Climate acts as an environmental filter to plant pathogens

Abstract Climate shapes the distribution of plant-associated microbes such as mycorrhizal and endophytic fungi. However, the role of climate in plant pathogen community assembly is less understood. Here, we explored the role of climate in the assembly of Phytophthora communities at >250 sites along a latitudinal gradient from Spain to northern Sweden and an altitudinal gradient from the Spanish Pyrenees to lowland areas. Communities were detected by ITS sequencing of river filtrates. Mediation analysis supported the role of climate in the biogeography of Phytophthora and ruled out other environmental factors such as geography or tree diversity. Comparisons of functional and species diversity showed that environmental filtering dominated over competitive exclusion in Europe. Temperature and precipitation acted as environmental filters at different extremes of the gradients. In northern regions, winter temperatures acted as an environmental filter on Phytophthora community assembly, selecting species adapted to survive low minimum temperatures. In southern latitudes, a hot dry climate was the main environmental filter, resulting in communities dominated by drought-tolerant Phytophthora species with thick oospore walls, a high optimum temperature for growth, and a high maximum temperature limit for growth. By taking a community ecology approach, we show that the establishment of Phytophthora plant pathogens in Europe is mainly restricted by cold temperatures.

Table S1.Functional traits of Phytophthora used for functional diversity analyses.
Table S2.Phytophthora species detected along the altitudinal and latitudinal gradients.
Table S3.Association between Phytophthora species during autumn and environmental factors.
Table S4.Association between Phytophthora species during spring and environmental factors.

Methods S1. Stream surveys and determination of water chemistry parameters.
We surveyed a total of 263 streams along two gradients, i.e., altitudinal and latitudinal (Fig. 1a).For the altitudinal gradient survey, 118 streams from independent watersheds were sampled in Catalonia (NE Spain) in the spring and autumn in 2018 and 2019 (Supplementary Information Fig. S1).The latitudinal gradient survey comprised 183 stream sites ranging from NE Spain to northern Sweden: 21 streams were surveyed in Brittany (NW France) between June and August 2018; 15 streams were surveyed in Ireland during the spring months of 2020; 16 rivers in southern Sweden were each sampled at six different sites (with an average distance of ca.20 km between sites) along their catchments (i.e., 96 sites in total) between August and October 2013, and again in 2014; 13 streams were surveyed in northern Sweden during August 2017; and 38 of the streams that were sampled as part of the altitudinal gradient survey in Spain in the autumn were also included in the latitudinal survey.These 38 streams were at an elevation of <479 m above sea level (m.a.s.l.), equivalent to the elevation of the highest site in the latitudinal gradient survey.The altitudinal gradient covered a stream network ranging from 53 to 1724 m.a.s.l., covering a range of climatic conditions (with mean annual temperatures ranging from 7.1 to 17.2°C and total annual precipitation ranging from 388 to 1180 mm) (Fig. 1d).The latitudinal gradient ranged from 40.9 to 68.4°N, covering areas with mean annual temperatures ranging from -3.1 to 17.2°C and total precipitation ranging from 388 to 1549 mm (Fig. 1d).Although no correlation between temperature and precipitation was found along the latitudinal gradient (Fig. 1b), temperature and precipitation were negatively correlated along the altitudinal gradient (Fig. 1c).Sampling locations were chosen on the basis that they had an upstream catchment area that was mainly forest with a minimal presence of agricultural land or urban areas and that they were easily accessible.
Sampling was carried out by collecting 6 l of water at each site, which were subsequently filtered through an 8-µm membrane (Merck Millipore, Cork, Ireland) attached to the pump of an agricultural hand sprayer with a polysulfone filter holder [1].Samples collected in France were filtered through a 5-µm membrane.Membranes were replaced every time they became obstructed until the entire 6 l sample had been filtered.Membranes were stored in Petri dishes at 5°C before transportation to the laboratory and then stored at −20°C until processed for DNA extraction.Pumps were rinsed with 5% sodium hypochlorite and distilled water between sampling sites to avoid cross-contamination.
During the altitudinal gradient survey in the spring of 2019, water samples were collected at each sampling site in 60-ml syringes.These samples were filtered through pre-combusted (450°C) GF/F filters (Whatman, Maidstone, UK) and stored in pre-combusted 42-ml glass vials at 4°C.Samples were analysed by the Catalan Institute for Water Research (ICRA) to determine the following parameters: the concentration of dissolved organic carbon (DOC) in samples acidified to pH 2-3 and using a Shimadzu TOC-V CSH analyser (Japan), the specific ultraviolet absorbance at 254 nm [2] (SUVA254) using an Agilent 8453 diode array spectrophotometer, and the fluorescence index (FI), humidification index (HIX) and specific fluorescence at various peaks (A, C, M, T, B), which were obtained using an F-7000 spectrofluorometer (Hitachi, Japan) according to previously described procedures [3].

1.
Redondo MA, Boberg J, Stenlid J, Oliva J. Contrasting distribution patterns between aquatic and terrestrial Phytophthora species along a climatic gradient are linked to functional traits.Mean annual temperature (°C) Oospore wall index

Figs. S1 .
Figs. S1.Location of the surveyed streams of the altitudinal gradient.

Fig. S2 .
Fig. S2.Density of Phytophthora species based on their residence time.

Fig. S5 .
Fig. S5.Association between functional traits of Phytophthora communities and climate.

Fig. S6 .
Fig. S6.Distribution of functional traits of Phytophthora communities of "old" terrestrial

Fig. S1 .
Fig. S1.Location of the surveyed streams of the altitudinal gradient.a,b, Location of (a) Fig. S2.Density of Phytophthora species based on their residence time."Old species"

Fig. S6 .
Fig. S6.Distribution of functional traits of Phytophthora communities of old terrestrial

Obtention of climatic and vegetation data.
Pastor A, Borrego CM, Casas-Ruiz JP, Hawkes JA, Gutiérrez C, et al.The relevance of environment vs. composition on dissolved organic matter degradation in freshwaters.Limnol Oceanogr 2021; 66: 306-320.Climatic data for the altitudinal gradient sampling plots were obtained from the Meteorological Service of Catalonia website (https://www.meteo.cat).These data were processed with the "meteoland" package[4]in R to obtain monthly mean temperature and precipitation values for 1976 to 2020.Climatic data for the latitudinal gradient sampling plots (i.e., plots in France, Ireland and Sweden) were obtained from the KNMI Climate Explorer webpage (https://climexp.knmi.nl/start.cgi).Monthly climatic data (mean temperature and precipitation) were obtained from the E-OBS 0.25° gridded dataset[5]for 1975 to 2021.For sampling plots of the altitudinal and latitudinal gradient surveys, we computed the average temperature and precipitation for each month over the available period as well as the average annual temperature and total annual precipitation.Mean temperature and precipitation values for winter, spring, summer and autumn were calculated using the mean monthly temperature or precipitation values for December to February, March to May, June to August and September to November, respectively.For each stream of the altitudinal gradient survey, tree diversity was computed with the Shannon index for the riverbank vegetation and the Shannon index for the watershed vegetation.For each watershed, we calculated the following topographical parameters: the proportion of each type of land cover (i.e., urban, agricultural or forest), the total watershed area, aspect and slope.The proportion of each tree species in the watershed was determined Forest Map, and the Shannon index for the riverbank vegetation was based on the visually estimated riverbank vegetation species (%) data.Altogether with the Shannon indices, the presence (%) of the most dominant tree genera in the watershed (i.e., Pinus, Land Use (SIOSE).Tree species data were obtained from the Spanish Forest Map 1:25 000.Shannon index for the watershed vegetation was based on the species (%) data obtained from the Spanish Cornes RC, van der Schrier G, van den Besselaar EJM, Jones PD.An ensemble version of the E-OBS temperature and precipitation data sets.J Geophys Res Atmos 2018; 123: