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Ecosystems (2019) 22: 266–282 https://doi.org/10.1007/s10021-018-0270-0 2018 The Author(s) Impact of the Urbanisation Process in the Availability of Ecosystem Services in a Tropical Ecotone Area 1 2 Lucianna Marques Rocha Ferreira, Luciana S. Esteves, * 3 3 Enio Pereira de Souza, and Carlos Antonio Costa dos Santos 1 2 Centre of Technology and Natural Resources, Federal University of Campina Grande, Campina Grande 58429-140, Brazil; Faculty of Science and Technology, Bournemouth University, Poole BH12 5BB, UK; Department of Atmospheric Sciences, Federal University of Campina Grande, Campina Grande 58429-140, Brazil ABSTRACT Urbanisation has been a main cause of land use ecosystem services, including climate regulation, land cover (LULC) change worldwide, often with water ﬂow regulation, moderation of disturbance, irreparable consequences to the provision of nutrient cycling and biological control, which are ecosystem services. Despite an increase in quanti- critical locally when considering the regional trend tative assessments of ecosystem service values towards aridiﬁcation and the existing pressures on (ESV) related to LULC changes, data are scarce for water resources. Ecosystem functions loss and cli- ecotones, such as the agreste in northeast Brazil (a mate change impacts may lead to a shift in ecotone transitional area between the Atlantic Forest and boundaries favouring the semiarid Caatinga vege- the Caatinga biomes). The beneﬁt transfer method tation. These results urge the implementation of was used to quantify changes in ESV between ecosystem-based spatial planning, focusing on ur- 1989, 2007 and 2014 due to urbanisation in the ban green infrastructure and restoration of natural microwatershed Riacho das Piabas (3660 ha) in the habitats and their connectivity, to prevent further agreste of Paraı´ba. Remote sensing techniques and ecosystem service losses. Local estimates of ESV a geographic information system were used to required to inform the suggested policy actions are quantify LULC changes. Loss of arboreal vegetation identiﬁed. (covering 46% of the study area in 1989 and 5% in 2014) was the key factor driving the 73.2% decline Key words: microwatershed; land use land cover; in the total ESV (from US$ 13.7 million to US$ 3.7 urbanisation; natural resources; ecosystem services million in 2017 values). LULC changes resulted in valuation; agreste; Brazil. losses of 89% in the estimated value of eight INTRODUCTION Received 25 January 2018; accepted 20 May 2018; Ecosystem dynamics are inﬂuenced by land use published online 5 June 2018 land cover (LULC), especially in the ecological Electronic supplementary material: The online version of this article functions that reﬂect into ecosystem services (https://doi.org/10.1007/s10021-018-0270-0) contains supplementary (Kindu and others 2016; Tolessa and others 2017). material, which is available to authorized users. Ecosystem services beneﬁt humans, directly or Authors’ Contribution LMRF and EPS designed the study; LMRF and LSE undertook most of the data processing and drafting the article; LMRF, indirectly, through the supply of goods (for exam- EPS, LSE and CACS contributed to data analyses and crafting the article. ple, water, food and raw material), life support, *Corresponding author; e-mail: email@example.com 266 Changes in ESV in a Tropical Ecotone 267 physical, mental and spiritual well-being and Biodiversity (TEEB) database (Van der Ploeg and de development of economic activities (MEA 2005; Groot 2010), there are 68 entries for monetary Hails and Ormerod 2013; Costanza and others value estimates of ecosystem services in coastal 2014). wetlands, 61 in tropical forest and only one in ur- Urbanisation is one of the main drivers of LULC ban settings, two in deserts and nine in marine changes globally (Elmqvist and others 2013), ecosystems. resulting in long-lasting (for example, McKinney Very little is known about ecosystem services in 2002) or irreversible (for example, Seto and others ecotones or how their availability is affected by 2011) environmental impacts. Increasing popula- urbanisation or other LULC changes. Ecotones are tion and urbanisation causes pressure on natural often neglected in terms of conservation despite resources and high demand for ecosystem services, being important buffer zones to adjacent biomes which combined can lead to critical environmental (Scarano 2009) and of relative high biodiversity degradation, such as water crisis, air pollution, (Bueno and others 2017). Fragmentation of habitat microclimatic alteration and collapse of natural and biodiversity loss are known effects of urbani- resources (Seto and others 2011; Solecki and others sation, and of great importance for ecotones, such 2013). Loss of ecosystem services due to human- as the agreste. This article presents the ﬁrst quan- driven conversion of vegetated areas into urban titative assessment of loss in ecosystem services land (for example, Tianhong and others 2010; values (ESV) associated with LULC changes in the Mendoza-Gonzalez and others 2012; Estoque and agreste. The agreste is an ecotone between the Murayama 2013; Crespin and Simonetti 2016;Yi Atlantic Forest and the Caatinga, two Brazilian and others 2017) has been widely reported in biomes (included in the World Network of Bio- developing countries, where urban centres are sphere Reserves) under great threat from human largely (and increasingly) dependent on the eco- and climate pressures. Besides being neglected in logical integrity of surrounding rural areas (Hails conservation efforts, the Caatinga (and its eco- and Ormerod 2013). tones) is one of the least studied biomes and one of It is estimated that between 2000 and 2030 ur- the most threatened natural vegetation in Brazil ban areas will expand by around 200% and (for example, Moro and others 2016). approximately 5 billion people will be living in ci- The assessment focuses on changes in ESV asso- ties at the end of the period (Fragkias and others ciated with rapid urbanisation occurring over a 25- 2013). In this context, Groffman and others (2017) year period (1989, 2007 and 2014) in the highlighted two challenges for the science of urban microwatershed Riacho das Piabas (MWRP), state ecosystems: (1) the ability to predict and explain of Paraı´ba, Brazil. ESV is used here as a proxy to structural and functional patterns of ecosystems quantify changes in ecosystem services availability, under altered conditions (for example, urbanisa- rather than an accurate estimate of their monetary tion); and (2) assimilating the understanding of an value. Watersheds are recognised as the spatial integrated socio-ecological system, in which hu- planning unit for water resources management by mans are an inseparable part of ecosystems. the National Policy for Water Resources (Law 9433, The identiﬁcation and valuation, monetary or 8 January 1997). The MWRP supported and was otherwise, of ecosystem services are increasingly greatly affected by the growth of Campina Grande, the focus of research worldwide (Nelson and others a city known as the technology centre of the 2009; Balvanera and others 2012; McDonough and agreste and for its contribution to the regional others 2017). These studies have quantiﬁed gains economy. and losses of ecosystem services brought about by First, this article summarises the key character- spatial and temporal changes (Kreuter and others istics of the study area and its relevance to the 2001; Mendoza-Gonza´lez and others 2012; Tolessa agreste. Then the remote sensing techniques used and others 2017; Yi and others 2017); applied the to classify LULC (detailed in the online supple- existing knowledge to inform decision-making and mentary material S1) and the beneﬁt transfer policy development (Green and others 2016); and method applied to estimate ESV for each LULC are raised public awareness through environmental described. The quantiﬁcation of LULC and ESV education (de Groot and others 2012; Tolessa and changes are presented and discussed, including an others 2017). Some biomes and types of ecosystems evaluation of the suitability of the monetary esti- (for example, coastal and inland wetlands and mates for ecosystem services (coefﬁcient values in -1 -1 tropical forests) seem to have attracted most of the US$ ha a ) calculated by de Groot and others attention, whereas others are still poorly studied. (2012) to reﬂect ESV changes in the study area. The For example, in The Economics of Ecosystems and discussion offers suggestions of management 268 L. M. R. Ferreira and others strategies that can be applicable to the agreste and The climate of this region is hot and humid with other areas of similar ecological importance a dry season in the summer, type As’ according to undergoing rapid and disorganised urbanisation. the Ko¨ ppen-Geiger classiﬁcation (Kottek and oth- ers 2006). The annual rainfall is approximately 800 mm with the wettest period occurring between STUDY AREA March and June (Macedo and others 2011). The The MWRP extends over 3659.82 ha within the combination of climate and geomorphology re- Paraı´ba River Basin, state of Paraı´ba, northeast sulted in a region dominated by non-cultivable Brazil, spreading across three municipalities, land, with limitations to permanent crops and steep mostly within Campina Grande (Figure 1). The lands susceptible to erosion (AESA 2010). Climate study area is dominated by semideciduous and predictions for the semiarid Northeast Brazilian deciduous forest (greatly deforested) and xero- indicate increased temperatures and decreased phytic ﬂora, reﬂecting an ecological tension be- rainfall in the twenty-ﬁrst century, leading to in- tween open ombrophylous forest and savanna- creased risk of desertiﬁcation and important steppe (Moro and others 2016). Natural vegetation socioeconomic impacts (for example, Marengo and covered 67.4% of the Caatinga biome in 1990 others 2017; Vieira and others 2015). declining to 63.2% in 2010 at average annual rates The ‘Tropeiros da Borborema’ (traditional trav- of - 0.19% between 1990 and 2000 and - 0.44% elling traders of the region) settled along the banks between 2000 and 2010 (Beuchle and others of the Piabas creek attracted by the easy access to 2015). Data on LULC changes speciﬁc to the agreste drinking water and the availability of pasture for were not found, but rates of vegetation cover loss horses and donkeys, important assets in the agreste. are assumed to be similar or higher than reported These settlements gave rise to Campina Grande, the for the Caatinga. most important cotton growing area in Brazil in the Figure 1. The microwatershed Riacho das Piabas is located in the state of Paraı´ba, Northeast Brazil. Changes in ESV in a Tropical Ecotone 269 early 1900s and now the most important city in the were used in the analysis (Table 1). Digital image agreste. Droughts are frequent and cause critical processing, calculations of the NDVI and the the- impacts in the region. The great drought of 1824– matic maps were produced using the Geographic 1828 resulted in the transformation of the Piabas Information System QGIS 2.8.3. Image processing creek into a large water reservoir (called Ac¸ude to generate the NDVI from Landsat 5 images in- Velho) to supply Campina Grande. Due to degra- cluded radiometric calibration and monochromatic dation of water quality, the Ac¸ude Velho is no reﬂectance as described in Waters and others longer used as a supply for human consumption, (2002). To obtain NDVI from the Landsat 8 image, but through time it became the city’s cultural the reﬂectance at the top of atmosphere was cal- heritage and iconic landmark (Caˆmara 2006). culated according to USGS (2016). The NDVI was Similar to other locations in Brazil and other then calculated using equation (1) (Rouse and developing countries, human occupation in the others 1974). MWRP was mainly unplanned and disregarded the q q nir r impacts on local ecological dynamics. The middle NDVI ¼ ð1Þ q þ q nir r and downstream sectors of the MWRP are urba- nised or channelled, surrounded by illegal housing where q is the radiant ﬂux reﬂected in the near- nir built in designated Permanent Preservation Areas, infrared and q is the radiant ﬂux reﬂected in red -1 which are protected by Brazilian legislation. Water (in J s ). The NDVI values range from - 1to1,so contamination is an important issue, aggravated by that pixel values closer to 1 represent greater veg- an inadequate sewage system. The upstream sector etation vigour (Jensen 2006). Further details of the of the MWRP, although mostly rural, is impacted calculations to obtain the NDVI from the satellite by unregulated development within private prop- images are presented in the online supplementary erties, including construction of small dams, re- material (S1). moval of riparian vegetation and farming activities. Based on the NDVI values, six LULC classes were identiﬁed in the study area: water (includes natural and artiﬁcial water bodies), grasslands (areas MATERIALS AND METHODS dominated by grasses, including cultivated land), LULC Classiﬁcation shrublands (dominated by scrublands and savanna- type vegetation), arboreal vegetation (dominated The LULC classiﬁcation was based on the nor- by trees), urban area and bare lands (Table 2). In malised difference vegetation index (NDVI), which the study area, cultivated land tends to be in small is used for both monitoring and interannual com- plots and used seasonally (regulated by rainfall and parisons of vegetation cover (Jensen 2006). The water availability). As the LULC were classiﬁed NDVI was obtained from the analysis of Landsat/ from imagery obtained on ‘dry conditions’, culti- TM 5 (Land Remote Sensing Satellite Thematic vated areas are depicted as grasslands. Urban areas Mapper) images taken in 1989 and 2007 and correspond to areas characterised by impermeable Landsat 8/Operational Land Imager and Thermal surfaces (for example, houses, buildings and paved Infrared Sensor images taken in 2014. The satellite roads or streets), whereas bare lands include areas images used in this work were downloaded from without vegetation and dirt roads. Green urban the United States Geological Survey (USGS 2014) areas large enough to be resolved by the satellite Global Visualization Viewer. The satellite images images are classiﬁed within one of the vegetated were georeferenced to UTM WGS 84, Zone 25 LULC. South using the orthorectiﬁed Landsat 8 image as reference. Ground-truth validation of the LULC Estimating the Ecosystem Services Value classiﬁcation was performed on 60 geographic control points using a GPSMAP Garmin 64S tied to The total ESV for the study area was estimated the Global Navigation Satellite System. using the beneﬁt transfer method (Figure 2), which The vegetation in the study area is dominantly has been widely used (for example, Kreuter and deciduous, with plant species that grow their leaves others 2001; Estoque and Murayama 2013; Crespin after a few days of rainfall and shed them during and Simonetti 2016; Tolessa and others 2017;Yi dry periods. Therefore, a careful selection of images and others 2017) to assist assessments in areas is essential to ensure consistency in the spectral where local valuations are lacking (Mendoza- response of vegetation and the associated range of Gonzalez and others 2012; Rolfe and others 2015; NDVI values. Only images with low cloud cover Kindu and others 2016). Here the coefﬁcient values -1 -1 captured on days preceding precipitation events (US$ ha a ) calculated by de Groot and others 270 L. M. R. Ferreira and others Table 1. Date and Speciﬁcation of the Satellite Images Analysed in This Study. Source: USGS 2014 Imagery Path/ Satellite/sensor Radiometric/space resolution date raw 10/07/ 214/65 Landsat 5/TM 8 bits/30 m (bands 1, 2, 3, 4, 5 e 7) e 120 m (band 6) 29/08/ 214/65 Landsat 5/TM 8 bits/30 m (bands 1, 2, 3, 4, 5 e 7) e 120 m (band 6) 26/04/ 214/65 Landsat 8/OLI and 16 bits/15 m (band 8), 30 m (bands 1, 2, 3, 4, 5, 6, 7 e 9) and 100 m (bands 2014 TIRS 10 e 11) Table 2. LULC Classes, Their Respective NDVI Range, Equivalent Biome and Value Coefﬁcient (VC) -1 -1 LULC classes NDVI range Equivalent biome VC (2017 US$ ha a ) LULC Water - 1–0 Rivers and lakes 5199.86 Urban area 0.01–0.3 – – Bare lands 0.31–0.4 – – Grasslands 0.41–0.5 Grasslands 3499.89 Shrublands 0.51–0.6 Woodlands 1935.19 Arboreal vegetation 0.61–0.9 Tropical forests 6413.61 VC from de Groot and others (2012) adjusted to the Consumer Price Index of November 2017. (2012) were used to quantify relative gains or los- ESV ESV =ESV j i i ses in ESV due to LULC changes in the MWRP. The CS ¼ ð2Þ VC VC =VC value coefﬁcient of the biome identiﬁed by de jk ik ik Groot and others (2012) best matching each LULC where ESV is the estimated total ecosystem service va- class identiﬁed in the study area (Table 2) was used -1 -1 lue, VC is the unit value coefﬁcient (in US$ ha a ), as a proxy for the local ESV. The description of the i and j represent the initial and adjusted values, ‘biome’ woodland (in de Groot and others 2012) respectively, and k is the LULC class. CS indicates the includes vegetation types such as savannas, proportion of change in ESV relative to the proportion shrublands and scrublands, which are a good rep- of change in VC. If CS is greater than 1, the estimated resentation of the vegetation found in the LULC total ESV is considered elastic or very sensitive to the shrublands. The tropical forests ‘biome’ includes VC, suggesting that a more accurate value coefﬁcient is deciduous/semideciduous tropical forests, which needed (Kreuter and others 2001). If CS is less than 1, more closely relate to the vegetation types found in the estimated total ESV is inelastic and robust, indicat- the arboreal forest LULC. ing that the VC is acceptable even if not very accurate The match between the LULC classes and the (Kindu and others 2016). biomes represented in the study of de Groot and To identify the ecosystem services most affected others (2012) was not perfect. Therefore, sensitivity by land use change in the MWRP, the value of each analyses were conducted to determine whether service associated with the LULC class was calcu- variations in the coefﬁcient values would result in lated using the average monetary value estimated unacceptable uncertainties associated with the unit by de Groot and others (2012) of that ecosystem value transfer. The coefﬁcient values used to esti- service for the equivalent biome. All monetary mate the ESV of the four LULC classes (water, values and VC estimated by de Groot and others grassland, shrublands and arboreal vegetation) (2012) were adjusted to November 2017 values were adjusted by 50%, and the coefﬁcient sensi- (Table 3) using the Consumer Price Index inﬂation tivity (CS) was calculated using equation (2) fol- calculator of the US Bureau of Labor Statistics inﬂa- lowing the standard economic concept of elasticity tion calculator (available at https://www.bls.gov/da (Mansﬁeld 1985), as proposed by Kreuter and ta/inflation_calculator.htm). others (2001) and applied by many (for example, Li Similar to the approach taken by others (for and others 2007; Hu and others 2008; Crespin and example, Mendoza-Gonza´lez and others 2012; Simonetti 2016; Kindu and others 2016). Changes in ESV in a Tropical Ecotone 271 Figure 2. Steps of the beneﬁt transfer method used to estimate the ecosystem service values in the study area. Crespin and Simonetti 2016), the LULC classes of RESULTS bare lands and urban areas were excluded from the Land Use Change calculations of total ESV. The key objective here is to quantify the impact of urbanisation on the pro- There were considerable changes in LULC between vision of ecosystem services using the relative 1989 and 2014 in the MWRP, with marked differ- change in ESV as an indicator. In the study area, ences in spatial and temporal distribution (Fig- bare lands and urban areas expanded at the ex- ure 3). In this period, the largest relative changes pense of the natural vegetation, resulting in net loss (in percentage of initial area) were a 465% increase of ecosystem services; therefore, justifying that of urban area and a 89% decrease in arboreal their contribution to local ESV is considered neg- vegetation (Table 4). In 1989, arboreal vegetation ligible for the purpose of this study. Note that the was the dominant class covering 46% of the study ESV calculations include the contribution of green area (Table 4), mainly in the northern and south- urban areas, as these are classiﬁed within one of ern sectors of the study area (Figure 3). In contrast, the vegetated LULC. this class covered less than 5% of the MWRP in 2014 (Table 4) and was substituted at average rates -1 of 61 ha a , mainly by grasslands and shrublands 272 L. M. R. Ferreira and others -1 -1 Table 3. Ecosystem Services and Their Monetary Value (2017 US$ ha a ) for Each Biome Equivalent to Local LULC Ecosystem service Rivers and lakes Grasslands Woodlands Tropical forest Provisioning services Food 129.17 1452.60 63.37 243.72 Water 2203.27 73.12 32.90 Raw materials 64.59 207.17 102.36 Genetic resources 15.84 Medicinal resources 1.22 1832.81 Ornamental resources 39.00 Sum 2332.44 1591.53 309.54 2227.63 Regulating services Air quality regulation 14.62 Climate regulation 48.74 8.53 2490.87 Moderation of disturbance 80.43 Water ﬂow regulation 416.77 Waste treatment 227.88 91.40 7.31 Erosion prevention 53.62 15.84 18.28 Nutrient cycling 3.66 Pollination 37.78 36.56 Biological control 13.40 Sum 227.88 193.76 62.15 3081.90 Support services Nursery service 1551.31 19.50 Genetic diversity 1479.41 3.66 28.03 Sum 1479.41 1554.97 47.53 Cultural services Aesthetics information 203.51 Recreation 2639.54 31.68 8.53 1056.55 Sum 2639.54 235.19 8.53 1056.55 ESV 5199.86 3499.89 1935.19 6413.61 LULC Values from de Groot and others (2012) adjusted to the Consumer Price Index of November 2017. in the northern sector and by urban areas else- the contrasting changes in the extent of shrub- where (Figure 3). Urban areas covered less than lands, which increased 3% between 1989 and 2007 10% of the study area in 1989 and 56% in 2014 and decreased 44% between 2007 and 2014 (Ta- -1 (Table 4), at an average rate of 67 ha a , reﬂecting ble 4). The data show a clear pattern of arboreal the rapid growth of Campina Grande in the central vegetation being substituted by shrublands, which sector of MWRP (Figure 3). The rate of urban in turn were later changed to grasslands and these -1 sprawl declined from an average of 74 ha a be- were then replaced by urban areas and bare lands. -1 tween 1989 and 2007 to 49 ha a between 2007 Despite the importance in triggering land use and 2014, expanding mainly in the southern sector changes in the study area, water bodies have a in the latter period (Figure 3). modest presence, occupying only 0.1% of the In the period 1989–2014, bare lands and grass- MWRP in 1989 and 0.5% in 2014 (Table 4). The land showed a small increase in area (3.8 and increase of 399% between 1989 and 2007 resulted 3.4%, respectively), but changes were variable from the creation of a reservoir to control the water through time (Table 4). Between 1989 and 2007, ﬂow of Ac¸ude Velho. there was a reduction in the area of these LULC classes mainly due to urban encroachment in the Changes in the Availability of Ecosystem central sector. The increase in bare lands and Services grasslands areas observed between 2007 and 2014 Between 1989 and 2014, the total ESV in the study resulted from degradation and substitution of veg- area decreased 73% (from US$ 13.7 million to US$ etated areas, particularly in the north sector (Fig- 3.7 million) mainly due to losses of arboreal vege- ure 3). Evidence of this degradation is provided by tation (Table 5). The rate of average annual loss Changes in ESV in a Tropical Ecotone 273 Figure 3. Land use land cover in the microwatershed Riacho das Piabas (Northeast Brazil) in 1989, 2007 and 2014. Table 4. Extent (ha) of Each LULC Class in 1989, 2007 and 2014, the Respective Cover (%) Relative to the Study Area and Land Use Change (%) in the Microwatershed Riacho das Piabas, Brazil LULC classes 1989 2007 2014 Change (%) Area (ha) % Area (ha) % Area (ha) % 1989– 2007– 1989– 2007 2014 2014 Water 4.31 0.12 21.52 0.59 19.21 0.52 399.30 - 10.73 345.71 Urban area 361.85 9.89 1702.57 46.52 2042.94 55.82 370.52 19.99 464.58 Bare lands 580.81 15.87 439.54 12.01 602.70 16.47 - 24.32 37.12 3.77 Grasslands 504.1 13.77 475.70 13.00 521.00 14.24 - 5.63 9.52 3.35 Shrublands 513.63 14.03 526.78 14.39 292.56 7.99 2.56 - 44.46 - 43.04 Arboreal vegetation 1695.12 46.32 493.71 13.49 181.42 4.96 - 70.87 - 63.25 - 89.30 Sum 3659.82 100 3659.82 100 3659.83 100 Table 5. Total Ecosystem Service Value (2017 US$) in 1989, 2007 and 2014 per LULC Classes in the Microwatershed Riacho das Piabas (Brazil) and the Respective Change Through Time (in US$ and % of Initial Value) LULC clas- ESV (2017 US$) ESV (2017 US$) LULC LULC ses 1989 2007 2014 1989–2007 % 2007–2014 % 1989–2014 % Water 22,411 111,901 99,889 89,490 399.3 - 12,012 - 10.7 77,478 345.7 Grasslands 1,764,295 1,664,898 1,823,443 - 99,397 - 5.6 158,545 9.5 59,148 3.4 Shrublands 993,972 1,019,419 566,159 25,448 2.6 - 453,260 - 44.5 - 427,812 - 43.0 Arboreal 10,871,839 3,166,463 1,163,557 - 7,705,375 - 70.9 - 2,002,906 - 63.3 - 9,708,281 - 89.3 vegetation Total ESV 13,652,516 5,962,681 3,653,048 - 7,689,835 - 56.3 - 2,309,633 - 38.7 - 9,999,468 - 73.2 274 L. M. R. Ferreira and others reduced from US$ 427,213 between 1989 and 2007 its value in 1989 and its share of the total ESV more to US$ 329,947 between 2007 and 2014. This than doubled in the period, increasing from 7.3 to reduction reﬂects the decrease in the average an- 15.5% (Figure 4). nual loss of ESV in the latter period (US$ Results indicate an overall reduction in the value arboreal 286,129) when compared with the former (US$ of 18 out of the 19 ecosystem services included in 428,076). Changes in the extent of arboreal vege- the calculations of ESV between 1989 and 2014 tation have the greatest inﬂuence on the total ESV (Table 6). The only exception was the cultural values of any LULC; mainly because it is the local service ‘aesthetic information’, which increased by LULC class with the highest coefﬁcient value (Ta- 3.4%. This increase mimics the variation in the ble 2) and was by far the most dominant in 1989 extent of the grasslands LULC, the only class in the (covering 46% of the study area). Therefore, the study area for which a coefﬁcient value for the total ESV declined considerably as arboreal vege- service ‘aesthetic information’ is provided by de tation was lost to urban areas (which are consid- Groot and others (2012). Between 1989 and 2014, ered to have negligible contribution to the total nine ecosystem services had a reduction of over ESV for the purpose of this study). 85% in their value (Table 6): genetic resources, Variations in the extent of other LULC classes medicinal resources, air quality regulation, climate have less effect on total ESV because their value regulation, moderation of disturbance, water ﬂow coefﬁcient (for example, shrublands), extent (for regulation, nutrient cycling, biological control and example, water) or change in area (grasslands) is recreation. Considering only these nine services, relatively small. Although these other LULC had the estimated loss reaches US$ 8.93 million or 89% minor inﬂuences on variations in total ESV, their of the total ESV loss in the period. Six of these relative contribution to it increased through time services (genetic resources, air quality regulation, (Figure 4). In the context of decapitalisation of total moderation of disturbance, water ﬂow regulation, ESV, the relative importance of arboreal vegetation nutrient cycling and biological control) account for decreased from 80% to 32% between 1989 and 82% (US$ 8.2 million) of the total ESV loss and this 2014, whereas the share of other LULC increased, is solely due to losses of arboreal vegetation. See particularly grasslands, which represented 13% of the online supplementary material (S2) for a the total ESV in 1989 and 50% in 2014 (Figure 4). breakdown of the values of each ecosystem service In absolute values, ESV increased 346% tri- per LULC in 1989, 2007 and 2014. water pling its contribution to total ESV from 0.2 to 2.7%, In 1989, the ecosystem services climate regula- whereas ESV increased only 3% but its tion (US$ 4.2 million), medicinal resources (US$ grasslands share of the total ESV increased four times. On the 3.1 million) and recreation (US$ 1.8 million) were other hand, in 2014 ESV was only 57% of the largest contributors to the total ESV (Table 6), shrublands Figure 4. Relative contribution of the different LULC classes to the total ESV (in brackets) in the microwatershed Riacho das Piabas in 1989, 2007 and 2014. Changes in ESV in a Tropical Ecotone 275 Table 6. Estimated Value of the 19 Ecosystem Services (2017 US$) in 1989, 2007 and 2014 Associated with the LULC Observed in the Microwatershed Riacho das Piabas (Brazil) and Their Respective Change Through Time (in US$ and % of Initial Value) Ecosystem Value (US$) Change (in US$ and %) service 1989 2007 2014 1989–2007 % 2007–2014 % 1989–2014 % Provisioning services Food 1,178,496 847,491 822,041 - 331,005 - 28.1 - 25,449 - 3.0 - 356,455 - 30.2 Water 102,125 98,441 86,389 - 3,685 - 3.6 - 12,052 - 12.2 - 15,736 - 15.4 Raw materi- 312,481 190,395 112,831 - 122,086 - 39.1 - 77,563 - 40.7 - 199,650 - 63.9 als Genetic re- 26,851 7820 2874 - 19,030 - 70.9 - 4947 - 63.3 - 23,977 - 89.3 sources Medicinal 3,107,448 905,457 333,144 - 2,201,991 - 70.9 - 572,313 - 63.2 - 2,774,304 - 89.3 resources Ornamental 20,032 20,544 11,410 513 2.6 - 9135 - 44.5 - 8622 - 43.0 resources Regulating services Air quality 4783 7218 2652 - 17,565 - 70.9 - 4566 - 63.3 - 22,130 - 89.3 regulation Climate reg- 4,251,275 1,257,446 479,783 - 2,993,828 - 70.4 - 777,664 - 61.8 - 3,771,492 - 88.7 ulation Moderation 136,339 39,709 14,592 - 96,629 - 70.9 - 25,117 - 63.3 - 121,747 - 89.3 of distur- bance Water ﬂow 706,475 205,764 75,610 - 500,712 - 70.9 - 130,153 - 63.3 - 630,865 - 89.3 regulation Waste treat- 59,448 51,992 53,323 - 7456 - 12.5 1331 2.6 - 6125 - 10.3 ment Erosion pre- 66,153 42,876 35,887 - 23,276 - 35.2 - 6990 - 16.3 - 30,266 - 45.8 vention Nutrient cy- 6204 1807 664 - 4397 - 70.9 - 1143 - 63.3 - 5540 - 89.3 cling Pollination 81,379 37,952 17,686 - 43,427 - 53.4 - 20,266 - 53.4 - 63,693 - 78.3 Biological 22,715 6616 2431 - 16,099 - 70.9 - 4185 - 63.3 - 20,284 - 89.3 control Support services Nursery ser- 829,854 826,826 457,389 - 3028 - 0.4 - 369,437 - 44.7 - 372,465 - 44.9 vice Genetic 795,165 719,522 776,929 - 75,643 - 9.5 57,407 8.0 - 18,236 - 2.3 diversity Cultural services Aesthetic 102,589 96,810 106,029 - 5780 - 5.6 9219 9.5 3439 3.4 informa- tion Recreation 1,822,707 597,996 261,386 - 1,224,711 - 67.2 - 336,610 - 56.3 - 1,561,321 - 85.7 Total ESV 13,652,516 5,962,681 3,653,048 - 7,689,835 - 56.3 - 2,309,633 - 38.7 - 9,999,468 - 73.2 corresponding to 67% of the total value. In 2014, climate regulation (US$ 0.48 million), representing these same three ecosystem services represented 57% of the total value. only 29% of the total ESV and have lost between 85.7% (recreation) and 89.3% (medicinal re- Ecosystem Service Sensitivity Analysis sources) of their value in 1989. In 2014, the three The sensitivity analysis considering ± 50% of the ecosystem services contributing the most to the coefﬁcient values of each LULC used to estimate total ESV in the study area were food (US$ 0.82 the total ESV resulted in coefﬁcients of sensitivity million), genetic diversity (US$ 0.78 million), and 276 L. M. R. Ferreira and others Table 7. Estimated Total Ecosystem Service Values Adjusted (ESVa in 2017 US$) to ± 50% of Ecosystem Service Valuation Coefﬁcients (VC), the Relative Change in the ESVa Through Time (in % of Initial Value) and the Coefﬁcient of Sensitivity (CS) LULC classes VC Total ESVa % CS 1989 2007 2014 1989– 2007– 1989– 1989 2007 2014 2007 2014 2014 Water + 50% 13,663,722 6,018,632 3,692,993 - 56.0 - 38.6 - 73.0 + 0.002 + 0.02 + 0.03 Water - 50% 13,641,310 5,906,731 3,593,104 - 56.7 - 39.2 - 73.7 - 0.002 - 0.02 - 0.03 Grasslands + 50% 14,534,663 6,795,130 4,554,770 - 53.2 - 33.0 - 68.7 + 0.129 + 0.28 + 0.5 Grasslands - 50% 12,770,369 5,130,233 2,731,327 - 59.8 - 46.8 - 78.6 - 0.129 - 0.28 - 0.5 Shrublands + 50% 14,149,502 6,472,391 3,921,128 - 54.3 - 39.4 - 72.3 + 0.073 + 0.17 + 0.15 Shrublands - 50% 13,155,530 5,452,972 3,364,969 - 58.5 - 38.3 - 74.4 - 0.073 - 0.17 - 0.15 Arboreal vegetation + 50% 19,088,435 7,545,913 4,224,827 - 60.5 - 44.0 - 77.9 + 0.796 + 0.53 + 0.32 Arboreal vegetation - 50% 8,216,597 4,379,450 3,061,270 - 46.7 - 30.1 - 62.7 - 0.796 - 0.53 - 0.32 (CS) lower than 1 (Table 7). The lowest and the VC from de Groot and others (2012), except when highest CS were obtained for the water LULC considering ± 50% VC . In this case, the dif- arboreal (± 0.002 for 1989 and ± 0.03 for 2014) and arbo- ference is around ± 48.6%. Despite this consider- real vegetation (± 0.796 for 1989 and ± 0.32 for able difference in absolute values, the relative loss 2014), respectively. Hence, the total ESV estimated in ESVa between 1989 and 2014 is - 62.7% and - for the MWRP are relatively inelastic, that is, they 77.9% for - 50% VC and +50% VC , arboreal arboreal show relative low sensitivity to variations of up to respectively (Table 7), quite similar to the - 73.2% 50% in the value coefﬁcients proposed by de Groot estimated without the adjustment (Table 6). and others (2012). Thus, the estimated ESV is considered to be reasonably acceptable. DISCUSSION The relative differences between adjusted total Implications of Ecosystem Services Loss ESV (ESVa, Table 7) and the total ESV calculated using the value coefﬁcients of de Groot and others to the Agreste Ecotone (2012) are lower for water LULC (largest differ- The effects of rapid and disorderly urbanisation ences are + 1% and - 1.7% of the ESV in 2014) (commonly observed in developing countries) and higher for arboreal vegetation (largest differ- caused a reduction of vegetated areas (that is, ences are around ± 39.9% of the ESV in 1989). shrublands and arboreal vegetation) from 60% to The CS is dependent on the LULC’s value coefﬁ- just less than 13% of the study area between 1989 cient (VC) and extent; therefore, the largest dif- and 2014. The serious effects of urbanisation and ferences between ESVa and total ESV occur due to the decline in vegetated areas on water resources changes in the LULC showing the highest VC and (Hu¨ mann and others 2011; Schneider and others largest area. Consequently, a greater relative con- 2012); microclimate regulation (Kalnay and Cai tribution of the LULC to the total ESV will result in 2003; Schneider and others 2012) and fragmenta- a larger difference between ESVa and ESV. For tion of habitats and biodiversity (Seto and others example, the difference between the ESVa and ESV 2012; Newbold and others 2015) are well described calculated considering ± 50% VC increased grasslands in the literature and have critical implications in from ± 6.5% in 1989 to ± 25% in 2014, following semiarid locations such as the agreste. an increase in its relative contribution to the total A global scale assessment indicates that the ESV from 13 to 50%, respectively. On the other ecoregion where the MWRP is located is amongst hand, there was a reduction in the difference be- the most vulnerable to climate change, as both low tween the ESVa and ESV calculated consider- climate stability and degradation of vegetated areas ing ± 50% VC from ± 39.8% in 1989 to arboreal are contributing to biodiversity and ecosystem ± 15.9% in 2014, as its relative contribution to the functions loss (Watson and others 2013). According total ESV decreased from 80 to 32%, respectively. to Vieira and others (2015), 94% of the Northeast In terms of decapitalisation in the period 1989– region of Brazil shows moderate to high suscepti- 2014, ESVa losses are within ± 2.3% or less of the bility to desertiﬁcation. Predictions indicate a large US$ 10 million loss (Table 6) calculated using the increase in temperature and reduction in precipi- Changes in ESV in a Tropical Ecotone 277 tation, with a trend for longer dry spells (Marengo climate regulation, moderation of disturbance and and others 2017), increasing evaporation and the water ﬂow regulation). Studies estimating ESV and pressure on freshwater water resources (Gutie´rrez their changes through time often claim that results and others 2014). The region is affected by serious provide useful evidence to guide policy and man- water shortages caused by droughts, the last per- agement decisions, but they rarely provide an sisting since 2012 (Marengo and others 2017) and indication on how or where this may be applicable. resulting in almost three years in which the The results obtained here provide context to iden- domestic water supply was restricted to a few days tify policy actions that can reduce or prevent im- per week and irrigation was prohibited in rural pacts from LULC (Table 8). areas. Increased temperature and drought will Maintaining or creating green infrastructure (for intensify socioeconomic impacts related to water example, interconnected green spaces and habitat scarcity, already a major issue in the region (for restoration) is increasingly used as an adaptive example, Marengo and others 2017). management strategy to reduce vulnerability to The climate trend of increased aridity can create climate extremes and other environmental disrup- conditions that are more favourable to the semiarid tions (Green and others 2016; Watson and others Caatinga vegetation, shifting or shrinking the eco- 2013; Silva and others 2017). In urban and peri- tone boundaries likely to increase pressure on the urban areas, investment in interconnected green humid Atlantic Forest. Such a shift could aggravate infrastructure, in private and public land, combined the decline in total ESV and lead to loss of ecosys- with restoration of vegetated areas (for example, tem services critical to climate and water ﬂow riparian vegetation) and environmental education regulation (greatly provided by forests) and main- are a solution to maintain and enhance the func- tenance of biodiversity (for example, pollination tioning of ecosystems services. Such investment in and biological control). The great reduction in these green infrastructure can be justiﬁed by the socioe- important services (for example, 78% of pollina- conomic beneﬁts that can be attained through the tion and 89% of climate regulation) observed in positive impact on human health (for example, the 25 years analysed here enhances the ecotone’s Tzoulas and others 2007) or disaster reduction (for vulnerability to climate change, likely contributing example, Dhyani and others 2018). to the desertiﬁcation trend (for example, acceler- Payment for Environmental Services (PES) ating its effects and/or expanding the area af- should be considered as one investment option (for fected). It is important to mention that in tropical example, Balvanera and others 2012), which could areas, loss of naturally vegetated areas currently is, beneﬁt the MWRP. Law 10165 (of 25 November and is likely to be in the future, a greater threat to 2013) established a Policy for PES in the State of ecosystem degradation or species extinctions than Paraı´ba (Brazil), but no schemes have been climate change (Watson and others 2013), making implemented within the MWRP so far, probably nature conservation and restoration interventions due to ﬁnancial constraints, lack of public aware- ever more important. ness and/or technical capacity. It is important to emphasise that decision-making, particularly that Spatial Planning and Environmental focused on speciﬁc ecosystem services and involv- ing PES, should be based on data validated for local Management Implications conditions (Nelson and others 2009). Implemen- The temporal changes in LULC driven by the urban tation of ecosystem-based spatial planning (for development of Campina Grande clearly reﬂect the example, Brussard and others 1998) through management (or political) priority for the potential Strategic Environmental Assessment (for example, socioeconomic beneﬁts of the built environment Rozas-Va´squez and others 2018) could help iden- without measuring the consequences of environ- tifying strategic areas where PES and other mech- mental degradation. As a result, the city became anisms could help reduce the ecosystem services increasingly dependent on the provision of loss associated with urbanisation (for example, ecosystems services (for example, water supply and Dhyani and others 2018). a great diversity of raw material and food) and the There is a growing interest in incorporating ecological integrity of the surrounding rural areas ecosystem-based management in spatial planning (Hails and Ormerod 2013). Predictions of climate (for example, Balvanera and others 2012; Rozas- change impacts in the agreste urge implementation Va´squez and others 2017). Incorporating ecosystem of more sustainable management of water re- services in spatial planning decisions is still limited sources able to prevent LULC changes leading to by lack of clear guidelines, poor understanding of further loss of key ecosystem services (for example, suitable governance mechanisms (for example, 278 L. M. R. Ferreira and others Table 8. Policy Actions to Minimise the Relative Losses of ESV Due to LULC Changes Policy action Objectives Where it is applicable Stimulate nature con- Avoid the environmental and socioeconomic Where natural environment is still present or servation impacts of the resulting LULC changes little altered Regulate or control Reduce ecosystem services losses and the Where urbanisation is favoured or needed types and rates of magnitude of investment that may be re- occupation quired to replace them with alternative op- tions Promote creation of Gain or enhance the provision of ecosystem Where human occupation has caused unde- habitats or guide nat- services most needed locally and reduce the sirable or unacceptable environmental or ure restoration efforts costs associated with environmental degra- socioeconomic impacts, including where dation environmental compensation is required Establishing payment Prevent losses of ecosystem services more at Where provision of ecosystem services can be for ecosystem services risk or in greater demand by reducing maintained or enhanced through ﬁnancial schemes detrimental, or promoting favourable, LULC incentives to owners/managers of relevant changes areas Strategic Environmental Assessment) and the need Gonza´lez and others 2012; Richardson and others for methodological support (Mascarenhas and 2015; Tolessa and others 2017; Yi and others 2017). others 2015; Rozas-Va´squez and others 2017). Nevertheless, it is important to illustrate some of However, these limitations can be overcome when the issues related to the application of the beneﬁt practitioners and academics work together to de- transfer method in the study area. velop methods that are robust but simple enough ESV data from ecotones, and semiarid conditions, for practical applications. For example, the Secre- are scarce (or non-existent) making difﬁcult the tary of Environment and Urbanism of the city of application of coefﬁcients that would be more Natal (capital of Rio Grande do Norte state, representative of local biophysical settings. The Northeast Brazil) has identiﬁed the potential to characteristics of the study area are very geo- enhance ecosystem services provision to support graphically speciﬁc, a transition area between two the creation of a corridor of green urban areas unique and threatened biomes (the Caatinga and connecting two important areas of conservation the Atlantic Forest). Using transfer values from (SEMURB 2017). The active engagement of prac- areas of similar socioeconomic characteristics (for titioners from this Secretary with researchers (from example, Latin America) may be more represen- Bournemouth University and the University Fed- tative if they reﬂect similar biophysical conditions. eral of Rio Grande do Norte) throughout the pro- Most data from Latin America were obtained from ject Valuation of Environmental Services Applied to locations (for example, the Amazon) that are con- Coastal Areas (CAPES/PVE 88881.068064/2014-01) siderably different (both in biophysical conditions was key for the development and implementation and in type and intensity of use) from the semiarid of methods. ecotone in the study area. Additionally, using data from Latin America only would limit both the Caveats of the Study number of ‘biomes’ and the ecosystem services that could be assessed. When data from equivalent sites The limitations of transferring a general unit coef- are not available (as it is the case here), using ﬁcient to represent the local ESV are well described generalised values are more likely to reduce biases (for example, Nelson and others 2009; Richardson (Richardson and others 2015; Crespin and Simon- and others 2015; Rolfe and others 2015) and etti 2016). recognised here. Although the absolute ESV ob- As exempliﬁed by the results in this study, ESV tained from beneﬁt transfer must be considered estimates can be greatly inﬂuenced by the domi- with caution, they are used here to give an indi- nant LULC class if: (a) its area is substantially larger cation of magnitudes of change, alerting to the than other LULC classes; (b) its area changes con- ecosystem services most affected, which should be siderably through time; and (c) it shows the highest prioritised for local valuations that can inform ESV . Although the sensitivity analysis indicates LULC policy and management decisions (Kreuter and that the total ESV estimated for the MWRP is ro- others 2001; Tianhong and others 2010; Mendoza- bust (that is, CS < 1), its value varies ± 40% and Changes in ESV in a Tropical Ecotone 279 the decapitalisation ± 49% when calculations higher for the LULC (US$ 2203) than for the water consider adjustments of ± 50% VC . The LULC (US$ 33); therefore, small changes in arboreal arboreal ESV depends on each ecosystem service’s the extent of LULC can have an important LULC water monetary value and the number of services that are relative contribution to this ecosystem service. Al- included in the calculations. The VC (from de Groot though there was an increase in LULC area in water and others 2012) used in this study accounts for a the MWRP, in recent years part of it provides water different number of ecosystem services to calculate for secondary use only (for example, irrigation of each ESV (17 for ESV , 10 for ESV urban green areas) due to water quality issues. The LULC arboreal grass- and four for ESV (Fig- importance of water supply, the environmental lands, nine for ESVshrubland water ure 2). The issue lies where ecosystem services and socioeconomic costs of existing and future exist but have been omitted due to the lack of pressures (for example, climate change impacts) valuation studies in some of the biomes/equivalent and the level of investment required in the MWRP LULC, creating a discrepancy in the ESV used urge valuation efforts at the local level. LULC to assess impacts of LULC changes. This discrepancy and the indiscriminate use of generalised coefﬁ- CONCLUSION cients can lead to misconstrued knowledge and This study adds to the current knowledge of im- misinformed decision-making and have been pacts from LULC changes on the provision of identiﬁed as weaknesses of the beneﬁt transfer ecosystem services by providing the ﬁrst assessment method (for example, Nelson and others 2009). The discrepancy in VC described in the previous of temporal changes in total ESV in an area of the Brazilian agreste, a tropical ecotone between the paragraph will gradually be minimised as more Atlantic Forest and the Caatinga biomes. The ben- valuation studies are added to global databases eﬁt transfer method was used to quantify ecosys- ﬁlling the existing gaps (Richardson and others tem services losses between 1989, 2007 and 2014 2015). Wherever possible, local valuations should due to urbanisation in the microwatershed Riacho be preferred, particularly on assessment of services das Piabas state of Paraiba, northeast Brazil. Con- considered locally valuable. In the study area, cul- sidering the lack of local data, the beneﬁt transfer tural services, such as aesthetic information, illus- method proved useful to identify: (a) the ecosystem trate these limitations. Valuation of aesthetic services that were most affected by urbanisation; information is only available for grasslands (Ta- and (b) the local valuations that could contribute ble 3), whereas very likely water would have the the most to support policy development and man- highest value if local valuation was available. The agement decisions. main course of Riacho das Piabas, particularly the Urbanisation caused great reduction of vegeta- Ac¸ude Velho, is an iconic landmark of Campina tion cover which led to a generalised loss of 18 out Grande (the image most used to reﬂect the city’s of the 19 ecosystem services analysed and a identity in postcards, paintings and advertising) reduction of 73.2% of the total estimated ESV. and the location selected to house sculptures, his- Considering the existing pressure on water re- toric monuments and the Museum of Popular Art sources and the regional trend towards desertiﬁ- of Paraı´ba. Valuation of cultural ecosystem services cation, urbanisation has likely increased the (for example, aesthetic information) should be ecotone’s vulnerability to climate change through stimulated at the local level as their value is very losses of key ecosystem services (for example, bio- site-speciﬁc and they are underrepresented in glo- bal databases. logical control water ﬂow and regulation of climate and water ﬂow). The combination of urbanisation Estimating ESV using a constant value coefﬁcient and climate change impacts may lead to the eco- irrespective of variations in quality and/or how the tone to shrink or shift boundaries favouring the market value may have changed through time is a semiarid Caatinga and increasing pressure on the limitation of the beneﬁt transfer method (Nelson humid Atlantic Forest. Better understanding of the and others 2009; Richardson and others 2015; LULC changes inﬂuencing water quality and Rolfe and others 2015). In the study area, changes availability and local valuation of related ecosystem in the ecosystem service provision of water (15.4% services (for example, water provision and water over the 25-year period) is likely to be underesti- ﬂow regulation) would be most useful to guide mated due to two main reasons: (a) the large dif- policy and decision-making actions. Impacts of ference in the value of this service attributed to current environmental degradation and predicted LULC and the other LULC; and (b) the reduc- water climate change on the agreste ecotone urge the tion in water quality through time in the study implementation of ecosystem-based spatial plan- area. The service of water provision is 67 times 280 L. M. R. Ferreira and others global value of ecosystem services. Global Environ Chang ning (for example, through Strategic Environ- 26:152–8. mental Assessment) to prevent further ecosystem Crespin SJ, Simonetti JA. 2016. Loss of ecosystem services and services loss. Investment should prioritise urban the decapitalization of nature in El Salvador. Ecosyst Serv green infrastructure, restoration of natural habitat 17:5–13. and payment for ecosystem services schemes more de Groot RS, Brander L, Van der Ploeg S, Costanza R, Bernard F, likely to promote the recovery of the identiﬁed key Braat L, Christie M, Crossman N, Ghermandi A, Hein L, ecosystem services lost. Hussain S, Kumar P, McVittie L, Portela R, Rodriguez LC, Brinkm P, Van Beukering P. 2012. Global estimates of the value of ecosystems and their services in monetary units. ACKNOWLEDGEMENTS Ecosyst Serv 1:50–61. The authors Ferreira and Souza acknowledge the Dhyani S, Lahoti S, Khare S, Pujari P, Verma P. 2018. Ecosystem based disaster risk reduction approaches (EbDRR) as a pre- ﬁnancial support to the PhD scholarship and Re- requisite for inclusive urban transformation of Nagpur City, search Productivity award, respectively, received India. International Journal of Disaster Risk Reduction, http from the National Council for Scientiﬁc and Tech- s://doi.org/10.1016/j.ijdrr.2018.01.018. nologic Development (CNPq/Brazil). Esteves col- Elmqvist T, Fragkias M, Goodness J, Gu¨ neralp B, Marcotullio PJ, laboration was facilitated by and resulted from McDonald RI, Parnell S, Schewenius M, Sendstad M, Seto KC, work developed within the project VALSA (Valua- Wilkinson C. 2013. Urbanisation, biodiversity and ecosystem services: challenges and opportunities. Dordrecht: Springer. p tion of Environmental Services Applied to Coastal Areas 775p. (funded by CAPES/PVE 88881.068064/2014-01). Estoque RC, Murayama Y. 2013. Landscape pattern and ecosystem service value changes: implications for environ- OPEN ACCESS mental sustainability planning for the rapidly urbanizing summer capital of the Philippines. Landsc Urban Plan 116:60– This article is distributed under the terms of the Creative Commons Attribution 4.0 International Fragkias M, Gu¨ neralp B, Seto KC, Goodness J. 2013. A synthesis License (http://creativecommons.org/licenses/by/4 of global urbanisation projections. Elmqvist T, Fragkias M, .0/), which permits unrestricted use, distribution, Goodness J, Gu¨ neralp B, Marcotullio PJ, McDonald RI, Parnell and reproduction in any medium, provided you S, Schewenius M, Sendstad M, Seto KC, Wilkinson C, Eds. Urbanisation, biodiversity and ecosystem services: challenges give appropriate credit to the original author(s) and and opportunities. Dordrecht: Springer, pp 409–35. the source, provide a link to the Creative Commons Green TL, Kronenberg J, Andersson E, Elmqvist T, Go´ mez- license, and indicate if changes were made. Baggethun E. 2016. Insurance value of green infrastructure in and around cities. Ecosystems 19:1051–63. REFERENCES Groffman PM, Cadenasso ML, Cavender-Bares J, Childers DL, Grimm NB, Grove JM, Hobbie SE, Hutyra LR, Jenerette GD, Ageˆncia Executiva de Gesta˜o das Aguas do Estado da Paraı´ba McPhearson T, Pataki DE, Pickett STA, Pouyat RV, Rosi- (AESA). 2010. http://www.aesa.pb.gov.br/. Accessed 17 Oct Marshall E, Ruddell BL. 2017. Moving towards a new urban systems science. Ecosystems 20:38–43. Balvanera P, Uriarte M, Almeida-Len˜ ero L, Altesor A, Declerck Gutie´rrez APA, Engle NL, De Nys E, Molejon C, Martins ES. F, Gardner T, Hall J, Lara A, Laterra P, Pena-Claros M, Matos 2014. Drought preparedness in Brazil. Weather Clim Extrem DMS, Vogl AL, Romero-Duque LP, Arreola LF, Caro-Borrero 3:95–106. AP, Gallego F, Jain M, Little C, Xavier RO, Paruelo JM, Pei- Hails RS, Ormerod SJ. 2013. Ecological science for ecosystem nado JE, Poorter L, Ascarrunz N, Correa F, Cunha-Santino services and the stewardship of natural capital. J Appl Ecol MB, Herna´ndez-Sa´nchez A, Vallejos M. 2012. Ecosystem 50:807–11. services research in Latin America: the state of the art. Ecosyst Serv 2:56–70. Hu H, Liu W, Cao M. 2008. Impact of land use and land cover changes on ecosystem services in Menglun, Xishuangbanna, Beuchle R, Grecchi RC, Shimabukuro YE, Seliger R., Eva HD, Southwest China. Environ Monit Assess 146:146–56. Sano E, Achard F. 2015. Land cover changes in the Brazilian Cerrado and Caatinga biomes from 1990 to 2010 based on a Hu¨ mann M, Schu¨ ler G, Mu¨ ller C, Schneider R, Johst M, Caspari systematic remote sensing sampling approach. Appl Geogr T. 2011. Identiﬁcation of runoff processes—the impact of 58:116–27. different forest types and soil properties on runoff formation and ﬂoods. J Hydrol 409:637–49. Brussard PF, Reed JM, Tracy CR. 1998. Ecosystem management: What is it really? Landsc Urban Plan 40(9–20):1998. Jensen JR. 2006. Remote sensing of the environment: an earth resource perspective. 2nd edn. Saddle River: Pearson Prentice Bueno ML, Rezende VL, Pontara V, Oliveira-Filho AT. 2017. Hall. p 608p. Floristic distributional patterns in a diverse ecotonal area in Kalnay E, Cai M. 2003. Impact of urbanization and land-use South America. Plant Ecol 218:1171–86. change on climate. Nature 423:528–31. Caˆmara E. 2006. Os alicerces de Campina Grande: esboc¸o his- Kindu M, Schneider T, Teketay D, Knoke T. 2016. Changes of to´ rico-social do povoado e da vila (1697–1864). 3rd edn. ecosystem service values in response to land use/land cover Campina Grande: Editora Caravela. dynamics in Munessa-Shashemene landscape of the Ethiopian Costanza R, de Groot R, Sutton P, van der Ploeg S, Anderson SJ, highlands. Sci Total Environ 547:137–47. Kubiszewski J, Farber S, Turner RK. 2014. Changes in the Changes in ESV in a Tropical Ecotone 281 Kottek M, Grieser J, Beck C, Rudolf B, Rubel F. 2006. World Rouse JW, Haas RH, Schell JA, Deering DW. 1974. Monitoring Map of the Ko¨ ppen–Geiger climate classiﬁcation updated. vegetation systems in the great plains with ERTS. Proceedings, Meteorologische Zeitschrift 15:259–63. Third Earth Resources Technology Satellite, in 1 Symposium, Greenbelt: NASA SP. pp 3010–17. Kreuter UP, Harris HG, Matlock MD, Lacey RE. 2001. Change in ecosystem service values in the San Antonio area, Texas. Ecol Rozas-Vasquez D, Fu¨ rst C, Geneletti D, Almendra O. 2018. Econ 39:333–46. Integration of ecosystem services in strategic environmental assessment across spatial planning scales. Land Use Policy Li RQ, Dong M, Cui JY, Zhang LL, Cui QG, He WM. 2007. 71:303–10. Quantiﬁcation of the impact of land-use changes on ecosys- tem services: a case study in Pingbian County, China. Environ Rozas-Va´squez D, Furst C, Geneletti D, Munoz F. 2017. Multi- ¨ ˜ Monit Assess 128:503–10. actor involvement for integrating ecosystem services in strategic environmental assessment of spatial plans. Environ Macedo MJH, Guedes RVS, Sousa FAZ. 2011. Monitoramento e Impact Assess Rev 62:135–46. intensidade das secas e chuvas na cidade de Campina Grande/ PB. Revista Brasileira de Climatologia 8:105–17. Scarano FR. 2009. Plant communities at the periphery of the Atlantic rain forest: rare-species bias and its risks for conser- Mansﬁeld E. 1985. Microeconomics: theory and applications. vation. Biol Conserv 142:1201–8. 5th edn. New York: W.W. Norton and Company. Schneider A, Logan KE, Kucharik CJ. 2012. Impacts of Urbani- Marengo JA, Torres RR, Alvez LM. 2017. Drought in Northeast sation on ecosystem goods and services in the U.S. Corn Belt. Brazil-past, present, and future. Theor Appl Climatol 124(3– Ecosystems 15:519–41. 4):1189–200. SEMURB (Secretary of Environment and Urbanism of the city of Mascarenhas A, Ramos TB, Haase D, Santos R. 2015. Ecosystem Natal). 2017. Projeto Trampolim Ecolo´ gico. Report from the services in spatial planning and strategic environmental Secretaria Adjunta de Informac¸a˜o, Planejamento Urbano e assessment—a European and Portuguese proﬁle. Land Use Gesta˜o Ambiental, Setor de Areas Verdes, Natal/RN: SEMURB Policy 48:158–69. (June 2017), 18p. McDonough K, Hutchinson S, Moore T, Hutchinson JMS. 2017. Seto KC, Fragkias M, Gu¨ neralp B, Reilly MK. 2011. A meta- Analysis of publication trends in ecosystem services research. analysis of global urban land expansion. PLoS ONE Ecosyst Serv 25:82–8. 6(8):e23777. McKinney ML. 2002. Urbanization, biodiversity, and conserva- Seto KC, Gu¨ neralp B, Hutyra LR. 2012. Global forecasts of urban tion. BioScience 52:883–90. expansion to 2030 and direct impacts on biodiversity and ´ ´ Mendoza-Gonzalez G, Martı´nez ML, Lithgow D, Perez-Maqueo carbon pools. PNAS 109(40):16083–8. O, Simonin P. 2012. Land use change and its effects on the Silva R, Lithgow D, Esteves LS, Martinez ML, Moreno-Casasola value of ecosystem services along the coast of the Gulf of P, Martell R, Pereira P, Mendoza E, Campos-Cascaredo A, Mexico. Ecol Econ 82:23–32. Winckler Grez P, Osorio AF, Osorio-Cano JD, Rivillas GD. Millennium Ecosystem Assessment (MEA). 2005. Ecosystems 2017. Coastal risk mitigation by green infrastructure in Latin and human well-being: biodiversity synthesis. Washington: America. Marit Eng 170:39–54. World Resources Institute. p 408p. Solecki W, Seto KC, Marcotullio PJ. 2013. It’s time for an Moro MF, Lughadha EN, Arau´ jo FS, Martins FR. 2016. Phyto- urbanisation science. Environ Sci Policy Sustain Dev 55:12– geographical Metaanalysis of the Semiarid Caatinga Domain in Brazil. Botanical Review 82:91–148. Tianhong L, Wenkai L, Zhenghan Q. 2010. Variations in Nelson E, Mendoza G, Regetz J, Polasky S, Tallis H, Cameron DR, ecosystem service value in response to land use changes in Chan KMA, Daily GC, Goldstein J, Kareiva PM, Lonsdorf E, Shenzhen. Ecol Econ 69:1427–35. Naidoo R, Ricketts TH, Shaw MR. 2009. Modeling multiple Tolessa T, Senbeta F, Kidane M. 2017. The impact of land ecosystem services, biodiversity conservation, commodity use/land cover change on ecosystem services in the central production and tradeoffs at landscape scales. Front Ecol highlands of Ethiopia. Ecosyst Serv 23:47–54. Environ 7:4–11. Tzoulas K, Korpela K, Venn S, Yli-Pelkonen V, Kaz´mierczak A, Newbold T, Hudson LN, Hill SLL, Contu S, Lysenko I, Senior RA, Niemela J, James P. 2007. Promoting ecosystem and human Boerger L, Bennett DJ, Choimes A, Collen B, Day J, Palma A, health in urban areas using Green Infrastructure: a literature Diaz S, Echeverria-Londono S, Edgar MJ, Feldman A, Garon review. Landsc Urban Plan 81(3):167–78. M, Harrison MLK, Alhusseini T, Ingram DJ, Itescu Y, Kattge J, Kemp V, Kirkpatrick L, Kleyer M, Correia DLP, Martin CD, United States Geological Survey (USGS). 2014. Global Visual- Meiri S, Novosolov M, Pan Y, Phillips HRP, Purves DW, ization Viewer. Available in: http://glovis.usgs.gov/. Accessed Robinson A, Simpson J, Tuck SL, Weiher E, White HJ, Ewers 17 Sept 2016. RM, Mace GM, Scharlemann JPW, Purvis A. 2015. Global United States Geological Survey (USGS). 2016. Using the USGS effects of land use on local terrestrial biodiversity. Nature Landsat 8 Product. Available in: http://landsat.usgs.gov/using- 520:45–50. usgs-landsat-8-product/. Accessed 3 Dec 2017. Richardson L, Loomis J, Kroeger T, Casey F. 2015. The role of Van der Ploeg S, de Groot RS. 2010. The TEEB valuation data- beneﬁt transfer in ecosystem service valuation. Ecol Econ base—a searchable database of 1310 estimates of monetary 115:51–8. values of ecosystem services. Wageningen, The Netherlands: Rolfe J, Windle J, Johnston RJ. 2015. Applying beneﬁt transfer Foundation for Sustainable Development. with limited data: unit value transfers in practice. In: Johnston Vieira RMSP, Tomasella J, Alvala RCS, Sestini MF, Affonso AG, RJ, Rolfe J, Rosenberger RS, Brouwer R, Eds. Beneﬁt transfer Rodriguez DA, Barbosa AA, Cunha APMA, Valles GF, Crepani of environmental and resource values: a guide for researchers E, de Oliveira SBP, de Souza MSB, Calil PM, de Carvalho MA, and practitioners. Dordrecht: Springer. p 141–62. Valeriano DM, Campello FCB, Santana MO. 2015. Identifying 282 L. M. R. Ferreira and others areas susceptible to desertiﬁcation in the Brazilian northeast. Watson JEM, Iwamura T, Butt N. 2013. Mapping vulnerability Solid Earth 6:347–60. and conservation adaptation strategies under climate change. Nat Clim Change 3:989–94. Waters R, Allen R, Tasumi M, Trezza R, Bastiaanssen W. 2002. SEBAL Surface Energy Balance for Land. Idaho implemen- Yi H, Gu¨ neralp B, Filippi AM, Kreuter UP, Gu¨ neralp I. 2017. Im- tation: Advanced Training and User’s Manual. Version 1.0. pacts of land change on ecosystem services in the San Antonio 97p. River Basin, Texas, from 1984 to 2010. Ecol Econ 135:125–35.
Ecosystems – Springer Journals
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