Linking demographic theory and data to forecast the dynamics of spatially-structured seasonally-mobile populations

Wild populations are facing unprecedented threats. Many habitats are naturally patchy or being fragmented by human activities. Many habitats also show seasonal variation in suitability, and climate models predict increasing frequencies of extreme seasonal weather events (e.g. storms, droughts, floods) that could cause high mortality or prevent reproduction in affected areas. Critical aims in ecology are therefore to understand and forecast the dynamics and persistence of populations inhabiting spatially-structured seasonal environments, including population responses to extreme seasonal events that alter demography.

Spatio-temporal population dynamics ultimately depend on four primary demographic rates: survival, reproduction, dispersal (permanent movements among breeding areas) and migration (reversible seasonal movements). However, to date, no empirical studies or population dynamic theory or models have fully quantified or considered spatio-temporal variation in migration alongside variation in survival, dispersal and reproduction. We consequently lack data, theory and models that quantify population dynamic effects of variation in and among all four key demographic rates, severely limiting our ability to forecast the dynamics of spatially-structured seasonally-mobile populations.

It is now clear that partial migration, where populations comprise mixtures of resident and migrant individuals, is very common in nature. Partially-migratory populations could show complex demography and dynamics because structured variation in migration could cause structured variation in current or subsequent survival, dispersal or reproduction, while extreme events could cause irruptive migration. Population dynamic models and empirical studies that ignore spatio-temporal variation in migration, and resulting carry-over effects, therefore ignore fundamental axes of demographic variation.

We will provide new empirical and theoretical understanding of the demography and dynamics of spatially-structured seasonally-mobile populations, and new capability for population dynamic forecasting, by:

1) Providing first empirical estimates of key demographic rates and relationships that drive population dynamics, including demographic responses to extreme events.

We will use an outstanding large-scale multi-year dataset that we have collected on a spatially-structured partially-migratory European shag population. During 2009-2017 we marked 14,500 individuals across 6 breeding colonies, collected 44,200 winter sightings to identify residents and migrants, and measured individual dispersal and reproduction. In 2012-2014, the system experienced extreme winter storms, causing high mortality. This system now provides an unrivalled opportunity to quantify sex-, age- and sub-population-specific variation in individual migration, and covariation with survival, dispersal and reproduction, before, during and after natural extreme seasonal events.

2) Providing new theory that identifies general principles of population dynamic responses to seasonal demographic variation.

We will build and analyse individual-based simulation models that quantify population consequences of demographic covariation involving migration. We will quantify sensitivities of population growth rate to hypothesised forms of structured partial migration and covariation with survival, dispersal and reproduction given varying life-histories and spatial habitat structures, and to hypothesised regimes of extreme events and resulting demographic perturbations.

3) Providing a new flexible modelling framework for forecasting spatio-temporal population dynamics.

We will build new migration models into our state-of-the-art 'RangeShifter' software for spatially-explicit population dynamic modelling and simulate spatio-temporal dynamics of the exemplar European shag system, thereby demonstrating new flexible forecasting capability and informing conservation policy.

Our project will achieve two major dimensions of economic and societal impact:

1) It will shape development of conservation policy for spatially-structured seasonally-mobile populations, which aims to maximize protection whilst supporting sustainable economic development.

2) It will facilitate 'citizen science' participation in cutting-edge science, and associated public understanding of science.

Under these two themes, our project will benefit the following stakeholders:

1i) National and devolved governments (Department of Environment, Food & Rural Affairs; Scottish Government) and their statutory advisers (Joint Nature Conservation Committee; Natural England; Scottish Natural Heritage) will benefit from new data, models and understanding that they urgently require to support conservation policy for seasonally-mobile species, many of which are of high conservation concern (e.g. great crested newt, harbour porpoise, kittiwake). Until recently, the degree of seasonal mobility of individuals in such populations was not fully appreciated. Consequently, conservation policy has often focused primarily on breeding areas and failed to provide effective protection in winter. European shags provide a striking example. The UK holds 34% of the world population, but UK populations have decreased by >30% since 2000. While major breeding colonies are designated Special Protection Areas (SPAs), existing policy provides no robust mechanism for conservation management in winter, potentially leaving UK populations at risk from marine developments and undermining investment in breeding area SPAs.

Government advisers recognise the limitations of current policy for seasonally-mobile species, and are currently developing new initiatives to deliver year-round conservation. They plan to adapt environmental assessment processes to include seasonal movements, and to develop integrated management approaches that combine site protection (Special Areas of Conservation; Special Protection Areas) with other management tools (e.g. agri-environment schemes, fisheries management). To support these initiatives, key advisers seek our data and models to develop good practice guidelines for conservation of seasonally-mobile species in general, and to establish the European shag as a flagship example of effective management of a partially-migratory species of high conservation concern.

1ii) Industrial developers (e.g. onshore and offshore renewable energy developers) will benefit from new data, models and understanding of seasonally-mobile populations, because resulting knowledge will expedite environmental assessments in line with policy directives. Lack of such data and knowledge has recently caused consenting delays, with major economic implications.

1iii) Non-Governmental Organisations (e.g. Royal Society for the Protection of Birds; Marine Conservation Society; National Trust) will benefit from new understanding of the demographic consequences of extreme weather for seasonally-mobile populations that they aim to conserve.

2) General public. It is increasingly recognised that science, and public understanding of science, can be jointly facilitated by public 'citizen science' participation in data collection. Our large-scale ringing and sighting field study provides an opportunity for extensive public participation, exemplifying how 'citizen science' can generate policy-relevant data and public understanding. Our project will benefit interested public (e.g. birdwatchers, naturalists, photographers) by providing supported opportunities to increase their knowledge of natural history and ecology. It will add substantial value to amateur-led bird-ringing projects and the NGOs that support them (e.g. British Trust for Ornithology). Finally, our project will benefit wider society by providing new understanding of challenges facing UK wildlife populations, including charismatic species in which there is substantial public interest.