Ecosystem disservices research: A review of the state of the art with a focus on cities

Ecological Indicators 52 (2015) 490–497

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Ecological Indicators journal homepage: www.elsevier.com/locate/ecolind

Review

Ecosystem disservices research: A review of the state of the art with a focus on cities Peer von Döhren a,∗ , Dagmar Haase a,b a b

Institute of Geography, Humboldt University Berlin, Unter den Linden 6, 10099 Berlin, Germany Department of Computational Landscape Ecology, Helmholtz Centre for Environmental Research – UFZ, 04318 Leipzig, Germany

a r t i c l e

i n f o

Article history: Received 24 September 2014 Received in revised form 27 November 2014 Accepted 20 December 2014 Keywords: Ecosystem disservices Human well-being Literature review Cities Indicators

a b s t r a c t Ecosystem services, the benefits produced by ecosystem functions and structures for human well-being, have received continuous international attention since the publication of the Millennium Ecosystem Assessment (MA) and the TEEB study (The Economics of Ecosystem Services and Biodiversity). Ecosystem functions also have effects that are harmful to human well-being, and these effects are called ecosystem disservices (EDS). The aim of this paper is to explore how ecosystem disservices have been recognised in the scientific literature and how the concept has been used in the discussion of socio-ecological systems. The paper analyses 103 studies on EDS. We use a quantitative approach to assess geographical spread, focus and indicator choice. This quantitative picture is supplemented by a qualitative discussion of the effects of ecosystem disservices on urban systems and cities. The results of the review show that although the idea of detrimental ecosystem effects is not new, systematic research on EDS has only just begun. Most studies on EDS focus on Western Europe or the USA. EDS have been more frequently discussed in the most human-dominated ecosystem types: i.e., in agricultural and urban ecosystems. The latter in particular will be central for future research on EDS, considering that more than 75% of the world’s population is expected to live in urban environments by 2050. © 2015 Elsevier Ltd. All rights reserved.

Contents 1. 2. 3.

4.

5.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Publication date of the case studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Context and type of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Spatial scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4. Types of indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5. Types of negative effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6. Affected elements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7. Geographical distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8. Urban ecosystem disservices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Possibilities and limitations identified by the literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. EDS and ES – the challenge of integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix A. Supplementary data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

490 491 491 491 492 492 492 492 493 493 493 494 494 495 495 495 495 496

1. Introduction ∗ Corresponding author. Tel.: +49 3020936905. E-mail address: [email protected] (P. von Döhren). http://dx.doi.org/10.1016/j.ecolind.2014.12.027 1470-160X/© 2015 Elsevier Ltd. All rights reserved.

Ecosystems are the basis for all life on Earth, particularly for human life and well-being. People receive many benefits from ecosystems, including clean air and water, food, and space for recreation (MA, 2005;

P. von Döhren, D. Haase / Ecological Indicators 52 (2015) 490–497

TEEB, 2010). However, alongside these benefits, ecosystems also produce nuisances, such as pests, litter and deterioration of infrastructure; biological hazards such as diseases, animal attacks, allergenic and poisonous organisms and geophysical hazards such as floods heat waves and storms. These are called ecosystem disservices (EDS) (Lyytimäki and Sipilä, 2009). The basic idea that natural or ecological processes or phenomena might cause nuisances or even harm people is not new; a substantial body of research has examined natural hazards (such as heat waves, floods, droughts, and storms) and assessed the negative impacts of water, soil or air pollution on human health and well-being (Fuchs et al., 2011; Handmer, 2004). These studies have been conducted across several scientific disciplines, including agriculture, natural disaster management, wildlife conservation, and public health (e.g., D’Amato, 2000; DeStefano et al., 2005; Treves et al., 2012). However, although these papers are about what we call EDS, they do not explicitly use this wording (Lyytimäki et al., 2008). In many articles, the negative ecological effects or impacts have been described as harmful consequences of ecological change or as deficient ecosystem services caused, for example, by the loss of biodiversity (Chapin et al., 2000; Folke et al., 2004; Balmford and Bond, 2005). A framework that systematically contextualises negative ecological effects as part of ecosystem structure and function seems to be comparatively novel and more rarely discussed (O’Farrell et al., 2007; Zhang et al., 2007; Lyytimäki et al., 2008; Lyytimäki and Sipilä, 2009; Bennett et al., 2010; Dobbs et al., 2011; Limburg et al., 2009; Escobedo et al., 2011; Gómez-Baggethun and Barton, 2013 have come to the same conclusion). However, as ecosystem services (ES) have been increasingly discussed, negative ecological effects have also been introduced and described as ecosystem disservices. The wording of EDS is imprecise; in contrast to the positive effects provided by ecosystem services for human well-being, the prefix ‘dis-’ in ‘disservices’ points to negative effects, and it can be unclear whether the disservice is to the ecosystem or to organisms interacting with it. One of the first definitions of EDS was published by Lyytimäki and Sipilä (2009), where EDS were defined as “functions of ecosystems that are perceived as negative for human well-being” (p. 311). The authors emphasise that the idea of purely beneficial ecological effects is in contrast to older interpretations of nature as the wild and dangerous opposite of civilisation that had to be tamed to be exploited; however, with the growing awareness of environmental challenges, the focus in industrialised countries changed from taming nature to protecting nature (Lyytimäki and Sipilä, 2009, p. 309; Limburg et al., 2009). This paper gives an overview of the state of the art EDS research across several disciplines.

491

Table 1 Review criteria and possible entries. Criterion

Possible entries

Paper/source Ecosystem context

Bibliographical reference of the paper Ecosystem(s) studied in paper (examples: urban, forest, aquatic) Research paper, review paper Qualitative data, quantitative data Local, regional, national, global scale (if possible, dimensions were more precise) Number of scientific fields from which indicators are used, names of scientific fields Thematic field/context of impact: ecological, economic, health, psychological, general (not specified) effect Societal groups that are affected, other elements (if not people), not specified City or comparable unit where field study took place, general (in case no field study is reported) Country where field study took place, global (if done) Yes (reference if possible), no, partially (if concept is explained)

Type of paper Type of data used Spatial scale of measurement Indicators Types (clusters) of negative effects Who is negatively affected? Spatial extent of field study Country Definition provided

quantitative), the spatial scale of the analysis (i.e., the scale on which ecosystem disservices were found), the process/function that describes the negative impact of the demonstrated EDS, the type of indicators used to demonstrate or measure the EDS, the affected groups mentioned, the geographical spread of case studies and whether a definition or at least an example was given in the paper. A detailed results database can be found in the supplementary material (Table 3).

3. Results 3.1. Publication date of the case studies Fig. 1 shows the change in the number of scientific research articles that used the term ‘ecosystem disservices’ over the past two decades. The term EDS, as understood in this paper, does not appear in scientific papers until 1998. We can see an increase in the number of published scientific papers from 2009 to the present. It becomes very clear that the majority of these papers were published after 2009, which proves that EDS is a new approach in research on socio-ecological systems.

2. Materials and methods 35 30

Number of papers

25 20 15 10 5 0

19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13

To assess the current state of the art in ecosystem disservices research, a review of the existing international journal literature was carried out. Thus, the core of this review describes the corpus of scientific papers that use the term ‘ecosystem disservices’. The key questions guiding the review are: what is understood by the term ‘ecosystem disservices’? Which phenomena are commonly associated with this term? Finally, how are ecosystem disservices identified or measured in these papers? Since the search strategy aimed at finding papers with a conceptual approach to EDS, contributions from research disciplines not using the term EDS, for example medical research, may be missing from the sample. A keyword search in the Web of Science database (www. thomsonreuters.com/web-of-science) and a full-text search of the ScienceDirect (www.sciencedirect.com) database using the terms ‘ecosystem’ connected to ‘disservice’, beginning with the year 1993, was carried out. The search resulted in 166 scientific papers that use both terms. The outcome sample includes papers that appear in both databases. Papers in which both terms were not used in relation to each other were excluded from the review. The remaining 103 papers were examined in detail, using a set of criteria, derived from the guiding questions stated above. The choice of evaluation criteria for this review builds on the approach of ecosystem disservices as defined by Lyytimäki and Sipilä (2009; Table 1), and comprise the date of publication, the context of the papers, the type of data used/analysed (qualitative or

Year Fig. 1. Number of studies about urban ecosystem disservices since 1998.

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3.2. Context and type of data

3.3. Spatial scale Fig. 2 shows the different spatial scales that were used in the papers to illustrate and analyse EDS. Although scale is important for any type of ecosystem services research, most of the reviewed papers do not contain any consistent information about scale; they instead discuss EDS in a rather abstract way. The papers that analyse EDS on a specific scale mostly work on local scales (27), ranging from sampling patches (Fischer et al., 2011) to city districts (Arnold, 2012; Bastian et al., 2012). The second most common papers used regional scales (20), such as regional woodlands (Agbenyega et al., 2009; Lele and Srinivasan, 2013), regional aquatic ecosystems (Limburg et al., 2009) or regional agricultural landuse (Ma and Swinton, 2011; Sagie et al., 2013).

Spatial response unit/ scale

global scale

regional scale

local scale

no information

0

10

20

30

40

Number of papers

Fig. 2. Spatial scales of the studies under review.

50

60

no indicator used Type of indicator

The category of ‘context’ was chosen to illustrate the thematic fields in which EDS have been studied so far. The 103 papers were classified according to the types of ecosystem that were examined. The analysis shows that EDS have gained comparably high recognition in studies about agricultural (33 papers) and urban (23) ecosystems. EDS in agricultural ecosystems are associated with natural factors that inhibit the production process, such as the effects of bad weather, predators and poisonous plants on livestock breeding (O’Farrell et al., 2007) or the negative consequences of agricultural land-use, for example, biodiversity reduction, increased soil erosion, groundwater depletion, or fertiliser and pesticide runoff (Swinton et al., 2007; Power, 2010; Firbank et al., 2013; Williams and Hedlund, 2013). In the papers focusing on urban ecosystems, EDS were associated with a wider range of negative natural effects, including health effects, from, for example the spread of allergenic pollen (Arnold, 2012) and the presence of animals as disease vectors (Lyytimäki et al., 2008); economic effects, such as from damage to infrastructure and maintenance costs for urban green structures (Dobbs et al., 2011; Escobedo et al., 2011); and socio-cultural effects, such as the discomfort caused by dark green spaces (Tzoulas et al., 2007) or the presence of animals or their droppings (Lyytimäki and Sipilä, 2009). The next category, ‘type of data,’ illustrates what type of data was used to identify, analyse and value EDS. This criterion is expected to reflect the operationalisation or realisation of the EDS concept in the papers examined. Quantitative data are more challenging to collect because they require more accurate measurement and a certain degree of scaling; qualitative data are easier to collect, and their scaling is of secondary importance. Most of the papers use qualitative data (63), such as a global increase in diseases from formerly undisturbed ecosystems (Dunn, 2010). “Ranked” qualitative data, obtained when different intensities of EDS were observed but not quantified, were treated as qualitative data. Forty papers used quantitative data to measure and assess EDS; for example, Dobbs et al. (2011) measured the damage to infrastructure, the risk to human safety and the decrease in air quality caused by organic aerosols and pollen from street trees.

cultural / social

economic

biophysical

0

10

20

30

40

50

60

Number of papers Fig. 3. Indicators used in the papers under review.

3.4. Types of indicators The term ‘indicator’ is used here in a broad sense to mean qualitative and quantitative proxies for EDS. Of interest are the aspects of EDS that are used to demonstrate the negative impact and how the impact has been measured. Three types of indicators were identified: social/cultural, economic and bio-physical/ecological indicators (Fig. 3). The total number of indicators characterising EDS exceeds the number of papers analysed, as 23 papers use more than one type of indicator to demonstrate or measure EDS. Most indicators (51 papers) refer to bio-physical/ecological properties that characterise EDS, such as nitrous oxide emissions from wetlands (Hefting et al., 2013) or rainfall, infiltration and runoff to indicate flood risks (Nedkov and Burkhard, 2012). Economic indicators constitute the second largest group of indicators (35 papers). These are primarily cost-indicators that relate EDS to damage costs (e.g., to repair damage by invasive ant species (Del Toro et al., 2012)) or maintenance costs (e.g., to maintain street trees (Escobedo et al., 2011)). Another 15 papers use indicators from social or cultural sciences and primarily refer to values obtained by interviews. These indicators are almost exclusively used to describe cultural EDS, such as the perception of discomfort of natural spaces (Plieninger et al., 2013).

3.5. Types of negative effect The potential negative effects that ecosystem processes might have on human quality of life have been reported in many different ways in the papers under review. Therefore, these impacts were clustered along thematic fields, of which the following five were identified: (1) ecological impact: EDS negatively affect ecosystem structures, processes and/or the services that they consequently provide. Examples for ecological impact are increased water consumption and emission of volatile organic compounds (VOC) by street trees (Escobedo et al., 2011) or emission of greenhouse gases by constructed stormwater wetlands (Moore and Hunt, 2011); (2) economic impact: EDS negatively affect (socio-) economic structures and processes, for example damage done to infrastructure from plant growth and microbial activity (Lyytimäki and Sipilä, 2009), maintenance costs associated with urban vegetation (Roy et al., 2012); (3) health impact: EDS negatively affect human health, which is one important aspect of quality of life. Effects like allergies caused by street trees (Arnold, 2012), vector-spread diseases from urban wetlands (Bolund and Hunhammar, 1999), attacks by animals (Del Toro et al., 2012; Barua et al., 2013) appear in this category; (4) psychological impact: EDS cause negative feelings (anxiety and discomfort) among the affected people, another aspect of human quality of life. Examples from this category are animal excrements or plant litter causing disgust (Lyytimäki et al., 2008; Agbenyega et al., 2009; Limburg et al., 2009) or feelings of insecurity and fear caused by densely grown urban green spaces (Tzoulas et al., 2007; Hofmann et al., 2012); and (5) general impact on human well-being: general assumptions about the negative effects of EDS on human well-being are presented. This category was chosen to account for papers which identify the damaging

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493

field of negative impact

general

psychological

human health

economic

ecological

0

10

20

30

40

50

60 Fig. 6. Geographical distribution of the case studies on ESD analysed in this review.

Number of papers Fig. 4. Major impact clusters of urban ecosystem disservices as reported in the literature.

effects generally without focussing on any specific cluster of impact (Fig. 4).

3.6. Affected elements The papers were reviewed according to the human populations or physical elements affected by EDS. The total number of affected populations again exceeds the number of papers because in some papers, more than one population was identified as being affected by EDS. Most of the reviewed papers do not specify the affected groups; focusing on the production of EDS, they leave further consequences to the anticipation of the reader. When an affected group is specified, the local population is most often identified as affected by EDS, for example residents living near urban greenspaces (Dobbs et al., 2011; Hofmann et al., 2012) followed by agricultural producers, crop farmers (Zhang et al., 2007; Gagic et al., 2012) or livestock-breeders (O’Farrell et al., 2007) (Fig. 5).

3.7. Geographical distribution Not all of the reviewed papers give clear geographic reference. Some of the reviewed papers include quantitative or measurement field studies, others use literature/cited examples to demonstrate EDS qualitatively. Those papers that do not give explicit examples or case study results but instead describe the impact of EDS from a global perspective without referring to a defined territorial unit/area were grouped in the global category. Thus, most of the examined papers gave no particular geographical information other than a general global perspective (45 studies). From the papers that included geographical references, the US (13 studies) was the most common origin, followed by Germany (11 studies). Clustering the examples by continent provides another picture. EDS have been demonstrated using case study research in Europe

not specified

negatively affected elements

local population farmers society (public) local businesses poor planning areas municipal land managers fishermen ecosystem processes 0

10

20

30

40

50

Number of papers

Fig. 5. Negatively affected groups/elements, as reported in the literature.

60

(28 studies), Americas (17 studies), Asia (7 studies), Australia/the Pacific (4 studies) and Africa (2 studies; Fig. 6). A review of studies on urban ecosystem services by Haase et al. (2014) shows a similar distribution of studies in the countries of the northern hemisphere. A review done by Martin et al. (2012) that explores what kinds of ecosystems are over- or understudied gives a plausible explanation for the uneven geographical distribution of the studies. The authors explain that scientific and financial concentration in the wealthier countries work in favour of the observed northern bias (p. 198).

3.8. Urban ecosystem disservices As a steadily increasing proportion of people live in cities (Haase, 2014; UN, 2012), urban ecosystems are expected to provide an increasing amount of goods and services to a substantial proportion of the global population. Disservices from urban ecosystems are called urban ecosystem disservices (UEDS). The reviewed papers provide a general overview of UEDS. Although examples of indicators and measurements for EDS are given (Dobbs et al., 2011; Escobedo et al., 2011; Arnold, 2012), such information is not sufficient to evaluate UEDS quantitatively. The following section focuses on the urban perspective of UEDS and provides some examples of how UEDS can be identified and distinguished from other EDS. As mentioned above, the urban environment holds significant importance for UEDS and influences the urban human–nature relationship in several ways. Respiratory allergies to wind-pollinated plants exemplify how the urban environment has substantial implications for UEDS. Windpollinated plant species typically produce large amounts of pollen compared with plant species with different reproductive strategies, which means that even a relatively small number of wind-pollinating plants, such as street trees, produce significant allergenic potential (Arnold, 2012). Even without assuming any difference in allergic sensitivity between rural and urban people, the higher population density implies a higher absolute number of affected individuals in the urban population. However, reports suggest that in urban areas, the sensitivity to respiratory allergies is increased (D’Amato, 2000), which is yet another influence of the urban environment on this UEDS. Urban ecosystem structures can even increase the production of UEDS; for example, a lack of species diversity of urban trees can lead to the overpopulation of specialised consumers, resulting in decreases in human well-being in several dimensions (e.g., aesthetically, financially, and even in health; Lyytimäki et al., 2008). As shown in the previous examples, the urban dimension of UEDS presents itself in various forms. UEDS can be urban in production or reception, meaning that not only EDS produced by urban ecosystems but also those that affect urban dwellers in a distinctive way can be considered UEDS. Comparing the last example with one from agricultural EDS shows that whereas an overpopulation of pest species in agriculture leads to a decrease in economic well-being (Zhang et al., 2007), the same basic ecosystem process decreases economic, aesthetic and health-related human well-being in urban environments (Lyytimäki et al., 2008), which corresponds to the different expectations of urban nature. The UEDS that are described in the reviewed literature and

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Table 2 Suggestions for UEDS indicators used in scientific literature. UEDS

Indicators

References

Plants and their pollens can cause allergies or poisoning

Allergenic potential of respective plants

Extensively managed (green) areas are considered unpleasant, ugly or unsafe

Area of non-illuminated parks

Plants can decrease air quality (emissions of VOC and PM, emissions in course of maintenance)

Emissions of volatile organic compounds (VOC), emissions from maintenance activities, concentrations of particulate matter (PM) in air Abundance of undesired species

Lyytimäki et al. (2008), Lyytimäki and Sipilä (2009), Dobbs et al. (2011), Escobedo et al. (2011), Pataki et al. (2011), Arnold (2012), Douglas (2012), Nowak (2012), Roy et al. (2012), Gómez-Baggethun and Barton (2013), Kabisch and Haase (2013), and Seamans (2013) Bolund and Hunhammar (1999), Tzoulas et al. (2007), Lyytimäki et al. (2008), Lyytimäki and Sipilä (2009), Escobedo et al. (2011), Douglas (2012), Hofmann et al. (2012), Kovacs (2012), Roy et al. (2012), Gómez-Baggethun and Barton (2013), and Kabisch and Haase (2013) Bolund and Hunhammar (1999), Dobbs et al. (2011), Escobedo et al. (2011), Manning (2011), Pataki et al. (2011), Nowak (2012), Roy et al. (2012), Gómez-Baggethun and Barton (2013), Seamans (2013), and Franck et al. (2014)

Sounds, smells, and behaviour of plants or animals cause anxiety Maintaining green spaces generates costs (financial, energy, opportunities) Damage to structures/people by biological activity

Animals can be disease vectors Plants can block views Decrease in water quality/quantity Harmful species damage those species that are cared for Urban green and blue spaces can obstruct traffic infrastructure Soil nutrient input

Displacement of endemic species Introduction of invasive species Presence of protected species can restrict other uses of an area

Maintenance cost for urban green areas Percentage of tree species susceptible to damage, percentage of trees yielding fruits, number of aged trees, amount of affected infrastructure Geographical range of respective diseases Number and size of trees near buildings Amount of water used for plant growth Not applicable to UEDS (in agriculture, EDS manifests as production loss, resp. pesticide costs) Amount of affected traffic infrastructure Not applicable to UEDS (in agriculture, EDS manifests as production loss, resp. amelioration costs) Population development of endemic species Population development of invasive species Not applicable

corresponding possible indicators or proxies are listed in Table 2. The list isn’t comprehensive, but gives relevant examples for UEDS and related indicators.

4. Discussion 4.1. Possibilities and limitations identified by the literature review The first evidence with which to evaluate the current state of recognition of EDS concepts in the scientific literature is the number of published papers that refer to EDS. The low total number of papers published on EDS indicates that this concept has not been as widely introduced or integrated into ecological sciences as the ES approach. The chronological distribution of the papers shows that a basic understanding of EDS started to exist at approximately the same time that the ES approach was introduced (see also Haase et al., 2014). The continuously increasing number of papers since 2009 suggests a growing recognition of EDS in connection with ES. Of considerable interest is the diversity of EDS in urban ecosystems research, which reflects the diversity of interests in urban environments. UEDS comprise several different effects that affect different parts of the urban population. The relevance of EDS is becoming increasingly well recognised in urban ecology (Haase et al., 2014). Regarding the geographical distribution of the reviewed case studies (58 papers), a bias towards developed countries (USA, Europe and Australia: 47 papers) is apparent. Assumptions about EDS for other parts of the world are uncertain, which has implications particularly for UEDS, considering that rapid, and even uncontrolled, urbanisation is occurring in the understudied parts of the world.

Bolund and Hunhammar (1999), Savard et al. (2000), Lyytimäki et al. (2008), Roy et al. (2012), Gómez-Baggethun and Barton (2013), and Seamans (2013) Lyytimäki et al. (2008), Escobedo et al. (2011), Kirkpatrick et al. (2011), Nowak (2012), Roy et al. (2012), and Seamans (2013) Lyytimäki et al. (2008), Dobbs et al. (2011), Escobedo et al. (2011), Roy et al. (2012), and Gómez-Baggethun and Barton (2013)

Tzoulas et al. (2007), Lyytimäki et al. (2008), Escobedo et al. (2011), Douglas (2012) Lyytimäki et al. (2008), Kirkpatrick et al. (2011), Roy et al. (2012), and Gómez-Baggethun and Barton (2013) Escobedo et al. (2011), Pataki et al. (2011), Roy et al. (2012), and Seamans (2013) Lyytimäki et al. (2008) and Escobedo et al. (2011)

Lyytimäki et al. (2008) and Lyytimäki and Sipilä (2009) Escobedo et al. (2011) and Pataki et al. (2011)

Escobedo et al. (2011) and Roy et al. (2012) Escobedo et al. (2011) Lyytimäki et al. (2008)

The state of integration of the term EDS in ecological science can be assessed by the type of data, the scale and the indicators that were used to demonstrate or measure EDS in the reviewed papers. The majority of the reviewed papers use qualitative data, which suggests that the concepts or methods used to measure EDS are not yet sufficiently developed, particularly concerning multiple effects. This hypothesis is supported by examination of the spatial scales on which EDS were studied. The finding that most papers mention EDS without reference to any specific spatial scale suggests an ongoing process of EDS identification. The second largest group of papers demonstrates or measures EDS at the local scale. At this scale, the processes and boundaries of the involved ecosystems are easier to study, and the uncertainty is lower than that of the identification and assessment of EDS on the regional or global scales. The EDS indicators, i.e., the qualitative and quantitative proxies used to demonstrate the EDS under review, provide further evidence of the systematic integration of EDS into the ES approach. The high number of biophysical indicators for EDS is most likely due to the biological, chemical and physical focus of ecosystems research in general; this group of indicators includes a wide variety of attributes, such as ecological indicators of soil organism populations (Ferris, 2010), the emission of pollen or volatile organic compounds by city trees (Arnold, 2012; Dobbs et al., 2011), and the global development of the number of infectious disease cases (Dunn, 2010). These indicators show the potential of ecosystems to generate EDS but are not specific about the actual impact on human health and well-being. The other types of indicators, economic and cultural, can be interpreted as different approaches to relate the biophysical ecosystem effects to decreases in human well-being, for example, damage costs in the economic context or disapproval in the cultural context. The clustering of negative impacts reveals a broad view in ecological science of the roles that EDS play. The distribution

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among the impact clusters shows that EDS are primarily observed as a hazard to beneficial ecosystem function and only secondly as a hazard to socioeconomic well-being. The evaluation of the reviewed papers regarding the definition of EDS shows a general understanding of EDS as being somehow opposed to or diminishing the value of ES. The distribution of the definitions can be attributed to the relatively low amount of scientific attention given to the systematic analysis of EDS so far. A closer look at the descriptions and examples reveals that some sources use the term EDS to describe impacts on ecosystems, whereas others use it to describe impacts from ecosystems. Only a minority of the reviewed papers provide a definition, based on the ES approach used in the Millennium Ecosystem Assessment (MA, 2005). The reviewed definitions describe the ecosystems as sources of EDS but acknowledge that human influence plays a role in the formation of EDS. A categorisation of EDS, comparable to the categories of ES from the MA, is not reported in the papers. It has to be noted, that this review does not cover the large amount of literature that study ecosystem processes that cause EDS without labelling them EDS. Research focussing EDS in a special context gain insights from this literature for a more detailed picture of EDS in different contexts.

4.2. EDS and ES – the challenge of integration The term ‘ecosystem disservice’ is derived from the ecosystem service approach and is thus conceptually related to it. The term is used sporadically in papers that were published before the MA (2005), and the meaning associated with EDS is rarely defined. After the dissemination of the ES approach following the MA, the recognition of EDS grew, and the integration of the EDS concept into the ES approach began (Zhang et al., 2007; Lyytimäki et al., 2008). The EDS concept as defined in recent literature has some deficits that must be addressed if the concept is to be fully integrated into the ES approach. At present, the EDS concept is not conceptually or analytically developed enough to be integrated into the ES approach. The main problem regarding integration is the small amount of systematic information on EDS, which is largely focused on certain ecosystem structures, rather than on categories comparable to those used in the ES approach. Connected to this is the lack of specified EDS inventories for most ecosystems. The concept must be specified in terms of the processes that are involved in driving the perceived harms. At the current stage of the EDS concept, there is uncertainty about the interactions between natural and anthropogenic ecosystem elements. A way of distinguishing between negative effects on ecosystems due to exploitation or pollution (which can also be interpreted as diminishing ES) and negative effects from ecosystems that occur as a consequence of ecological production or regulation is needed. The challenge is that this distinction is very difficult to hold up in practice, especially in highly influenced ecosystems where anthropogenic influence is a major driving force. Another challenge is the anthropocentric perspective of the definition, which was also adopted from the ES definition. The MA (2005) uses a general, anthropocentric perspective that builds on a general, universal understanding of human well-being, which is perfectly suited for disseminating the ES approach. However, on a closer look, the general idea of human well-being can be divided into a multitude of categories of human well-being, representing the different values, beliefs and necessities of a multitude of different groups. This subdivision leads to the problem that the identification of EDS becomes very dependent on which effects are perceived by individuals and societies as negative in a given context. The fact that ecosystems produce effects that might be positive (ES) for one group of people while being negative (EDS) for another may lead to social conflicts, too. This is of special relevance for UES/UEDS, assuming that green spaces in cities are limited and the expectations of different stakeholders diverge. The anthropocentric perspective cannot be ignored because it is central to the ES approach; it makes the ES approach compatible with social science and economics and thus provides a way to incorporate ecological considerations into planning and decision-making. However, studies dealing with EDS must consider that the overall comparability of inventories of EDS is limited, depending on the values, beliefs and traditions of the affected societies or groups (Lyytimäki et al., 2008).

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One of the major challenges in EDS research remains the identification and quantification of the magnitude of effects: that is, of the factors working together to produce negative ecosystem effects and the people who are affected by EDS. The physical parameters of a given ecosystem can be examined to assess the potential to produce potential EDS. The perceived severity of EDS depends on the social and economic situation, the age and the health status of the affected people. This somewhat subjective approach to EDS calls for a concept for measuring the scope of the negative impact relative to the situation of the affected people. An existing concept to approach the challenge of measuring EDS is provided by natural hazards and vulnerability research, which can be considered a comparably well-researched scientific field with connections to EDS. In hazard research, vulnerability reflects the differences in being affected by harmful effects (Lee, 2014; Palliyaguru et al., 2014). Assuming that natural hazards can be described as EDS on the very harmful end of the scale, it seems plausible to use an indicator comparable to vulnerability, or at least building on the same basic ideas from which vulnerability indicators are constructed, to measure the magnitude of the negative effects of EDS.

5. Conclusions The ES approach has proven very successful for establishing an overall understanding of the beneficial output of ecosystems for human well-being. The detrimental output of ecosystems has largely been left out of the picture. Although the recognition of EDS is growing, the number of dedicated studies is still low; consequently, the understanding of EDS is less developed than that of ES. The basic understanding in the current scientific literature defines EDS as an additional aspect of the ES approach that represents the negative effects of natural and ecosystem processes on humans. However, a real integration of both concepts has not yet been properly developed. Such an integrated ES/EDS approach must consider that the same natural functions and structures which provide beneficial services are also responsible for detrimental disservices. To reflect this, the definitions of ES and EDS can be rephrased: ES and EDS are those functions, structures and aspects of nature that can be either beneficial or detrimental for human wellbeing. This definition, although still abstract, is slightly more precise than the current understanding of EDS. It builds on the definition given by Lyytimäki and Sipilä (2009), which focuses on human well-being, and extends it by highlighting the ecological foundations for the realised positive or negative effects. The term ‘ecological potential’ requires some further clarification. The definition does not focus on ecosystem functions as the origin for ES or EDS but instead follows the idea of Bastian et al. (2012) that ecosystem processes generate potentials that are utilised to achieve human well-being. The quality of the utilisation and whether it is beneficial or detrimental for human well-being determines whether ES or EDS are realised. Another issue arising from the way in which EDS are reported in the scientific literature is the origin of the EDS. By definition, EDS originate from the ecosystem. However, the quality of the involved ecosystem functions is not defined. As a consequence, all negative ecosystem effects, regardless of whether they were produced by disturbed or ‘healthy’ ecosystem functions, are considered EDS, resulting in a wide range of phenomena being interpreted as EDS. In the context of urban ecosystems, where managed ecosystem structures are intensely intertwined with natural ecosystem structures, this issue requires further clarification to trace UEDS to their origin.

Acknowledgements We would like to thank our colleagues Salman Qureshi and Neele Larondelle for the very helpful comments on an earlier version of this manuscript.

Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.ecolind. 2014.12.027.

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