Integrating Ecosystem Services and Eco-Security to Assess Sustainable Development in Liuqiu Island

Abstract

Developing sustainable island tourism must be thoroughly evaluated in consideration of ecological, economic, and social factors on account of the fragility of island ecosystems. This study evaluated the ecological footprint (EF) and ecological capacity of Liuqiu Island from 2010 to 2015 using the EF model, establishing an indicator to estimate the value of ecosystem service and eco-security. The empirical results include: (1) the overall value of ecosystem service on Liuqiu Island increased from US$3.75 million in 2010 to US$5.11 million in 2015; (2) the total per capita EF considerably increased from 0.5640 gha/person in 2010 to 4.0845 gha/person in 2015; and (3) the ecological footprint index increased from 0.30 in 2010 to 2.28 in 2015. These findings indicate that island tourism recreational zones gradually increased the pressure on its ecosystem, reduced the eco-security level, and severely damaged the environment, thereby threatening the function and structure of the entire ecosystem. The innovations and contributions of this study is integrating ecological footprint and ecosystem services valuation provide insights into sustainability of an island. The theoretical and practical implications identified in this study should contribute to reducing the gap between research and practice.

1. Introduction

With the increased demand for tourism and recreation resources along with changes in travel patterns and the growing awareness of conservation, the rapid development of island tourism has engendered concern among scholars and experts and encouraged research on international investment [1,2,3,4]. Scheyvens and Momsen (2008) [5] indicated that island tourism can be regarded as a new opportunity for development in economically vulnerable small-island developing states (SIDS). Liou and Ding (2004) [6] indicated that the overall characteristics of island and inland resources, including the economy of scale, vulnerability, degree of development, and natural disasters, are different than those of mainland areas. Thus, the development of island tourism faces more restrictions and uncertainties and must be treated differently from tourism development in mainland areas. Moreover, Macleod (2004) [7] reported that the fragility of island ecosystems coupled with traffic restrictions, land and economic patterns, and ethnic and cultural conditions necessitate a comprehensive consideration of island tourism development.

Broadly speaking, the preferences of tourists have changed in recent times as greater numbers of travelers have exhibited an increasing inclination toward ecotourism. At the same time, Taiwan has become an increasingly popular destination for tourists from a variety of other countries. In light of these two trends, the numbers of recreational travelers making visits to Taiwan’s national scenic areas have increased substantially. One such destination, Liuqiu Island, is among the the smaller offshore islands located south of the main island of Taiwan. The island is particularly popular among travelers wishing to experience nature via the island’s wildlife tourism opportunities and wetland ecosystems. The island’s intertidal zone provides some of its most popular recreational experiences, such as the opportunity to see green turtles in their native habitat, with these activities being enhanced by the provision of on-site interpretation services that also serve to encourage sustainable tourism (Lo, 2013) [8]. Relatedly, studies have previously been conducted in order to assess how such recreational tourist activities affect the biodiversity of Liuqiu Island (Lo, 2013) [8], as well as how such experiences impact the behavior of tourists in terms of their being environmentally responsible (Lee et al., 2015) [9]. Unfortunately, it is clear that the island’s burgeoning tourist industry brings with it a number of negative environmental impacts that affect the quality of life for locals as well as aspects of the island’s cultural heritage, with such problems including traffic jams, the excessive use of natural resources, and issues stemming directly from the inappropriate actions of tourists themselves.

Liuqiu Island provides multiple uses including food provision, biodiversity maintenance, climate and water regulation, and recreational opportunities. When facing these uses, it is critical to understand the environmental conservation issues. Numerous studies have investigated land use in relation to disaster prevention (Lo, 2013) [8] and developed associated management-oriented mitigation plans (Lee et al., 2015) [9]. This study attempts to enhance the understanding of the factors that influence decision-making processes when managing island sustainability. The primary purpose of this study is to develop and test a revised ecological footprint model to estimate the value of ecosystem service and eco-security, from the perspective of the supply and demand of ecosystem services.

The remainder of this article is organized. Section 2 provides the literature review of land use change, the value of ecosystem services, and the ecological securities. Section 3 illustrates the methods comprising the study area, estimation approaches and models. Our study integrates ecosystem service value model and the ecological footprint model. Section 4 presents the results and interpretations of data analysis, and discussions of findings. Section 5 focuses on the conclusion, limitations, and suggestions for future research.

The present study contributes three key innovations. First, it introduces the use of the equivalence factor as a means of correcting the model by which the value of ecosystem services are calculated. Second, it provides a table listing the value of ecosystem services per unit area within the area investigated by the study. Third, it applies an enhanced model for determining an ecological footprint that includes the ecosystem service function value, with that model utilized to predict and evaluate eco-security in a quantitative manner. The approach of integrating evaluations of both ecological footprints and ecosystem services seems to be particularly innovative and may provide insights regarding the sustainability of various practices on a given island, even as the island itself is altered over time. It is hoped, relatedly, that the gap between research and practical applications in this field can thus be reduced by the theoretical and practical implications of the study.

2. Literature Review

This research discusses topics related to the land-use change affected by tourism development; sustainable management and ecosystem conservation; and consideration of biodiversity, climate change, and other critical environmental concerns. Two models, including ecological footprint and ecosystem services valuation model, were used to construct the theoretical framework for this study in the island context. The proposed incorporated model attempts to advance the understanding and knowledge base of how to assess island sustainability. In short, the section of literature reviewed is organized in the following three sections: land use change; the value of ecosystem services; and the ecological securities. The purpose of reviewing prior literature would identify remaining gaps in the literature.

2.1. Land Use Change

Advances in research on changes in the global environment have shifted both temporal- and spatial-scale studies on land-use and cover change (LUCC) from a global to a regional scale; such studies have focused particularly on administrative, vulnerable, and other ecologically sensitive areas [10,11,12,13,14,15]. The region analyzed in this study, Liuqiu Island, includes both administrative regions (Liuqiu Township) and natural areas (a fragile, environmentally sensitive area). This study analyzed six years of data on land-use variation on Liuqiu Island by evaluating the changes in land use, and other major types of land-use transfer. To promote a sustainable use of land resource, tourism development on island could bring economic, social, and environmental impacts [16], particularly provide environmental and economic benefits for island tourism or emphasize the reduction of their environmental impacts [17]. Previous research on land use and its influence on the environment have explored the effects from only a single perspective; studies investigating the effects of changes in land development and land use on the natural environment are relatively scarce. Therefore, the current analysis and prediction model of land use change was developed based on model simulations and elucidated and integrated the complex socio-economic and interaction processes of natural ecosystems to examine the trends in land-use change and spatial patterns [18,19,20,21]. The most common models used to examine land-use change are the econometric model [22,23], statistical model [24,25,26,27,28,29], and cellular automata model [30]. Chapin et al. (2000) [31] claimed that ecosystem processes and biological diversity are two vital intermediaries in the entire economic and human systems global environment. Nevertheless, the lack of a theoretical framework may lead to subjective judgment and criticism. Accordingly, Burkhard et al. (2013) [32] believed that the processes of various ecosystems and benefits of land cover types should also be considered to ensure a more realistic assessment. For this reason, experts and scholars have integrated the Millennium Ecosystem Assessment (MEA) and other assessment indicators into comprehensive evaluation indices [33,34,35].

2.2. The Value of Ecosystem Services

In order to investigate the association between biodiversity competition and other ecosystem services, Nelson et al. (2009) [36] conducted a study in which they combined the integrated valuation of ecosystem services and tradeoffs (InVEST) model with land use change ecosystem services. Subsequently, in 2011, Polasky et al. [37] conducted a study in which they used the InVEST model as a means of quantifying biodiversity, land use, and ecosystem service changes that occurred from 1992 to 2001 in Minnesota, in addition to using it to evaluate the effects of the various land-use changes on both biodiversity and the ecosystem services. Lautenbach et al. (2011) [34] analyzed the historical development of Leipzig, Germany from 1964 to 2004 and determined regional-scale indicators for various ecosystem services associated with land-use structure (e.g., water purification, pollination, food production, and outdoor recreation); they also assessed the systemic functions and sensitivities of the indicators under various land-use conditions. On the basis of historical evidence of land use, Geneletti (2012) [38] simulated the future impacts of various land management policies on ecosystem services. In summary, the value of ecosystem services has become a major research focus.

2.3. The Ecological Securities

The rather dramatic and ongoing changes to the global climate that have occurred in recent decades have caused a variety of impacts in regions around the world, including reductions in biodiversity, the destruction of ecosystem resilience, and desertification [13]. In reaction to and anticipation of such impacts, the 1972 United Nations Declaration on the Human Environment and Eco-security provided an outline of the key principles for sustainable human development projects, which in turn provided a novel outlook regarding how environmental resources, sustainable development, and human survival itself should be assessed, while at the same time bringing attention to a number of concerns relating to the protection and conservation of food sources and related ecosystems. Along the same lines, as various environmental problems have grown increasingly dire and as ecological security theory has developed still further in response, scholars and research institutions around the world have made use of a variety of measurement models and indicators in order to provide evaluations and predictions regarding the ecological security of various regions, thereby providing a number of early-warning models that can be used as references for still further research efforts [39]. The use of quantitative evaluation methods to evaluate eco-security and criteria remains in the exploratory stage. Ecosystem services can serve as a reference for the establishment of a system to assess the economic value of changes in land use; such a system could be used to modify the services provided by humans to reflect changes in eco-security. This supposition should be explored more thoroughly.

According to Irwin et al. (2007) [40], ecosystem services can essentially be defined as the various goods and processes that humans produce or engage in through their interactions with the ecosystems around them, a definition which underscores the fundamental importance of such services to all human activities. The functions of the ecosystem services of small islands, for example, include functions relating to production, preservation, regulation, recreation, and education. At the same time, human activities can cause a wide range of environmental problems, even to the extent that the changes wrought by ecosystem services can have decisive impacts on a region’s ecological security. With this in mind, the present study utilized quantitative approaches to model ecological security in order to investigate the effects of ecosystem services with different spatial scales; it is hoped that the study’s findings will in turn provide a framework through which to address problems resulting from regional environmental change. Relatedly, it is arguably necessary that future studies and practical applications utilize the sort of systemic approach suggested by this study, one in which climate change considerations, concerns relating to biological diversity, and the successful long-term development of tourism are all incorporated. In that sense, it is hoped that this study can serve as a milestone of sorts in terms of its development and assessment of an integrated model, one based on an extensive review of the relevant literature, that takes into account both eco-security and the effects of ecosystem services. At the same time, it was felt that Liuqiu Island provided a useful focus for the present investigation insofar as it has a relatively limited range of geographical conditions and natural resources that must be considered.

In summary, investigations aimed at providing evaluations of the ecological security of different regions according to the land-use changes they undergo have come to constitute a become a substantial trend in LUCC research. In the present study, the EF model was applied first in order to analyze the temporal changes in EF (that is, the demand for various ecosystem services) and the ecological carrying capacity (that is, the supply of various ecosystem services) across a variety of time scales. An eco-security indicator system was then established so as to provide an estimation of the eco-security of Liuqiu Island in particular. More specifically, both the eco-security and the ecosystem service value of the Liuqiu Island area were evaluated and estimated. It is hoped that the results will serve as a reference that can aid the responsible agencies in maintaining ecological balance and while also fostering the development of sustainable tourism.

3. Methods

3.1. Study Area

Liuqiu Islande, which is located at 22°33′86″ N and 120°36′98″ E, is in the southwest of the port of Pingtung County and is the only coral island in Taiwan. The Liuqiu Island has an area of 6801 square kilometers, and has a population of around 13,000 residents. Reefs are rare among the tourist islands of Asia. Liuqiu Island has a rich terrain, marine ecosystems, and historical monuments. In addition, it is Taiwan's only winter tourist island and has various attractions including natural resources, cultural heritage, traditions, and festivals. A variety of activities including snorkeling and water sports are also available. Scholars have assessed the impact of recreation on the biodiversity [8] and recreation experience [9] of Liuqiu Island. Negative impacts generated by numerous visitors and recreational activities may affect the biodiversity and reduce the biological populations in the intertidal zones. According to statistics from the Tourism Bureau (2016) [41], the annual number of visitors to Liuqiu Island increased by approximately 54% from 260 thousand tourists in 2010 to 400 thousand in 2015. Thus, tourism has become a crucial industry on Liuqiu Island. As such, local residents have increasingly been providing lodging and recreational facilities in order to meet the growing demand from both local and international visitors. However, the construction of such facilities can cause substantial negative impacts to the environment, including to water and land resources, because the terrain and geology of this ecologically sensitive island are relatively fragile. With this in mind, assessments of the sustainability of tourist and recreational facilities that can guide the relevant decision-makers with respect to efficient resource usage are urgently required to ensure that the environment and its ecosystems are protected even as operational efficiency is increased and associated costs are reduced.

3.2. Estimation Approaches

To reclassify the EF ecosystem, this study integrates both ecosystem services and the EF model based on the specific feature of land use on each ecosystem service at the Liuqiu Island. First, we evaluated the EF (demand) and ecological capacity (supply) of Liuqiu Island in various periods using the EF model, which was developed under the concept of ecosystem services. Second, we established an indicator for evaluating eco-security to estimate the eco-security of Liuqiu Island. The steps used to accomplish these objectives are detailed below.

3.3. Ecosystem Service Value Model

Costanza et al. (1997) [42] defined ecosystem services as “the benefits human populations derive, directly or indirectly, from ecosystem functions.” According to the Millennium Ecosystem Assessment (MEA) published by the United Nations in 2005, ecosystem services comprise supply services, regulating services, cultural services, and support services [43]. In this study, the ecosystem service value was assessed using the money value assessment method. Using the models proposed by Costanza et al. (1997) [42], Mamattursun et al. (2010) [44], and Sawut et al. (2013) [45], we calculated the ecosystem service value in the research area.

We estimated the equivalence factor of the ecosystem service values for the various types of land use and land cover on Liuqiu Island according to the following assessment model [39], as presented in Formula (1):

$${\mathrm{ESV}}_k={{\displaystyle \sum }}_i^m{{\displaystyle \sum }}_j^n{A}_i\times f_{ij}\times E_a\times S_k\times T_k$$

(1)

where the total ecosystem service value is denoted by ESV; the distribution area of the ith type of land use and cover (gha) is denoted by $A_i$; the equivalence factor for the jth item of ecosystem goods and services provided by the ith ecosystem is denoted by $f_{ij}$; the production per unit area or the ecosystem service value coefficient is denoted by $E_a$; a K coefficient of regional differences is denoted by $S_k$; a K regional service support coefficient is denoted by $T_k$; the type of land use and cover in a particular ecosystem is denoted by i; and the ecosystem service category is denoted by j.

3.4. Evaluation Items of the EF Model

Due to the ongoing and progressively increasing interest in sustainable development, interested researchers and institutions around the world have gradually developed a range of tools and indicators that can be utilized in order to evaluate sustainable development efforts. Ideally, such tools and indicators should provide accurate and reasonable reflections of the actual environmental features which they refer to while also providing effective analyses of resource consumption as well as explorations of the relationships among distinct types of environmental impacts. In general terms, the indicators and measurement models of sustainable development currently in use, whether developed domestically or internationally, all have their own particular features. The majority of them succeed in terms of giving due consideration to how various aspects of societies, economies, ecologies, and environments affect sustainable development. However, the existing indicators and measurement models nonetheless exhibit several key shortcomings. First, some of the indicators and measurement models appear to be too complex to provide accurate reflections of the specific connotations of sustainable development, even as the dynamic indicators of sustainable development suggested in previous research appear to be insufficient. Second, a number of the existing indicators and their related measurement models were based on comprehensive systems, making the quantification of the indicators difficult and even impossible, which in turn makes them relatively inoperable with respect to practical purposes. Third, data accessibility problems affect several more of the indicators and measurement models, making them difficult to apply in various contexts.

Rees first proposed the EF model in 1992 [46]. The key aspect of the model consists of its capacity to measure and compare human environmental demands in relation to the biosphere’s capacity to replenish its resources and yield the services demanded. In a subsequent study, Wackernagel and Rees (2000) [47] suggested that the magnitude of EF is inversely proportional to the per capita usable area of biologically productive land while also being directly proportional to the environmental impact. Due to the fact that it is relatively easy to both understand and calculate, EF has become a quantitative indicator that is now widely utilized in the field of ecological economics. A number of studies conducted in Taiwan have investigated the EF model in terms of its basic concepts, theoretical hypotheses, assessment methods, deficiencies, and empirical applications [48,49,50], in addition to developing a number of EF-related theories and estimation methods. Relatedly, Lee and Peng conducted a study in 2014 [51] in which they expanded upon earlier research in order to analyze Taiwan’s EF from 2008 to 2011. In a study the following year, Lee [52] expanded upon that preceding study still further by conducting a time-series analysis in order to evaluate the land footprint, carbon footprint, and water footprint in Taiwan from 2000 to 2011. Among that study’s specific findings was the finding indicate that Taiwan’s land footprint declined from 5.39 gha in 2000 to 3.63 gha in 2011.

In the present study, we sought to evaluate the EF of Liuqiu Island from 2010 and 2015, adopting the EF concept previously suggested by Gössling et al. (2002) [53] and subsequently utilized by Martin-Cejas and Sanchez (2010) [54] as the theoretical framework through which to do so. Using this approach, the evaluation items were categorized according to three types, namely, transportation EF, activity EF, and food and fiber consumption EF items, in order to assess the impacts of EF on the island’s environment. The transportation EF category was further divided in terms of two key features: (a) the built-up area of transportation facilities utilized by travelers (i.e., road areas and parking lot areas) and (b) the energy consumed for the purpose of transportation during travel activities. The computation of the activity EF category was also broken down in terms of two key aspects: (a) the built-up land areas within various types of scenic areas, including tourist trails, highways, and scenic view spaces and (b) the area transformed through fossil-based energy consumption, such as the areas in touring scenic sites transformed by vehicle usage. The food and fiber consumption EF category, meanwhile, consisted of three key features: (a) the land area occupied by food and beverage service facilities (for example, restaurants and beverage sellers), (b) the total area of biologically productive land transformed as a result of by tourists through the consumption of foods, and (c) the total area of biologically productive land transformed by tourists through the consumption of fiber. The sources of data and main evaluation items for each of these categories are listed in

Table 1. Evaluation items and data sources.

EF Category	Evaluation Indicators	Evaluation Items	Evaluation Content	Data Sources
Transportation EF	Built-up land	Road use area	Road use area	Dapeng Bay National Scenic Area Administration Office [55]
		Parking lot area	Large vehicles, small vehicles, motorcycles, and bicycles	Dapeng Bay National Scenic Area Administration Office [55]
	Fossil energy	Resource usage	Transportation energy consumption	Dapeng Bay National Scenic Area Administration Office [55]
Activity EF	Built-up area	Recreation area	Recreation area	Dapeng Bay National Scenic Area Administration Office [55]
	Fossil energy	Recreation energy consumption	Recreation energy expense
Food and fiber consumption EF	Crop land	Food and fiber consumption when traveling	Grains, potatoes, sugar and honey, seeds and oilseeds, vegetables, fruits, fats, tobacco, and cotton	Food Supply and Utilization, Council of Agriculture [56]
	Grazing land		Meat, eggs, and diary
	Carbon land		Coniferous trees, broad-leaved trees, fuel wood, and faggots of wood
	Fishing grounds		Aquatic products

Data source: Compiled in this study.

.

The general formulas for calculating the EF and ecological carrying capacity (EC) are presented in (2) and (3) as

$$\mathrm{EF}=N\times ef=N\times {{\displaystyle \sum }}_{i=1}^n\left(a\times a_i\right) =N\times {\displaystyle \sum }_{j=1}^6\left(r_j{{\displaystyle \sum }}_{i=1}^n\frac{c_i}{p_i}\right) \left(i=1,2,3,\dots ,n ；\mathrm{j}=1,2,3,\dots ,6\right)$$

(2)

$$\mathrm{EC}=N\times {{\displaystyle \sum }}_{j=1}^{6}e{c}_j=N\times {{\displaystyle \sum }}_{j=1}^6\left(A_j\times r_j\times y_j\right) \left(j=1,2,3,\dots ,6\right)$$

(3)

where EF denotes the total EF (gha); N denotes the total population; ef denotes the per capita EF (gha); aa_i denotes the per capita biologically productive area (gha) converted to the ith traded commodity type; c_i denotes the per capita consumption (kg) of the ith commodity type; p_i denotes the average global productive capacity [kg/(t/gha)] of the ith consumer good type; r_j and y_j denote the equivalence factor (EQF) and yield factor (YF) of the jth land type, respectively, j denotes the corresponding type of land use or cover; EC denotes the total ecological capacity, ec_j denotes the ecological carrying capacity per capita; and A_j denotes the per capita area of the jth land type in the region [39].

3.5. Ecological Footprint Model

A national footprint model aimed at classifying biologically productive land into six types, namely, grazing, crop, fishing, forest, carbon uptake, and built-up land, has been developed by the Global Footprint Network. Because these six types of land have differing levels of biological productivity, their areas are weighted such that they can be represented using a unit of measurement known as the global hectare, or “gha”, with 1 gha of a given land type representing an area equivalent in terms of biological productivity to 1 gha of any other type. In effect, the global hectare can be used to quantify the biocapacity of the earth in a given year, with 1 gha representing the average productivity of the various types of biologically productive areas. The calculation utilized to convert raw land area values into gha values mainly relies on the terms EQF and YF.

EQF is used to evaluate the differences among the aforementioned six types of productive land; specifically, it represents the ratio of the average potential biological productivity of all global lands to the potential biological productivity of a specific land type. That said, because the lands in different regions and countries have different levels of available resources, the biological productivity of even the same type of land may vary across different regions, to say nothing of the variations across the different types of land themselves. Therefore, in order to make accurate comparisons among different regions, the area of each type of land in the region or regions under consideration must be converted into an equivalent area corresponding to the global average for biological productivity, and the conversion factor used for such conversion calculations is known as the YF.

The traditional EF model classifies the EF and ecological carrying capacity of land ecosystems into biological resource consumption (e.g., agricultural land, forest land, grassland, and fisheries) and energy consumption (carbon footprint) along with six other ecological system units [39]. However, the EF model combines the ecological function of systems and services to calculate the ecological carrying capacity in consideration of the ecosystem services of various land ecosystem supply units. Therefore, this study determined the ecological carrying capacity by reclassifying the ecosystem service value of land ecosystems into the following categories: (1) agricultural ecosystems; (2) forest ecosystems; (3) grassland ecosystems; (4) settlement ecosystems; (5) fishery ecosystems (including lakes, rivers, and wetlands); and (6) unutilized land and the six other ecosystem units. By contrast, traditional EF estimates consider only food and raw material production to provide two ecological functions [39].

In contrast, in the integrated EF model, an appropriate EQF and YF are employed in order to ascertain the ecological functions for the biological land productivity and the raw materials for food production rather than the ecological functions and the ecosystem service value. The YF was thus primarily used in this study for the purpose of representing the differences in ecosystem service values per unit area across various regions of Liuqiu Island, and was calculated as follows (4):

$${\mathrm{YF}}_j=v_j/v_j^{-}$$

(4)

where YF_j represents the YF of the jth ecosystem unit type, with j = 1, 2, …, 6 indicating the six ecosystem unit types; v_j represents the function of the ecosystem service value per unit area of the jth ecosystem type of a region; and $v_j^{-}$ represents the function of the mean ecosystem service value per unit area of the jth ecosystem type in Taiwan.

According to Formula (4), this study calculated the YF values of Liuqiu Island from 2010 to 2015 (

Table 2. YF values of ecosystems on Liuqiu Island with different land uses and covers (2010 to 2015).

Year	Agricultural Ecosystem	Forest Ecosystem	Grassland Ecosystem	Fishery Ecosystems	Settlement Ecosystems	Unutilized Land and Other Six Units Ecosystems
2010	1.46	0.87	1.10	1.78	0.52	2.13
2011	1.29	0.74	1.11	1.57	0.37	1.95
2012	1.03	0.59	0.85	1.26	0.13	1.60
2013	1.11	0.61	0.91	1.31	0.14	1.76
2014	1.04	0.55	0.85	1.20	0.10	1.63
2015	0.97	0.50	0.75	1.09	0.07	1.53

).

3.6. Ecological Analysis and Safety Evaluation

This study used the EF method to evaluate the use of ecological resources on Liuqiu Island to determine whether the current tourism levels exceed the land assimilative capacity of the area. The ecological remainder status is defined as a biocapacity value greater than zero (on the environmental resource supply side) assuming that the EF (on the environmental resource demand side) is neglected. A value of zero or lower indicates ecological deficit. Furthermore, to make EF capacity per unit area more accurately reflect environmental pressure, the ecological footprint index (EFI) was adopted to evaluate regional ecological security. EFI is also known as the EF pressure index and refers to the EF based on the ecological carrying capacity per unit area of a certain region. EFI levels are listed in

Table 3. Description of EFI.

Degree	Status	Index Range	Degree	Status	Index Range
1	Good	EFI < 0.5	3	Poor	EFI = 0.8–1.0
2	Fair	EFI = 0.5–0.8	4	Bad	EFI > 1.0

and were calculated as follows (5):

EFI = EF/EC

(5)

where EC represents biocapacity. When 0 < EFI < l, the supply of ecological resource supply exceeds the corresponding demand, and the region is ecologically secure. When EFI = 1, the supply and demand of ecological resources are balanced, and the region is ecologically unstable. When EFI > 1, the pressure per unit biocapacity area exceeds the supporting capacity. Thus, the supply and demand are unbalanced, and ecological security is under threat; the greater EFI deviates from 1, the greater the degree of ecological insecurity. As shown in Table 3, EFI < 0.5 is good to maintain a sustainable ecosystem. EFI = 0.5–0.8 and EFI = 0.8–1 indicate fair and poor situations, respectively. If EFI > 1.0, a long-term sustainable ecosystem is unlikely to be maintained.

4. Results and Discussion

4.1. Computation and Analysis Results of Ecosystem Services Value

Formula (1) was manipulated to estimate the ecological service value of each ecosystem type on Liuqiu Island from 2010 to 2015 (

Table 4. Ecosystem service value of each ecosystem type on Liuqiu Island from 2010 to 2015.

Value of Ecosystem Services (106 TWD)	Year	Fishery Ecosystems	Grassland Ecosystem	Forest Ecosystem	Agricultural Ecosystem	Unutilized Land and Other Six Units Ecosystems	Settlement Ecosystems	Total
	2010	88.53	10.58	0.56	18.03	2.25	0.01	119.96
	2011	101.49	10.65	0.60	16.84	2.40	0.01	131.99
	2012	108.51	11.04	0.92	20.14	2.31	0.01	142.93
	2013	139.65	5.57	0.07	21.27	2.61	0.02	169.19
	2014	130.30	7.28	0.08	24.27	2.40	0.02	164.35
	2015	123.54	6.85	0.09	30.82	2.19	0.03	163.52

). From 2010 to 2013, the total ecosystem service value on Liuqiu Island increased by TWD$49.23 million. This increase can be attributed to the increased areas of fisheries (including lakes, rivers, and wetlands) and cultivated lands, which have high ecological service value coefficients. However, from 2013 to 2015, the total ecosystem service value of Liuqiu Island decreased by TWD$5.67 million, primarily because the area of fisheries decreased greatly, and the increased area of cultivated land was not sufficient to compensate for the reduced ecological service value of fisheries. Furthermore, since 2013 the overall value of ecosystem service on Liuqiu Island has been reduced.

The ecological service values of the different ecosystem types on Liuqiu Island during the study period (Table 4) indicate that the fisheries ecosystem services function value increased then decreased, the forest ecosystem services function value increased, decreased then it increased again, the grassland ecosystem services function value had an M-shaped pattern; increase-decrease-increase-decrease; the agricultural ecosystem services function value decreased and then increased, with the overall ecosystem services function value increasing, consistent with previous study [39]. The net increase in total ecosystem service value in the study area increased by 36.3% during the study period. The ecosystem service value of fisheries showed the largest increase (39.5%), whereas that of the forest ecosystem showed the largest decrease (−83.9%), followed the grassland ecosystem (−35.2%). Fisheries accounted for 27% of the total area of utilized land in the study area, but the corresponding ecological service value accounted for approximately 75.5% of the total ecosystem service value in the study area. Namely, this high contribution is attributed to the high ecosystem service value coefficient of and the large area covered by fisheries in the study area. Thus, the findings of this study indicate that fisheries have the highest total ecosystem service value, stressing the importance of this sector in island ecosystems.

4.2. Variation in the EF of Liuqiu Island

This study calculated the per capita EF for each ecological unit of Liuqiu Island from 2010 to 2015 using Formulae (2) and (3); the results are presented in

Table 5. Six types of land use and their total per capita EF (gha/person).

Year	Ecological Footprint of Fossil Fuel per Capita	Ecological Footprint of Forest Land per Capita	Ecological Footprint of Grassland per Capita	Ecological Footprint of Agricultural Land per Capita	Ecological Footprint of Settlements Land per Capita	Ecological Footprint of Fishery per Capita	Total Ecological Footprint per Capita
2010	0.2101	0.0043	0.2144	0.1245	0.0049	0.0058	0.5640
2011	0.3273	0.0052	0.2605	0.1561	0.0076	0.0072	0.7639
2012	0.5721	0.0060	0.3043	0.2010	0.0106	0.0083	1.1023
2013	0.8167	0.0089	0.5392	0.2697	0.0572	0.0962	1.7879
2014	1.3266	0.0150	0.8225	0.3807	0.1169	0.0097	2.6714
2015	2.0712	0.0220	1.2099	0.5804	0.1899	0.0111	4.0845

. Generally, The per capita EF has exhibited a upward trend for nearly 6 years, increasing from 0.5640 ha in 2010 to 4.0845 ha in 2015. Among the six types of land use, the per capita ecological footprint of settlements land was considerably affected by the number of trips made by both domestic and international visitors. The per capita EF as fossil fuel has exhibited a year-over-year upward trend since 2010.

The per capita EF by ecological unit decreased in the following order: fossil fuel land > grassland > agricultural land > settlement land > forest land > fisheries. In conclusion, the per capita EFs of all land types increased between 2010 and 2015, and the change in the EF of fossil fuel land had a substantial effect on the change in the total EF of the research area. Tourism and recreation on Liuqiu Island have resulted in the consumption of substantial amounts of energy and a rapid increase in the consumption of biological resources, which explain the increase in EF during the study period. In addition, the rapid development of the tourism industry is exerting increasing pressure on the environment, with negative effects including traffic jams and the associated increases in harmful particles from vehicle emissions along with the excessive exploitation of natural resources, leading to considerable impacts on the environment. Such activities affect both humans and natural environments in addition to causing pollution.

4.3. Evaluation of Eco-Security on Liuqiu Island

To measure the eco-security of Liuqiu Island, Formula (5) was adopted to exam the ecological footprint index (EFI) from 2010 to 2015 based on the EF and ecological capacity. The calculation results are presented in

Table 6. EFI of Liuqiu Island from 2010 to 2015.

Year	PEC	PEF	Ecological Deficit/Remainder	EFI	Level	Status
2010	1.8722	0.5640	1.3082	0.30	1	Good
2011	1.6983	0.7639	0.9344	0.45	1	Good
2012	1.2395	1.1023	0.1372	0.89	3	Poor
2013	1.3061	1.7879	−0.4818	1.37	4	Bad
2014	1.0447	2.6714	−1.6267	2.56	4	Bad
2015	1.7919	4.0845	−2.2926	2.28	4	Bad

Abbreviations: PEC, per capita biocapacity; PEF, per capita EF; EFI, EF intensity index.

. The EFI of Liuqiu Island predominantly increased from 0.30 in 2010 to 2.28 in 2015. The most rapid increase in EFI occurred between 2013 and 2015. This indicates that tourism and recreation gradually increased the pressure on the ecosystem, reduced the eco-security level, and severely damaged the ecological environment, thereby threatening ecosystem function and structure. . In addition to the pressure on the environment generated by human activities, the fragile ecosystem was a critical contributing factor to the decline in the eco-security level of Liuqiu Island Moreover, changes in the natural environmental (e.g., the uneven distribution of water resources, severe vegetation damage, and forest community degradation) were critical factors that weakened the ecosystem in the study area and should not be neglected.

5. Conclusions

This paper first applied the EF model to analyze the changes from the demand and supply perspectives by considering both ecological footprint and carrying capacity on a variety of time scales. This study evaluated the ecological service values and their trends for different ecosystem types on Liuqiu Island from 2010 to 2015. The key results are summarized as follows. The total ecosystem service value of Liuqiu Island increased by TWD$43.56 million (from TWD$119.96 million to TWD$163.52 million) over the six-year study period. The overall value of ecosystem service increased rapidly from 2010 to 2013 by TWD$49.23 million. Nevertheless, the total ecosystem service value of Liuqiu Island has been increased during the study period. As mentioned previously, fisheries reached 27% of the total utilized land, but produced approximately 75.5% of the total ecosystem service value. This sector has the highest value of ecosystem service, indicating the importance of fisheries in island ecosystems.

Second, we introduced the equivalence factor of ecosystem service value and integrated the equivalence factor and YF into the EF model. We then evaluated the EF and ecological capacity of Liuqiu Island from 2010 to 2015. The per capita EF of Liuqiu Island increased from 0.5640 gha/person in 2010 to 4.0845 gha/person in 2015, and the EF on fossil fuel land increased more rapidly. This increase may be attributed to the promotion of tourism and recreation on Liuqiu Island, leading to higher energy consumption and rapid growth in EF. In addition, the EFI of Liuqiu Island predominantly increased from 0.30 in 2010 to 2.28 in 2015, indicating that the development of tourism and recreation gradually increased the pressure on the ecosystem, reduced the eco-security level, and severely damaged the ecological environment, thereby threatening ecosystem function and structure.

This study has empirically demonstrated that developing suitable indices and employing EF theory to analyze SIDS in order to estimate ecological security could objectively guide decision makers to utilize adequate types of measures, ensuring that maintenance of eco-security in SIDS can be performed safely and efficiently. For policy implication, considering the fact that EFI has been larger than 1.0 since 2013 and even reached to 2.38 in 2015, the ecosystem of Liuqiu Island has to be protected to revert its ecological function. It is evident that the current tourism scale already exceeds the capacity of Liuqui Island, the authorities may consider either to limit the number of visits or to set up environment protected areas. Since the area of fossil fuel land increases more rapidly, it is suggested to develop green energy, such as solar energy, by leveraging the sunny weather of the island. Electrical vehicles can be adopted for the entire island to avoid carbon emissions and harmful particles. The goal is to reduce the EFI to a good level with EFI < 0.5 that allows for a sustainable ecosystem that favors the development of ecotourism in Liuqiu Island.

In addition, the development of this industry is hindered by challenges such as a relatively deficient water supply and an inconvenient transportation system. In response to climate change and trends in island tourism, Taiwan Tourism Bureau proposed the “low-carbon island sightseeing plan on Liuqiu Island from 2010 to 2012 [57]”. Future development strategies should focus on developing low-carbon energy sources, recycling systems, ecotourism, low-carbon communities, and green transportation on Liuqiu Island with the help of low-carbon industries, tourism, and sustainable planning concepts.