The ADnet Bayesian belief network for alder decline: Integrating empirical data and expert knowledge.

The globalization in plant material trading has caused the emergence of invasive pests in many ecosystems, such as the alder pathogen Phytophthora ×alni in European riparian forests. Due to the ecological importance of alder to the functioning of rivers and the increasing incidence of P. ×alni-induced alder decline, effective and accessible decision tools are required to help managers and stakeholders control the disease. This study proposes a Bayesian belief network methodology to integrate diverse information on the factors affecting the survival and infection ability of P. ×alni in riparian habitats to help predict and manage disease incidence. The resulting Alder Decline Network (ADnet) management tool integrates information about alder decline from scientific literature, expert knowledge and empirical data. Expert knowledge was gathered through elicitation techniques that included 19 experts from 12 institutions and 8 countries. An original dataset was created covering 1189 European locations, from which P. ×alni occurrence was modeled based on bioclimatic variables. ADnet uncertainty was evaluated through its sensitivity to changes in states and three scenario analyses. The ADnet tool indicated that mild temperatures and high precipitation are key factors favoring pathogen survival. Flood timing, water velocity, and soil type have the strongest influence on disease incidence. ADnet can support ecosystem management decisions and knowledge transfer to address P. ×alni-induced alder decline at local or regional levels across Europe. Management actions such as avoiding the planting of potentially infected trees or removing man-made structures that increase the flooding period in disease-affected sites could decrease the incidence of alder disease in riparian forests and limit its spread. The coverage of the ADnet tool can be expanded by updating data on the pathogen's occurrence, particularly from its distributional limits. Research on the role of genetic variability in alder susceptibility and pathogen virulence may also help improve future ADnet versions.

Historical disconnection from floodplain alters riparian forest composition, tree growth and deadwood amount.

Riparian forests are among the most dynamic but threatened terrestrial ecosystems. Their dynamism and conservation depend on historical changes in river geomorphology, which can be evaluated through changes in channel sinuosity. However, we lack long-term assessments on sinuosity and how they impact riparian forest composition, tree growth and deadwood amount. To fill this research gap, we reconstructed river sinuosity in 14 sites across the middle Ebro basin, north-eastern Spain, using historical aerial photographs taken in 1927, 1956, 1998-2003 and 2014-2015. Relationships between sinuosity, stand composition and deadwood amount and decay degree were calculated. We also reconstructed radial growth of the major tree species (Populus alba, Populus nigra, Fraxinus angustifolia, Salix alba and Ulmus minor) in two sites to evaluate how coupled it was with changes in river flow after dam building. From 1927 to 2015, sinuosity decreased passing from 1.39 to 1.20. The river dynamics were altered in the 1950s and 1960s after dam and dyke building. Sites with high sinuosity values in 1956 corresponded to mature stands with large P. nigra individuals. Sinuosity was negatively related to F. angustifolia (rs = -0.83, p < 0.001) and P. alba (rs = -0.64, p = 0.02) abundance, whereas sites dominated by P. alba and U. minor presented abundant decayed deadwood. A loss of sinuosity and a contraction of the riverbank gradient increased disconnection of active channel from floodplain, with a mixing of more (e.g., P. nigra) and less phreatophytic species (e.g., U. minor). River flow diversion reduced growth and increased the tree-to-tree P. alba growth coherence. Hydrological droughts contributed to growth decline and dieback of U. minor, which is sensitive to spring river flow. Conservation and restoration of riparian forests must consider historical changes in river geomorphology related to human activities.

Modeling the evolution of riparian woodlands facing climate change in three European rivers with contrasting flow regimes.

Global circulation models forecasts indicate a future temperature and rainfall pattern modification worldwide. Such phenomena will become particularly evident in Europe where climate modifications could be more severe than the average change at the global level. As such, river flow regimes are expected to change, with resultant impacts on aquatic and riparian ecosystems. Riparian woodlands are among the most endangered ecosystems on earth and provide vital services to interconnected ecosystems and human societies. However, they have not been the object of many studies designed to spatially and temporally quantify how these ecosystems will react to climate change-induced flow regimes. Our goal was to assess the effects of climate-changed flow regimes on the existing riparian vegetation of three different European flow regimes. Cases studies were selected in the light of the most common watershed alimentation modes occurring across European regions, with the objective of appraising expected alterations in the riparian elements of fluvial systems due to climate change. Riparian vegetation modeling was performed using the CASiMiR-vegetation model, which bases its computation on the fluvial disturbance of the riparian patch mosaic. Modeling results show that riparian woodlands may undergo not only at least moderate changes for all flow regimes, but also some dramatic adjustments in specific areas of particular vegetation development stages. There are circumstances in which complete annihilation is feasible. Pluvial flow regimes, like the ones in southern European rivers, are those likely to experience more pronounced changes. Furthermore, regardless of the flow regime, younger and more water-dependent individuals are expected to be the most affected by climate change.