Background of the StudyThe Philippines is regarded as one of the biodiversity hotspots in the world because of its diverse habitats and high rates of endemism. In fact, the country is harboring more than 12, 000 flora and fauna, with records of 9, 253 species of plants, in which 6, 091 species are considered as endemic – or can only be found in the Philippines (IUCN Red List, 2011 as cited by Pacquit, 2017). However, the country is continuously losing its rich biodiversity resources due to various human activities resulting in the increase in the number of endangered and threatened species and decrease of environmental quality (Garcia, et al, 2013). As per record of the Department of Environmental and Natural Resources on the actual number of threatened plant species in their Administrative Order Number (DAO) 2007-01 (2002), there are 176 vulnerable species, 187 endangered, 99 critically endangered and 64 threatened plant species all over the Philippines. Aside from various human activities, climate change is also a major threat to biodiversity and various functions of an ecosystem.
The evident warming of the atmosphere affects the balance between different species of an ecosystem in all parts of the world (Amedie, 2013). In the study of Fichlin et al (2007), it is estimated that about 20-30% of both plants and animals worldwide will be at risk of extinction with a particular emphasis to endemic species due to the evident continuous warming of the atmosphere caused by Greenhouse gasses emissions. Therefore, species under categories of vulnerable, critically endangered, endangered and threatened have a greater risk to become extinct in the coming years. For the past years, scientists and researchers have developed modeling programs that will allow them to evaluate the potential impacts of climate change on natural system by assessing the potential shift in geographic distribution and habitat suitability of a species due to future climate (Martinez-Meyer, 2005). Species distribution modeling has become popular in recent years due to its wide range of uses. It can make accurate predictive distribution maps efficient and effective for multiple species or habitat types as well as identifying patterns in biological diversity which can be of a great value for assessing conservation priorities. Due to its wide array of advantages, in the last decade, several international organizations (such as UNEP, the convention of Biological diversity, Organization for Economic Cooperation and Development, European Union, Conservation International, IUCN, WWF, etc.
) have decided to use species modeling in order to address key policy objectives at a global scale (Cayuela et al, 2009). Among the most widely used SDM-based program is the Maxent which involves maximum entropy. It is based on presence-only modeling method which is designed to make prediction from incomplete data (Baldwin, 2009). With changes in present and future climate, species must adapt or shift their geographical distributions to avoid habitat loss and extinction.
However, some tropical forest trees especially native forest species may not be able to adapt to climate change due to rapid alteration caused by various intervening factors. Climate change potential impacts to forest tree species are inevitable but with intensified research, knowledge gaps can be addressed and appropriate conservation initiatives can be made (Torres, et al, 2016).Objectives of the StudyGenerally, the study aims to predict the potential effects of climate change on species distribution and habitat suitability of selected native forest tree species in the province of Leyte. This can be achieve through the following specific objectives: 1.
To assess the potential current and future spatial distribution of the selected forest tree species;2. To determine the intervening factors that significantly affect the changes in geographic distribution and shift in habitat suitability of the critically endangered forest tree species, and3. To provide species distribution and habitat suitability maps that illustrate the current and future spatial distribution of the selected species.Significance of the StudyJust like other ecosystems, forest ecosystems provide us with an array of environmental services. Thus, it is vital that they are protected not only from human intervention but also from potential impacts of climate change. Science-based studies serve as guide for policy-makers and implementers in crafting appropriate mitigating measures, programs and policies to increase the resiliency of the forests ecosystems to climate change.However, our country have limited records investigating forests ecosystems and climate change interaction.
Most of the studies in this field focused on carbon sequestration and climate change mitigation. Only recently that impacts of climate change on forest ecosystems and its potential adaptation measures have been also investigated. (Lacso, et al, 2008). The study aims to provide additional knowledge on how regional climate will affect the distribution of the forest tree species in the provincial level.
The results of the study will be useful as basis in formulating science-based adaptation policies, strategies and measures that will enhance resilience of forest tree species to climate change. It will also help conservationist, environmental managers and practitioners promoting conservation initiatives in Leyte province with estimates of the spatial distributions of critically endangered forest tree species requiring more attention.Scope and Limitations of the StudySince the study is anticipated to accomplish in 4 months, it will only cover Leyte Province and the distribution modeling will be limited to 8 native forest tree species belonging to Family Dipterocarpaceae. Environmental variables that will be used in this study will be specified once the actual data collection is conducted.
The study will only be using presence-only data of forest species based on the georeferenced data available. Hypothesis of the StudyThe following are the hypotheses of the study:H0 – Changes in climate due to various intervening factors will not affect the future geographical distribution and habitat suitability of four critically endangered forest tree species in LeyteH1 – Changes in climate due to various intervening factors (edaphic, topographic, vegetation) significantly affect the current and future geographical distribution and habitat suitability of selected critically endangered forest tree species in Leyte.Conceptual FrameworkAccording in the report of Fischlin et al (2007), resilience or the ability to adapt naturally of many ecosystems is possible to be exceeded by an unprecedented combination of change in the global climate associated by other disturbances and other drivers such as pollution, over-exploitation of natural resources and unregulated land use. Furthermore, it is also expected that ecosystems exposed to higher temperature due to atmospheric CO2 levels, will likely to experienced alteration in their structure, reduce in biodiversity as well as compromise many ecosystem functions and services.
The conceptual framework that will be used in this study is developed under the concept that most ecosystems are likely to show a wide range of vulnerabilities to climate change, depending on the extent of exposure (Fishlin et al, 2007). It is further assumed that terrestrial ecosystems, specifically forest species will also experience negative impacts due to climate change. The constructed framework that will be employed in this study shows the components that determine the factors affecting the current and future distribution and habitat suitability of the forest tree species. The framework is adapted from the study conducted by Torres et al, 2016 and Garcia et al, 2013.Forest Ecosystem: Services providedThe Forest Management Bureau (FMB) of the Department of Environmental and Natural Resources (DENR) defines forest (as cited in SEPO, 2015), “as land with an area of more than 0.5 hectare and tree crown cover (refers to the area covered by the living branches and foliage of trees) of more than 10%. The trees should be able to reach a minimum height of 5 meters at maturity in its original location. Furthermore, a forest consist of either closed forest formations where trees of various storeys and undergrowth cover a high proportion of the ground or open forest formations with a continuous vegetation cover in which tree crown cover exceeds 10%.
Young natural stands and all plantations established for forestry purposes, which have yet to reach a crown density of more than 10% or tree height of 5 meters are included under forest”. Forests are important to a healthy environment. They provide an array of environmental, economic and social services which are all significant to human development. Philippine forests is a home for numerous plant and animal species and serve as ancestral domain for 12 – 15 million of indigenous people, of which it is 30% of the country’s total population (Pamintuan, 2011).
The table below shows the summary of the various ecosystem services that forests provide.Among all the environmental services that forests provide, scientists and researchers today have the utmost interest in their role in mitigating climate change. Many studies revealed that tropical forests have the largest potential to mitigate climate change among other types of forest in the world. With continuous conservation of existing carbon pools by reducing impacts of logging, expansion of carbon sinks by reforestation, and reducing the use of fossil fuel by using renewable energy, carbon dioxide increase in the atmosphere can be controlled (Lacso, et al, 2008).Status of Philippine Forests: The Native TreesDespite all the environmental services that they offer, forests continually face destruction. Philippines ranks 4th in the world’s top 10 most threatened forest hotspots due to the country’s fast rate of forest cover loss. In fact, dipterocarps which dominated the lowland forests of the Philippines before have only a few remnants left in the whole country.
This is because many forested areas have been logged and transformed into permanent agricultural land and settlements (Langenberger, 2005).According to Pamintuan (2011), combined reforestation efforts by the government and private sectors are inadequate to address the rapid deforestation in the country. Previous administrations had been weak in compelling timber license holders to fulfill their obligation of reforesting concession areas. These Reforestation efforts also tend to endanger forest biodiversity. Many studies have been conducted, and recommended the use of native species in reforestation projects. Native trees establish the basic foundation of the country’s forest ecosystems. Aside from that, these forest tree species possess the natural ability to recover from damage caused by pests and disease and are adaptable to their respective local environments.
In fact, DENR stated the used of these species for planting under the National Greening Program in 2011. However, exotic species are used in the program on account of their economic importance (Lantican, 2015). Fast-growing, exotic tree species such as Mahogany, Gmelina and Acacia are ecologically harmful because they prevent indigenous species from growing. Added to that, endemic animals as well as insects that highly depend to native forest species for shelter and food will be likely affected because they are not adapted to these exotic tree species (Pamintuan, 2011). In 2010, a report from Forest Management Bureau stated that Philippine forests had increased to 7.665 million hectares, which covers almost 25.
6 percent of the country’s 30 million hectares land area. However, these figures may not represent the actual or on-ground forest cover because the additional categories that were used during the calculation were not actually forests. Tree plantations, bamboo, and palm were included in the calculation. Another reason to doubt the figures is that, the areas that are expected to revert to forests but are not yet planted with trees were also included (Pamintuan, 2011).
Impacts of Climate Change to Philippine ForestsNot all global vegetation models agree on whether tropical forests will increase or decrease due to climate change. Changes in rainfall pattern usually result to either increase or decrease of water use and temperature. Any shift in the pattern can lead to a change in the forests ecosystem particularly in areas with severely limited rain. Some of forest tree species may die and become extinct because the geographical condition is no longer favorable especially for highly sensitive species. Humans are also affected with the changes in the forest ecosystems. Communities particularly the indigenous people that largely depend on ecological services provided by forests may need to alter their traditions and shift their livelihoods.
This change in practices and behavior can further degrade the forests ecosystem because they need to resort to more extensive agricultural production. Greater impacts on forest ecosystem could be expected as the climate becomes warmer (PAGASA, n.d.). In the study conducted by Cruz (1997) as cited in Lacso, et al (2011), it was hypothesized that forest areas in the Philippines will expand as precipitation and temperature increase due to climate change. Many species from both plants and animals may suffer loss due to increase in temperature. However, it is also possible that over a period of time some species will develop and can adapt with the changes. Hence, it can be said that climate change have both positive and negative impacts on certain species.
Paquit et. al. (2017) conducted a study that predicted the potential effects of climate change to the present and future habitat distribution of Smooth Narra in Mindanao.
The study employed maxent to generate the needed results and only used climatic factors as environmental variables that will predict the shift. The study revealed that the Smooth Narra benefited from the current climate due to its vast habitat distribution. However, it will likely experience decline from future climate due to reduction in its suitable habitat. Moreover, Torres, et al (2016) also used the same model and concept in his study. He used five variables: (1) climatic variables as the predictor, (2) topographic, (3) edaphic, (4) vegetation and (5) anthropogenic (population) variables as the intervening factors to predict the future spatial distribution of Shorea polysperma and Shorea palosapis in Northern Sierra Madre Natural Park (NSMNP). His study revealed that S. palosapis and S. polysperma under future climate will gain more suitable ecological niche in the park.
It is further revealed that predicting the occurrence of the two species was largely determined by climatic variables, followed by anthropogenic variables, topographic and vegetation-related and edaphic variables respectively. It is evident in the studies cited that a certain forest tree species might not be found in the suitable habitat as predicted. Suitable habitats were forest tree species currently harbored may have likely been altered and be devoid of any representative trees in the future. It can be due to change in land use and human exploitation exacerbated with climate change. Although some of forest tree species may able to withstand and adapt to climatic changes, they can still be affected by continuing land use change and other pressing pressures and their remaining remnants can still be subjected to over-exploitation. Information that can be generated from habitat distribution modeling studies could aid in predicting the potential habitats of forest tree species needing much attention. The suitable areas that will be identified can help in rehabilitating habitats where forest tree species had existed before as well as in improving their conservation status (Paquit, 2017).
The Study SiteLeyte is the largest of the six provinces of Eastern Visayas, which is the 8th largest island comprising the Philippine archipelago. It is located between 9° 55′ and 11° 48′ northern latitude and 124° 17′ to 125° 18′ eastern longitude (Langenberger, 2005). The said island is divided into two- Leyte Province on the north, which will be the study area and Southern Leyte province on the south (Leyte, 2017). The province lies adjacent to Samar Island, connected by the San Juanico Bridge. It lies east of the islands of Cebu and Bohol, bounded by the Carigara Bay in the north, Camotes Sea to the west and province of Southern Leyte in the south (NSCB-RD8, n.d).The province is known as an excellent producer of agricultural crops which include coconut, palay, abaca, sugarcane and corn.
It is also known for its abundant geothermal reserves. The Leyte Geothermal Power Field in Tongonan, Ormoc City, managed by the Energy Development Corporation (EDC) is the second geothermal power producer in the world. The two of the country’s top dollar earners: the Philippine Phosphate Fertilizer Corporation (PHILPHOS) and the Philippine Associated Smelting and Refinery Corporation PASAR) are also located in the province (NSCB-RD8, n.d).Leyte province also have a rich biodiversity. In the study conducted by Langenberger (2005), results shows that Leyte harbors at least 28% of the Philippine dipterocarp species and represents all Philippine dipterocarp timber groups. The results also indicates that it can provide essential seeds and seedlings required to establish reforestation programs in the future.
Furthermore, it shows that dipterocarp species distribution and occurrence is dependent to environmental factors. In this study, elevation plays an important role in species occurrence. However, illegal logging remains the major reason for the diminishing number of dipterocarp species in the mountain areas while forest trees species scattered to lowland areas continues to have low abundance due to shifting cultivation or kaingin for agricultural purposes.
Leyte also housed one of the protected areas in the country, the Lake Danao Natural Park. The said protected area under NIPAS has several mountain peaks guarding its natural lake formed by the activity along the Philippine Fault. The park depicts the bio-geographic zones of mid-mountain forest habitat and lake ecosystem. It is one of the famous attraction in the province owing to its 148 hectares guitar-shaped inland lake nestling in an elevation ranging from 480 to 900 meters above sea level.
The park is also home for diverse flora and fauna (LDNP Report, n.d.). Collection of occurrence records and selection of speciesOccurrence records is one of the essential components needed in Maxent modeling. The occurrence data that will be used in this study were taken from the georeferenced database developed by Ramos et al in 2012.
The threatened native forest tree species that will be subjected in this study were selected based on (1) their ecological and economic importance, (2) present conservation status based on IUCN Lists, and (3) availability of georeferenced database. A total of 8 species from Dipterocarpaceae family species with at least 23 occurrences record were chosen to model their distribution. The table below shows the summary of the selected species under the Dipterocarpaceae family with their number of occurrence records, economic importance and conservation status.Environmental VariablesA total of 24 environmental variables will be used as potential indicators of species distribution and will be classified into 4 groups: (1) climatic factors, (2) edaphic factors, (3) topographic factors, and (4) vegetation factor. However, number of variables that will be used per group will be limited depending on the availability of datasets during the actual data collection. Primary datasets will be acquired from relevant government agencies like the Department of Environment and natural Resources (DENR), Bureau of Soils and Water Management (BSWM), National Mapping Resources and Information Authority (NAMRIA), and PAGASA while other datasets will be downloaded from Worldclim database (for climatic datasets), Digital Soil Map of the World (for soil datasets), and other website having GIS datasets. The table below summarizes the environmental variables that will be used in this study.
Species Distribution ModelingSpecies distribution modeling will be perform to determine the factors affecting the distribution of the selected forest tree species. The analysis will be run using the maximum entropy algorithm or MaXent. The Maxent model that will be used in this study was developed by Phillips et al (2006) and was chosen among other SDMs because of its ability to perform and provide efficient results using limited records and presence-only data (Garcia et al, 2013). The modeling stage will include two parts. The first part will be modeling for the potential current distribution and the second part will be modeling the future distribution of the selected forest tree species.Data AnalysisThe results of the modeling will be analyze using Area under Curve (AUC) which will provide the quantitative measure of model performance, True Skill Statistic (TSS), which will be able to compares the number of correct forecasts, minus those attributable to random guessing, to that of a hypothetical set of perfect forecasts and Pearson correlation (Garcia et al 2013) . Maps for both current and future potential distribution will be produced for each selected forest tree species using Quantum GIS.
The figure below shows the research flow diagram that will be used in this study adapted from the study conducted by Garcia et al (2013) and Torres et al (2016).