Do you want to breach an embankment? Synthesis of the literature and practical considerations for breaching of tidally influenced causeways and dikes

Gerwing, Travis G.; Davies, Morgan M.; Clements, Jeff C.; Flores, Anne-Marie; Thomson, Hanna M.; Nelson, Kyle R.; Kushneryk, Katrina; Brouard-John, Eleanor K.; Harvey, Bronwyn; Plate, Elmar

doi:10.1016/j.ecss.2020.107024

Cited by 17 publications

(13 citation statements)

References 135 publications

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“…It is often assumed, if not implicitly stated, that increasing similarity is desirable, especially between reference and restored habitats. However, similarity targets are seldom quantified or discussed (Roman et al 2002; Moir et al 2005; Hobbs et al 2007; Gerwing et al 2017 b ; Campbell et al 2019; Gerwing et al 2019; Gerwing et al 2020 a ; Gerwing et al 2020 b ), an issue that could have substantial impacts upon restoration success or failure for two important reasons. First, all biological communities vary through space and time, and no two communities will ever be identical in species composition or density.…”

Section: Achievable Community Similarity As Restoration Targetsmentioning

confidence: 99%

“…Particularly, we want to raise awareness of two key questions with regards to the utilization of similarity percentages analyses in restoration ecology: (1) what levels of community similarity should a restoration project strive for, and (2) does ecosystem function necessarily follow from high community similarity? It is important to note that we are not discussing the well recognized issue of including ecosystem variability in generating restoration targets (Choi et al 2008; Diefenderfer et al 2016; Gilby et al 2018; Campbell et al 2019; Hawkes & Gerwing 2019; Gerwing et al 2020 a ). Nor are we discussing the need to include some measure of ecosystem functionality and ecological processes into restoration assessments.…”

Section: Introductionmentioning

confidence: 99%

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Similarity analyses in restoration ecology and how to improve their utility

Gerwing

Hawkes

2021

Restoration Ecology

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Use of multivariate and nonparametric statistical analyses such as similarity percentages analysis has increased in the past decade within restoration studies. While very useful to compare community composition of restored habitats to reference areas, the ease in which these analyses can be applied, coupled with their power, can result in interpretation errors that could have negative ramifications upon restoration projects. Primarily, similarity measures are often used without stipulating similarity or dissimilarity targets. Despite these drawbacks, the benefits of these methods far outweigh the risks, especially if practitioners take care to specify their community similarity targets a priori and base these targets upon a representative range of reference conditions. However, restoration practitioners should remain focused on fulfilling the objectives of ecological restoration, by ensuring the development of functional habitat that is informed, but not dictated by, statistical analyses. As such, practitioners should take steps to ensure that meaningful univariate trends (e.g. an important species at risk or invasive species) and the overall functionality of the habitat should not be neglected, in favor of these methods of data analysis.

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Section: Achievable Community Similarity As Restoration Targetsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Similarity analyses in restoration ecology and how to improve their utility

Gerwing

Hawkes

2021

Restoration Ecology

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“…When the mats reached maximum cover (July-September), their benthic filter effect probably prevented further DIN efflux from the soil, leading to even lower DIN loading to the overlying water (Ladakis et al, 2006;Kristensen et al, 2020). Furthermore, it is known that over-consolidated (compacted or compressed) flooded agricultural soils may promote the formation of cyanobacterial mats and hinder ecosystem recovery (Gerwing et al, 2020). Accordingly, the massive cyanobacterial bloom in summer 2017 coincided with a decline in species richness of all macroalgal groups (Figure 3).…”

Section: Late Succession Phases With Dominance Of Benthic Cyanobactermentioning

confidence: 99%

“…Maintaining protective defenses is expensive (e.g., Bosello et al, 2012;Hinkel et al, 2014), and coastal retreat by natural processes or through managed realignment (MR) is an alternative solution with the potential to restore otherwise lost coastal ecosystems (Boorman and Hazelden, 2017;Carey, 2020). Since the long-term ecological development after flooding agricultural land with seawater is almost unknown, there is a need for new research corroborating the development of best restoration practices and management of coastal areas threatened by sea level rise (Gerwing et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Ecological succession of benthic primary producers within a newly flooded MR area is controlled by the prevailing physical, chemical, and biological factors (Hughes et al, 2009;Mossman et al, 2012;Sullivan et al, 2017;Gerwing et al, 2020). Physical factors include the availability of suitable attachment sites, and the proportion of soft and hard substrata is crucial for the recruitment of flora communities (Raffaelli and Hawkins, 1999;Dale et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Internal Nutrient Loading Controls Macroalgal and Cyanobacterial Succession in a Coastal Lagoon Restored by Managed Realignment of Agricultural Land

et al. 2021

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Managed realignment (MR) has been increasingly applied as an adaptation strategy to sea level rise in low-lying coastal areas, but the ecological consequences after flooding agricultural land with seawater are not well known. The restored Gyldensteen Coastal Lagoon represents one of the largest MR projects in Europe to date. The area served as agricultural land for about 150 years before being deliberately flooded with seawater in 2014. This study monitored for 5 years the succession of macroalgae and benthic cyanobacteria driven by changing internal nutrient (DIN = NH4+ + NO2– + NO3–, DON = dissolved organic nitrogen, and DIP = PO43–) loadings in the lagoon after flooding. A massive bloom of opportunistic green macroalgae (dominated by Cladophora spp.) occurred during the first year as response to a substantial loading of DIN and DIP from the newly flooded soils. The macroalgal cover was sparse the following years and the species richness increased with lower loading of particularly DIN. A cyanobacterial bloom controlled by declining DIN and steady DIP concentrations in the water dominated the lagoon and covered all solid surfaces 4 years after flooding. Highest macroalgal species richness with dominance of perennial Fucus vesiculosus and Agarophyton vermiculophylla was recorded 5 years after flooding following a temperature-induced stimulation of soil nitrogen transformation, leading to increased water column DON concentrations and DIN:DIP ratios. The lagoon remains therefore at an unstable tipping point where small and random changes in the DIN:DIP ratio control the balance between blooms of benthic cyanobacteria and high macroalgal species richness. Future MR projects involving agricultural land should prepare the soil to prevent algal blooms driven by sustained internal nutrient loading. Particularly P loading should be avoided to minimize the chances for recurrent blooms of benthic cyanobacteria.

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