Changes to seabird distribution
A GEE-GLM modelling approach was used to predict the at-sea distribution and abundance of seven of the study species (Atlantic puffin, black-legged kittiwake, common guillemot, great black-backed gull, herring gull, northern gannet and razorbill; European shag could not be reliably modelled due to insufficient at-sea survey data and issues related to their very coastal distribution) in the past (1961-1990), present (2017) and future (2070-99) in both summer (June) and winter (January). The analyses built on models previously developed for the NERC/DEFRA funded MERP project (Waggitt et al. 2020) and ORJIP Sensitivity Mapping Tool (Searle et al. 2019).
Underpinning the results were thermal niches of each species. Atlantic puffin and black-legged kittiwake were most likely to respond negatively to climate warming because they favoured the coldest waters. Great black-backed gull and herring gull were also associated with cooler temperatures, and are therefore also likely to respond negatively to predicted future warming. In contrast, common guillemot, razorbill and in particular northern gannet showed an association with warmer temperatures, and were therefore likely to be least negatively affected by warming.
The results predicted widespread declines among the majority of species. For Atlantic puffin and black-legged kittiwake, this was apparent in both summer and winter, whereas it was only the case for summer in common guillemot, herring gull and razorbill, and in winter in great black-backed gull. In contrast, razorbill were in fact predicted to increase in winter, and the northern gannet was predicted to increase in both summer and winter.
The predicted declines were apparent across the North Sea in most cases, with relative distributional changes apparent only in common guillemot and razorbill, which were predicted to see increases in the northern North Sea and decreases in the southern North Sea. Changes in seasonal use were generally not forecasted. Atlantic puffin and northern gannet use the region more extensively in summer than winter and this pattern was predicted to remain under future climate scenarios. Black-legged kittiwake were predicted to continue to use the North Sea throughout the year. Common guillemot, razorbill, great black-backed gull and herring gull currently show higher numbers across the North Sea in winter, and under future climate scenarios, the difference between summer and winter densities were predicted to become more marked in common guillemot and razorbill.
These results are in keeping with past work which has investigated the effect of temperature on distribution and environmental suitability in the North Sea. Frederiksen et al. (2013) predicted that seabird habitat suitability will shift northward over the next century, and concluded that northern distributional shifts and reduced densities in the North Sea are likely in future. Russell et al. (2015) used climate envelope models to predict that 65% of seabird species that breed in the UK would show a decline in their European range, with some declining by as much as 80%. This work was focussed on colony location, which has a strong influence on at-sea distribution in particular in summer. The study estimated that, under a best case scenario of unlimited dispersal, the ranges of black-legged kittiwake and auks would still decline significantly. The marked variation among species in their responses is challenging to interpret. The decline in kittiwake abundance supports past work on the negative effects of future predicted warming (Carroll et al. 2015), and the increase in gannets suggest the current situation of population increases under climate warming is set to continue. However, the reasons underpinning the variation in responses of the three auk species is unclear. A recent analysis of summer diet from the Isle of May suggests that common guillemots and razorbills are becoming less reliant on lesser sandeels Ammodytes marinus, whereas there is no such trend in puffins (Wanless et al. 2018). Puffins may thus be less able to switch prey under climate warming, and single prey loading may constrain guillemots if future warming results in further declines in prey size, which may have less impact on razorbills. However, it is not clear why puffin abundance was also predicted to decline in winter, and razorbills to increase. There are differences in winter distribution and trophic position between these species (Glew et al. 2018), but these do not provide a clear explanation for the decrease in puffins and increase in razorbills predicted in winter. Clearly, further mechanistic studies of diet and foraging ecology are needed to understand among-species variation in summer and winter distribution and abundance.
It is important to recognise that underlying at-sea survey data were an open-access subset of that used in Waggitt et al. (2020) – namely that used by Bradbury et al. (2014) plus additions from Marine Scotland and Natural England. As a consequence, coverage in the most recent decade (2010-2020) and in southern regions (Bay of Biscay, English Channel) is limited. The inclusion of data in the latest decade could have stabilised interaction terms based on climatic indices, identifying differences between the northern and southern North Sea. Whilst outside the study area, the inclusion of data in the southern region would have improved quantification of thermal associations. Further developments to the GEE-GLM would be enhanced if these data could be included.
The effect of climate on productivity (the number of chicks fledged per breeding attempt) was investigated in eight species - the same seven species considered in the analyses of seabird distribution (Atlantic puffin, black-legged kittiwake, common guillemot, great black-backed gull, herring gull, northern gannet and razorbill) plus European shag. The statistical analyses were conducted using colony-specific and year-specific values for breeding colonies throughout the region of interest to estimate associations between productivity and climate variables, and to subsequently generate predictions of future productivity under a projected future climate scenario.
There was a strong negative effect of pre-breeding sea surface temperature and a strong positive effect of pre-breeding sea surface salinity on productivity of Atlantic puffins (
Table 14). This resulted in a future projected decline in productivity from the present day to 2070-99, with limited opportunity to increase foraging range to compensate for these productivity declines. For the black-legged kittiwake, the best supported model for productivity included marine and terrestrial climate variables from the pre-breeding period, with a strong negative effect of sea surface salinity and terrestrial temperature and a strong positive effect of terrestrial precipitation (
Table 14). As with Atlantic puffin, this resulted in a future projected decline in productivity in 2070-99, with no apparent opportunity to compensate for these declines by increasing foraging range. For common guillemots, the best supported model for productivity included marine and terrestrial climate variables, as well as terrestrial wind, during the pre-breeding period, with some evidence for negative relationships between productivity and sea surface temperature and sea surface salinity, and for a positive relationship with terrestrial rain (
Table 14). Because we could not generate future predictions from this model due to the lack of reliable wind projections at the time of modelling, we used the second best supported model, which included both marine and terrestrial climate variables to generate future projections, which indicated a future projected decline in common guillemot productivity in 2070-2099. Again, there was no evidence that increasing foraging range would allow common guillemots to access better marine conditions. For productivity in great black-backed gull, there was a strong negative relationship with sea surface salinity, and a strong negative relationship with terrestrial temperature (
Table 14). Interestingly, in great black-backed gull, there was more support for effects of climate over the breeding season, rather than over the pre-breeding period as for the previous three species (
Table 14). Future productivity in great black-backed gull was projected to decline in common with the previous three species, and there was little evidence that this species would have the ability to compensate for predicted declines in productivity by increasing its foraging range around breeding colonies to access more climatically suitable conditions. The results for northern gannet were markedly different, with the model receiving the most support including a strong negative relationship between sea surface salinity and productivity (
Table 14). As with great black-backed gull, there was more support for an effect of climate during the breeding season on subsequent productivity, rather than the pre-breeding period (
Table 14). Notably, northern gannet was the only species for which productivity was predicted to increase in the future. The null model, including no climatic variables, was best supported in the three remaining species (European shag, herring gull and razorbill), suggesting that in these species there was insufficient information in the data to be able to detect relationships between productivity and climate variables.
|Atlantic puffin||Sea surface temperature -** Sea surface salinity +*||Pre-breeding|
|Black-legged kittiwake||Sea surface salinity -*||Temperature -** Rainfall +**||Pre-breeding|
|Common guillemot||Sea surface temperature -* Sea surface salinity -*||Rainfall +*||Pre-breeding|
|Great black-backed gull||Sea surface salinity -**||Temperature -**||Breeding|
|Northern gannet||Sea surface salinity -**||Breeding|
Our results support previous findings that have demonstrated the importance of temperature on productivity in seabirds in the northern hemisphere (Frederiksen et al. 2004; Jones et al. 2007, Lewis et al. 2009, Smith and Gaston 2012, Watanuki and Ito 2012, Cook et al. 2014; Burthe et al. 2014; Monticelli et al. 2014, Lewis et al. 2015, Zuberogoitia et al. 2016, Howells et al. 2017, Christensen-Dalsgaard et al. 2018, Pakanen 2018, Gardarsson and Jonsson 2019, Michielsen et al. 2019). The most likely mechanism underpinning temperature effects is via changes in the abundance and trophic matching of lower trophic levels with negative consequences on the availability of key prey to seabirds, notably lesser sandeels Ammodytes marinus (van Deurs et al. 2009, 2014; Engelhard et al, 2014; McDonald et al, 2015; Eerkes-Medrano et al. 2017; Regnier et al. 2019). Note that evidence for negative effects between temperature and productivity have not always been found - indeed, recent studies at two North Sea colonies did not find significant relationships between sea surface temperature and black-legged kittiwake breeding success (Carroll et al., 2017; Eerkes-Medrano et al. 2017). However, our results predicting a future decline in black-legged kittiwake productivity of approx. 19% (percentage points), linked to warming, matched closely the findings of Carroll et al. (2015) who showed that kittiwake breeding success is predicted to decline by 21-43% between 1961−90 and 2070−99. Sea surface salinity also played a role in resulting predictions for productivity declines in five species (
Table 14). We detected a negative link between productivity and sea surface salinity in four species (black-legged kittiwake, common guillemot, great black-backed gull and northern gannet), and a positive link in just one species, Atlantic puffin (
Table 14). Fewer studies have examined the relationship between seabird distribution or density and sea surface salinity than for sea surface temperature, and in general those studies that have considered salinity tend to suggest a positive association between seabird distribution or density with increasing salinity, linked to the degree of ocean mixing and its effects on prey availability (e.g., Balance 2007, Serratosa et al. 2020). However, this relationship has been shown to vary by species; Garthe (1997) found positive associations between sea surface salinity and the density of two species in the southern North Sea (Northern fulmar and common guillemot), but a negative association for five other species in that region, including black headed gull, common gull, herring gull, common tern and arctic tern. In our study, only one species (Atlantic puffin) showed a positive relationship between salinity and productivity, with four other species showing evidence for a negative relationship. This evidence points to sea surface salinity being a potentially strong indicator of seabird breeding success, and as such warrants further investigation as to the underlying mechanisms linking sea surface salinity to seabird demography. The mechanisms underpinning the positive effects of terrestrial rain on productivity apparent in some species is not clear, but overall these were not sufficiently strong to counteract the negative effects of temperature and, across most species, a predicted overall decline in breeding success in future.
An important finding was that pre-breeding conditions were generally more important than conditions during the breeding season, which may result from the effect of such conditions on the quality or abundance of prey during the period of peak energy demand during breeding, or may represent a carry-over effect whereby conditions experienced by seabirds in one season (in this case late winter) have downstream consequences on subsequent seasons (Daunt et al. 2014).
These declines in productivity, together with declines in at-sea density and shifts in range in certain species support past work on effects of climate warming on distribution and demography that threaten the future well-being of many breeding seabirds in the UK. However, a more positive outlook is apparent for northern gannet, whose productivity is predicted to increase and likely reflects its more catholic diet, with less dependence on prey species that are negatively affected by warming.
We used count and productivity data to estimate survival because it was the only approach that would allow us to study climate effects across multiple populations and species. Mark-recapture data are only available for a few species and sites, and therefore do not allow for a UK-wide multi-species assessment of relationships between adult survival and environmental variables. However, survival estimates derived from mark-recapture data are a significantly more powerful and reliable approach for estimating drivers of change in survival. For example, using that approach, Frederiksen et al. (2008) demonstrated the effect of wind on survival of European shags, whereas we could not detect any climatic effects in this species. Of more concern are cases where we found opposing results than published survival studies using mark recapture, such as the effects of warming on survival of black-legged kittiwakes. This, together with predictions of survival in our models that exceeded one, and the very low levels of explanatory power, leads us to conclude that estimating survival from counts and productivity using this method was not reliable within the timeframes of this project.
A further challenge is that for several species in this study – notably black-legged kittiwake and northern gannet – a considerable proportion of the adult population spends the winter outside UK waters. As such, the environmental variables used here may not be particularly relevant to survival prospects, because most adult mortality occurs at this time. Thus, incorporating environmental drivers at wintering grounds would potentially have provided important insights (Reiertsen et al. 2014).
Seabird Population Growth Rates
Using SMP count data to estimate population trends for seabirds has proved very difficult in previous projects (Searle et al. 2020). This is because of missing counts and extremely high uncertainty associated with model estimates. It is likely that the abundance data contain insufficient information to meaningfully constrain the parameters of trend models. Fitting models using non-Bayesian methods resulted in the detection of some significant effects of climate on population growth rates, however these models will have underestimated uncertainty, and could only be fitted to complete time-series of counts as they are unable to estimate counts in missing years. This means results from the non-Bayesian models are very limited in their application, and should be treated with considerable caution. Similarly, all population growth rate models had extremely low explanatory power, and therefore we were unable to generate predictions for future population growth rates using climate projections.
Given the strong influence of adult survival on population trends in seabirds, and the tendency for most adult mortality to occur overwinter, we might expect climate during the non-breeding period to exert the most influence on population growth rates, as was detected for three species (European shag, northern gannet, razorbill; Table 15). One species showed evidence for effects of climate on population growth rate over the whole year (herring gull), with two species having more evidence for climate impacts occurring over the summer (black-legged kittiwake, pre-breeding; great black-backed gull, breeding season; Table 15). These results suggest that both immediate effects of prevailing conditions and carry-over effects of previous seasons are important in determining demographic rates and, in turn, population growth rate, in line with findings from other studies (Oro & Furness 2002; Frederiksen et al. 2008; Erikstad et al. 2009; Bogdanova et al. 2011; Reiertsen et al. 2014; Daunt et al. 2014). Our results are in line with previous studies that have found links between population trends and sea surface temperature, with higher sea surface temperatures associated with lower population growth rates in both herring gull and northern gannet (Table 15). Similarly, we found a positive association between the strength of NAO and population growth rates in black-legged kittiwake, European shag and northern gannet. Finally, for marine variables, as with seabird productivity, we also detected significant effects of sea surface salinity on population growth rates in three species, with higher salinity associated with lower growth rates in black-legged kittiwake and razorbill, but with higher growth rates in herring gull (Table 15).
|Black-legged kittiwake||NAO +* Sea surface salinity -*||Wind speed +**||Pre-breeding|
|European shag||NAO +**||Non-breeding|
|Great black-backed gull||Rain +*||Wind speed +**||Breeding|
|Herring gull||Sea surface temp -** Sea surface salinity +**||Wind speed -**||All year|
|Northern gannet||NAO +* Sea surface temp -**||Temp +**||Non-breeding|
|Razorbill||Sea surface salinity -**||Wind speed +**||Non-breeding|
The future predictions of seabirds under projected warming of the climate investigated in this project suggest that there will be marked changes in at-sea density and productivity and moderate changes in distribution, which accords with previous work in this field largely undertaken in single populations and/or species. Importantly, our results suggest that potential declines in the future are expected to occur in a wider suite of species than has been demonstrated before. We have demonstrated important links between climate variables and seabird productivity. Strong declines in future productivity associated with climate change were predicted for four of the five species in which climate effects were detected. These changes will likely result in significant shifts in seabird population demography, trends and distribution over the coming decades, with consequences for the interaction of these species with offshore wind developments in the North Sea.
We also found evidence suggesting widespread declines in spatial habitat use among the majority of species, particularly for Atlantic puffin, but also for black-legged kittiwake, great black-backed gull, common guillemot, herring gull and razorbill. Puffin and kittiwake were predicted to decline in both summer and winter, whereas it was only the case for summer in common guillemot, herring gull and razorbill, and in winter in great black-backed gull. One species, razorbill, was predicted to increase its spatial habitat use of the North Sea in winter, and only one species, northern gannet, was predicted to increase its spatial habitat use of the North Sea in both summer and winter. This suggests that interactions between razorbill and northern gannet and ORDs may increase in the North Sea in coming decades. Relative distributional changes were apparent only in common guillemot and razorbill, which were predicted to see increases in the northern North Sea and decreases in the southern North Sea. This suggests that for these two species, impacts from offshore wind may be more strongly felt in Scottish populations than in English populations over future decades. Importantly, although changes in seasonal use were generally not forecasted, we did detect some evidence for a greater proportional use of the North Sea in winter for guillemots and razorbills, which implies a greater importance of assessing offshore wind impacts during the non-breeding season in coming decades for some species.
In general, our models for seabird productivity and population growth rates performed poorly in explaining the observed variation in the SMP dataset, despite identifying significant relationships between climate variables and demographic rates. This is not uncommon with ecological data, particularly, as is the case with the SMP, where there is likely to be significant sampling or observer error in counts and productivity data. Moreover, seabird demography will respond to environmental fluctuations from year to year, including lag effects, which are difficult to capture precisely with environmental variables that have relatively coarse spatial and temporal resolution. This is particularly true during the non-breeding season when a lack of knowledge inhibits strong spatio-temporal coherence between the habitats seabird populations are utilising and their associated climatic and environmental characteristics used within models. It is therefore, unsurprising that the models for productivity performed better, when individuals are constrained to forage within the vicinity of their breeding colony. The lack of explanatory power very much hinders our ability to make reliable future predictions for changes to seabird demography in response to changing climate. A key priority for future research will be to identify stronger associations between demographic rates and population trends and more refined, lagged climate variables, ideally collected with a greater spatio-temporal coherence to the habitat usage of individual populations across different seasons. In addition, there are other drivers of seabird population growth rate whose investigation was beyond the scope of this study. For example, the patterns observed in large gull species may have been affected by historic culls and current licensing regimes. Future modelling would ideally consider these additional factors in order to more accurately assess the effect of future climate change on these populations.
The results on survival rates derived from models using count and productivity data with assumed species-level estimates for juvenile survival, do not appear to have produced robust or defensible results. This arises from the inability to accurately estimate survival from population count data and productivity in datasets such as the SMP with a high incidence of missing data, considerable potential for observer variation and the potential influence of other factors (notably variation in immature survival rates and net movements) that may affect the link between productivity, adult survival and population size. Accordingly, a future priority is to increase the number of survival estimates obtained from mark-recapture data, which in some cases will require the development of new empirical studies of individually marked birds. A second priority is to address the drastic shortage of estimates of juvenile survival and net movements, which are only available for very few populations of a subset of species. A third priority is to undertake analyses using environmental variables that are more directly related to seabird distribution and demography, such as direct measures for prey availability and the inclusion of extreme weather events. However, although these will improve our explanatory power in retrospective analyses, there remains the limitation of working only with variables that are available in climate projections.
Implications for offshore wind assessments
The results of these analyses suggest that climate change will potentially have substantial impacts on demography and abundance of seabirds in the North Sea over the 21st century, and the impacts are likely to vary, in magnitude and form, between species.
Estimation of impacts
A failure to account for these changes in ORD assessments may lead to misidentification of the key affected populations, as well as misjudgement of the extent to which seabirds are likely to interact with ORDs over time, and inclusion in assessments could be considered at the scoping stage of the EIA process. Climate-induced changes to the spatial distribution of seabirds within the North Sea reveal that habitat use in UK seabirds will not be static over the coming decades. Any directional shift in habitat use, from South to North, will mean that the number and source populations of individual birds interacting with specific ORD footprints will alter over time. This could mean that a static assessment identifying the protected populations of concern using apportioning methods applied to current day distributions could fail to identify populations that would come to interact with those footprints as their population sizes evolve over time, and their spatial habitat use changes in coming decades. For example, smaller populations to the North may increase in abundance as climate shifts prey suitability northwards, expanding their foraging ranges as a result of density-dependent interactions with conspecifics, and thereby starting to interact with an ORD footprint with which they previously had no contact. Similarly, the evidence supporting potential seasonal shifts in habitat use of the North Sea for two species suggests that the seasonal period of greatest importance for ORD impacts on protected populations may change as climate alters. If species begin to use the North Sea proportionately more in the overwinter period than the breeding season, ORD impact assessments in the non-breeding season will become more critical to performing robust and accurate assessments. This is particularly problematic because at present, available methods for assessing impacts of ORD in the non-breeding season, and apportioning impacts back to protected colonies, are much cruder than those available for the breeding season. Moreover, it will become increasingly important that cross-border efforts to assess impacts for seabirds originating from different countries are better developed (e.g., MarPAMM project, 2022), because the ratio of seabirds from UK and non-UK populations in the North Sea during winter is likely to alter under future climate change.
Population Viability Analysis
Population Viability Analysis (PVA) methods use population models to quantify the projected impacts of offshore renewable energy developments (ORD) upon seabird and abundance, using estimates of annual effects on demography as a result of collision, displacement and barrier effects.
The PVAs used in assessing impacts of ORD developments do not currently account for climate change, but the results of this project imply that it could be potentially important to account for climate change when running PVAs. Climate change impacts on productivity were estimated to be negative for four species in this study, which implies that the absolute condition or conservation status of populations under ORD impacts (e.g., quasi-extinction probabilities) may be substantially under-estimated when the impacts of climate change are ignored within PVAs. It is not clear, however, that relative comparisons relating to ORD (e.g. comparisons of growth rates under ORD impacts and baseline conditions) would necessarily be systematically under-estimated as a result of failing to account for climate change effects. Under-estimation of relative impacts may occur if there are interactions between climate and ORD effects, but additional work would be needed (e.g. via individual-based modelling) to understand whether such interactions actually exist, and what form they take. The implications of the current project are also complicated by the fact that our assessments, of necessity, focused upon change over a longer period (baseline period until 2070-2099) than the periods, of up to 30 years, typically considered in assessments of ORD impacts, so it is not clear if the consequences of climate change for estimates of ORD impacts will be as great, over these shorter periods, as the results of this project may initially suggest.
It is technically feasible to modify PVAs so that they can incorporate the sort of climate impacts that we have estimated within this project, because the models used in PVAs have the same basic structure (stochastic Leslie matrix models) as the models considered here. One key practical challenge in incorporating climate change into PVA models, however, would be the need to consider much shorter periods of time than those considered here (e.g. changes over the next 10 years or 30 years, rather than over the entire course of the 21st century), and the need to consider multiple emissions scenarios (to reflect uncertainty about actual future emissions). The models that we have developed in this project could easily be used to produce projections of seabird demography and abundance for other periods, or under other scenarios, once relevant marine and terrestrial climate projections become available (e.g. through UKCP18). Similarly, climate projections would need to be available for each future year within the PVA so as to be able to generate climate-driven changes to demographic rates at each time step.
The other key challenge in incorporating climate change into PVA models is the low explanatory power of the models considered in this project, which implies that the models are not capturing the full range of climate and non-climate variables that influence changes in population demography and abundance. This low explanatory power means that the predictions produced by models should be treated with substantial caution. We would suggest that the predictions produce by the models we have fitted here should not be over-interpreted, but that there is likely to be value in applying PVA models with and without climate change impacts, to see the extent to which these differ, and to examine whether PVAs that ignore climate change are likely to systematically under-estimate key metrics of ORD impacts.
It is increasingly recognised that the scale of ORD development in the North Sea will necessitate the use of compensatory measures to counteract the negative impacts arising from collision, displacement and barrier effects on seabirds. Compensatory measures are best applied strategically across the Natura 2000 Network in order to maintain the coherence of the Natura 2000 network. Strategic implementation of compensatory measures for ORDs requires an understanding of the population status and trends across colonies comprising the network, and the mechanisms for any strong declines. This is because the application of compensatory measures in strongly declining populations are unlikely to result in a net gain of individuals, potentially applying efforts that ultimately fail to contribute to the overall coherence and integrity of the Natura 2000 network. Similarly, a lack of understanding for the reasons of climate-induced changes to population trends could undermine the success of specific compensatory measures. For example, if a population is declining primarily due to declines in prey availability within the foraging range of the breeding colony then compensatory measures such as artificial nest creation may not result in an increase in productivity due unless nest site availability is also limiting breeding population size.
Recommendations and future work
Ideally, methods for conducting assessments of ORD impacts should be developed so as to allow for a year by year prediction of the spatial habitat use, demography and abundance of protected seabird populations. This would allow estimated impacts to evolve dynamically through time as climate-driven changes to species' ecology occur. This is true for both the estimation of impacts (changes to demographic rates and abundance arising from collision, displacement and barrier effects), and their use within PVA models incorporating climate-induced changes to demographic rates. Developing such a framework is, in principle, straightforward, but is currently hindered by a lack of empirical understanding for how seabird space use and demography will change through time as future climate change occurs. This understanding requires the projection of seabird distribution and demography for each future year in which an assessment is required. Without this empirical quantification it is not currently possible to estimate ORD impacts on a year by year basis in a predictive way, or to robustly account for climate induced changes to demographic rates within PVAs.
Our results have also demonstrated the difficulty in estimating survival rates of seabird populations from abundance and productivity data. More sophisticated statistical methods may yield more defensible estimates of survival, but this is only likely to be successful if these approaches can accurately capture the observation processes associated with collection of count and nest monitoring data within the SMP. This is not straightforward, and requires considerable understanding of the form and magnitude of the errors and biases associated with the data collection process. For example, whole colony counts are typically undertaken once in a given year, precluding an estimate of error in the estimate. Further, levels of observation error are likely to be higher in colonies where these have been derived from plot counts that in colonies where whole colony counts have been taken, but this difference can only be quantified through detailed modelling of the relationship between plot-level and colony-level counts – and this relies, in turn, upon modelling the process by which plots are selected. Collection of empirical data on adult survival at more colonies and for more species, through mark-recapture studies, is a critical data gap which would facilitate more defensible use of survival rates within PVA models. Another key priority is to obtain more empirical data on immature survival rates and net movements between colonies, in order to improve accuracies of population forecasts. However, these would not immediately help with identifying climate effects on survival because this requires long time-series of survival data to robustly link with climate variables.
A key finding is that the overwintering period may become more dominant in determining ORD impacts on two UK seabird species, and this highlights the need for future work to develop both impact estimation and apportioning methods in this critical seasonal period. Overall, our results are important because these effects of climate change are of direct relevance to assessments of ORDs, creating complex interactions that could have a significant bearing on the effect of the ORD on protected populations over the lifespan of the project. Our results are also relevant to other key policy initiatives, such as marine protection. We strongly encourage that climate change effects are incorporated into ORD assessments and conservation designation in future.
This project was funded by the Scottish Government, through Marine Scotland. We particularly wish to thank the project steering group for their time and assistance with the science and reporting of this project: Tom Evans, Janelle Braithwaite, Finlay Bennet, Erica Knott, Lucy Quinn, & Kerstin Kober. We also wish to thank Jonathan Tinker at the MET Office for providing climate indices and Gerard McCarthy (ICARUS; Irish Climate Research and Analysis Unit) for his assistance with interpretation of climate variables; and Mark Lewis (JNCC), Jared Wilson (MSS), Grant Humphries (Hi-Def), Nicolas Vanermen, Eric Stienen (both Research Institute for Nature and Forest) and Gareth Bradbury (WWT) for providing at-sea data. SMP data were extracted from JNCC's online database at www.jncc.gov.uk/smp. These data were provided to the SMP by the generous contributions of its partners: BirdWatch Ireland, British Trust for Ornithology, Natural Resources Wales, Department of Environment, Food and Agriculture (Isle of Man), Department of Environment, Heritage and Local Government (Republic of Ireland), States of Guernsey Government, Joint Nature Conservation Committee, Manx Birdlife, Manx National Heritage, The National Trust, The National Trust for Scotland, Natural England, NatureScot, Northern Ireland Environment Agency, Royal Society for the Protection of Birds, Scottish Wildlife Trust, The Seabird Group, Shetland Oil Terminal Environmental Advisory Group and UK Centre for Ecology & Hydrology. UKCEH's long-term study on the Isle of May was supported by Natural Environment Research Council Award number NE/R016429/1 as part of the UK-SCaPE programme delivering National Capability and the Joint Nature Conservation Committee.
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