1

1

2

Paradigms in the Recovery of Estuarine and Coastal Ecosystems 3

4

Carlos M. Duarte1,2,3*, Angel Borja4, Jacob Carstensen5a, Michael Elliott6, Dorte Krause-5

Jensen5b, Núria Marbà1 6

1Department of Global Change Research, IMEDEA (CSIC-UIB), Institut Mediterrani 7

d’Estudis Avançats, Miquel Marquès 21, 07190 Esporles (Illes Balears), Spain 8

2Faculty of Marine Sciences, King Abdulaziz University, P. O. Box 80207, Jeddah 9

21589 Saudi Arabia 10

3The UWA Oceans Institute, University of Western Australia, 35 Stirling Highway, 6009 11

Crawley, WA, Australia 12

4AZTI-Tecnalia; Marine Research Division; Herrera Kaia, Portualdea s/b; 20110 Pasaia, 13

Spain 14

5aDepartment of Bioscience, Aarhus University, Frederiksborgvej 399, 4000 Roskilde, 15

Denmark 16

5bDepartment of Bioscience, Aarhus University, Vejlsøvej 25, 8600 Silkeborg, Denmark 17

6Institute of Estuarine & Coastal Studies, University of Hull, Hull, HU6 7RX, United 18

Kingdom 19

20

*Corresponding author: email: carlosduarte@imedea.uib-csic.es21

*ManuscriptClick here to view linked References

2

Abstract 1

Following widespread deterioration of coastal ecosystems since the 1960s current 2

environmental policies demand ecosystem recovery and restoration. However, vague 3

definitions of recovery and untested recovery paradigms complicate efficient 4

stewardship of coastal ecosystems. We critically examine definitions of recovery and 5

identify and test the implicit paradigms against well-documented cases studies based 6

on a literature review. The study highlights a need for more careful specification of 7

recovery targets and metrics for assessing recovery in individual ecosystems. Six 8

recovery paradigms were identified and examination of them established that partial (as 9

opposed to full) recovery prevails, that degradation and recovery typically follow 10

different pathways as buffers act to maintain the degraded state, and that recovery 11

trajectories depend on the nature of the pressure as well as the connectivity of 12

ecosystems and can differ between ecosystem components and among ecosystems. A 13

conceptual model illustrates the findings and also indicates how restoration efforts may 14

accelerate the recovery process. 15

16

17

3

Introduction 1

Growing evidence of the widespread deterioration of coastal ecosystems due to 2

increased inputs of materials, such as nutrients, organic matter, sediments and 3

pollutants; physical disturbance through shoreline and offshore constructions, and 4

trawling fisheries among others, has led to policy decision aiming, directly or indirectly, 5

to improve the status of our coastal ecosystems. Examples of these policies include the 6

European Water Framework Directive (WFD, 2000/60/EC) and the Marine Strategy 7

Framework Directive (MSFD, 2008/56/EC), the Clean Water Act (CWA) and the 8

National Estuary Program (www.epa.gov/nep) in the US, and the recently announced 9

UN Oceans Compact (www.un.org/Depts/los/ocean_compact /oceans_compact.htm). 10

Many of these statutory instruments work on the simple premise of assessing 11

whether the status of a system is as expected and if not then requiring management 12

measures to restore the system (Mee et al. 2008). Regulatory measures set targets for 13

the recovery process (Borja et al. 2012), which in turn demand an understanding of the 14

trajectories of recovery, and the traits that allow determining when coastal ecosystems 15

can be declared recovered (Elliott et al. 2007). However, the scientific input demanded 16

by regulators in applying these instruments for the efficient stewardship of coastal 17

ecosystems appears not to be as simple and straightforward as expected, providing an 18

impetus for research on the recovery of coastal ecosystems. 19

Stress ecology, aimed at understanding the responses of ecosystems to 20

stressors, developed as a research program during the 1970s and 1980s as pressures 21

on the environment increased (Odum 1985). Subsequent efforts to alter and reverse 22

deterioration of coastal and estuarine ecosystems led to the development of recovery 23

4

ecology (Lotze et al. 2011). However, few examples of successful ecosystem recovery 1

are available to date (e.g. Jones and Schmitz 2009, Borja et al. 2010, Greening et al. 2

2011, Lotze et al. 2011, Orth and McGlathery 2012), with most examples focused on 3

recovery of populations (Lotze et al. 2011) and, at most, habitats (Elliott et al. 2007), but 4

not ecosystems (Duarte et al. 2009, Steckbauer et al. 2011). 5

Ecosystem restoration is more challenging than biological conservation, where 6

the target is to recover a species or habitat of interest rather than an ecosystem, as the 7

targets for ecosystem restoration involve both structural and functional attributes. 8

However, both are often confounded (Lotze et al. 2011). Available examples of coastal 9

ecosystem recovery show, for instance, that recovery is rarely complete and is a slow 10

process involving several decades (Borja et al. 2010, Duarte et al. 2009, Lotze et al. 11

2011, Steckbauer et al. 2011, Verdonschot et al. 2013). The conceptual model 12

proposed by Elliott et al. (2007) indicates that in many cases other habitats are created 13

which may approximate but not replicate that which was originally lost. This is 14

particularly the case where statutory instruments require compensatory habitat to be 15

created to accommodate habitat loss due to human activities such as the building of a 16

new port. 17

The paucity of observations on the recovery of estuarine and coastal ecosystems 18

has led to recovery ecology being guided by theory (Lotze et al. 2011). However, theory 19

needs be confirmed by observations, and thus, the theoretical underpinnings of marine 20

recovery ecology remain primitive, and often draw from assumed axioms and circular 21

reasoning. For instance, the recovery of coastal and estuarine ecosystems has been 22

suggested to depend on the removal of the pressure (Jones and Schmitz 2009, Lotze et 23

5

al. 2011), and evolve from a rudimentary structure first to a more optimal state later 1

(Thom et al. 2012). It has been assumed that if the suitable physico-chemical 2

environment, i.e. the boundary conditions, is created then the natural ecology will 3

develop (Elliott et al. 2007, Simenstad et al. 2006). Ecosystem recovery has been 4

classified into complete recovery, partial recovery and no recovery (Lotze et al. 2011) 5

and has been argued to be dependent on ecosystem recoverability defined as ‘the 6

ability of a habitat, community or individual (or individual colony) of species to redress 7

damage sustained as a result of an external factor’ (Elliott et al. 2007). Despite this, no 8

guidance has been provided as to what determines ecosystem recoverability or how to 9

assess whether recovery has been achieved. 10

Assessing when the recovery process has reached an end point is non-trivial, as 11

baselines are dynamic and change through time (Jackson et al. 2001, Mee et al. 2008, 12

Duarte et al. 2009, Carstensen et al. 2011) and may not be reached simultaneously for 13

different indicators of ecosystem status (Borja et al. 2010). Similarly, there is the need to 14

be especially clear what characteristics are required to indicate that a healthy, fully-15

functioning ecosystem has been achieved (Tett, et al. in press). The expectation that 16

recovery is simply the inverse process of deterioration through reversible trajectories 17

proved too naïve, since there is now ample evidence that eutrophication (Duarte et al. 18

2009), hypoxia (Steckbauer et al. 2011), and overfishing (Jackson et al. 2001) are not 19

fully reversible processes. Indeed coastal ecosystems follow complex trajectories and 20

exhibit hysteresis during recovery (Elliott et al. 2007, Duarte et al. 2009). In addition, 21

coastal and estuarine systems are inherently variable, which make the detection of both 22

degradation and recovery more difficult (Elliott and Whitfield 2011). Growing frustration 23

6

with failure of recovery efforts to meet targets may act as a deterrent to engage society 1

in further efforts to restore coastal ecosystems. 2

Failure to acknowledge and anticipate the trajectories of recovering ecosystems 3

or even diagnose whether an ecosystem has recovered generate considerable unrest to 4

environmental managers and society. Diagnosing whether an ecosystem has recovered 5

may require a defined state, often summarised as ‘good’ (Mee et al. 2008), but this is of 6

little use if the status is poorly defined or has a large subjective element (Tett et al, in 7

press). Developing objective and precise definitions of recovery is not only a matter of 8

academic interest, given that the restoration of estuarine and coastal ecosystems now 9

carry considerable financial and legal repercussions. For example, developers may be 10

required to invest considerable funds to restore habitats or at least to produce 11

compensatory areas for damaged habitats; similarly states and developers may be in 12

breach of statutory instruments if they cannot demonstrate recovered ecosystems. 13

Hence, the scientific underpinning of efforts to restore estuarine and coastal 14

ecosystems must be rapidly improved and a new framework guiding these efforts that 15

acknowledges and faces the complexities involved need be established. 16

Here we offer a ‘conceptual model’ of the recovery of estuarine and coastal 17

ecosystems. We do so by first critically examining current definitions of recovery, and 18

identifying and testing the implicit paradigms and beliefs against well-documented cases 19

of responses of coastal and estuarine ecosystems to restoration efforts. This is based 20

on a review of the literature on recovery of estuarine and coastal ecosystems, which is 21

dominated by studies focused on benthic systems and fish. The term paradigm is used 22

here sensu lato, as a pattern or model (Oxford Dictionary), and not in the more 23

7

restricted form of a Khunian paradigm (1962). 1

2

Definitions of coastal ecosystem recovery 3

The concept of ecosystem recovery draws from health sciences to embed a 4

concept of damage to the health or integrity of an ecosystem (Tett et al. in press). For 5

instance, the journal “Aquatic Ecosystem Health and Management” focuses on the 6

health of freshwater, marine and estuarine ecosystems with the objective to “promote 7

an understanding of the functioning of ecosystems, the remediation, healing, recovery, 8

and restoration of stressed environments from the impact of anthropogenic stresses” 9

(www.aehms.org/journal.html#objectives). Unfortunately, both the concept of ecosystem 10

recovery and health involve much vagueness and circular reasoning, such as 11

ecosystem health defined as the absence of signs of ecosystem distress (Costanza 12

1992). In turn, healthy ecosystems have been described as those being ‘stable and 13

sustainable, maintaining its organization and autonomy over time and its resilience to 14

stress’ (Rapport et al. 1998; Tett et al, in press). Implicitly, ecosystem recovery implies 15

returning a distressed ecosystem to a healthy condition. Unfortunately, these definitions 16

are not easy to operationalize, which underlines difficulties to ascertain whether an 17

ecosystem has recovered from stress. 18

A recent review (Lotze et al. 2011) acknowledged the diversity of definitions of 19

coastal ecosystems and suggested that the definition is better described by the different 20

metrics used to assess recovery. Indeed, many explicit or implicit definitions for the 21

recovery of coastal ecosystems have been proposed (Table 1). Examination of these 22

definitions shows that they focus on various combinations of a restricted set of metrics 23

8

and targets. Metrics used to define recovery focus on marine ecosystem structure (e.g. 1

species abundance, 36%), function (e.g. growth, 28%), or services (e.g. nutrient cycling, 2

8%), while a significant number of definitions are not prescriptive as to the metric to be 3

used to diagnose recovery (28%). Recovery is defined as the achievement of a 4

particular target in those metrics. These targets can involve a baseline, which can refer 5

to pre-disturbance levels or include an allowance for tolerable deviations due to human 6

activities; a trend, such as an increase or improvement in the metric, or a particular 7

response to disturbance, such as resistance (the ability to withstand stressors) or 8

resilience (the ability to return to the previous stable state following disturbance). Most 9

definitions focus on targets based on baselines (54%), whether pre-disturbance or 10

allowing for some human interference, and many also focus on resilience (25%). The 11

emphasis on resilience rests on the belief that this property, regarded as the ability to 12

absorb stress perturbations, is a trait characteristic of healthy ecosystems (Elliott et al. 13

2007). However, some definitions remain vague as to the target of restoration efforts 14

(e.g. Kingston 2002). 15

Legislative frameworks, such as the WFD or CWA use metrics and targets of 16

environmental/ecological status to manage pressures on aquatic ecosystems - indeed, 17

it is axiomatic that ‘if you cannot measure it then you cannot manage it’. The WFD 18

equates healthy ecosystems with those showing “good ecological status”, and have 19

formulated a number of metrics for “good ecological status” around Europe, most of 20

them based on ecosystem structure (Hering et al. 2010), together with some tolerable 21

deviations. Whenever coastal ecosystems fall below good status (i.e. is assessed as 22

9

having moderate, poor or bad status), managers are obliged to take action to re-1

establish a “good status” of the ecosystem. 2

Large, multi-billion dollar coastal restoration programs are ongoing in the Gulf of 3

Mexico to restore ecosystems impacted by the oil spill associated with the Macondo 4

well blow out. These efforts follow the Natural Resources Damage Assessment (NRDA) 5

process under two laws in the U.S., the Comprehensive Environmental Response, 6

Compensation and Liability Act (CERCLA) and the Oil Pollution Act. The NRDA process 7

involves a primary restoration action to return injured resources to baseline conditions 8

and a compensatory restoration action to compensate for the interim loss of services 9

pending return to baseline conditions (cf. 10

http://www.epa.gov/superfund/programs/nrd/nrda2.htm). 11

12

Paradigms of coastal and estuarine ecosystem recovery 13

Most importantly, the literature on the recovery of coastal and estuarine 14

ecosystems has expanded rapidly, at 15.4 % year-1, since 1980 (Fig. 1), accumulating 15

evidence of a number of paradigms that represent constructs as to the trajectories or 16

drivers of ecosystem recovery (Table 2) (see also Elliott and Whitfield 2011). These 17

paradigms refer to the magnitude, type and frequency/timing of the pressures 18

supported, the role of ecosystem structure and connectivity in affecting the outcome of 19

recovery efforts, and the trajectories of recovery towards baselines. 20

21

Paradigm 1. Recovery of marine ecosystems is idiosyncratic 22

10

Ecosystem structure is believed to affect the recovery of marine ecosystems. For 1

instance, biotic factors and interactions are believed to affect recovery trajectories, 2

positively or negatively, rendering these highly idiosyncratic (Table 2, Perkol-Finkel and 3

Airoldi 2000, Rosenberg et al. 2002). Moreover, biotic interactions are dependent or 4

superimposed on and ultimately influence physico-chemical factors and interactions, 5

thereby further enhancing idiosyncrasy (Gray and Elliott 2009). Recovery time-scales 6

are expected to be dependent on the specific community affected and the magnitude of 7

the impacts, such that changes in habitats, for instance, are expected to delay recovery 8

(Table 2). Evidence of idiosyncratic recovery has been derived, for instance, from 9

observations of divergent trajectories and outcomes of recovering macrophyte beds 10

within different areas of an estuary following nutrient reduction plans (Orth et al. 2006). 11

This paradigm implies that recovery is highly variable and essentially unpredictable. 12

Species traits may be able to provide clues to recovery processes. For instance, 13

a long-held tenet is that recovery involves a succession from r-strategist to k-strategist 14

species (e.g. Dolbeth et al. 2007). This observation compares to arguments that 15

ecosystems dominated by long-lived, large, k-strategists species often require longer 16

time scales to recover than those dominated by short-lived, small, r-strategist species 17

(e.g. Kingston 2002, Jones and Schmitz 2009, Lotze et al. 2011). Hence, ecosystems, 18

such as estuaries, which have naturally large populations of stress-tolerant strategists, 19

may recover relatively fast (Elliott and Whitfield 2011). Recovery also often follows a 20

pathway by which environmental conditions recover first, followed by primary producers 21

and lastly consumers (Borja et al. 2010). However, this pattern is not always observed, 22

11

and environmental variables can recover in parallel to communities (Jones and Schmitz 1

2009). 2

3

Paradigm 2. Ecosystem function is easier to recover than ecosystem structure 4

Whereas indeed recovery of marine ecosystems can be often idiosyncratic when 5

focusing on ecosystem structure, there is evidence that ecosystem function recovers 6

relatively rapidly, with the consequences that recovery efforts sometimes lead to 7

different species composition in the communities, but with similar functional traits to 8

those existing prior to disturbance (Norkko and Bonsdorff 1996). Indeed, that ecosystem 9

function seems to be more stable and robust, i.e. shows more homeostasis (Odum 10

1985), than ecosystem structure has long been argued to characterise the response of 11

ecosystems to stress (Odum 1985). However, there are dissenting views, in that 12

ecosystem function is sometimes slower to recover than structure (Ruíz-Jaén and Aide 13

2005). 14

15

Paradigm 3. Degradation is fully reversible 16

Some authors, as well as many management and legislative frameworks, such 17

as the WFD and the NRDA process, implicitly or explicitly assume degradation to be a 18

fully reversible process, with recovery reaching pre-disturbance or baseline status (e.g. 19

Dolbeth et al. 2007, Jones and Schmitz 2009). There is, however, considerable debate 20

and disagreement on this paradigm as degradation can be, in some cases, irreversible 21

(Lotze et al. 2011). The reversibility of degradation processes may involve an element 22

of time scales, for it can be argued that some ecosystems will eventually return to the 23

12

original status, but so slowly that degradation is considered irreversible in management 1

time scales. For instance, slow growing seagrass, Posidonia oceanica meadows have 2

been shown to display little recovery from trawling after 100 years (González-Correa et 3

al. 2005), and models indicate that recovery of these meadows require many centuries 4

(Duarte 1995). Possibly the only truly irreversible degradations are those involving 5

species extinction, such as the extinction of the Steller’s sea cow following intense 6

hunting in the 1800s (Turvey and Risley, 2006). Moreover, shifting baselines due to 7

large-scale environmental changes, such as climate change or increased UVB 8

radiation, during the degradation-recovery process has been argued to lead to 9

deviations from the pre-disturbance ecosystem status following recovery of eutrophied 10

coastal ecosystems (Duarte et al. 2009; Carstensen et al. 2011). Villnäs et al. (2011) 11

reported that shifting baselines in community structure affected the definition of 12

reference conditions in the recovery of benthic systems impacted by aquaculture. 13

Recovery often involves the transition of coastal ecosystems across alternative 14

stable states. However, the number of alternative stable states is not necessarily just 15

two, a degraded and a healthy state, and recovery efforts have sometimes found that 16

the ecosystems recover to a different alternative stable state than that present prior to 17

disturbance (Munkes 2005). This is compounded further as coastal and estuarine 18

ecosystems are arguably more dominated by gradients, both of biological and physico-19

chemical elements, and multiple ecotones, with each part of that continuum being stable 20

under differing time scales. 21

22

Paradigm 4. Degradation and recovery follow similar, but opposite, trajectories 23

13

Degradation and recovery trajectories are similar, but opposite. This is often 1

assumed in regulatory frameworks, such as the WFD (Hering et al. 2010). However, 2

most evidence available contradicts this paradigm. Degradation and recovery 3

trajectories generally differ from degradation ones due to shifting baselines and 4

hysteresis (Duarte et al. 2009), and the reconfiguration of ecosystem buffers (Lardicci et 5

al. 2001, Elliott et al. 2007, Taylor et al. 2011, Villnäs 2011, Krause-Jensen et al. 2012). 6

The consequence is that thresholds separating alternative states often differ between 7

ecosystem degradation and recovery, with the consequence that degradation and 8

recovery trajectories follow different paths resulting in non-linear relations between 9

ecosystems status and pressure (Elliott et al., 2007, Duarte et al. 2009, Borja et al. 10

2010, Fig. 2). Time lags in ecosystem responses to the removal of pressures 11

responsible for degradation are often reported, resulting in hysteresis (Perkol-Finkel and 12

Airoldi 2010). For instance, nutrient reduction plans often fail to return coastal 13

ecosystems to the pre-disturbance state due to hysteresis and shifting baselines 14

(Duarte et al. 2009), and recovery from hypoxia often shows hysteresis and long-time 15

lags (Steckbauer et al. 2011), which render the assessment of recovery difficult (Duarte 16

et al. 2009). 17

18

Paradigm 5. Recovery depends on the characteristic of the pressures 19

Recovery is believed to be dependent on the characteristics of the pressures 20

conducive to degradation, particularly their type, magnitude, frequency and timing 21

relative to key ecosystem events and stages (Jones and Schmitz 2009, Taylor et al. 22

2011, Villnäs et al. 2011, Lotze et al. 2011). Recovery times have been argued to be 23

14

directly related, for any one ecosystem type, to the severity of the disturbance (Shaffner 1

2010), and to be slower when the disturbance is anthropogenic than for natural 2

disturbance (Jones and Schmitz 2009). Recovery then depends on the ability of the 3

stressor-receiving environment to absorb and assimilate the stressor, for example 4

recovery from a degrading waste (e.g. sewage, oil) is likely to be faster than from a non-5

degrading one such as metal pollution; the latter requires sequestration/burial to remove 6

the stressor. Recovery will also proceed faster if the pressure is reduced before the 7

main annual recruitment period than after this event (Borja et al. 2010). 8

9

Paradigm 6. Connectivity accelerates recovery 10

Recovery is believed to be dependent on connectivity between the degraded 11

ecosystem and healthy adjacent ecosystems. For instance, the availability and import of 12

propagules affect the recovery of marine ecosystems (Pratt 1994). Connectivity thus 13

affects the structural trajectories of recovering ecosystems by influencing colonization 14

patterns and pioneer assemblages (Norkko and Bonsdorff 1996). Connectivity also 15

affects functional aspects of recovery through influence on the resistance and resilience 16

of ecosystems (Elliott et al. 2007, Gaines et al. 2010), where resistance is defined as 17

the ability to withstand a stressor before adverse changes occur and resilience is 18

defined as the ability to return to the previous stable state following disturbance. There 19

is ample consensus on this paradigm, which is supported by solid evidence, as well as 20

theory (Gaines et al. 2010, Elliott and Whitfield 2011). 21

In summary, paradigms 5 (the dependence of recovery on the characteristics of 22

the pressures) and 6 (the importance of connectivity for recovery) are strongly 23

15

supported by observations (Table 2). Two paradigms, paradigms 3 (recovery can be a 1

full reversal of degradation) and 4 (degradation and recovery follow similar but opposite 2

trajectories) should be rejected, with some evidence still supporting paradigm 3 though 3

partial recovery prevails, but no evidence supporting paradigm 4 (Table 2). Paradigm 3 4

could thus be modified to indicate that whilst some recovery of an ecosystem state is 5

always likely, it should not be assumed that the recovered state equals the pre-6

disturbance situation. Lastly, paradigms 1 and 2 have both supporting and opposing 7

evidence. Whereas indeed species traits and interactions render recovery rather 8

idiosyncratic, as postulated in paradigm 1, there are indeed patterns that can be used to 9

formulate useful predictions (Table 2). Paradigm 2, that ecosystems function recovers 10

prior to structure, has both comparable supporting and opposing evidence (Table 2). 11

12

Recovery vs. restoration of coastal and estuarine ecosystems 13

Ecosystem recovery involves the recovery of structure and function following the 14

removal of the stress, whether natural or anthropogenic. This may be a passive process 15

(merely with the stressor naturally removed such as self-cleaning after an oil spill) or an 16

active removal of the stress. In contrast, restoration always involves the deliberate 17

(active) attempt to catalyse recovery. Whereas the removal of the stress is a critical 18

requisite for restoration, ecosystem restoration typically extends beyond stress 19

alleviation to include additional interventions conducive to accelerated recovery. 20

The ecosystem response to pressures often involves shifts between alternative 21

states when a threshold of pressure has been exceeded (Fig. 2). Despite this, most 22

marine ecosystems receive multiple pressures, which may act in a synergistic manner 23

16

to stress the ecosystem, such that action on one pressure alone (e.g. nutrient reduction) 1

may not be conducive to recovery when other pressures (e.g. overfishing, dredging, 2

climate change, or pollution) have not been removed (Stelzenmüller et al. 2010). An 3

adequate understanding of the role of multiple pressures on ecosystem degradation is, 4

therefore, necessary to identify the conditions conducive to recovery. 5

Restoration efforts involve supplementing the natural process for the recovery 6

process to be accelerated and/or achieve a status closer to the baseline, for example 7

the artificial re-aeration of the Thames Estuary, London, accelerated the recovery of the 8

estuarine fish community towards the historical baseline (McLusky and Elliott, 2004), 9

and the regulation of freshwater inflow to the San Francisco Delta to catalyse the 10

recovery of vulnerable fish species of concern (Kimmerer 2002). Extended experience 11

at ecosystem restoration has also provided some clues to successful approaches, 12

which represent the foundations of a new discipline, coastal eco-engineering, focused 13

on solutions to achieve recovery (Mitsch 2012, Simenstad et al. 2006). In many 14

examples of estuarine and coastal degradation, restoration has not been 15

exerted/enforced?. For instance, eutrophication or hypoxia are often managed through 16

the simple removal of the stress (nutrient and organic inputs), without any further 17

actions to catalyse recovery. However, some actions are possible, such as 18

manipulations of the biotic structure or the physical or chemical conditions. 19

Biotic manipulations involve the recovery of target populations, through the 20

transplant or reintroduction of seagrasses (e.g. van Katwijk et al. 2009, Orth and 21

McGlathery 2012), salt-marsh plants (Mazik et al. 2010), mangroves (Greening et al. 22

2011) or algae (Perkol-Finkel and Arioldi 2010). The introduction of target populations 23

17

should consider the genetic structure of the donor populations, as the success of these 1

introductions may depend on the vigour and genetic diversity of the introduced 2

specimens (van Katwijk et al. 2009, Frankham 2010). Successful biotic manipulations 3

may also involve the introduction of additional engineer species able to improve 4

environmental conditions, such as the establishment of oyster reefs or mussel 5

populations to filter out particles and increase water transparency, and the use of 6

wetlands and macroalgal cultures as biofilters of nutrients (Greening et al. 2011). 7

However, the success of manipulations involving transplants or introductions is critically 8

dependent on the selection of suitable habitats (van Katwijk et al. 2009). Removal of 9

invasive species, such as Caulerpa species in the Mediterranean, has also proven 10

efficient in restoring degraded estuarine and coastal ecosystems (Piazzi and Ceccherelli 11

2006). 12

Moreover, establishment of marine protected areas or effective fisheries 13

regulations have also been successful in recovering fish stocks from overfishing 14

(Hutchings and Rangeley 2011), but can also catalyse the recovery of ecosystems by 15

recovering food web integrity and associated buffers, increasing connectivity and 16

removing physical impacts of some fishing practices, such as trawling (Gaines et al. 17

2010). The benefits of individual marine protected areas can be further enhanced by 18

building networks of protected areas which, if properly designed in terms of size, 19

spacing, location, and configuration, may also reduce or eliminate the tradeoff between 20

achieving conservation and fishery goals (Gaines et al. 2010). 21

Manipulations of the physical and chemical conditions of degraded coastal and 22

estuarine environments to catalyse recovery include the use of aeration devices to 23

18

increase oxygen concentration (e.g. McLusky and Elliott 2004, Conley 2012) and avoid 1

phosphate release from anoxic sediments (e.g. Conley et al. 2009), use of gates, dykes 2

or dredging to increase flushing and restore the salinity of the ecosystem (e.g. Petersen 3

et al. 2008), and the use of barriers (Greening et al. 2011) or sandbags or fibertex to 4

reduce wave action and sediment resuspension (Fischer 2011). Deployment of rocks or 5

other settling structures, such as seagrass mimics (e.g. Cardoso et al. 2007), has also 6

been used to facilitate the establishment of benthic communities (e.g. the EU Life 7

project ‘Blue Reef’ carried out in Denmark). A mimic of rock-pool habitats on natural 8

rocky shores has been experimented in seawalls, creating shaded vertical substratum 9

and pools that retained water during low tide and increased diversity of foliose algae 10

and sessile and mobile animals, especially higher on the shore (e.g. Chapman and 11

Underwood 2011). 12

The effectiveness of restoration efforts is rarely evaluated (Benayas et al. 2009). 13

A meta-analysis of restoration efforts concluded that restoration helped recover 14

biodiversity and ecosystem services by, on average 44% and 25% respectively, but 15

rarely achieved recovery back to the baseline (Benayas et al. 2009). Cost-benefit 16

analyses should be used to decide among the alternative restoration strategies to be 17

deployed in order to maximize the return on investment on restoration (Benayas et al. 18

2009), keeping in mind that the evaluation of benefits is often more cumbersome than 19

that of costs. 20

Through these series of actions, ecosystem restoration can achieve a number of 21

goals, such as accelerate recovery, reduce hysteresis and time lags, remove buffers 22

19

precluding recovery, and drive the recovery trajectory towards desired outcomes and 1

stable states. 2

3

Towards a conceptual model of the recovery of coastal and estuarine ecosystems 4

The elements identified in the preceding sections can be articulated in a 5

conceptual model of the recovery process guiding management and policy actions to 6

improve the status of degraded coastal and estuarine ecosystems. A general model of 7

the degradation and recovery of coastal and estuarine ecosystems acknowledges that 8

the trajectories of degradation and recovery are not parallel, but display hysteresis, and 9

that the threshold of pressures conducive to degradation or allowing recovery often 10

differ (Table 2, Fig. 3). The pressure causing the degradation often needs be reduced 11

much more to allow recovery than to cause degradation, implying that the threshold of 12

recovery is often set at a much lower level of the pressure than the threshold conducive 13

to degradation, as ecosystem buffers and feed-back effects, such as resuspension of 14

sediments devoid of vegetation, act to maintain the degraded state (e.g. Duarte et al. 15

2009, Steckbauer et al. 2011). A pre-requisite for recovery to be initiated is that the 16

pressures responsible for degradation be reduced below the threshold for recovery 17

(Figs. 2 and 3). Restoration can catalyze recovery and/or help the ecosystem achieve a 18

status closer to the pre-disturbance state. As restoration acts by removing or reducing 19

the negative buffers, it may also affect the location of the recovery threshold, thereby 20

lowering the demand for reduction of the pressures (Figs. 2 and 3). 21

One important caveat in this conceptual model is that the recovery of coastal and 22

estuarine ecosystems takes place in a context of global change, where drivers of 23

20

ecological processes are shifting over time (i.e. a moving baseline), including 1

atmospheric composition, climate change, and pollutant loads, among others (Duarte et 2

al. 2009). As a result, the baseline towards which ecosystems recover following 3

perturbations is constantly shifting, further amplifying hysteresis, and the time scale to 4

achieve recovery, and confounding the assessment of recovery, as the state to what 5

ecosystems recover is not necessarily that they displayed before perturbation occurred 6

(Duarte et al. 2009). Moreover, the drift of coastal ecosystems baselines with global 7

change may render recovery trajectories and targets less predictable and, as a 8

consequence, more idiosyncratic in the future, as past states cannot be used to 9

confidently predict recovery targets (Carstensen et al. 2011). 10

Overall, the review provided here highlights a need for more careful definition of 11

recovery targets as well as methods and metrics needed to assess the course of 12

recovery in specific ecosystems. The exploration of recovery paradigms established that 13

1) partial recovery prevails, 2) degradation and recovery typically follow different 14

pathways as buffers act to maintain the degraded state and, 3) recovery trajectories 15

depend on the nature of the pressure as well as the connectivity of ecosystems and can 16

differ among ecosystem components and among ecosystems. These paradigms are 17

contained in the conceptual model, which also illustrates how restoration efforts may 18

catalyze recovery (Figs. 2 and 3). The paradigms can also be used to guide restoration 19

efforts, as restoration efforts directed at increasing connectivity or directly initiating 20

populations (e.g. seagrass restoration projects) and at reducing thresholds for recovery 21

(e.g. biogeochemical manipulations to revert hypoxia) should be most effective in 22

catalyzing recovery. The conceptual model provided can be used as a basis to 23

21

formulate numerical models allowing testing various recovery and restoration scenarios 1

for specific ecosystems. 2

3

Acknowledgements 4

This paper is a result of the project WISER (Water bodies in Europe: Integrative 5

Systems to assess Ecological status and Recovery, www.wiser.eu) funded by the 6

European Union under the 7th Framework Programme, Theme 6 (Environment 7

including Climate Change) (contract No. 226273) and the Baltic Nest Institute 8

(www.balticnest.org). 9

10

References 11

12

Benayas JMR, Newton AC, Diaz A, Bullock JM. 2009. Enhancement of biodiversity and 13

ecosystem services by ecological restoration: A meta-analysis. Science 325: 1121-14

1124. DOI: 10.1126/science.1172460. 15

16

Borja Á, Dauer D, Elliott M, Simenstad C. 2010. Medium- and Long-term Recovery of 17

Estuarine and Coastal Ecosystems: Patterns, Rates and Restoration Effectiveness. 18

Estuaries and Coasts 33: 1249-1260. 19

20

Borja Á, Dauer DM, Grémare A. 2012. The importance of setting targets and reference 21

conditions in assessing marine ecosystem quality. Ecological Indicators 12: 1-7. 22

23

22

Bradshaw AD 2002. Introduction and philosophy. Pages 3-9 in Perrow MR, Davy AJ, 1

eds. Handbook of Ecological Restoration, Volume 1, Principles of Restoration. 2

Cambridge University Press, Cambridge. 3

4

Cardoso PG, Bankovic M, Raffaelli D, Pardal MA. 2007. Polychaete assemblages as 5

indicators of habitat recovery in a temperate estuary under eutrophication. Estuarine, 6

Coastal and Shelf Science 71: 301-308. 7

8

Carstensen J, Sánchez-Camacho M, Duarte CM, Krause-Jensen D, Marbà N. 2011. 9

Connecting the dots: Responses of coastal ecosystems to changing nutrient 10

concentrations. Environmental Science & Technology 45: 9122-9132. 11

12

Chapman MG, Underwood AJ. 2011. Evaluation of ecological engineering of 13

"armoured" shorelines to improve their value as habitat. Journal of Experimental Marine 14

Biology and Ecology 400: 302-313. 15

16

Conley DJ. 2012. Save the Baltic Sea. Nature 486: 463-464. 17

18

Conley DJ, Bonsdorff E, Carstensen J, Destouni G, Gustafsson BG, Hanson L-A, 19

Rabalais NN, Voss M, Zillen L. 2009 Tackling hypoxia in the Baltic Sea: Is large-scale 20

engineering a solution? Environmental Science and Technology 43: 3407-3411. 21

22

23

Costanza R. 1992. Toward an operational definition of ecosystem health. Pages 239–1

256 in Costanza R, Norton BG, Haskell BD, eds. Ecosystem Health: New Goals for 2

Environmental Management. Island Press. 3

4

Dolbeth M, Cardoso PG, Ferreira SM, Verdelhos T, Raffaelli D, Pardal MA. 2007. 5

Anthropogenic and natural disturbance effects on a macrobenthic estuarine community 6

over a 10-year period. Marine Pollution Bulletin 54: 576–585. 7

8

Duarte CM. 1995. Submerged aquatic vegetation in relation to different nutrient 9

regimes. Ophelia 41: 87–112. 10

11

Duarte CM, Conley DJ, Carstensen J, Sánchez-Camacho M. 2009. Return to 12

Neverland: Shifting baselines affect eutrophication restoration targets. Estuaries and 13

Coasts 32: 29-36. 14

15

Elliott M, Burdon D, Hemingway KL, Apitz SE. 2007. Estuarine, coastal and marine 16

ecosystem restoration: Confusing management and science - A revision of concepts. 17

Estuarine, Coastal and Shelf Science 74: 349-366. 18

19

Elliott M, Whitfield A. 2011. Challenging paradigms in estuarine ecology and 20

management. Estuarine, Coastal & Shelf Science 94: 306-314. 21

22

24

Fischer A. 2011. Stone age on the continental shelf: an eroding resource. Ch. 24, pages 1

298-310 in Benjamin J, Bonsall C, Pickard C, Fischer A. Submerged Prehistory. Oxbow 2

Books 2011. ISBN 978-1-84217-418-0. 3

4

Frankham R. 2010. Challenges and opportunities of genetic approaches to biological 5

conservation. Biological Conservation 143: 1919-1927. 6

7

Gaines SD, White C, Carr MH, Palumbi SR. 2010. Designing marine reserve networks 8

for both conservation and fisheries management. PNAS 107: 18286–18293. 9

10

González-Correa JM, Bayle JT, Sánchez-Lizaso TJL, Valle C, Sánchez-Jerez P, Ruiz 11

JM. 2005. Recovery of deep Posidonia oceanica meadows degraded by trawling. 12

Journal of Experimental Marine Biology and Ecology 320: 65–76. 13

14

Gray JS, Elliott M. 2009. Ecology of marine sediments: science to management. OUP, 15

Oxford, 260pp. 16

17

Greening HS, Cross LM, Sherwood ET. 2011. A multiscale approach to seagrass 18

recovery in Tampa Bay, Florida. Ecological Restoration 29: 1-2. 19

20

Hering D, Borja A, Carstensen J, Carvalho L, Elliott M, Feld C-K, Heiskanen A-S, 21

Johnson RK, Moe J, Pont D, Solheim AL, van de Bund W. 2010. The European Water 22

25

Framework Directive at the age of 10: A critical review of the achievements with 1

recommendations for the future. Science of the total environment 408: 4007-4019. 2

3

Hiddink JG, Jennings S, Kaiser KJ. 2006. Indicators of the ecological impact of 4

bottom-trawl disturbance on seabed communities. Ecosystems 9: 1190–1199. DOI: 5

10.1007/s10021-005-0164-9. 6

7

Higgs E. 2005. The two-culture problem: Ecological restoration and the integration of 8

knowledge. Restoration Ecology 13: 159–164. 9

10

Hutchings JA, Rangeley RW. 2011. Correlates of recovery for Canadian Atlantic cod 11

(Gadus morhua). Canadian Journal of Zoology 89: 386–400. 12

13

Jackson JBC, Kirby MX, Berger WH, Bjorndal KA, Botsford LW, Bourque BJ, Bradbury 14

RH, Cooke R, Erlandson J, Estes JE, Hughes TP, Kidwell S, Lange CB, Lenihan HS, 15

Pandolfi JM, Peterson CH, Steneck RS, Tegner MJ, Warner RR. 2001. Historical 16

overfishing and the recent collapse of coastal ecosystems. Science 293: 629–638. 17

Jones HP, Schmitz OJ. 2009. Rapid recovery of damaged ecosystems. PLoS ONE 4(5): 18

e5653. doi:5610.1371/journal.pone.0005653. 19

20

Kaiser MJ, Edwards DB, Armstrong PJ, Radford K, Lough NE, Flatt RP, Jones HD. 21

1988. Changes in megafaunal benthic communities in different habitats after trawling 22

disturbance. ICES Journal of Marine Science 55: 353–361. 23

26

1

Khun TS. 1962. The Structure of Scientific Revolutions. University of Chicago Press, 2

264 pp. 3

4

Kimmerer WJ. 2002. Physical, biological, and management responses to variable 5

freshwater flow into the San Francisco Estuary. Estuaries 25: 1275-1290. 6

7

Kingston PF. 2002. Long-term environmental impact of oil spills. Spill Science and 8

Technology Bulletin 7: 53–61. 9

10

Kraufvelin P, Sinisalo B, Leppäkoski E, Mattila J, Bonsdorff E. 2001. Changes in 11

zoobenthic community structure after pollution abatement from fish farms in the 12

Archipelago Sea (N. Baltic Sea). Marine Environmental Research 51: 229-245. 13

14

Krause-Jensen D, Markager S, Dalsgaard T. 2012. Benthic and pelagic primary 15

production in different nutrient regimes. Estuaries and Coasts 35: 527-545. 16

17

Lardicci C, Como S, Corti S, Rossi F. 2001. Changes and recovery of macrozoobenthic 18

communities after restoration measures of the Orbetello Lagoon (Tyrrhenian coast, 19

Italy). Aquatic Conservation: Marine and Freshwater Ecosystems 11: 281–287. 20

21

Lotze HK, Coll M, Magera AM, Ward-Paige C, Airoldi L. 2011. Recovery of marine 22

animal populations and ecosystems. Trends in Ecology and Evolution 26:595-605 23

27

1

Marbà N, Krause-Jensen D, Alcoverro T, Birk S, Pedersen A, Neto JM, Orfanidis S, 2

Garmendia JM, Muxika I, Borja A, Dencheva K., Duarte CM. Diversity of European 3

seagrass indicators - Patterns within and across regions. Hydrobiologia,704 (1): 265-4

278. DOI: 10.1007/s10750-012-1403-7. 5

6

Mazik K, Musk W, Dawes O, Solyanko K, Brown S, Mander L, Elliott M. 2010. Managed 7

realignment as compensation for the loss of intertidal mudflat: A short term solution to a 8

long term problem? Estuarine, Coastal and Shelf Science 90: 11-20. 9

10

McLusky DS, Elliott M. 2004. The Estuarine Ecosystem; ecology, threats and 11

management, 3rd Edn. OUP, Oxford. Pp216. 12

13

Mee LD, Jefferson RL, Laffoley Dd’A, Elliott M. 2008. How good is good? Human values 14

and Europe’s proposed Marine Strategy Directive. Marine Pollution Bulletin, 56: 187-15

204. 16

17

Middleton BA. 1999. Wetland restoration, Flood Pulsing and Disturbance Dynamics. 18

John Wiley and Sons Inc., New York, NY, 388 pp. 19

20

Mitsch WJ. 2012. What is ecological engineering? Ecological Engineering 45: 5-12. 21

22

28

Moore DC, Rodger GK. 1991. Recovery of a sewage sludge dumping ground. 11. 1

Macrobenthic community. Marine Ecology Progress Series 75: 301-308. 2

3

Munkes B. 2005. Eutrophication, phase shift, the delay and the potential return in the 4

Greifswalder Bodden, Baltic Sea. Aquatic. Sciences 67: 372–381. 5

6

National Research Council (NRC). 1992. Restoration of Aquatic Ecosystems—Science, 7

Technology and Public Policy. National Academy Press, Washington, DC, 576 pp. 8

9

Norkko A, Bonsdorff E 1996. Population responses of coastal zoobenthos to stress 10

induced by drifting algal mats. Marine Ecology Progress Series 140: 141-151. 11

12

Odum EP. 1985. Trends Expected in Stressed Ecosystems. Bioscience 35: 419-422. 13

14

Orth RJ, Carruthers TJB, Dennison WC, Duarte CM, Fourqurean JW, Heck Jr KL, 15

Hughes AR, Kendrick GA, Kenworthy WJ, Olyarnik S, Short FT, Waycott M, Williams 16

SL. 2006. A global crisis for seagrass ecosystems. Bioscience 56: 987–996. 17

18

Orth RJ, Williams MR, Marion SR, Wilcox DJ, Carruthers TJB, Moore KA, Kemp WM, 19

Dennison WC, Rybicki N, Bergstrom P, Batiuk RA. 2010. Long term trends in 20

submersed aquatic vegetation (SAV) in Chesapeake Bay, USA, related to water 21

quality. Estuaries and Coasts 33: 1144−1163. 22

23

29

Orth RJ, McGlathery KJ. 2012. Eelgrass recovery in the coastal bays of the Virginia 1

Coast Reserve, USA. Marine Ecology Progress Series 448: 173-176. 2

3

Park SR, Kim J-H, Kang C-K, An S, Chung IK, Kim JH, Lee K-S. 2009. Current status 4

and ecological roles of Zostera marina after recovery from large-scale reclamation in the 5

Nakdong River estuary, Korea. Estuarine, Coastal and Shelf Science 81: 38–48. 6

7

Perkol-Finkel S, Airoldi L. 2010. Loss and recovery potential of marine habitats: An 8

experimental study of factors maintaining resilience in subtidal algal forests at the 9

Adriatic Sea. PLoS ONE 5: e10791. doi:10.1371/journal.pone.0010791. 10

11

Petersen JK, Hansen JW, Laursen MB, Clausen P, Carstensen J, Conley D. 2008. 12

Regime shift in a coastal marine ecosystem. Ecological Applications 18: 497–510. 13

14

Piazzi L, Ceccherelli G. 2006. Persistence of biological invasion effects: Recovery of 15

macroalgal assemblages after removal of Caulerpa racemosa var. cylindracea. 16

Estuarine, Coastal and Shelf Science 68: 455-461. 17

18

Pratt, J.R., 1994. Artificial habitats and ecosystem restoration: managing for the future. 19

Bulletin of Marine Science 55: 268-275. 20

21

Rapport DJ, Costanza R, McMichael AJ. 1998. Assessing ecosystem health. Trends in 22

Ecology and Evolution 13: 397-402. DOI: 10.1016/S0169-5347(98)01449-9. 23

30

1

Rosenberg R, Agrenius S, Hellman B, Nilsson HC, Norling K. 2002. Recovery of marine 2

benthic habitats and fauna in a Swedish fjord following improved oxygen conditions. 3

Marine Ecology Progress Series 234: 43–53. 4

5

Ruíz-Jaén MC, Aide TM. 2005. Restoration success: How is it being measured? 6

Restoration Ecology 13: 569–577. 7

8

Schaffner LC. 2010 Patterns and rates of recovery of macrobenthic communities in a 9

polyhaline temperate estuary following sediment disturbance: Effects of disturbance 10

severity and potential importance of non-local processes. Estuaries and Coasts 11

33:1300–1313. DOI 10.1007/s12237-010-9301-6. 12

13

Simenstad C, Reed D, Ford M. 2006. When is restoration not? Incorporating landscape-14

scale processes to restore self-sustaining ecosystems in coastal wetland restoration. 15

Ecological Engineering 26: 27-39. 16

17

Temperton VM, Hobbs RJ, Nuttle T, Halle S. 2004. Assembly rules and restoration 18

ecology – bridging the gap between theory and practice. Society for ecological 19

restoration international. 20

21

31

Steckbauer A, Duarte CM, Carstensen J, Vaquer-Sunyer R, Conley DJ 2011. 1

Ecosystem impacts of hypoxia: thresholds of hypoxia and pathways to recovery. 2

Environmental Research Letters 6: 025003. doi:10.1088/1748-9326/6/2/025003 3

4

Stelzenmüller V, Lee J, South A, Rogers SI. 2010. Quantifying cumulative impacts of 5

human pressures on the marine environment: a geospatial modelling framework. Marine 6

Ecology Progress Series 398: 19-32. 7

8

Taylor DI, Oviatt CA, Borkman DG. 2011. Non-linear Responses of a Coastal Aquatic 9

Ecosystem to Large Decreases in Nutrient and Organic Loadings. Estuaries and Coasts 10

34: 745–757. DOI 10.1007/s12237-010-9312-3 11

12

Thom RM, Diefenderfer HL, Vavrinec J, Borde A. 2012. Restoring resiliency: Case 13

studies from Pacific northwest estuarine eelgrass (Zostera marina L.) Ecosystems. 14

Estuaries and Coasts 35:78–9. DOI 10.1007/s12237-011-9430-6 15

16

Turvey ST, Risley CL. 2006. Modelling the extinction of Steller's sea cow. Biology 17

Letters 2: 94–97. 18

19

van Katwijk MM, Bos AR, de Jonge VN, Hansse LSAM, Hermus DCR, de Jong DJ. 20

2009. Guidelines for seagrass restoration: importance of habitat selection and donor 21

population, spreading of risks, and ecosystem engineering effects. Marine Pollution 22

Bulletin 58: 179−188. 23

32

Verdonschot PFM, Spears BM, Feld CK, Brucet S, Keizer-Vlek H, Borja A, Elliott M, 1

Kernan M, Johnson RK. 2013. A comparative review of recovery processes in rivers, 2

lakes, estuarine and coastal waters. Hydrobiologia 704: 453-474. 3

4

Villnäs A, Perus J, Bonsdorff E. 2011.Structural and functional shifts in zoobenthos 5

induced by organic enrichment — Implications for community recovery potential. 6

Journal of Sea Research 65: 8–18. 7

8

Weinstein MP. 2007. Ecological restoration and estuarine management: placing people 9

in the coastal landscape. Journal of Applied Ecology 45: 296-304. doi: 10.1111/j.1365-10

2664.2007.01355.x. 11

12

33

1

Table 1. Examples of definitions of recovery (in some cases referred to as restoration), the type of metric use to assess recovery (Ecosystem structure, Ecosystem function, Ecosystem services, undefined standards), the recovery target used in the definition (baseline referring to pre-disturbance levels, baseline adjusted for human activities, baseline referring to resilience/resistance/sustainability/integrity, baseline undefined) and the reference citing the definition.

Definition Metric Target Reference

The return of key variables to the pre-perturbation state Undefined standards

Baseline at/near predisturbance level

Jones and Schmitz 2009

A return to pre-disturbance conditions Undefined standards

Baseline at/near predisturbance level

Kraufvelin et al. 2001, Lardicci et al. 2001, Kaiser et al. 1988

Realistic baselines (for estuarine restoration) must be established at a post-industrial starting point

Baseline adjusted for human activities Weinstein 2007

The desired outcome of any ecosystem approach is not only to restore and rehabilitate the health, productivity and biodiversity of ecosystems but also the overall quality of human life through a resource management approach that is fully integrated with social and economic goals.

Ecosystem structure Ecosystem function Ecosystem services

Baseline adjusted for human activities Weinstein 2007

An obvious improvement as shown by community and environment variables Undefined standards Increase/improvement

Moore and Rodger 1991

Restoration was assessed relative to targets for seagrass extent based on pre-disturbance levels Ecosystem structure

Baseline at/near predisturbance level Orth et al. 2010

Recovered seagrass meadows were persistent and able to adjust to changing conditions; they were healthy [as shown by shoot characteristics and growth parameters]

Ecosystem structure Ecosystem function

Resistance Resilience Park et al. 2009

Recovery was related to a significant increase in species richness and cover of macroalgae Ecosystem structure Increase/improvement

Piazzi and Ceccerelli 2006

34

Recovery was defined as benthos attaining a climax community Undefined standards Increase/improvement Rosenberg et al. 2002

Ecological restoration is the process of assisting the recovery of an ecosystem that has been degraded, damaged, or destroyed

Temperaton et al.(2004)

These attributes [showing recovery] include the capacity of the physical environment to sustain reproducing populations, the integration with the landscape, and self sustainability. Ecosystem function Resilience

Ruiz-Jaen and Aide 2005

A close approximation of its condition prior to disturbance” which requires “reestablishment of predisturbance aquatic functions and related physical, chemical and biological characteristics.

Ecosystem structure Ecosystem function

Baseline at/near predisturbance level

NRC 1992 (see also Simenstad et al. 2006)

Restoration as seeking to establish ‘a site that is self-regulating and integrated within its landscape, rather than to reestablish an aboriginal condition that can be impossible to define and/or restore within the context of current land use or global change Resilience

Middleton 1999 (see also Simenstad et al. 2006)

The benthic community in an area was assumed to be in a state of near recovery from trawling when the biomass (B) or production (P) reached 90% of predicted biomass that would occur in the absence of trawling (B0.9 or P0.9). This 90% value was chosen arbitrarily as a value that was close to the pristine state

Ecosystem structure Ecosystem function

Baseline at/near predisturbance level Hiddinck et al. 2006

35

Restoration targets must be defined based on ecological and cultural knowledge= ecocultural restoration. (“..our values toward those ecosystems will shift over time as they have been doing throughout history”)

Baseline adjusted for human activities Higgs 2005

Recovery (of fish populations) implies reaching a target level of abundance Ecosystem structure Baseline unspecified

Hutchings and Rangeley 2011

Recovery of an ecosystem is characterized by the re-establishment of a biological community in which the plants and animals characteristic of that community are present and functioning normally.'

Ecosystem structure Ecosystem function Kingston 2002

The restoration process or trajectory reestablishes a dynamically stable ecosystem that is fully developed structurally and functionally and is resistant and resilient to disturbances

Ecosystem structure Ecosystem function

Resistance Resilience Thom et al. 2010

In practice, recovery is often measured as some form of increase, improvement or shift in certain response variables, ideally reversing to pre-disturbance conditions Undefined standards

Baseline at/near predisturbance level Lotze 2011

The process of re-establishing, following degradation by human activities, a sustainable habitat or ecosystem with a natural (healthy) structure and functioning

Ecosystem structure Ecosystem function Sustainability Elliot et al. 2007

The process of assisting the recovery and management of ecological integrity. Ecological integrity includes a critical range of variability in biodiversity, ecological processes and structures, regional and historical context, and sustainable cultural practices.

Ecosystem structure Ecosystem function Integrity Bradshaw 2002

36

1

2

3

37

1

Table 2. Overview of paradigms on the trajectories or drivers of ecosystem recovery

expressed explicitly or implicitly in the literature. The paradigms refer to the magnitude,

type and frequency/ timing of the pressures supported, the role of ecosystem structure

and connectivity in affecting the outcome of recovery efforts, and the trajectories of

recovery towards baselines. For each paradigm, supporting and opposing evidence is

summarized and where there is a clear overweight of supporting or opposing evidence,

this is indicated in bold.

Paradigms Evidence in support/opposition to paradigm

1. Recovery of marine

ecosystems is

idiosyncratic

Supporting Species traits and interactions render recovery

trajectories and outcomes unpredictable

Opposing Predictable patterns have been reported with

small, fast-growing r-strategists species

recovering fast and large, slow-growing k-

strategists being slow to recover

2. Ecosystem function

is easier to recover than

ecosystem structure

Supporting Although ecosystem structure may differ from

the baseline after recovery, functions are often

similar

Opposing Ecosystem function has been observed to

recover more slowly than ecosystem structure

in some cases

38

3. Degradation is fully

reversible

Supporting Recovered ecosystems have been shown to

reach pre-disturbance status in some cases

Opposing A review of the extent of recovery of estuarine

and coastal ecosystems showed that partial

recovery prevails

4. Degradation and

recovery follow similar

but opposite trajectories

Supporting Parallel degradation and recovery trajectories

have not yet been observed in coastal and

estuarine ecosystems

Opposing Recovery trajectories always show hysteresis

due to the presence of buffers that slow down

recovery and differential thresholds between the

degradation and recovery phases

5. Recovery depends

on the characteristics of

the pressure

Supporting Overwhelming evidence shows that recovery

depends on the type, magnitude, frequency and

timing of the pressures

Opposing No studies provide evidence of independence of

recovery of the characteristics of the pressure

6. Connectivity

accelerates recovery

Supporting All available evidence along with theory point at

connectivity being essential for the recovery

through the supply of propagules and

colonizers.

Opposing No evidence suggests that connectivity does

not play a role in recovery.

1

39

Figure Headings 1

Fig. 1. Number of papers on estuarine and coastal recovery published annually. Data 2

obtained from the Web of Science (accessed June 3, 2013) using the search string 3

(Estuar* OR Coast*) AND (recovery OR restoration). 4

Fig. 2. Left to right: Schematized trajectories of ecosystem response to increasing 5

pressure (red) showing degradation from a pre-disturbance state (A) to a degraded 6

state (B) upon exceeding a pressure threshold. Right to left: Trajectories of ecosystem 7

response to decreasing pressure (green) operating through an initial ‘lag/hysteresis-8

phase’ where buffers maintain the degraded state followed by a recovery phase which, 9

over time, leads to the recovered state (C) as pressures are further reduced. Grey lines 10

illustrate the recovery phase for a situation where restoration efforts are applied to 11

facilitate recovery (+ restoration) as opposed to a situation without such initiatives (No 12

restoration). The identified paradigms (Table 2) refer to the recovery trajectories. 13

14

Fig. 3. Schematic illustration of an increase in pressure shifting the ecosystem state 15

from a pre-disturbance state (A) to a degraded state (B) (Degradation phase, red), and 16

a subsequent release of pressure reflected in an initial ‘lag/hysteresis-phase’ where 17

buffers maintain the degraded state followed by a ‘recovery phase’ (green) which, over 18

time, leads to the recovered state (C). Grey lines illustrate the recovery phase for a 19

situation where restoration efforts are applied to facilitate recovery (+ restoration) as 20

opposed to a situation without such initiatives (No restoration). The identified paradigms 21

(Table 2) refer to the recovery phase. 22

23

40

Fig. 1. 1

2

3

41

Eco

syst

emst

ate

Pressure

A

B

C

Degradationtrajectory

Recovery trajectories

Threshold for recoveryThreshold for degradation

+ Restoration

No restoration

1

2

Fig. 2 3

4

42

Eco

syst

emst

ate

Time

A

B

C

Degradation Timelag, hysteresis

T1: Release of pressure

Recovery

T0: Increase of pressure

+ Restoration

No restoration

1

Fig. 3 2