1. Introduction
As outlined in the Millennium Ecosystem Assessment of the United Nations, wetlands are one of the most threatened ecosystem in the world, with biodiversity loss being the major concern. With the continued loss and degradation of wetlands, ecological services are declining, negatively impacting human life. Factors such as climate change, rural poverty, and increased human population size have resulted in a wetlands loss of ~30%–50% in the last decade [
1,
2,
3]. As well as providing ecosystem services such as flood control, coastline protection, nutrient recycling, carbon sequestration, and ecotourism, wetlands support many specialized plants and animal species [
4,
5,
6,
7,
8].
This study was conducted in the Gaomei wetlands, located in Shimizu, Taichung, Taiwan, and designated national Taiwanese wetlands in 2007 (Construction and Planning Agency Ministry of the Interior, 2007). Recently, the Gaomei wetlands have become a major bird destination as a critical winter habitat. However, human activities such as highway construction have led to significant reductions in the sandbars and mangroves with a concurrent loss of biodiversity. Sustainable economic and societal development and reductions in the impact of tourism must be addressed when developing natural resources. This study sought to balance resource and biodiversity conservation with sustainable management and resource development. Because the Gaomei wetlands have similar topography and ecosystems to other Taiwanese wetlands systems, the evaluation model developed in this paper could be used for similar wetlands systems.
Chapin et al. (2000) suggested that ecosystem processes and biological diversity are crucial intermediaries in the overall economic and human systems’ global environment [
9]. Costanza et al. (1997) defined ecosystem services (ES) as ecosystems that “provide, directly or indirectly, the material and services to promote human welfare” [
10]. The UN published the Millennium Ecosystem Assessment (MEA) in 2005, in which ecosystem services are divided into supply services, regulating services, cultural services, and support services [
11]. Ecosystem service (ES) assessments have traditionally focused on identifying the individual monetary values for each ecosystem service [
12,
13]. However, the lack of theoretical frameworks has led to subjective judgments and criticisms [
14,
15,
16]. The integration of deliberate and non-monetary valuation approaches to ES valuations has increasingly been advocated as a way of revealing the wider value concepts. Such methods, however, have had limited application in practice and have been mostly focused on localized case studies [
17,
18,
19]. Barbier et al. (2011) evaluated the ecosystem service values in wetlands, mangroves, coral reefs, seagrass beds, and sandy beaches [
20]. Bateman et al. (2011) explored the contribution of land use changes on ecosystem services and ecosystems [
21]. Su et al. (2012) focused on four ecological zones in Hangzhou, China, to investigate the effect of landscape patterns and ecosystem service changes on urbanization [
7]. To examine ecosystem services and biodiversity in Europe, Maes et al. (2012) used four supply function indicators, five adjustment function indicators, and a cultural function indicator to calculate ecosystem service values, and used average species richness and species diversity to measure biodiversity [
22].
As previous research on land use and its impact on the environment has tended to focus more on exploring the single highest impact level, there has been less focus on the analysis and evaluation of the impact land-use development and the changes it has had on the natural environment. An econometric model [
23,
24], a statistical model [
25,
26,
27,
28,
29,
30] as well as a cellular automata model [
31] have to date been the most commonly used evaluation models. Burkhard et al. (2013) believed that, for a more realistic ecosystem service status assessment, ecosystem services at different ecosystems, and the benefits that different ecosystems and land cover types provide, should also be considered [
32]. Therefore, some studies have integrated the Millennium Ecosystem Assessment (MEA) and other assessment indicators into comprehensive evaluation indices [
33,
34,
35]. Nelson et al. (2009) combined land use change ecosystem services with the integrated valuation of ecosystem services and tradeoffs (InVEST) mode to explore the relationship between biodiversity competition with other ecosystem services [
36]. Polasky et al. (2011) also used the InVEST mode to quantify changes in ecosystem services, biodiversity, and land use in Minnesota from 1992 to 2001, and to assess the impact of different land use change scenarios on ecosystem services and biodiversity. Using the historical development (1964–2004) in Leipzig, Germany [
37], Lautenbach et al. (2011) developed regional scale indicators for different land use structure ecosystem services, such as water purification, pollination, food production, and outdoor recreation, and calculated the systemic functions and analyzed sensitivity tests under different land use types [
34]. Geneletti (2012) simulated the impact generated by different land management policies on ecosystem services in the future based on historical land use [
38]. In summary, using analysis and prediction modes for land use change along with mode simulations, decomposition, the analysis and synthesis of the complex socio-economic factors, and the interaction processes in natural ecosystems for given land uses to determine land-use change and spatial pattern trends [
39,
40,
41,
42] have become the focus of current research trends.
Sharp variabilities in the global climate have resulted in desertification, reduced ecosystem resilience, and loss of biodiversity. The 1972 United Nations Declaration on the Human Environment and Eco-Security raised concerns related to the preservation of food and ecosystems and outlined principles for sustainable human development projects, providing a new perspective on environmental resources, human survival and sustainable development reviews. With the development of ecological security theory and as ecological problems became increasingly prominent, researchers began using different indicators and measurement system models or methods to evaluate the ecological security of different regional scales, thus providing early warning models that could serve as vital references [
43].
As using quantitative indicators to analyze complex information increases objectivity [
44,
45], a three-dimensional (economy, ecology, and society) indicator system was developed to study ecological security in Western Nepal [
46]. Ecological security has also been measured using the Ecological Footprint Index (EFI) and environmental carrying capacity (ECC) [
47].
The Ecological Footprint (EF) Model was proposed by Rees (1992) [
48], with the primary feature being its ability to compare human demands on the environment with the biosphere’s ability to regenerate resources and provide services. Wackernagel and Rees (2000) proposed that the EF magnitude was directly proportional to the environmental impact (the greater the EF, the greater the environmental impact), and was inversely proportional to the per-capita usable area of biologically productive land (the greater the EF, the smaller the per-capita usable area of biologically productive land) [
49]. It is now a widely used measure in the field of ecological economics as it is a quantitative indicator that is easy to understand and calculate. Therefore, this paper uses sustainable ecological evaluation indicators (SEEIs) to measure regional ecological security on a per-unit ecological footprint basis.
In summary, this paper first combines the ecosystem services and ecological footprint models to evaluate the sustainability status based on each of the ecosystem service features for the different Gaomei wetlands land use covers, after which the ecosystem service values are calculated. Subsequently, the SEEI—the ecological remainder (ER), the ecological deficit (ED), the EFI and ESI—is used to analyze the resource utilization efficiency and ecological security in the Gaomei wetlands. The problems identified by the different indicator values are evaluated to develop a systematic measurement apparatus to encourage sustainable development and to review the evolution in sustainable development trends.
4. Conclusions
This study employed the ecosystem service value, ecological capacity, EF, and sustainable ecological evaluation indicators (SEEIs) to assess the ecological security and the efficient use of resources in the Gaomei wetlands. We came to the following conclusions:
The total value of the ecosystem services in the Gaomei wetlands increased from 59.24 million TWD in 2008 to 98.10 million TWD in 2015. The EF gradually increased from 244.03 gha in 2008 to 380.98 gha in 2015. Of the three activity EFs, TREF had the biggest proportion (70.18%), with ACTEF (24.97%) and FEF (4.85%) following thereafter. The SEEI indicated that the ED grew by about 106.54% from 2008 to 2015. In 2015, the EFI was rated Level 4 at 1.02, and the ESI was rated Level 3 at 0.49. Therefore, as the Gaomei wetlands are predicted to become ecologically unsustainable over time, local, regional, and national governments need to implement regulations to strictly control the Gaomei wetlands land use.
According to the empirical analysis results, the primary factors influencing various types of activity EFs are presented below.
(a) Tourists had a negative effect on the overall EF from all activities. Therefore, when tourist numbers increased, the EF increased and there was a greater environmental impact. Attempts should be made to increase the environmentally friendly behavior of tourists to decrease the impact of increasing tourist numbers.
(b) The fossil fuels used for transportation had the greatest influence on the TREF. Therefore, strategies aimed at reducing energy use and the commensurate carbon footprints should be developed. Using public transportation and using environmentally friendly vehicles and services such as electric cars and motorcycles and bicycle rental services should be encouraged. Global positioning systems could be used in rental cars to monitor tourist activity, which can then be used to develop effective transportation systems aimed at decreasing overall fossil fuel use and minimizing the associated carbon footprints.