kordofan state, Sudan

#### **1. Introduction**

Forest resources in Sudan's drylands are subject to variations in tree cover and ecological functionality. Reliable and up-to-date information on these resources is essential for addressing their socio-economic and environmental roles within the national environmental policy framework [1–4]. Accurate measurements of the current extent and rate of change in forest areas are imperative for devising effective management strategies to sustain the diverse ecosystem services they offer [5–9].

Forests cover over 11 billion acres in arid regions globally and are integral to local ecosystems and traditional food supply chains [10–16]. However, countries, such as Sudan, near deserts are experiencing a decline in tree cover and associated ecosystem services. Indiscriminate clearing for urbanization and economic pursuits threatens

the study area's protected forests. Escalating land prices have accelerated deforestation, transforming previously forested reserves into areas for housing construction, unauthorized residential developments, and various agricultural activities. Illegal logging and firewood harvesting persist as concerns [5, 17].

For sustainable resource management, precise and current land use and cover data are indispensable. Understanding the causes and impacts of land cover changes is crucial for identifying their adverse effects on biological diversity and human development [18–22]. Remote sensing technologies offer valuable tools for monitoring these changes [23–26]. Forest composition and distribution alterations substantially influence various biological, biochemical, and ecological processes [10–12]. Data from remote sensing are often used for natural resource analysis, including tracking shifts in land use, such as forest degradation [25–28].

Temporal comparisons of satellite imagery facilitate easily identifying landscape changes [29]. Landsat data, frequently employed to monitor land cover changes at regional and global scales, helps identify and map landscape features with a high level of detail [30]. Up-to-date resource inventories are vital for effective land use planning and sustainable management [31]. By integrating remote sensing, GIS, and landscape metrics, researchers can achieve more spatially consistent outcomes, better pinpointing the social and biophysical factors behind landscape fragmentation [10, 32–34].

This study aims to assess and map temporal changes in the forest cover of Nabag Forest Reserve using multi-temporal satellite imagery, ground-truth data, and GIS integration. Information from these sources was synthesized and analyzed using matrix analysis methods to provide a comprehensive view of forest cover dynamics.

#### **2. Material and methods**

#### **2.1 Study area**

The Nabag Forest Reserve (NFR) is situated in the northern region of South Kordofan State in Sudan. Spanning 4174.2 hectares, its geographical coordinates range from 12° 30′ 0″ N to 12° 36′ 0″ N in latitude and 29° 36′ 0″ E to 29° 58′ 0″ E in longitude (**Figure 1**). The reserve lies within a low-rainfall woodland savannah zone, experiencing an annual precipitation of 350–900 mm, primarily between May and September. The area's temperature varies between 30 and 35°C.

The soil composition in the NNFR predominantly consists of clay plains interspersed with sandy clay, locally referred to as "Gardud." The vegetative cover could be more sparse and more degraded. It features a scattering of acacia trees, with Acacia seyal, Acacia mellifera, and Acacia Senegal being the dominant species. Other tree varieties, such as Balanitis aegyptiaca, are also present but less prevalent.

This setting provides a challenging backdrop for the conservation and management of the forest reserve, highlighting the importance of rigorous, science-based approaches to sustain its ecological functionality.

#### **2.2 Detecting land use/land cover, changes**

We utilized remotely sensed data from Landsat 5 and Landsat 8 satellites to assess changes in land use and land cover. These images, featuring a spatial resolution of 30 meters, were cloud-free and sourced from the United States Geological Survey's GloVis website. Specifically, we downloaded images from path 175 and row 51 for

*Assessment and Mapping of Forest Cover Change in Dryland, Sudan Using Remote Sensing DOI: http://dx.doi.org/10.5772/intechopen.113862*

#### **Figure 1.**

*Maps for the location of South Kordofan state in the southern part of Sudan (A) and the location of Nabag natural Forest reserve (study area) in South Kordofan state (B), as well as the overview of Nabag natural Forest reserve (C).*


#### **Table 1.**

*Landsat 5 TM and OLI that used in LULC determination of the study area.*

2011 and 2021 (**Table 1**). Landsat 5 and 8 were selected by their geographical coverage and temporal availability, ensuring that the data would be relevant and current for our study area.

Our methodology employed an integrated approach that combined remote sensing data with field information for comprehensive data collection and analysis. This integrated process is illustrated in **Figure 2** of the paper. By synthesizing satellite imagery and on-the-ground data, we aimed to generate a robust, multidimensional perspective on land use and land cover changes within the Nabag Natural Forest Reserve.

The analysis of satellite images was performed using ERDAS Imagine 2014 and QGIS (Version 3.22.1) software, supplemented by Microsoft Excel 2019 for statistical calculations. Various stages of image processing were executed, including calibration, geometrical, atmospheric corrections, layer stacking, and composite banding. These steps converted the individual bands from each year's dataset into single-layer files. After the preprocessing, sub-scenes from the larger images were extracted (clipped) to focus on the area of interest. Supervised classification was then carried out using the maximum likelihood classifier. This method was employed to classify land use and land cover (LU/LC) in the acquired Landsat images from 2011 and 2021. To evaluate the accuracy of the classification, we relied on ground truth data, Google Earth imagery, and preexisting knowledge of the study area. Quantitative metrics,

#### **Figure 2.**

*Flowchart for data collection and analysis.*

including users' and producers' accuracies, overall accuracy, and Kappa coefficients, were calculated to assess the reliability of the classification. To evaluate the accuracy of the classification, we relied on ground truth data, Google Earth imagery, and pre-existing knowledge of the study area. Quantitative metrics, including users' and producers' accuracies, overall accuracy, and Kappa coefficients, were calculated to assess the reliability of the classification. The results demonstrated that each classified image's overall accuracy and Kappa coefficients exceeded 85%. This high level of accuracy underscores the classification process's reliability, confirming the approach's utility in capturing the dynamics of land use and land cover changes within the Nabag Natural Forest Reserve (**Tables 2** and **3**).

#### **3. Results and discussion**

#### **3.1 Land use/land cover results in 2021**

The supervised image classification identified four distinct land cover classes: Dense forest, light forest, agriculture, and bare land. These categories are visually represented in **Figure 3**. According to the OLI 2021 classification results, dense forests *Assessment and Mapping of Forest Cover Change in Dryland, Sudan Using Remote Sensing DOI: http://dx.doi.org/10.5772/intechopen.113862*


#### **Table 2.**

*Accuracy assessment of classified map of 2021.*


#### **Table 3.**

*Accuracy assessment of classified map of 2011.*

accounted for 38.9% of the total area, equivalent to 1623.78 hectares. Light forest occupied 30.9%, translating to 1289.97 hectares. Agricultural land constituted 18.7% of the area, or 780.75 hectares, while bare land comprised 11.5%, totaling 479.97 hectares. These figures and their corresponding percentages are further detailed in **Table 4**.

This classification provides a comprehensive up-to-date understanding of land use and land cover within the Nabag Forest Reserve. The results offer valuable insights into the current state of the forest and the broader landscape, essential for informed decision-making in conservation and land management strategies.

#### **3.2 Assessment of land use/land cover change**

Globally, changes in land use and land cover (LULC) are among the most significant and enduring modifications to the Earth's surface [35, 36]. Monitoring these changes is essential for generating baseline thematic maps and facilitating ongoing assessments. In the current study, as illustrated in **Figure 4** and **Table 5**, substantial LULC changes were observed during the study periods of 2011 and 2021, attributable to both human and environmental factors.

Specifically, the results reveal a significant increase in dense forest cover, growing from 9% in 2011 to 38.9% in 2021—an impressive net change of 29.9% and an annual growth rate of 2.99%. Studies on forest rehabilitation indicate that tree planting typically accelerates the recovery of forest vegetation [37]. Hemida et al. [38] found

#### **Figure 3.**

*Distribution of LU/LC classes detection in NFR in 2021.*


#### **Table 4.**

*Distribution of LULC in the study area (ha) in 2021.*

#### *Assessment and Mapping of Forest Cover Change in Dryland, Sudan Using Remote Sensing DOI: http://dx.doi.org/10.5772/intechopen.113862*

that the increase in forest cover during a certain period can be attributed to the Taungya agroforestry program initiated by the FNC in early 2005 and continuing to the present day. Salih [39] also reported that the Taungya program positively contributed to rehabilitating 3024 ha of NFR between 2005 and 2013. Similarly, a study from Nigeria highlighted the advantages of the Taungya system in promoting forest conservation and regeneration [40]. Conversely, light forest cover decreased from 34.4% in 2011 to 30.9% in 2021, with a net change of 3.5% and an annual decline rate of 0.35%. Agricultural land also reduced from 37.2% in 2011 to 18.7% in 2021, marking a net change of 18.5% and an annual decrease of 1.85%. Lastly, bare land areas contracted from 19.4% in 2011 to 11.5% in 2021, experiencing a net change of 7.9% and an annual reduction rate of 0.79%. It is important to note that other factors, including environmental, political, and agricultural influences, might have contributed to the observed changes in the reserve during this period. These factors significantly impact land use and land cover transformations [1, 41]. Historical reviews of the study region reveal that since 1982, there have been recurrent dry years. Additionally, frequent civil wars have resulted in significant losses of vegetation cover [42].

**Figure 4.** *Maps of land cover change in NFR between 2011 and 2021.*

*Mitigating Global Climate Change – Enhancing Adaptation, Evaluation, and Restoration…*


#### **Table 5.**

*LU/LC classes and their area in percentage for 2011 and 2021.*

A study by [1, 2, 38, 43] corroborates these findings, suggesting deforestation, flooding, soil erosion, and unplanned urban and agricultural expansion could lead to such LULC changes. The study also emphasizes that LULC modifications, influenced by varying environmental, political, demographic, and socio-economic conditions, are dynamic and directly affect communities living near forests.

In light of our findings, it is evident that anthropogenic activities are the driving forces behind these significant changes and disruptions, impacting the natural vegetation cycles in the study area. This research provides valuable insights into the human and environmental dimensions of LULC changes, underscoring the urgency for informed and adaptive land management strategies.

Land use and land cover (LULC) change is not merely a straightforward or linear conversion between different land types but involves a complex interplay of human activities, environmental conditions, and policy frameworks [43, 44]. This multifaceted nature of LULC makes its study particularly compelling as it can offer insights into broader sociocultural and environmental trends and processes.

Utilizing temporal remote sensing data enables the analysis of dynamic processes, emphasizing not only static snapshots of land cover at specific times but also the sequences and rates of their changes [2, 45]. In the case of the Nabag Forest Reserve, the dynamic nature of land transitions is evident spatially and temporally, especially in recent years. Use of transition matrices (as shown in **Table 4** and the maps in **Figure 5**) underscores the complex and dynamic landscape of the forest's changes. Transition matrices provide valuable analytical tools for understanding how these complex systems evolve, particularly in semiarid regions, where the conservation of natural resources is a significant concern [46].

Transition matrices allow for a multidimensional view of change over time by showing what changes have occurred and the extent and direction of these changes. In essence, they can provide insights into what drives the change in each class and help predict future trends based on past and current activities [47].

By employing matrix analysis tools, you have captured the systematic transitions in land use and land cover over the study period of 2011–2021. These matrices, visualized in **Figure 5** and **Table 6**, offer a nuanced understanding of the factors affecting Nabag forest, thereby providing a basis for more informed and targeted conservation and land management strategies.

Understanding the multilayered factors driving LULC changes is essential for developing robust and sustainable management plans. It enables stakeholders, from local communities to policymakers, to make evidence-based decisions considering the complex realities of land transformation and its implications.

*Assessment and Mapping of Forest Cover Change in Dryland, Sudan Using Remote Sensing DOI: http://dx.doi.org/10.5772/intechopen.113862*

#### **Figure 5.**

*LU/LC change trajectory matrix 2011–2021.*


*Note: Highlighted values illustrate areas and percentages of the unchanged classes.*

#### **Table 6.**

*Land use and land cover trajectory matrix 2011–2021.*

The intricacies of land use and land cover changes in the Nabag Natural Forest Reserve from 2011 to 2021 are highly revealing. The transition matrices offer a nuanced view, showing that the area under dense forest has seen a significant net gain of 1326.04 hectares over the decade, largely attributed to the Forest National

Corporation's agroforestry activities. However, this positive trend is counterbalanced by a loss of 118.26 hectares of dense forest, mostly converted to agriculture and bare land. This indicates that issues, such as rainfed agriculture still significantly threaten forest conservation. Furthermore, the area under light forest, categorized as fragile, has seen degradation, largely through its conversion to dense forest. This could signal environmental stress due to natural and anthropogenic factors. The decline in agricultural land could be seen as beneficial for natural ecosystems. However, it also raises concerns about declining soil fertility and the socio-economic implications for local communities. A similar decline in bare land, partially converted to dense forest, appears to be a positive trend but necessitates further inquiry into the driving factors for long-term planning. The data also flags a concerning lack of participation from local communities in forest management, emphasizing the need for more community-based, sustainable approaches. Ultimately, the transition matrix is an invaluable ledger for policymakers, offering a detailed account of losses and gains in land cover categories. Given the dynamic nature of these changes, adaptive evidence-based management strategies are crucial for the long-term conservation and sustainable development of the Nabag Forest Reserve (**Table 2**).

Sudan forests grapple with deforestation, primarily driven by agricultural growth and infrastructure projects. Despite initiatives promoting reforestation and sustainable land use, there remains a pressing need for a unified national strategy. Such a strategy should not only focus on forest conservation but also intertwine with community development, emphasizing the forest's role in climate change mitigation and biodiversity preservation (**Table 3**) [48–51].

#### **4. Conclusion and recommendations**

A multifaceted approach involving satellite imagery, geospatial technology, and ground inventories was utilized to detect, assess, monitor, and map land use and land cover (LULC) changes in the Nabag Natural Forest Reserve in South Kordofan State, Sudan. This study elucidated spatial and temporal patterns of LULC variations, offering insights for effective forest management and future rehabilitation plans. The research found substantial LULC alterations between 2011 and 2021, with differing trends and percentages. Specifically, the analysis revealed that dense forest cover increased from 9% in 2011 to 38.9% in 2021, while light forest cover declined from 34.4% to 30.9% in the same period. Agricultural and bare land areas also decreased, dropping from 37.2 and 19.4% in 2011 to 18.7 and 11.5% in 2021, respectively. These shifts were primarily driven by anthropogenic activities such as illegal tree felling, woodcutting, overgrazing, and infrastructural development. These factors contribute to both deforestation and alterations in forest cover. Such changes are anticipated to affect the forest's ecosystem services significantly. If the current degradation rate persists, the long-term sustainability of the forest could be jeopardized. Therefore, the Forestry National Corporation (FNC) should focus on preserving the remaining areas of Nabag forest. The active participation of local communities in rehabilitation efforts while respecting their interests is crucial for the success of any restoration program. Ignoring this could lead to the failure of rehabilitation initiatives. The outcomes of this study can inform the development of comprehensive forest management and rehabilitation plans that are conscious of community needs.

### **Acknowledgements**

This chapter has been supported by the BorderEye project (TKP2021-NVA-13), which has been implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund, financed under the TKP2021-NVA funding scheme. We also wish to express our gratitude to our colleagues for their contributions, both direct and indirect, to the data collection and analysis. The authors affirm that there are no conflicts of interest that could have affected the publication of this paper.

### **Author details**

Emad H.E. Yasin1,2\*, Czimber Kornel1 and Mohamed Hemida1,2

1 Faculty of Forestry, Institute of Geomatics and Civil Engineering, University of Sopron, Sopron, Hungary

2 Faculty of Forestry, Department of Forest Management, University of Khartoum, Khartoum North, Sudan

\*Address all correspondence to: emad.hassanelawadyasin@phd.uni-sopeon.hu; emad.yasin823@gmail.com

© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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### Section 3
