SummaryAn analysis of incidence of Phytophthora spp. in 732 European nurseries producing forest transplants, larger specimen trees, landscape plants and ornamentals, plus 2525 areas in which trees and shrubs were planted, is presented based on work conducted by 38 research groups in 23 European countries between 1972 and 2013. Forty-nine Phytophthora taxa were recorded in 670 nurseries (91.5%); within these nurseries, 1614 of 1992 nursery stands (81.0%) were infested, although most affected plants appeared healthy. In forest and landscape plantings, 56 Phytophthora taxa were recovered from 1667 of 2525 tested sites (66.0%). Affected plants frequently showed symptoms such as crown thinning, chlorosis and dieback caused by extensive fine root losses and/or collar rot. Many well-known highly damaging host-Phytophthora combinations were frequently detected but 297 and 407 new Phytophthora-host associations were also observed in nurseries and plantings, respectively. On average, 1.3 Phytophthora species/taxa per infested nursery stand and planting site were isolated. At least 47 of the 68 Phytophthora species/taxa detected in nurseries and plantings were exotic species several of which are considered well established in both nurseries and plantings in Europe. Seven known Phytophthora species/taxa were found for the first For. Path. 46 (2016) 134-163 doi: 10.1111/efp.12239 © 2015 http://wileyonlinelibrary.com/ time in Europe, while 10 taxa had not been previously recorded from nurseries or plantings; in addition, 5 taxa were first detections on woody plant species. Seven Phytophthora taxa were previously unknown to science. The reasons for these failures of plant biosecurity in Europe, implications for forest and semi-natural ecosystems and possible ways to improve biosecurity are discussed.

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This paper describes the data set from the 6540‐km2 Goulburn River experimental catchment in New South Wales, Australia. Data have been archived from this experimental catchment since its inception in September 2002. Land use in the northern half of the catchment is predominantly cropping and grazing on basalt‐derived soils, with the south being cattle and sheep grazing on sandstone‐derived soils; only the floodplains are cleared of trees in the south. Monitoring sites are mainly concentrated in the nested Merriwa (651 km2) and Krui (562 km2) subcatchments in the northern half of this experimental catchment with a few monitoring sites located in the south. The data set comprises soil temperature and moisture profile measurements from 26 locations; meteorological data from two automated weather stations (data from a further three stations are available from other sources) including precipitation, atmospheric pressure, air temperature and relative humidity, wind speed and direction, soil heat flux, and up‐ and down‐welling short‐ and long‐wave radiation; streamflow observations at five nested locations (data from a further three locations are available from other sources); a total of three surface soil moisture maps across a 40 km × 50 km region in the north from ∼200 measurement locations during intensive field campaigns; and a high‐resolution digital elevation model (DEM) of a 175‐ha microcatchment in the Krui catchment. These data are available on the World Wide Web at http://www.sasmas.unimelb.edu.au.

The recently released Shuttle Radar Topography Mission (SRTM) 3-arc second digital elevation data set provides a complete global coverage of the Earth's land surface. In this paper we examine the SRTM data for three catchments in Australia over a range of climates, geology and resultant geomorphology. To test this new data set the SRTM data are compared with high resolution digital elevation models. We use basic hydrological and geomorphological statistics and descriptors such as the area-slope relationship, cumulative area distribution and hypsometric curve, along with Strahler and networking statistics. The above measures describe the surface morphology of a catchment, therefore integrating catchment geology, climate and vegetation. The SRTM data were also assessed as input into the SIBERIA landscape evolution and soil erosion model as were runoff properties, using a wetness index. The results demonstrate that the 90 m SRTM data provide a poor catchment representation. Hillslopes appear as a linked set of facets and display little of the complex curvature that is observed in high resolution data. While catchment area-slope and areaelevation (hypsometry) properties are largely correct, catchment area, relief and shape (as measured by the width function) are poorly captured by the SRTM data. Catchment networking statistics are also variable. The large grid size of the SRTM data also results in incorrect drainage network patterns and different runoff properties. Consequently, care must be used for quantitative assessment of catchment hydrology and geomorphology, as in all cases SRTM-derived catchment area is incorrect and smaller digital elevation grid sizes are required for accurate catchment-wide assessment. While only a limited number of catchments have been examined, we believe our findings are applicable to other areas. © Crown Figure 1. Tin Camp Creek catchment with a high resolution 10 m by 10 m DEM (top), regridded 90 m by 90 m DEM (middle), and 90 m by 90 m SRTM DEM (bottom). is located in the wet/dry tropics region and has a climate very similar to Tin Camp Creek (Saynor et al., 2004). The catchment is located on the Arnhem Land sandstone plateau and flows to the Magela Creek floodplain. In this study we examine a major tributary of Swift Creek -East Tributary. The upper reaches of the study catchment flow through a sandstone-bedrock-confined channel on the plateau. The catchment then flows onto a wooded lowland Digital elevation models in catchment geomorphology and hydrology 1397 Figure 2. Swift Creek catchment with high resolution 20 m by 20 m DEM (top), regridded 90 m by 90 m DEM (middle), and 90 m by 90 m SRTM DEM (bottom). The 10 m grid digital elevation model for Tin Camp Creek displays well-rounded hillslope of regular curvature and hillslope length over the entire domain, and is well dissected by a regularly spaced drainage network (Figure 1). Digital elevation models in catchment geomorphology and hydrology 1401 Figure 4. Area-slope relationship for Tin Camp Creek (top), Swift Creek (middle) an...