Spatial Gaussian processes improve multi‐species occupancy models when range boundaries are uncertain and nonoverlapping

A within-lake occupancy model for starry stonewort, Nitellopsis obtusa, to support early detection and monitoring

To efficiently detect aquatic invasive species early in an invasion when control may still be possible, predictions about which locations are likeliest to be occupied are needed at fine scales but are rarely available. Occupancy modeling could provide such predictions given data of sufficient quality and quantity. We assembled a data set for the macroalga starry stonewort (Nitellopsis obtusa) across Minnesota and Wisconsin, USA, where it is a new and high-priority invader. We used these data to construct a multi-season, single-species spatial occupancy model that included biotic, abiotic, and movement-related predictors. Distance to the nearest access was an important occurrence predictor, highlighting the likely role boats play in spreading starry stonewort. Fetch and water depth also predicted occupancy. We estimated an average detection probability of 63% at sites with mean non-N. obtusa plant cover, declining to ~ 38% at sites with abundant plant cover, especially that of other Characeae. We recommend that surveyors preferentially search for starry stonewort in areas of shallow depth and high fetch close to boat accesses. We also recommend searching during late summer/early fall when detection is likelier. This study illustrates the utility of fine-scale occupancy modeling for predicting the locations of nascent populations of difficult-to-detect species.

Context matters in ecological forecasting: Lessons in predicting species distributions

Forecasting the future state of a species is a tricky process, as there are numerous hidden factors that influence species trajectories in addition to the obvious unknowns about the future state of the planet. We echo the guidance of Clare et al. (2024) to use near‐term and long‐term forecasting in complementary ways. Near‐term forecasts can be used to guide specific management and conservation actions, which can be updated as new data and evidence are collected. Long‐term forecasts can be used to characterize uncertainty further into the future, which can help guide longstanding conservation planning and legislative actions that are based on such uncertainty in possible future outcomes.

A gradual migratory divide determines not only the direction of migration but also migration strategy of a social migrant bird

Migratory divides separate populations of migratory animals, facilitating the evolution of intraspecific differences in migration strategies. Migration strategies are expected to be different for birds using different flyways and environments, but the knowledge regarding the impact of the flyway on individual migration strategies is scarce. By using satellite tracking and neckband resightings, we reveal the existence and structure of a gradual migratory divide between two European flyway populations of greylag geese Anser anser. Birds breeding at the far end of the Gulf of Bothnia in the Baltic Sea coast use the Western Flyway, those breeding in the Gulf of Finland the Central Flyway and those breeding between these extremes scatter to the two flyways. By using Gaussian process modelling, we show that migration strategies differed between the flyways. The birds using the Western Flyway migrated earlier in autumn, performed longer annual migration and made a clear stopover during migration, whereas the birds using the Central Flyway flew directly to their wintering sites. The gradual migratory divide that also divides migration strategies provides insights into migratory divides on birds with learned migration. Distinct migration strategies in different flyways provide exciting possibilities to further study the factors driving migration strategies.