The effects of temporary exclusion of activity due to wind farm construction on a lobster (Homarus gammarus) fishery suggests a potential management approach

Abstract

Offshore wind farms (OWF) form an important part of many countries strategy for responding to the threat of climate change, their development can conflict with other offshore activities. Static gear fisheries targeting sedentary benthic species are particularly affected by spatial management that involves exclusion of fishers. Here we investigate the ecological effect of a short-term closure of a European lobster (Homarus gammarus (L.)) fishing ground, facilitated by the development of the Westermost Rough OWF located on the north-east coast of the United Kingdom. We also investigate the effects on the population when the site is reopened on completion of the construction. We find that temporary closure offers some respite for adult animals and leads to increases in abundance and size of the target species in that area. Reopening of the site to fishing exploitation saw a decrease in catch rates and size structure, this did not reach levels below that of the surrounding area. Opening the site to exploitation allows the fishery to recuperate some of the economic loss during the closure. We suggest that our results may indicate that temporary closures of selected areas may be beneficial and offer a management option for lobster fisheries.

Introduction

Globally there has been an increase in energy provided from the wind industry, surpassing 63 GW in 2015, an 18% increase since 2014 (Global Wind Energy Council, 2015). Wind energy developments are often the most used tool by national governments to meet their energy demands from renewable sources, seeing an increase in offshore wind developments in recent years. Offshore wind developments are often located to exploit the optimum wind energy and be able to transmit the energy to shore. For example, the United States is estimated to have a 4000 GW capacity for wind energy (US Department of Energy 2012). The development of offshore wind farms (OWF) can cause spatial conflicts with other sea users. For example, the eastern sea board of the United States is prime location for both offshore wind energy and nationally important crustacean fisheries (Breton and Moe, 2009; Brehme et al., 2015). Co-location of marine users and spatial management of resources is being observed in the United Kingdom; one of the world leaders in offshore wind exploitation (Hooper and Austen, 2014; Kota et al., 2015).

UK government has a target of 15% of its energy from renewable sources by 2020 (European Commission, 2016). There are currently 25 OWF operational or under construction within UK waters currently providing approximately 5% of the UK demand with a further 16 with development consent (The Crown Estates, 2017). There has been a steady increase in research into the impacts of OWF on the marine ecosystem. This increase in literature is largely review based with the few empirical studies available, not being able to give a reliable assessment of the cumulative impact of offshore wind development (Lindeboom et al., 2015). The current empirical studies have largely focussed on the impact to seabird interactions (15 out of 78 publications reviewed by Hooper et al. [2017]), marine mammals (Madsen et al., 2006; Thomsen et al., 2008; Bailey et al., 2010; Brandt et al., 2011), substrate and infauna disturbance (Coates et al., 2014; De Backer et al., 2014; Vandendriessche et al., 2015) and fish populations (Wahlberg and Westerberg, 2005; De Troch et al., 2013; Bergman et al., 2014; Stenberg et al., 2015). Most empirical studies investigating effects on macrobenthic crustaceans form part of an environmental impact assessment or statutory monitoring programmes.

To date the majority of OWF constructed in European waters are in shallow water (typically less than 30 m) on sand-based substrates. The introduction of individual turbines and associated stone protection (used to protect monopole bases from sand scour), can introduce a new hard substrate habitat to an area. This can increase shelter and hard substrate habitat in areas that it may not have existed previously. This introduced habitat has been found to increase biodiversity and biomass of associated fauna in some areas (Lindeboom et al., 2011; De Backer et al., 2014; Stenberg et al., 2015). Krone et al. (2017) observed over 5000 Cancer pagurus on individual monopoles with scour stone protection, which was more than double that found on monopoles without scour stone protection. However, this was observed in areas characterized by sandy substrate, the effect of scour stone protection on areas characterized by rock and cobble is yet to be understood. Using studies from sites that are not comparable to each other to understand effects of OWF installations can lead to misunderstanding of the processes involved (Lindeboom et al., 2015).

OWF and individual turbines can act as fish aggregation devices, providing a refuge for fish species from predation and exploitation, although the effects can be spatially limited to the OWF (Griffin et al., 2016). An OWF can act as a quasi-marine protected area (MPA) or no take zone (NTZ). This can be due to exclusion during construction or operation, to all fishing vessels or the physical presence of the turbines excluding certain gear types such as mobile gear (Bergman et al., 2014; Krone et al., 2017). There is potential for co-location of fisheries and OWF developments, however, these are predominantly static fisheries (Christie et al., 2014; Hooper and Austen 2014; Stelzenmüller et al., 2016). The effects of OWF on mobile benthic megafauna that are targeted by static gear fisheries are little understood (Hooper and Austen 2014; Lindeboom et al., 2015). The potential of spill-over effects of MPA/NTZ can be difficult to ascertain (Moland et al., 2013; Smyth et al., 2015; Vandendriessche et al., 2015), the temporal scale of studies can often not be of sufficient duration to observe the spill over. However Goñi et al. (2010) and Hoskin et al. (2011) observed spill-over effects of different lobster populations within a closed area over a period of 10 and 4 years, respectively. Homarus gammarus have been shown to have strong site fidelity and defined home ranges (Bannister and Addison, 1998; Smith et al., 1998; Moland et al., 2011) although there is a seasonal migration to deeper water during the colder months. Any spill-over effects of closed areas are likely to be only observed locally or during immigration/emigration from the site. The implementation of an MPA/NTZ has often been met with resistance by commercial fisheries. The potential for positive ecological and possible economic effects of closed areas are often met with scepticism from the fishing industry. This is due to the implementation of surveys not reflecting the way fishermen operate and the fact that data are not in the public domain (Hooper and Austen 2014; Hooper et al., 2015).

The spill-over effect can lead to the process of “fishing the line,” where fishing intensity is increased on the boundaries of a closed area (Kellner et al., 2007). Spatial displacement of effort into another area can increase pressure on fisheries and lead to increased competition among fishers. This is especially the case in static gear fisheries where individual fishers can have a strong fidelity to specific sites (Hart et al., 2002; Turner et al., 2013). The implementation of closed areas can often be considered by industry and some in the scientific community to be conducted for political purposes as opposed to ecological. The use of MPA’s as a fisheries management tool should be treated as a rigorously designed experiment with accurate cost/benefit analysis (Kaiser 2005; Caveen et al., 2014). During construction of OWF, the fishing industry are often excluded from the area for safety reasons; this can have a potential short-term positive effect on the local population due to the removal of fishing mortality.

Here we investigate the short-term effects of construction of an OWF on a commercially exploited European lobster (H. gammarus, Homaridae (L.) subsequently referred to as lobster) population. We also highlight the effects of reopening the site to exploitation on completion of the OWF construction and their use as a potential management tool. The study also highlighted the potential positive effects of the fishing industry engaging in research of OWF effects.

Methods

Site description

The Holderness coast lobster fishery is the largest lobster fishery in the United Kingdom, representing approximately 20% of national lobster landings. Landings of European lobster, into the regions’ main port of Bridlington in 2015 were 405 tonnes with an estimated first sale value of £4.2 million (Marine Management Organisation, 2015). The fishery in the area targets lobster almost exclusively using static creels generally baited with mackerel. Creels are immersed for varying periods depending on the fisher, but generally 2–3 days.

The Westermost Rough wind farm, constructed in 2014/2015 at a cost of £800 million, and is located within the Holderness fishery, situated within one of the fisheries main target areas. The site was one of the first to be located on a rock and cobble substrate. The Westermost Rough OWF extends from 7.7 km off the coast to 13.3 km offshore and is approximately 35 km² in area (Figure 1). It consists of 35, 6 MW turbines and associated substation, located in a depth of water ranging from 15 to 23 m. The substrate is predominantly rock and cobble with sand patches, the area was subjected to boulder removal prior to the construction phase.

Figure 1.

Location of the Westermost Rough OWF, the individual turbine locations marked and the locations of the treatment strings within the turbine array and the control strings to the North of the site.

The study was conducted using a fishing industry managed research vessel, the R.V. Huntress. The study was a collaboration between the local fishery; The Holderness Fishing Industry Group (www.hfig.org.uk) and the OWF developer, DONG Energy.

Sampling methods

There were two sites chosen to assess the effects of the construction of the Westermost Rough OWF, one site in the OWF (treatment [subsequently referred to as the wind farm]) and a site to the north of the OWF (control) (Figure 1). The sites were restricted in their spatial distribution within the OWF due to the process of the construction of the OWF. The site was agreed with the developer as the area that could be surveyed without disruption to the sampling protocol. The control site was located 1 km to the north of the OWF. The prevailing current drifts north/south, any effects of the construction should not have been observed. This site was also selected due to the substrate reflecting that within the OWF. There were further spatial restrictions of the control site due to displacement of fishing gear from the OWF to the surrounding area, care was taken to avoid gear conflict.

Sampling strings consisting of 30 creels were deployed both within the wind farm and the control. The strings consisted of 25 standard commercial creels with a 70 mm mesh and 96.5 cm base; and 5 creels with a 30 mm mesh and a 76.2 cm base. All creels were exempt from local byelaws ordering the use of escape gaps. The smaller mesh creels were used to sample catch that may escape the larger mesh creels. On every haul, each creel was baited with two mackerel “frames,” which are commonly used in the region to target lobsters. Each string was secured at either end with a 20 kg anchor and marked with a surface marker buoy. The gear configuration mirrored that of the commercial fishing strings in the area.

A baseline survey was carried out prior to the wind farm construction, taking into account the spatial restrictions that were predicted once the construction began. The survey was timed to target the lobster fishery between June and September of 2013, maintaining a mean immersion period of 3.0 days (SD ±1.34 days) and all creels from both the control and treatment were processed on every survey day (n = 24 hauls each site). Following the before/after, control/impact (BACI) approach (Carstensen et al., 2006; Hoskin et al., 2011; Moland et al., 2013; Vandendriessche et al., 2015) sampling was mirrored in June–September of 2015 for the first-year post build of the wind farm. The immersion period of the creels in 2015 was 3.9 days (SD ±2.1 days) and all creels from both the control and treatment were processed on every survey day (n = 23 hauls each site). Variation in immersion periods to the baseline survey was due to inclement weather. There was no survey during 2014 as the site was under construction.

During the baseline survey of 2013 both the wind farm and control were subjected to fishing exploitation for the entire period. During construction, the wind farm was closed to fishing exploitation for a period of 20 months during 2014/2015, until the middle of August 2015 (13/08/2015). This was part way through the 2015 sampling period, with 13 sample days when the site was closed and 11 sample days when the site was open to exploitation. For the entire survey periods in both 2013 and 2015 there were no restrictions to fishing exploitation in the control site and the main management of effort in the area was based on minimum landing size (87 mm carapace length [CL]) of the catch.

Abundance of lobster was recorded from each creel. Sex, condition, ovigerous status and size (CL) were recorded for the aggregated catch within each string. All animals were returned to sea after recording. The survey was timed and designed to assess the effects of the wind farm construction on the region’s most valuable fishery, this study reports lobster status only.

Data analysis

Analysis was conducted on the overall differences in size and catch rates between the baseline (2013) and the first-year post build (2015). Because the previously closed site was reopened to fishing during the 2015 sampling regime, analysis was also conducted on the status of the wind farm (open/closed to fishing exploitation). All analysis was conducting using R statistical software (R Core Team, 2017).

Size distribution

Differences in size frequency for both between years and between statuses of the wind farm (open and closed) were analysed using the two-sample Kolmogorov–Smirnov (K-S) test. Empirical cumulative distribution function (ECDF) plots were generated to demonstrate the proportion of lobsters between the two sites that are less than each observed length (Ogle, 2016). Generalized Linear Mixed Models (GLMM) are used when the data are not normally distributed and when there is the potential for pseudo-replication (Zuur and Ieno, 2016). Due to the limitations of survey sites, the size data not conforming to normality (K-S, p < 0.05) and the variability in the number of lobsters sampled on each day (range = 13–137 [2013], 44–179 [2015]), GLMM was deemed a more suitable analysis. We therefore applied a GLMM in which the relative catch probability of the lobsters entering the pots within each site/year was the response variable, carapace length (length) of lobster as the fixed effect and haul (survey day) was used as a crossed random intercept. A binomial error was applied due to the response variable being the relative catch probability of lobsters entering pots within each site/year. Sex, ovigerous status and condition of the lobsters were investigated as factors within the model but were rejected due to either insignificance (p > 0.05 [sex and condition]) or unsuitable factors to include (ovigerous status). Soak time was investigated to see whether it should be included as an offset within the model. There was a poor relationship (R² < 0.1 on all occasions) between the daily abundance of lobsters within each string and the soak time they were subjected to. Soak time was also negated for the between sites comparison within the survey design, as both sites were subjected to the same soak time on all occasions. It was decided that soak time was not required as an offset within the GLMM. Therefore, the simplest model was the best description of the relative catch probability of lobsters of each size entering the strings/pots between the two sites/status of the wind farm (open/closed);

$$\mathrm{Pr}\left\{\frac{\mathrm{T}\mathrm{e}\mathrm{s}\mathrm{t}}{\mathrm{T}\mathrm{e}\mathrm{s}\mathrm{t}\mathrm{ }+\mathrm{ }\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}}\right\}=1/(1+e^{-\left(\mathrm{h}\mathrm{a}\mathrm{u}\mathrm{l}+{\mathrm{\beta }}_1\times \mathrm{l}\mathrm{e}\mathrm{n}\mathrm{g}\mathrm{t}\mathrm{h}+{\mathrm{\beta }}_2\times \mathrm{l}\mathrm{e}\mathrm{n}\mathrm{g}\mathrm{t}\mathrm{h}2\right)})$$

GLMM was applied using the lme4 package in R statistical software (Bates et al., 2015). This follows the methodology described by Holst and Revill (2009), analysing differences in catch composition at length between tests and controls (Van Marlen et al., 2014; Vogel et al., 2017). Test was determined as the strings sampled in 2015 for the between years comparison with the strings sampled in 2013 (baseline) as the control. The analysis of the wind farm status in 2015 (open/closed), test was always the wind farm site and the control was always the control site to the north of the wind farm.

Validation of each GLMM model was conducted by checking that the normality of the standardized residuals conformed to a normal distribution (Shapiro–Wilkes, p > 0.05) (Thomas et al., 2015) and also comparing the GLMM results to the two-sample K-S analysis. GLMM results were also presented graphically, allowing for inference as to where within the distribution the significance lay.

Catch comparison

Catch per unit of effort (CPUE) was determined as the total number of lobsters caught in a string (Davies et al., 2015). Landings per unit of effort (LPUE) was determined as the total number of lobsters per string that were above the minimum landing size (87 mm CL) and of a good enough quality (i.e. not missing limbs and no visible signs of disease) to be landed to market. The CPUE and LPUE data conformed to a normal distribution (K-S, p > 0.05) but the variances could not be considered equal (F-test, p < 0.05). A Welch’s t-test assuming unequal variances was applied to the CPUE and LPUE to analyse the differences in site, year and wind farm status (open/closed).

Results

A total of 1440 creels (720 at each site) were hauled during the baseline data collection in 2013 (n = 24 survey days) recording 6051 lobsters. During the 2015 post-build survey (n = 23 survey days), 1380 creels (690 at each site) were hauled and 8734 lobsters were recorded.

Size distribution

The size frequency distributions of lobsters differed significantly between the two years (K-S, D = 0.10, p < 0.001). The windfarm in 2015 showed a larger proportion of lobsters at a larger size (>100 mm CL) than sampled in 2013 (Figure 2a and b), there was a greater proportion of lobsters from the MLS (87 mm)—96 mm CL sampled in 2013. There was a broader size range, 39–126 mm CL in 2015 as opposed to 56–114 mm CL in 2013. The ECDF plot (Figure 2c) demonstrates that the greatest difference in distributions were between 75 and 92 mm CL. This was supported by the GLMM plot (Table 1, Figure 2d), which demonstrates that there was a greater proportion of lobsters sampled over 70 mm CL in 2015 than in 2013.

Table 1.

GLMM parameters for both the comparison between years and the comparison between the control and wind farm, in relation to the status of the wind farm being subjected to fishing exploitation.

Treatment	Response	Intercept variance	Parameter	Estimate	Standard error
Wind farm	Between 2013 and 2015	0.755	β0	0.215	0.347
			β1	−0.009	0.004
Wind farm closed	Wind farm and control	0.031	β0	6.678	0.385
			β1	−0.081	0.005
Wind farm open	Wind farm and control	0.036	β0	2.045	0.464
			β1	−0.020	0.006

Figure 2.

Size distributions of lobsters sampled within the Westermost Rough OWF for the baseline survey in 2013 (a) and the first-year post-build survey in 2015 (b), both plots fitted with the density curve of the distribution and the bins set to 2 mm carapace length. (c) ECDF for the sampled lobsters for the wind farm and control site in 2013 (red and black) and the wind farm and control site in 2015 (blue and grey). (d) Plot derived from GLMM modelling of the proportion of the lobsters sampled at each size in 2013 (top box) and 2015 (bottom box). The grey-shaded areas represent the 95% confidence intervals and the bold black line the mean value. The central horizontal line represents the 0.5 (50%) value, points overlapping this line indicate that there was no significant difference in the proportion of that sized animal between the two years. A value of 0.75 indicates that 75% of the lobsters sampled at that size were sampled in 2013 and the other 25% were sampled in 2015. This applies to all subsequent plots derived from GLMM analysis. The vertical line on all plots represents the minimum landing size of lobsters in the fishery, which is 87 mm carapace length. This applies to all subsequent plots reported.

During the wind farm closure in 2015 (prior to 13/08/2015), the size distribution of lobsters in the control site (Figure 3b) had a narrower distribution (39–117 mm CL) than within the wind farm (40–126 mm CL) and there was generally a greater proportion of lobsters within the wind farm than within the control site (Figure 3a). The size distribution of lobsters within the wind farm was significantly different to both the control site (K-S, D = 0.32, p = < 0.0001) and the baseline data (K-S, D = 0.14, p < 0.0001) (Figure 3a and b). Although Figure 3c shows that the size of lobsters within the wind farm (red) differed from the baseline (black and grey) and the control (blue) between 60–107 mm CL, Figure 3d shows that the distribution was split approximately at the MLS (vertical line). The graphical representation of the GLMM (Table 1) shows that there was a greater proportion of lobsters below the MLS in the control site and the inverse in the wind farm.

Figure 3.

Size distributions of lobsters sampled at the Westermost Rough OWF for both the wind farm site (a), which was closed to fishing for the period and the control (b), which was subjected to fishing throughout the period. ECDF plot for the period before the wind farm site was opened to fishing showing the wind farm (red), control (blue) and baseline for the two sites: black (wind farm), grey (control) (c) and the plot derived from GLMM analysis for both the control and wind farm site (d) for the period before the wind farm was opened to fishing.

There was a decline in the proportion of lobsters above MLS in the control site after the wind farm had been opened to fishing (Figure 4a) in comparison to the period when the wind farm was closed (Figure 3a) (K-S, D = 0.07, P < 0.05). This was also reflected within the wind farm site (Figures 3b and 4b) (K-S, D = 0.28, p < 0.0001). The sampling period post opening of the wind farm to fishing demonstrated a greater proportion of lobsters within the wind farm in comparison to the control site (K-S, D = 0.11, p < 0.0001). Although there was a difference in the cumulative distribution between the wind farm and the control site between 70 and100 mm CL, both sites also showed a difference from the baseline data (Figure 4c). GLMM analysis (Table 1) shows that after opening of the site to fishing there was a greater proportion of lobsters below MLS in the control site as opposed to the wind farm (Figure 4d). There was no significant difference in the proportion of lobsters above MLS between the two sites post opening of the site.

Figure 4.

Size distributions of lobsters sampled at the Westermost Rough OWF for both the wind farm site (a) after the site was opened to fishing and the control (b), which was subjected to fishing throughout the period. ECDF plot for the period after the wind farm site was opened to fishing showing the wind farm (red), control (blue) and baseline for the two sites: black (wind farm), grey (control) (c) and plot derived from GLMM analysis for both the control and wind farm site (d) for the period after the wind farm was opened to fishing.

Catch and landings per unit of effort between years

Mean CPUE (Table 2) was significantly greater in 2015 for both sites than in 2013 (p < 0.01, Table 3), however did not differ significantly between control and wind farm within the same year (p > 0.05, Table 3). Mean LPUE (Table 2) was also significantly greater in the wind farm in 2015 than in 2013 and it was also significantly greater in the wind farm than the control site in the year 2015 (p < 0.01, Table 3). The control site showed no significant difference in mean LPUE between sample years (p > 0.05, Figure 5 and Table 3). The greatest ratio between CPUE and LPUE (0.25) was within the wind farm during the year 2015, this was when the wind farm was closed for a period during the sampling regime (Figure 5).

Table 2.

Descriptive statistics of CPUE and LPUE of lobsters sampled at both sites of the Westermost Rough OWF during the 2013 and 2015 surveys.

Year	Site	Effort	Mean	SD
2013	Wind farm	CPUE	63.14	34.68
2013	Control	CPUE	74.27	45.48
2015	Wind farm	CPUE	93.30	32.14
2015	Control	CPUE	107.30	29.46
2013	Wind farm	LPUE	11.51	6.75
2013	Control	LPUE	11.28	5.71
2015	Wind farm	LPUE	23.39	16.68
2015	Control	LPUE	10.26	4.67
Status	Site	Effort	Mean	SD
Closed	Wind farm	CPUE	113.08	29.31
Closed	Control	CPUE	107.08	35.44
Open	Wind farm	CPUE	71.73	18.59
Open	Control	CPUE	107.55	22.98
Closed	Wind farm	LPUE	36.83	10.43
Closed	Control	LPUE	12.08	4.23
Open	Wind farm	LPUE	8.73	6.25
Open	Control	LPUE	8.27	4.47

Table 3.

Results from Welch’s two-sample t-test for the mean CPUE/LPUE data analysed between the control and treatment sites of the Westermost Rough OWF and between the baseline and post-build surveys.

Factors analysed	Response	p	t	DF
Treatment between years	CPUE	<0.01	−3.02	29.27
Control between years	CPUE	<0.01	−2.88	35.75
Treatment between years	LPUE	<0.01	−3.16	29.27
Control between years	LPUE	n.s.	0.65	40.62
Treatment vs. control in 2013	CPUE	n.s.	0.91	39.25
Treatment vs. control in 2015	CPUE	n.s.	1.54	43.67
Treatment vs. control in 2013	LPUE	n.s.	−0.12	40.88
Treatment vs. control in 2015	LPUE	<0.01	−3.64	25.43

The significant results are displayed in bold.

Figure 5.

Mean catch per unit effort (a) and landings per unit effort (b) for the wind farm (dark grey) and the control site (light grey) for the baseline survey (2013) and the first-year post-build survey (2015). The top of the bars represent the mean CPUE/LPUE and the error bars the standard deviation of the data. The values above the LPUE bars represent the ratio between CPUE and LPUE. The letters above the bars indicate the factors that showed a significant difference. This applies to all subsequent bar plots reported.

Influence of wind farm opening

After the wind farm opened to fishing exploitation, mean CPUE (Table 4) within the wind farm reduced significantly (p < 0.001, Table 5), this was not the case in the control site (p > 0.05, Table 5). Mean CPUE (Table 4) was also significantly greater prior to the wind farm being opened to fishing exploitation (p < 0.001, Figure 6 and Table 5). Mean LPUE (Table 4) was significantly greater in the wind farm when it was closed than the control site during the same period and once the wind farm was opened to fishing (p < 0.001, Table 5). Mean LPUE (Table 4) was significantly greater in the control site when the wind farm was closed than the period when the area was open to fishing exploitation (p < 0.05, Figure 6 and Table 5). The greatest ratio of LPUE against CPUE (0.33) was during the period when the wind farm was closed to fishing, indicating a higher proportion of high quality lobsters that were not being exploited (Figure 6).

Table 4.

Descriptive statistics of CPUE and LPUE of lobsters sampled at both sites of the Westermost Rough OWF before and after the wind farm was opened to fishing exploitation.

Status	Site	Effort	Mean	SD
Closed	Wind Farm	CPUE	113.08	29.31
Closed	Control	CPUE	107.08	35.44
Open	Wind Farm	CPUE	71.73	18.59
Open	Control	CPUE	107.55	22.98
Closed	Wind Farm	LPUE	36.83	10.43
Closed	Control	LPUE	12.08	4.23
Open	Wind Farm	LPUE	8.73	6.25
Open	Control	LPUE	8.27	4.47

Table 5.

Results from Welch’s two-sample t-test for the mean CPUE/LPUE data analysed between the status of the Westermost Rough OWF in 2015, i.e. open or closed to fishing.

Factors analysed	Response	p	t	DF
Treatment between status of OWF	CPUE	<0.001	4.08	18.79
Control between status of OWF	CPUE	n.s.	−0.04	19.01
Treatment between status of OWF	LPUE	<0.0001	7.92	18.23
Control between status of OWF	LPUE	<0.05	2.10	20.56
Treatment when OWF was open	CPUE	<0.001	4.02	19.16
Control when OWF was closed	CPUE	n.s.	−0.45	21.25
Treatment when OWF was open	LPUE	n.s.	−0.20	18.12
Control when OWF was closed	LPUE	<0.0001	−7.62	14.53

The significant results are displayed in bold.

Figure 6.

Mean CPUE (a) and LPUE from the wind farm (dark grey) and the control site (light grey) before and after the wind farm was opened to fishing exploitation.

Discussion

Size distribution

The exclusion of fishing effort within the OWF was found to have an effect on the size distribution of lobsters within the area. There was a greater total number of lobsters observed during the post-build survey than during the baseline survey (n = 2683 difference). Within the wind farm, there was a greater proportion of lobsters, over MLS observed in 2015 than in 2013 (Figure 2). The absence of fishing exploitation within the wind farm during construction acted as a NTZ, protecting lobsters greater than the MLS. There is potential for spill-over effects of an MPA/NTZ (McClanahan and Mangi 2000; Smyth et al., 2015), this can be observed locally for species with reduced movement patterns. (Moland et al., 2011). When a NTZ is created it has been reported to initially show an increase in lobster abundance and biomass (Hoskin et al., 2011; Wootton et al., 2012; Davies et al., 2015). The increase in the proportion of larger lobster (> 100 mm CL) reported in Figure 2 and the overall higher number of lobsters observed was expected due to the closure of the site when compared to the baseline data.

Prior to the wind farm being opened, the size distribution of lobsters within the wind farm was significantly different to the control site and the wind farm baseline distribution (Figure 3). The density of lobsters can be influenced by the availability of shelters within a habitat (Ball et al., 2001; Steneck 2006). The size of lobsters within a population has also been demonstrated to be limited by the size and number of shelters available (Bushmann and Atema 1997; Debuse et al., 1999). The addition of scour stone protection to the base of each monopole could potentially increase the available habitat and shelters for lobsters. The Westermost Rough OWF site was subjected to boulder removal prior to construction so the additional habitat creation may have been negated by the boulder removal. As the difference in size within the wind farm was described by lobsters over 75 mm CL (Figure 3d), the absence of fishing effort in the site is most likely to have greater influence than the habitat change.

Opening of the site to fishing exploitation led to a rapid, short-term increase in landings from the wind farm in comparison to the surrounding area. After the wind farm was reopened to fishing, the previously unfished population of larger lobsters was reduced by intensive fishing over a short period. This reduction, however, did not drop below that reflected by the control site, which was subjected to exploitation for the entire period. The proportion of lobsters above MLS did not differ between the wind farm and the control site in the period after opening to fishing (Figure 4d). However, there was a greater proportion of smaller lobsters observed in the control site than within the wind farm (Figure 4d). The presence of a greater abundance of larger lobsters may have deterred the smaller lobsters from the wind farm (Steneck 2006; Émond et al., 2010). Their immigration into the site once lobsters above MLS were again being exploited may not have occurred during the timeframe of the survey. The smaller lobsters may have also been displaced into areas surrounding the wind farm due to inter-specific competition for resources (Wahle et al., 2013), which was reflected in the control site (Figures 3b and 4b). This indicates potential overspill effects, however, of the pre-recruits rather than recruits into a fishery. There are also influences in catch dynamics of a creel, smaller lobsters may use creels as shelter from predation and as feeding stations (Grabowski et al., 2010). The greater abundance of larger lobsters in the area that were subsequently caught in the survey creels, may have deterred the smaller lobsters from entering the creels (Jury et al., 2001). This interaction could have skewed the data to present a population biased in favour of larger lobsters. Alternatively the construction of the OWF and associated disturbance may have had a greater effect on the smaller, less robust lobsters (Rodmell and Johnson, 2002). As the fishing pressure returns to a stable state, again removing lobsters above MLS, it’s likely that smaller lobsters will again be observed within the area.

Catch and landings per unit of effort

The increase in lobster abundance observed in 2015 was reflected by the CPUE, showing a significant increase in catch rate of lobsters for both sites in 2015. There was no significant difference in catch rates of lobsters between the wind farm and control site in 2015 (Figure 5). Indicating that the difference between the years was due to natural variation and not just the closure of the wind farm. The LPUE, i.e. the number of lobsters of good quality per string that were above the MLS of 87 mm CL also showed a significant increase within the wind farm between years and with the control site in 2015. Wootton et al. (2012) and Davies et al. (2015) both observed a greater prevalence of injury and disease in lobsters within an NTZ. The increased LPUE observed in this study, indicating a greater abundance of lobsters without injury above MLS, suggests that this was not the case here. This could be attributed to the period of closure, as this site was only closed for 20 months in comparison to 2 and 5 years in their respective studies. The area may not have been closed long enough for true competition of resources that can result in increased occurrences of injuries.

After the wind farm was opened to fishing the CPUE reduced significantly within the wind farm when compared to when the site was closed. It also differed significantly to the control site after opening (Figure 6 and Table 5). This demonstrates the effect of opening the area to exploitation after a period of closure. The mean LPUE however, after opening of the wind farm did not differ significantly to the control site (Figure 6 and Table 5). This indicates that although effort was high, within a relatively short period (6 weeks survey period after opening), the landings fishermen were getting within the site reflected the surrounding area.

It has been demonstrated that periodic (Murawski et al., 2000) or permanent (Bergman et al., 2014) closure of areas to exploitation can enhance commercial fisheries. Closure of areas can allow the larger, more fecund lobsters to contribute to the spawning stock without fishing pressure (Moland et al., 2010; Leal et al., 2012). Periodically closing and reopening of the site has the potential to offset the possible detrimental effects of a permanent NTZ as observed by Wootton et al. (2012) and Davies et al. (2015). Economic loss to the fishery of a closed area may be offset by the increased earning potential once the site has been opened. Figure 6 demonstrates a 22% increase in LPUE in comparison to the control site. This, however, was only a short-term effect as the LPUE returned to background levels within the 6-week period of the survey.

There is the potential for OWFs with their easily identifiable delineation to be used as a stock management tool for lobster fisheries. Combined with other suitable and easily identifiable sites, rotational closures could protect spawning stocks whilst offsetting economic loss and detrimental effects of permanently closed areas (Cohen and Foale, 2013).

Conclusion

This study has demonstrated the short-term effects on size distribution, CPUE and LPUE of OWF construction on a commercially important lobster fishery. The construction of the OWF created a temporary NTZ during the construction period, which resulted in an increase in larger, good quality lobsters in comparison to both the baseline data and control sites. The opening of the wind farm during the sampling period has highlighted that exploitation levels immediately following reopening of a site are high but quickly return to reflect surrounding areas. This study, whilst spatially limited has also presented a BACI approach to monitoring effects of OWF construction. Presenting a high number of individuals sampled, that represented the main fishing season for lobsters in the area. The collaboration between industry and developers has led to a study using industry data collection, that enables a high number of lobsters sampled, to aid in addressing a current gap in the literature. Subsequent monitoring of the site will highlight any longer-term effects of the OWF construction and its operation on the local lobster stocks when fishing exploitation is stable. Opening of the site during the sampling period has also highlighted the potential for OWF sites to be used as a stock management tool for periodic closures.

Acknowledgements

We would like to thank DONG Energy for funding the research and encouraging industry/developer collaboration. The crew of the R.V. Huntress for extensive sea time and advice on local fisheries and Rebecca Skirrow for assistance with data recording. The authors would also like to thank the reviewers for their advice in improving the manuscript.