Integration of juvenile habitat quality and river connectivity models to understand and prioritise the management of barriers for Atlantic salmon populations across spatial scales.

Diadromous fish populations are strongly affected by in-stream barriers that cause river network fragmentation, constraining productivity or preventing completion of their lifecycle. Removal or reduction of barrier impacts is a restoration measure associated with unambiguous benefits. Management of barriers is therefore often prioritised above other restoration actions. Barrier management is prioritised at local and national scales depending on funding. However, barrier prioritisation is potentially sub-optimal because existing tools do not consider habitat quality. Furthermore, effects of partial barriers (those passable under certain conditions) are uncertain, depending on location and potential cumulative effects. A framework is presented for assessing effects of impassable manmade barriers (IMBs) on longitudinal river network connectivity (percentage of upstream habitat accessible from the river mouth) for Atlantic salmon across spatial scales, using Scotland as an example. The framework integrates juvenile habitat quality and network connectivity models to (1) provide information necessary for local and national prioritisation of barriers, and (2) assess potential effects of passable manmade barriers (PMBs) within a sensitivity framework. If only IMBs are considered, high levels of longitudinal connectivity are observed across most of Scotland's rivers. Barrier prioritisation is sensitive to habitat weighting: not accounting for habitat quality can lead to over- or underestimating the importance of IMBs. Prioritisation is also highly sensitive to the passability of PMBs: if passability drops to <97% (combined up- and downstream passability), the mean effect of PMBs becomes greater than IMBs at the national level. Moreover, impacts on catchment connectivity, and thus production (number of juvenile salmon produced by the river), could be severe, suggesting a better understanding of the passability of PMBs is important for future management of migration barriers. The presented framework can be transferred to other catchments, regions, or countries where necessary data are available, making it a valuable tool to the broader restoration community.

A spatio-temporal statistical model of maximum daily river temperatures to inform the management of Scotland's Atlantic salmon rivers under climate change.

The thermal suitability of riverine habitats for cold water adapted species may be reduced under climate change. Riparian tree planting is a practical climate change mitigation measure, but it is often unclear where to focus effort for maximum benefit. Recent developments in data collection, monitoring and statistical methods have facilitated the development of increasingly sophisticated river temperature models capable of predicting spatial variability at large scales appropriate to management. In parallel, improvements in temporal river temperature models have increased the accuracy of temperature predictions at individual sites. This study developed a novel large scale spatio-temporal model of maximum daily river temperature (Twmax) for Scotland that predicts variability in both river temperature and climate sensitivity. Twmax was modelled as a linear function of maximum daily air temperature (Tamax), with the slope and intercept allowed to vary as a smooth function of day of the year (DoY) and further modified by landscape covariates including elevation, channel orientation and riparian woodland. Spatial correlation in Twmax was modelled at two scales; (1) river network (2) regional. Temporal correlation was addressed through an autoregressive (AR1) error structure for observations within sites. Additional site level variability was modelled with random effects. The resulting model was used to map (1) spatial variability in predicted Twmax under current (but extreme) climate conditions (2) the sensitivity of rivers to climate variability and (3) the effects of riparian tree planting. These visualisations provide innovative tools for informing fisheries and land-use management under current and future climate.