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Supporting information A in S1 File. Glossary of additional key terms. Supporting information B in S1 File. Table reporting contrasting arguments and approaches used to define how alien taxa are considered and should be managed in accordance with different conservation values/motivations. As multiple values/motivations exist and determine which entities we are interested in (see also Supporting information A), distinct conservation targets can be identified. Note that here, we only consider conservation values/motivations that are expressed regardless of any nature’s instrumental (utilitarian) value, i.e., regardless of nature’s contributions to human well-being (see “nature for itself” framing [9]). Also, note that such contrasting arguments and approaches are not necessarily mutually exclusive and have been occasionally combined to find a middle ground to achieve broader conservation goals [10–13]. Supporting information C in S1 File. Circumstances under which the prevention/mitigation of a decreasing change is considered as a positive change under EICAT+. In EICAT+, we also consider as positive impacts (i.e., increasing changes) cases in which an alien species prevents/mitigates decreasing changes, e.g., when the performance of a native individual, the size of a native population, or the occupancy of a native species would have decreased, or decreased to a greater extent, if the alien species had not been introduced. Although some of these positive impacts can be inferred, the prevention of a decreasing change should be assessed under EICAT+ only when there is convincing evidence that a certain biodiversity attribute (e.g., population size) would have decreased, or decreased to a greater extent, in the absence of the alien species. In the case of extinction prevention, for instance, it must be clear that (i) the population was locally heading toward extinction before the introduction of the alien; and (ii) the alien taxon prevented, through a specific impact mechanism, an extinction that would have occurred in its absence [41,42] (Fig 2b). Other cases where an alien species may prevent or mitigate decreasing changes are, for instance, those in which the abundance (i.e., a proxy for population size) of a native species declined in the uninvaded (i.e., control) plots but not, or to a lesser extent, in the plots invaded by the alien. Note that positive impacts associated with the prevention/mitigation of a decreasing change will generally be more difficult to study and identify than those associated with actual increasing changes, as the former require extensive data regarding the temporal trend of individual performance, population size, or area of occupancy. Supporting information D in S1 File. EICAT+ mechanisms and submechanisms by which an alien taxon can cause positive impacts on native biodiversity attributes and examples of positive impacts sourced from the literature and assessed under EICAT+ (ML+ = Minimal positive impact, MN+ = Minor positive impact, MO+ = Moderate positive impact, MR+ = Major positive impact, MV+ = Massive positive impact). Rationales behind the formulation of the mechanisms and submechanisms can be found in the main text and in Supporting information G, H, and J. Supporting information E in S1 File. Table reporting examples sourced from the literature and classified as information that cannot be classified under EICAT+, but that contain information about mechanisms and might set the stage for future studies. Although these studies described the existence of mechanisms by which alien taxa may cause positive impacts on native taxa, such literature is considered as nonrelevant, as it did not measure, or provide information on, biodiversity attributes used in EICAT+ (e.g., performance of individuals or population size). Rationales behind the formulation of the mechanisms and submechanisms can be found in the main text and in Supporting information G, H, and J. Supporting information F in S1 File. How to attribute a confidence score in EICAT+. Supporting information G in S1 File. Additional information around the rationale behind the formulation of the EICAT+ mechanisms and submechanisms. Supporting information H in S1 File. Additional information about how alien species can cause positive impacts on native biodiversity through overcompensation. Supporting information J in S1 File. Additional information about how alien species can cause positive impacts on native biodiversity through hybridization. Supporting information K in S1 File. References used in the Supporting information., Peer reviewed

Supplementary methods, tables and figures., Peer reviewed

Supplementary Figures (1-15) and Tables (1-2). © The Authors under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/, which permits unrestricted use, provided the original author and source are credited., Drought is one of the most difficult natural hazards to quantify and is divided into categories (meteorological, agricultural, ecological and hydrological), which makes assessing recent changes and future scenarios extremely difficult. This opinion piece includes a review of the recent scientific literature on the topic and analyses trends in meteorological droughts by using long-term precipitation records and different drought metrics to evaluate the role of global warming processes in trends of agricultural, hydrological and ecological drought severity over the last four decades, during which a sharp increase in atmospheric evaporative demand (AED) has been recorded. Meteorological droughts do not show any substantial changes at the global scale in at least the last 120 years, but an increase in the severity of agricultural and ecological droughts seems to emerge as a consequence of the increase in the severity of AED. Lastly, this study evaluates drought projections from earth system models and focuses on the most important aspects that need to be considered when evaluating drought processes in a changing climate, such as the use of different metrics and the uncertainty of modelling approaches.This article is part of the theme issue ‘Drought risk in the Anthropocene’., Peer reviewed

Supplementary Figures (1-4) and Tables (S1-S5)., Drought is an important driver of forest dynamics in the Mediterranean region. The forecasted increase in drought frequency and severity can notably influence tree growth, forest structure, composition and productivity. Understanding how coexisting tree species respond to drought is thus crucial to understand which are less vulnerable and will perform better in a warmer and drier world. To assess drought vulnerability, we used dendrochronology to study the radial growth trends and responses to a drought index of four pine species (Pinus halepensis, Pinus pinea, Pinus nigra, and Pinus sylvestris) coexisting in North-eastern Spain. We reconstructed the growth of each species and evaluated their short- and long-term growth response to drought for the common period 1980–2017. The growth of the four pine species depended on water availability and high early spring temperatures impacted the growth of P. nigra and P. sylvestris negatively. The occurrence of a severe drought between 2005 and 2007 lead to marked growth reductions in the four species, but it was greater in magnitude in P. pinea and P. halepensis in 2005, and in P. nigra in 2007. The results of basal area increment models at the individual tree level suggested that P. halepensis trees grow more than the rest of species. After accounting for age and drought effects, P. nigra and P. sylvestris displayed negative growth trends in the 2008–2017 period while P. pinea and P. halepensis displayed positive growth trends. P. sylvestris was the most resistant species and P. pinea the less resistant. Conversely, P. halepensis and P. pinea were slightly more resilient than P. sylvestris. Moreover, P. sylvestris was the species displaying the highest autocorrelation and the lowest coefficient of variation in ring-width indices. A marked drop in the autocorrelation of P. pinea ring-width index was observed in response to the 2005 drought. These results indicate that all study species are vulnerable to drought but in different degrees. The strong resilience capacity of P. halepensis suggests that it will better thrive in a drier future, but mixed pine forests, such as the one here studied, may contract or become rare due to the strong sensitivity of P. pinea to drought and the lower post-drought performance of P. nigra and P. sylvestris., Peer reviewed

21679463.zip contains: Cera et al. PED.R; Supplementary files_25112022.docx; data_Cera et al. Plant Ecology and Diversity.xlsx, Plants growing on extreme soils have mainly been described in relation to their adaptations to edaphic conditions, although herbivores may also be an important factor in these ecosystems. Gypsum soils occur in drylands often where livestock practices occur. However, it is unknown whether plant traits related to gypsum soil constraints are associated with resistance to herbivory. In order to assess whether gypsum specialist species might be favoured at higher grazing levels and to detect the traits involved, we evaluated the responses of gypsum specialists vs. generalists to three intensities of livestock pressure. We analysed the relative cover shifts of species along a livestock gradient, and variation in canopy height, canopy area, leaf carbon (C), nitrogen (N), and sulphur (S), specific leaf area (SLA) and leaf dry matter content (LDMC). We found that gypsum-specialists responded by increasing or maintaining their cover at medium and high grazing pressure, whereas most generalists responded by decreasing it. Gypsum-specialists showed higher leaf S than generalists, regardless of grazing intensity. All species showed similar patterns for traits linked to loss of above-ground biomass when grazing increased. Plant affinity to gypsum soils mediates vulnerability to grazing with foliar S possibly being a defence trait., This work was supported by Gobierno de España [MICINN, CGL2015-71360-P, CGL2016-80783-R and PID2019-111159GB-C31]; by European Union’s Horizon 2020 [H2020-MSCA-RISE-777803]; and by Consejo Superior de Investigaciones Científicas [COOPB20231]. AC and SP were funded by a FPI fellowship [MICINN, BES-2016-076455] and a Ramón y Cajal Fellowship [MICINN, RYC-2013-14164], respectively., Peer reviewed

Table S1. Results from DNA concentration and purity quantification using ND-1000-Spectrophotometer (mean ± sd). Large standard deviations for average concentration values are due to variation in tissue quantity among samples. All samples were however diluted to the concentration of 2.5 ng/µl before telomere length estimation. Three linear models (Concentration/[260/289]/[260/230] as dependent variable with Kenward-Roger approximation for degrees of freedom) were ran to test the differences among populations. Differences in DNA concentration were not statistically significant (F5, 531=1.02, p=0.40) while the differences in both 260/280 (F5, 531=2.45, p=0.03) and 260/230 (F5, 531=8.70, p<.0001) ratios reached statistical significance. Including the ratio-values as covariates in the statistical analyses presented in the main text with telomere length as dependent variable did not change the results or conclusion, thus these covariates were removed from the final models to reduce model parameters., Table S2. Population specific (Mean ± sd) efficiencies and Cq-values for control gene (SCG) and telomere (TELO) assays. Three linear models (SCG Cq/SCG Efficiency/TELO Efficiency as dependent variable with Kenward-Roger approximation for degrees of freedom) were ran to test the differences among populations. Differences in SCG Cq-values were not statistically significant (F5, 528=1.48, p=0.20) while the differences in both SCG (F5, 528=8.11, p<.0001) and TELO (F5, 528=12.66, p<.0001) efficiencies reached statistical significance. Including both assay efficiencies as covariates in the statistical analyses presented in the main text with telomere length as dependent variable did not change the results or conclusion, thus these covariates were removed from the final models to reduce model parameters., Table S3. Results of linear mixed models explaining the effects of Age class and Population on telomere length using subsets of the whole data including samples analyzed only with a) QuantStudio or b) MicPCR, Figure S1. Locations of the study sites; breeding area of the pied flycatcher in Eurasia shown in orange. Birds from all populations are expected to migrate through Iberian Peninsula and west coast of Africa to their Sub-Saharan non-breeding grounds described in Ouwehand et al. 2016 (black circle; Finnish and Estonian birds blue circle; English and Spanish birds red circle). Map modified from: BirdLife International. 2018. Ficedula hypoleuca. The IUCN Red List of Threatened Species 2018: e.T22709308A131952521. https://dx.doi.org/10.2305/IUCN.UK.2018-2.RLTS.T22709308A131952521.en. Downloaded on 10 August 2021., Figure S2. Illustrating the telomere lengths (T/S ratios) of the same sample measured both with QuantStudio and MicPCR. Telomere length estimates are consistently somewhat higher for MicPCR (15 out of 20 samples) accounting for somewhat low agreement repeatability of 0.851 (95% Cl [0.66, 0.94], P<0.001) between the two machines., Figure S3. Individual raw telomere length values (T/S ratio) per population and age class. See sample sizes for Population: Nestling/Fledgling/Adult in the caption for Figure 1., Figure S4. Relative telomere length in six pied flycatcher populations across a north-south gradient in Europe, from the early nestling period (Nestling; 5 days after hatching), to fledging (Fledgling; 12 days after hatching) and adulthood (Adult; end of the rearing period) using subsets of data including rTL values obtained only with a) QuantStudio, or b) MicPCR. Values are estimated marginal means based on z-scored telomere length values ± s.e.m. Sample sizes [for Population: Nestling/Fledgling/Adult] are a) Oulu: 16/15/29; Turku: 15/13/32; Kilingi-Nõmme: 18/17/31; East Dartmoor: 17/17/31; La Hiruela: 23/12/33; Valsaín: 19/17/39, and b) Oulu: 3/4/12; Turku: 6/6/9; Kilingi-Nõmme: 4/3/12; East Dartmoor: 6/5/14; La Hiruela: 12/7/19; Valsaín: 5/6/10., Figure S5. Associations between migration distance (km) and relative telomere length (mean based on z-scored values) in the pied flycatcher fledglings (12 days after hatching; circles) and adults (averaged breeding pair; squares). Standard errors of the means (± sem) have been added to illustrate the population variation in telomere length. Fledgling values (circles) have been moved slightly to the right to clarify the error bars. Populations from the shortest migration distance to the longest: Spain (average of Valsaín and La Hiruela, red), England (East Dartmoor, yellow), Estonia (Kilingi-Nõmme, green), southern Finland (Turku, blue), and northern Finland (Oulu, purple)., Figure S6. Pied flycatcher chick body mass adjusted for clutch size at day 5 (A), day 12 (B) and growth rate (Δ mass between days 12 and 5; C) in six populations across a north-south gradient in Europe. Statistically significant differences after Tukey-Kramer adjustment for multiple comparisons are indicated with different letters. Values are estimated marginal means ± s.e.m. Sample sizes [for Population: Day5/Day12/Growth] are: Oulu, Finland: 19/19/17; Turku, Finland: 21/19/18; Kilingi-Nõmme, Estonia: 22/20/19; East Dartmoor, England: 20/22/18; La Hiruela, Spain: 33/19/18; Valsaín, Spain: 24/23/21., Figure S7. Change in relative telomere length during nestling period in the pied flycatcher (Δ telomere length between days 12 and 5) in six populations across a north-south gradient in Europe. The effect of population was marginally significant (p = 0.06) in explaining variation in early-life telomere change (see results for details). Values are estimated marginal means based on z-scored telomere length values ± s.e.m. Sample sizes [for Population] are: Oulu, Finland: 17; Turku, Finland: 18; Kilingi-Nõmme, Estonia: 19; East Dartmoor, England: 21; La Hiruela, Spain: 18; Valsaín, Spain: 21., Table of Contents: Table S1. Results from DNA concentration and purity quantification (p. 2).-- Table S2. Population specific efficiencies and Cq-values for control gene and telomere assays (p. 3).-- Table S3. Results of linear mixed models explaining the effects of Age class and Population on telomere length using subsets of the data (p. 4).-- Figure S1. Locations of the study sites (p. 5).-- Figure S2. Illustrating the telomere lengths of the same sample measured both with two qPCR machines (p. 6).-- Figure S3. Individual raw telomere length values (p. 6).-- Figure S4. Telomere length values in different populations using subsets of the data (p. 7).-- Figure S5. Associations between migration distance and telomere length (p. 8).-- Figure S6. Pied flycatcher chick body mass adjusted for clutch size (p. 9).-- Figure S7. Change in telomere length during nestling period (p. 10)., Peer reviewed

Supplementary Figure 1 | Root diversity in example individuals of Papaver rhoeas from the experiment. From left to right: roots with decreasing numbers of secondary roots. The scale bar represents 50 mm., Supplementary Figure 2 | Temperature, potential evapotranspiration and precipitation at the study site. (A) Average daily temperature per month for each of the four experimental years. Colors and dot symbols correspond to the different experimental years and dotted lines to second order polynomial regressions. (B) Average potential evapotranspiration (PET) per month at the field site (Atlas Climático Digital de Aragón). The dotted line corresponds to a second order polynomial regression. (C) Difference between monthly precipitation (P) and potential evapotranspiration (PET) at the field site (red dots and red dotted line) and including the irrigated amount of water (yellow dots and yellow dotted line). Dotted lines correspond to second order polynomial regressions., Supplementary Figure 3 | Selection acting on root traits of ancestors. Model predictions of selection gradients are shown for number of secondary roots (A) and maximum rooting depth (B). Since no significant interactions with treatments existed (see ‘Results’), only significant linear (A) and quadratic (B) predictions are shown., Supplementary Figure 4 | Selection acting on root traits indicating root allocation strategies of ancestors. Selection gradients are shown for root weight ratio (RWR) (A), relative root branching (B), and relative rooting depth (C). Since no significant interactions with treatment existed (see ‘Results’), model predictions of significant quadratic (A, C) and linear (B) relationships are shown., Supplementary Table 1 | Means and coefficients of variation of measured root traits depending on maternal predictability treatments. The means of all root traits are shown for each of the descendant treatments depending maternal treatment, and also for each descendant treatment independent of the maternal treatment. The coefficient of variation (the ratio of the standard deviation to the mean, based on means, CVm) among treatments in descendants for each maternal treatment is also shown as well as the overall CV of ancestors (CVa) and the overall CV of descendants (CVd)., Supplementary Table 2 | Sample size per treatment, year and generation. The sample size per treatment and year is presented for the ancestral plants, and the sample size per treatment and generation is presented for the descendants that were subjected to the same treatment for four generations (referred to as ‘descendants – pure lines’) and for the descendants from all treatment combinations over generations used for the analysis on transgenerational plasticity. The hypothesis (H) tested for each group of data is shown., Climate forecasts show that in many regions the temporal distribution of precipitation events will become less predictable. Root traits may play key roles in dealing with changes in precipitation predictability, but their functional plastic responses, including transgenerational processes, are scarcely known. We investigated root trait plasticity of Papaver rhoeas with respect to higher versus lower intra-seasonal and inter-seasonal precipitation predictability (i.e., the degree of temporal autocorrelation among precipitation events) during a four-year outdoor multi-generation experiment. We first tested how the simulated predictability regimes affected intra-generational plasticity of root traits and allocation strategies of the ancestors, and investigated the selective forces acting on them. Second, we exposed three descendant generations to the same predictability regime experienced by their mothers or to a different one. We then investigated whether high inter-generational predictability causes root trait differentiation, whether transgenerational root plasticity existed and whether it was affected by the different predictability treatments. We found that the number of secondary roots, root biomass and root allocation strategies of ancestors were affected by changes in precipitation predictability, in line with intra-generational plasticity. Lower predictability induced a root response, possibly reflecting a fast-acquisitive strategy that increases water absorbance from shallow soil layers. Ancestors’ root traits were generally under selection, and the predictability treatments did neither affect the strength nor the direction of selection. Transgenerational effects were detected in root biomass and root weight ratio (RWR). In presence of lower predictability, descendants significantly reduced RWR compared to ancestors, leading to an increase in performance. This points to a change in root allocation in order to maintain or increase the descendants’ fitness. Moreover, transgenerational plasticity existed in maximum rooting depth and root biomass, and the less predictable treatment promoted the lowest coefficient of variation among descendants’ treatments in five out of six root traits. This shows that the level of maternal predictability determines the variation in the descendants’ responses, and suggests that lower phenotypic plasticity evolves in less predictable environments. Overall, our findings show that roots are functional plastic traits that rapidly respond to differences in precipitation predictability, and that the plasticity and adaptation of root traits may crucially determine how climate change will affect plants., Peer reviewed

Semi-structured interview questions: Adaptability (1-12); Practices related to the river (13-14); Milestones for the relation between society and the river (15-18)., The relations between preparedness and psycho-social attributes of people and communities exposed to river floods in a nearly pristine socio-hydrological system were investigated, applying a hydrological-hydraulic analysis of flood risk in combination with results from a survey, social cartography, semi-structured non-participant observation, and semi-structured interviews. Results show that preparedness in nearly pristine systems is noticeably different to that reported for altered systems. People adopt innovative and simple but efficient measures against floods, conditioned by (1) damage suffered during past floods, (2) perceived exposure to floods, and (3) the number of dependent people in the household. The studied system proved to be well adapted to floods but not resilient. Studying attributes that explain preparedness as part of flood risk management plans would contribute towards uncertainty reduction in risk calculations and increase the safety of goods and people from floods., This work was supported by the ARAUCO SA [PREGA Nr. 4503152513]., Peer reviewed

Supplementary Material for Frontiers in Environmental Science 10: 868527 (2022), 1. Riparian zones are vital areas of interaction between land and rivers and are often degraded by several pressures such as urbanisation, intensive agriculture and river engineering works. 2. This policy brief provides five key policy messages and recommendations to be considered by policy-makers, scientists, managers, and stakeholders to enhance riparian zone management. 3. Adopting an integrated socio-economic and environmentally dynamic view will ensure the sustainable management of riparian zones. 4. In light of climate change, it is critically important to conserve and/or restore the ecological integrity of riparian zones. 5. European Union Directives and national-scale legislation and regulations need updating to ensure coordinated implementation of riparian zone-related policies. 6. Stakeholder knowledge exchange, policy co-creation and adaptive management are key to enhancing riparian zone functions., Peer reviewed

Fig B. Error matrix for supervised classification in Celestun mangrove area., Mangrove vegetation is strongly dependent on the climate, the physicochemical variables of the sediment, and the hydrological dynamics. These drivers regulate the distribution of different mangrove ecotypes and their ecosystem services, so the net sediment accumulation rates in different mangrove ecotypes in Celestun Lagoon, a karstic zone in the NW Yucatan Peninsula, SE Mexico, were estimated. The measurements considering mangrove ecotypes and their spatial variability concerning the lagoon's salinity gradient (inner, middle, and outer lagoon zones) in three climate seasons (dry, rain, and “nortes”) were realized. We registered the structural variables of the forest, interstitial water physicochemical characteristics, and sediment variables that could influence the net sediment deposition. Fringe mangroves are exposed to low hydrodynamism and show the highest sedimentation rate (3.37 ± 0.49 kg m−2 year−1) compared to basin (1.68 ± 0.22 kg m−2 year−1), dwarf (1.27 ± 0.27 kg m−2 year−1), and “peten” (0.52 ± 0.12 kg m−2 year−1) mangroves. The highest sedimentation rate was recorded in the rainy season (0.24 ± 0.08 kg m−2 month−1), while spatially, the highest value was registered in the outer zone (0.44 ± 0.09 kg m−2 month−1). If the extension of each mangrove ecotype is considered, dwarf mangroves have the highest annual sediment accumulation (1,465 t year−1 in 14,706 ha). The structural, physicochemical, and sediment variables of the sites by mangrove ecotype show that dwarf mangroves represent a distinct group from those formed by fringe, basin, and peten mangroves. However, the sedimentation is high in fringe mangroves at the front of the lagoon and diminishes inland where peten mangroves exist. The differences are given by tree density, but salinity, as a proxy variable of the freshwater influence, significantly influences the sedimentation rate. These results indicate that mangroves in karstic environments can have critical roles in confronting climate change, considering water and sediment flows are the basis of sediment accumulation. According to their hydrogeomorphological drivers, conserving, managing, and restoring the mosaic of mangrove ecotypes improves ecosystem services, including mitigation and adaptation to climate change., Peer reviewed