A shift from individual species to ecosystem services effect: Introducing the Eco-indicator Sensitivity Distribution (EcoSD) as an ecosystem services approach to redefining the species sensitivity distribution (SSD) for soil ecological risk assessment.

Incorporating the ecosystem services (ES) approach into soil ecological risk assessment (ERA) has been advocated over the years, but implementing the approach in ERA faces some challenges. However, several researchers have made significant improvements to the soil ERA, such as applying the species sensitivity distribution (SSD) to discern chemical effects on the soil ecosystem. Despite the considerable contributions of SSD to ERA, SSD fails to relate chemical impact on individual species to ES and account for functional redundancy as well as soil ecosystem complexity. Here, we introduce the Eco-indicator Sensitivity Distribution (EcoSD). An EcoSD fits ecological functional groups and soil processes, termed "eco-indicators," instead of individual species responses to a statistical distribution. These eco-indicators are related directly to critical ecosystem functions that drive ES. We derived an EcoSD for cadmium as a model chemical and estimated a soil ecosystem protection value (EcoPVSoil ) based on the eco-indicator dataset for cadmium from the literature. The EcoSD identified nitrogen cycling as the critical process disrupted by cadmium. A key advantage of EcoSD is that it identifies key ecological and chemical indicators of an ES effect. In doing so, it links chemical monitoring results to sensitive ecological functions. The estimated EcoPVSoil for cadmium was slightly more protective of the soil ecosystem than most regional soil values derived from this study's dataset and soil guideline values from the literature. Thus, EcoSD has proven to be a practical and valuable ES concept with the potential to serve as an initial step of the tiered ERA approach. Integr Environ Assess Manag 2023;00:1-14. © 2023 SETAC.

Linking niche size and phylogenetic signals to predict future soil microbial relative abundances.

Bacteria provide ecosystem services (e.g., biogeochemical cycling) that regulate climate, purify water, and produce food and other commodities, yet their distribution and likely responses to change or intervention are difficult to predict. Using bacterial 16S rRNA gene surveys of 1,381 soil samples from the Biomes of Australian Soil Environment (BASE) dataset, we were able to model relative abundances of soil bacterial taxonomic groups and describe bacterial niche space and optima. Hold out sample validated hypothetical causal networks (structural equation models; SEM) were able to predict the relative abundances of bacterial taxa from environmental data and elucidate soil bacterial niche space. By using explanatory SEM properties as indicators of microbial traits, we successfully predicted soil bacterial response, and in turn potential ecosystem service response, to near-term expected changes in the Australian climate. The methods developed enable prediction of continental-scale changes in bacterial relative abundances, and demonstrate their utility in predicting changes in bacterial function and thereby ecosystem services. These capabilities will be strengthened in the future with growing genome-level data.

Light to moderate long-term grazing enhances ecosystem carbon across a broad climatic gradient in northern temperate grasslands.

Grasslands are globally abundant and provide many ecosystem services, including carbon (C) storage. While grasslands are widely subject to livestock grazing, the influence of grazing on grassland ecosystem C remains unclear. We studied the effect of long-term livestock grazing on C densities of different ecosystem components in 110 northern temperate grasslands across a broad agroclimatic gradient in Alberta, Canada. These grasslands stored 50 to 180 t ha-1C in live and dead vegetation, as well as soil C to 30 cm depth, with the majority as soil organic C (SOC). The mulch layer comprised a large amount of C (~18 t ha-1C) especially within humid grasslands. Although grazing reduced C densities in litter mass, total ecosystem C was 8.5 % greater under grazing (127.8 t ha-1) compared to those non-grazed (117.8 t ha-1), primarily due to increases in SOC and roots. Increases in SOC were consistently observed in the 0-15 cm layer across all climatic conditions, with changes in SOC of the 15-30 cm layer inversely related to aridity. A structural equation model revealed that increased SOC under grazing was indirectly attributed to increases in eudicot rather than graminoid biomass. In addition, SOC increased with graminoid quality (i.e., a reduced carbon to nitrogen ratio), which together with elevated eudicots, increased litter and mulch C, and ultimately enhanced SOC densities. When applied to spatial maps of habitat type and land use (livestock grazing) activity across the region, an area of ~3.8 M ha of grassland was projected to contain an additional 17.1 M t of C under grazing, primarily in mesic grasslands, worth an estimated $3.1 B (Cdn.) under current C valuation guidelines in Canada. Overall, these results highlight the importance of grasslands for C storage and establishing policies that maintain and promote their sustainable use, including light to moderate grazing.

Rocks, lichens, and woody litter influenced the soil invertebrate density in upland tundra heath.

Soil invertebrates are an integral part of Arctic ecosystems through their roles in the breakdown of litter, soil formation, and nutrient cycling. However, studies examining soil invertebrates in the Arctic are limited and our understanding of the abiotic and biotic drivers of these invertebrate communities remains understudied. We examined differences in soil invertebrate taxa (mites, collembolans, enchytraeids) among several undisturbed upland tundra heath sites in Nunavut Canada and identified the drivers (vegetation and substrate cover, soil nutrients and pH) of the soil invertebrate community across these sites. Soil invertebrate densities were similar to that of other Arctic studies. While invertebrate communities were relatively consistent between our sites, cover of rocks, woody litter, and the lichen Alectoria nigricans had significant, positive influences on the density of all invertebrates studied. Mites and collembolans were more closely associated with cover of lichens, whereas enchytraeids were more closely associated with woody litter and rocks. Our results suggest that anthropogenic (e.g., resource exploration and extraction) and/or natural (e.g., climate change) disturbances that result in changes to the vegetation community and woody litter inputs will likely impact soil invertebrates and the ecosystem services they provide.

Plant responses to soil biota depend on precipitation history, plant diversity, and productivity.

Soil biota are critical drivers of plant growth, population dynamics, and community structure and thus have wide-ranging effects on ecosystem function. Interactions between plants and soil biota are complex, however, and can depend on the diversity and productivity of the plant community and environmental conditions. Plant-soil biota interactions may be especially important during stressful periods, such as drought, when plants can gain great benefits from beneficial biota but may be susceptible to antagonists. How soil biota respond to drought is also important and can influence plant growth following drought and leave legacies that affect future plant responses to soil biota and further drought. To explore how drought legacies and plant community context influence plant growth responses to soil biota and further drought, we collected soils from 12 grasslands varying in plant diversity and productivity where precipitation was experimentally reduced. We used these soils as inoculum in a growth chamber experiment testing how precipitation history (ambient or reduced) and soil biota (live or sterile soil inoculum) mediate plant growth and drought responses within an experimental plant community. We also tested whether these responses differed with the diversity and productivity of the community where the soil was collected. Plant growth responses to soil biota were positive when inoculated with soils from less diverse and productive plant communities and became negative as the diversity and productivity of the conditioning community increased. At low diversity, however, positive soil biota effects on plant growth were eliminated if precipitation had been reduced in the field, suggesting that diversity loss may heighten climate change sensitivity. Differences among species within the experimental community in their responses to soil biota and drought suggest that species benefitting from less drought sensitive soil biota may be able to compensate for some of this loss of productivity. Regardless of the plant species and soil origin, further drought eliminated any effects of soil biota on plant growth. Consequently, soil biota may be unable to buffer the effects of drought on primary productivity or other ecosystem functions as extreme events increase in frequency.

Global pattern and associated drivers of grassland productivity sensitivity to precipitation change.

Precipitation is a primary climatic determinant of grassland productivity, with many global change experiments manipulating precipitation. Here we examine the impacts of precipitation addition and reduction treatment intensity and duration on grassland above- (ANPP) and below- (BNPP) ground net primary productivity in a large-scale meta-analysis. We tested, 1) the double asymmetry model of sensitivity, specifically whether the sensitivity of productivity decreases with treatment intensity under increased precipitation and increases with treatment intensity under decreased precipitation, 2) whether the sensitivity of productivity to precipitation change decreases with treatment length, and 3) how the sensitivity of productivity changes with climate conditions. ANPP showed higher sensitivity than BNPP under increased precipitation but similar sensitivity to BNPP under decreased precipitation. The sensitivity of ANPP and BNPP decreased with increasing treatment intensity (e.g., percentage change in precipitation, ΔPPT) and leveled off in the long-term. With increased precipitation, the sensitivity of productivity decreased with increasing treatment length (e.g., experimental duration) and leveled off in the long-term, whereas the sensitivity increased with increasing treatment length under reduced precipitation. Furthermore, the sensitivity of productivity to precipitation change decreased with increasing mean annual precipitation and temperature. Finally, our meta-analysis shows that above- and belowground net primary productivity have asymmetric responses to precipitation change. Together these results highlight the complex mechanisms underlying the impacts of precipitation change, particularly the intensity and duration of such changes, on grassland productivity.

An intensive multilocation temporal dataset of fungal and bacterial communities in the root and rhizosphere of Brassica napus.

The plant microbiome has been recently recognized as a plant phenotype to help in the food security of the future population. However, global plant microbiome datasets are insufficient to be used effectively for breeding this new generation of crop plants. We surveyed the diversity and temporal composition of bacterial and fungal communities in the root and rhizosphere of Brassica napus, the world's second largest oilseed crop, weekly in eight diverse lines at one site and every three weeks in sixteen lines, at three sites in 2016 and 2017 in the Canadian Prairies. We sequenced the bacterial 16S ribosomal RNA gene generating a total of 127.7 million reads and the fungal internal transcribed spacer (ITS) region generating 113.4 million reads. 14,944 unique fungal amplicon sequence variants (ASV) were detected, with an average of 43 ASVs per root and 105 ASVs per rhizosphere sample. We detected 10,882 unique bacterial ASVs with an average of 249 ASVs per sample. Temporal, site-to-site, and line-driven variability were key determinants of microbial community structure. This dataset is a valuable resource to systematically extract information on the belowground microbiome of diverse B. napus lines in different environments, at different times in the growing season, in order to adapt effective varieties for sustainable crop production systems.

An intensive multilocation temporal dataset of fungal communities in the root and rhizosphere of Brassica napus.

The plant microbiome has been recently recognized as a plant phenotype to help in the food security of the future population. However, global plant microbiome datasets are insufficient to be used effectively for breeding this new generation of crop plants. We surveyed the diversity and temporal composition of fungal communities in the root and rhizosphere of Brassica napus, the world's second largest oilseed crop, weekly in eight diverse lines at one site and every three weeks in sixteen lines, at three sites in 2016 and 2017 in the Canadian Prairies. 14,944 unique amplicon sequence variants (ASV) were detected based on the internal transcribed spacer region, with an average of 43 ASVs per root and 105 ASVs per rhizosphere sample. Temporal, site-to-site, and line-driven variability were key determinants of fungal community structure. This dataset is a valuable resource to systematically extract information on the belowground microbiome of diverse B. napus lines in different environments, at different times in the growing season, in order to adapt effective varieties for sustainable crop production systems.

A survey of invasive plants on grassland soil microbial communities and ecosystem services.

Invasive plants can cause changes in the structure and function of the ecosystem being invaded. Any changes in ecosystem diversity and community composition will likely alter ecosystem services provided by that ecosystem. However, how these ecosystem services may change is poorly understood. To elucidate how these ecosystem services will change with invasion, we sampled 561 plots undergoing invasion by smooth brome (Bromus inermis) and four other invasive species at a native Rough Fescue prairie located near Saskatoon, Saskatchewan, Canada. Soil and plant surveys were undertaken weekly for 26 weeks between May of 2014 and November of 2014, or the growing season. We measured a suite of ecosystem services, including greenhouse gasses, extracellular enzyme function, forage production, glyphosate degradation and decomposition. Furthermore, soil physical and chemical properties were measured, and soil bacterial and fungal communities were sequenced. This is a large and multifaceted dataset with complex temporal and spatial attributes which can be used to answer numerous questions regarding the functioning of prairie ecosystems and how invasive species will impact that functioning.

Structural equation modeling of a winnowed soil microbiome identifies how invasive plants re-structure microbial networks.

The development of microbial networks is central to ecosystem functioning and is the hallmark of complex natural systems. Characterizing network development over time and across environmental gradients is hindered by the millions of potential interactions among community members, limiting interpretations of network evolution. We developed a feature selection approach using data winnowing that identifies the most ecologically influential microorganisms within a network undergoing change. Using a combination of graph theory, leave-one-out analysis, and statistical inference, complex microbial communities are winnowed to identify the core organisms responding to external gradients or functionality, and then network development is evaluated against these externalities. In a plant invasion case study, the winnowed microbial network became more influential as the plant invasion progressed as a result of direct plant-microbe links rather than the expected indirect plant-soil-microbe links. This represents the first use of structural equation modeling to predict microbial network evolution, which requires identification of keystone taxa and quantification of the ecological processes underpinning community structure and function patterns.

Core and Differentially Abundant Bacterial Taxa in the Rhizosphere of Field Grown Brassica napus Genotypes: Implications for Canola Breeding.

Modifying the rhizosphere microbiome through targeted plant breeding is key to harnessing positive plant-microbial interrelationships in cropping agroecosystems. Here, we examine the composition of rhizosphere bacterial communities of diverse Brassica napus genotypes to identify: (1) taxa that preferentially associate with genotypes, (2) core bacterial microbiota associated with B. napus, (3) heritable alpha diversity measures at flowering and whole growing season, and (4) correlation between microbial and plant genetic distance among canola genotypes at different growth stages. Our aim is to identify and describe signature microbiota with potential positive benefits that could be integrated in B. napus breeding and management strategies. Rhizosphere soils of 16 diverse genotypes sampled weekly over a 10-week period at single location as well as at three time points at two additional locations were analyzed using 16S rRNA gene amplicon sequencing. The B. napus rhizosphere microbiome was characterized by diverse bacterial communities with 32 named bacterial phyla. The most abundant phyla were Proteobacteria, Actinobacteria, and Acidobacteria. Overall microbial and plant genetic distances were highly correlated (R = 0.65). Alpha diversity heritability estimates were between 0.16 and 0.41 when evaluated across growth stage and between 0.24 and 0.59 at flowering. Compared with a reference B. napus genotype, a total of 81 genera were significantly more abundant and 71 were significantly less abundant in at least one B. napus genotype out of the total 558 bacterial genera. Most differentially abundant genera were Proteobacteria and Actinobacteria followed by Bacteroidetes and Firmicutes. Here, we also show that B. napus genotypes select an overall core bacterial microbiome with growth-stage-related patterns as to how taxa joined the core membership. In addition, we report that sets of B. napus core taxa were consistent across our three sites and 2 years. Both differential abundance and core analysis implicate numerous bacteria that have been reported to have beneficial effects on plant growth including disease suppression, antifungal properties, and plant growth promotion. Using a multi-site year, temporally intensive field sampling approach, we showed that small plant genetic differences cause predictable changes in canola microbiome and are potential target for direct and indirect selection within breeding programs.

Linking Herbicide Dissipation to Soil Ecological Risk along Transmission Rights-of-Way in the Yukon Territory, Canada.

In the Yukon Territory, transmission rights-of-way (ROWs) are managed using brushing and mowing techniques alone. When cut, target species such as Michx. and spp. grow rapidly shortening maintenance cycles. Long-term vegetation control may be improved by integrating herbicide application. However, prior to implementation, the dissipation and toxicity of herbicides in northern latitudes needed to be assessed. The dissipation of Garlon XRT (triclopyr) and Arsenal Powerline (imazapyr) in soils was assessed at five ROW locations representative of the main ecoregion types where ROWs occur within the Yukon Territory. Soils from four sites were collected at 1, 30, and 365 d after treatment to determine persistence of herbicides for each of three application methods (backpack spraying, cut stump, and point injection). Increased sampling intervals were added to better determine the dissipation rate of each herbicide in Yukon Territory soils. Soil dissipation data were linked to a series of standardized toxicity tests, including three soil invertebrates (, , and ). Additionally, the dissipation of both herbicides from the target species L. was assessed at one site. Herbicide residues persisted in soils for longer than 365 d after treatment and longer than 30 d after treatment in . However, concentrations were below the concentration that would affect 25% of the invertebrate species tested. Weight of evidence and toxic exposure ratios were used to characterize the risks associated with herbicide application in northern latitudes and provided both qualitative and quantitative means to communicate the results to the public.

Salix arctica changes root distribution and nutrient uptake in response to subsurface nutrients in High Arctic deserts.

Moisture is critical for plant success in polar deserts but not by the obvious pathway of reduced water stress. We hypothesized that an indirect, nutrient-linked, pathway resulting from unique water/frozen soil interactions in polar deserts creates nutrient-rich patches critical for plant growth. These nutrient-rich patches (diapirs) form deep in High Arctic polar deserts soils from water accumulating at the permafrost freezing front and ultimately rising into the upper soil horizons through cryoturbated convective landforms (frost boils). To determine if diapirs provide an enhanced source of plant-available N for Salix arctica (Arctic willow), we characterized soil, root, stem, and leaf 15 N natural abundance across 24 diapir and non-diapir frost boils in a High Arctic granitic semi-desert. When diapir horizons were available, S. arctica increased its subsurface (i.e., diapir) N uptake and plant root biomass doubled within diapir. Plant uptake of enriched 15 N injected into organic rich soil patches was 2.5-fold greater in diapir than in non-diapir frost boils. S. arctica percent cover was often higher (7.3 ± 1.0 [mean ± SE]) on diapiric frost boils, compared to frost boils without diapirs (4.4 ± 0.7), potentially reflecting the additional 20% nitrogen available in the subsurface of diapiric frost boils. Selective N acquisition from diapirs is a mechanism by which soil moisture indirectly enhances plant growth. Our work suggests that diapirs may be one mechanism contributing to Arctic greening by shrub expansion.

Herbicide Toxicity Testing with Non-Target Boreal Plants: The Sensitivity of Achillea millefolium L. and Chamerion angustifolium L. to Triclopyr and Imazapyr.

Terrestrial plant toxicity tests were conducted to determine the sensitivity of two boreal plants, yarrow (Achillea millefolium L.) and fireweed (Chamerion angustifolium L.), to the herbicides imazapyr and triclopyr. Both plants are common non-target species on northern powerline rights-of-way where the impacts of proposed herbicide applications are of concern. In the vegetative vigour test, triclopyr foliar spray caused extensive damage to A. millefolium at <50% of the maximum field application rate (inhibition concentration (IC)50 = 1443.8 g a.i. ha-1) and was lethal to C. angustifolium at the lowest dose tested (1210.9 g a.i. ha-1). Both species demonstrated extremely high sensitivity to imazapyr foliar spray: IC50s = 8.29 g a.i. ha-1 and 4.82 g a.i. ha-1 (<1.5% of the maximum field rate). The seedling emergence and seedling growth tests were conducted in the organic horizon of five boreal soils. Few differences in herbicide bioavailability between soils were detected. Triclopyr limited growth of A. millefolium, C. angustifolium and standard test species Calamagrostis canadensis at low levels (most IC50 estimates between 2-20 µg g-1). For imazapyr, IC50 estimates could not be calculated as there was >75% inhibition of endpoints at the lowest doses of ~2 µg g-1. A foliar application of triclopyr or imazapyr for woody species control would likely cause significant damage to boreal non-target plants. The high sensitivity of both species to herbicide residues in soil indicates long term impacts are dependent on herbicide degradation rates in northern conditions. A. millefolium performed well and is recommended for use in toxicity testing relevant to boreal regions.

Ex-post assessment of genetically modified, low level presence in Canadian flax.

Canada is the world's largest producer and exporter of flaxseed. In 2009, DNA from deregistered genetically modified (GM) CDC Triffid was detected in a shipment of Canadian flaxseed exported to Europe, causing a large decrease in the amount of flax planted in Canada and a major shift in export markets. The flax industry in Canada undertook major changes to ensure the removal of transgenic flax from the supply chain. To demonstrate compliance, Canada adopted a protocol involving testing grain samples (post-harvest) using an RT-PCR test for the construct found in CDC Triffid. Efforts to remove the presence of GM flax from the value chain included reconstituting major flax varieties from GM-free plants. The reconstituted varieties represented the majority of planting seed in 2014. This study re-evaluates GM flax presence in Canadian grain stocks for an updated dataset (2009-2015) using a previously described simulation model to estimate low-level GM presence. Additionally, losses to the Canadian economy resulting from the reduction in flax production and export opportunities, costs associated with reconstituting major flax varieties, and testing for the presence of GM flax along the flax value chain are estimated.

Archaea and bacteria mediate the effects of native species root loss on fungi during plant invasion.

Although invasive plants can drive ecosystem change, little is known about the directional nature of belowground interactions between invasive plants, native roots, bacteria, archaea and fungi. We used detailed bioinformatics and a recently developed root assay on soils collected in fescue grassland along a gradient of smooth brome (Bromus inermis Leyss) invasion to examine the links between smooth brome shoot litter and root, archaea, bacteria and fungal communities. We examined (1) aboveground versus belowground influences of smooth brome on soil microbial communities, (2) the importance of direct versus microbe-mediated impacts of plants on soil fungal communities, and (3) the web of roots, shoots, archaea, bacteria and fungi interactions across the A and B soil horizons in invaded and non-invaded sites. Archaea and bacteria influenced fungal composition, but not vice versa, as indicated by redundancy analyses. Co-inertia analyses suggested that bacterial-fungal variance was driven primarily by 12 bacterial operational taxonomic units (OTUs). Brome increased bacterial diversity via smooth brome litter in the A horizon and roots in the B horizon, which then reduced fungal diversity. Archaea increased abundance of several bacterial OTUs, and the key bacterial OTUs mediated changes in the fungi's response to invasion. Overall, native root diversity loss and bacterial mediation were more important drivers of fungal composition than were the direct effects of increases in smooth brome. Critically, native plant species displacement and root loss appeared to be the most important driver of fungal composition during invasion. This causal web likely gives rise to the plant-fungi feedbacks, which are an essential factor determining plant diversity in invaded grassland ecosystems.

The Influence of Matrix Size on Statistical Properties of Co-Occurrence and Limiting Similarity Null Models.

Null models exploring species co-occurrence and trait-based limiting similarity are increasingly used to explore the influence of competition on community assembly; however, assessments of common models have not thoroughly explored the influence of variation in matrix size on error rates, in spite of the fact that studies have explored community matrices that vary considerably in size. To determine how smaller matrices, which are of greatest concern, perform statistically, we generated biologically realistic presence-absence matrices ranging in size from 3-50 species and sites, as well as associated trait matrices. We examined co-occurrence tests using the C-Score statistic and independent swap algorithm. For trait-based limiting similarity null models, we used the mean nearest neighbour trait distance (NN) and the standard deviation of nearest neighbour distances (SDNN) as test statistics, and considered two common randomization algorithms: abundance independent trait shuffling (AITS), and abundance weighted trait shuffling (AWTS). Matrices as small as three × three resulted in acceptable type I error rates (p < 0.05) for both the co-occurrence and trait-based limiting similarity null models when exclusive p-values were used. The commonly used inclusive p-value (≤ or ≥, as opposed to exclusive p-values; < or >) was associated with increased type I error rates, particularly for matrices with fewer than eight species. Type I error rates increased for limiting similarity tests using the AWTS randomization scheme when community matrices contained more than 35 sites; a similar randomization used in null models of phylogenetic dispersion has previously been viewed as robust. Notwithstanding other potential deficiencies related to the use of small matrices to represent communities, the application of both classes of null model should be restricted to matrices with 10 or more species to avoid the possibility of type II errors. Additionally, researchers should restrict the use of the AWTS randomization to matrices with fewer than 35 sites to avoid type I errors when testing for trait-based limiting similarity. The AITS randomization scheme performed better in terms of type I error rates, and therefore may be more appropriate when considering systems for which traits are not clustered by abundance.

Predicting Polycyclic Aromatic Hydrocarbon Bioavailability to Mammals from Incidentally Ingested Soils Using Partitioning and Fugacity.

Soil and dust ingestion is one of the major human exposure pathways to contaminated soil; however, pollutant transfer from ingested substances to humans cannot currently be confidently predicted. Soil polycyclic aromatic hydrocarbon (PAH) bioavailability is likely dependent upon properties linked to chemical potential and partitioning such as fugacity, fugacity capacity, soil organic carbon, and partitioning to simulated intestinal fluids. We estimated the oral PAH bioavailability of 19 historically contaminated soils fed to juvenile swine. Between soils, PAH blood content, with the exception of benzo(a)pyrene, was not linked to fugacity. In contrast, between individual PAHs, using partitioning explained PAH blood content (area under the curve = 0.47 log fugacity + 0.34, r(2) = 0.68, p < 0.005, n = 14). Soil fugacity capacity predicts PAH soil concentration with an average slope of 0.30 (µg PAH g(-1) soil) Pa(-1) and r(2)'s of 0.61-0.73. Because PAH blood content was independent of soil concentration, soil fugacity correlated to PAH bioavailability via soil fugacity's link to soil concentration. In conclusion, we can use fugacity to explain PAH uptake from a soil into blood. However, something other than partitioning is critical to explain the differences in PAH uptake into blood between soils.

Increased competition does not lead to increased phylogenetic overdispersion in a native grassland.

That competition is stronger among closely related species and leads to phylogenetic overdispersion is a common assumption in community ecology. However, tests of this assumption are rare and field-based experiments lacking. We tested the relationship between competition, the degree of relatedness, and overdispersion among plants experimentally and using a field survey in a native grassland. Relatedness did not affect competition, nor was competition associated with phylogenetic overdispersion. Further, there was only weak evidence for increased overdispersion at spatial scales where plants are likely to compete. These results challenge traditional theory, but are consistent with recent theories regarding the mechanisms of plant competition and its potential effect on phylogenetic structure. We suggest that specific conditions related to the form of competition and trait conservatism must be met for competition to cause phylogenetic overdispersion. Consequently, overdispersion as a result of competition is likely to be rare in natural communities.

Patterns of cross-continental variation in tree seed mass in the Canadian Boreal Forest.

Seed mass is an adaptive trait affecting species distribution, population dynamics and community structure. In widely distributed species, variation in seed mass may reflect both genetic adaptation to local environments and adaptive phenotypic plasticity. Acknowledging the difficulty in separating these two aspects, we examined the causal relationships determining seed mass variation to better understand adaptability and/or plasticity of selected tree species to spatial/climatic variation. A total of 504, 481 and 454 seed collections of black spruce (Picea mariana (Mill.) B.S.P.), white spruce (Picea glauca (Moench) Voss) and jack pine (Pinus banksiana Lamb) across the Canadian Boreal Forest, respectively, were selected. Correlation analyses were used to determine how seed mass vary with latitude, longitude, and altitude. Structural Equation Modeling was used to examine how geographic and climatic variables influence seed mass. Climatic factors explained a large portion of the variation in seed mass (34, 14 and 29%, for black spruce, white spruce and jack pine, respectively), indicating species-specific adaptation to long term climate conditions. Higher annual mean temperature and winter precipitation caused greater seed mass in black spruce, but annual precipitation was the controlling factor for white spruce. The combination of factors such as growing season temperature and evapotranspiration, temperature seasonality and annual precipitation together determined seed mass of jack pine. Overall, sites with higher winter temperatures were correlated with larger seeds. Thus, long-term climatic conditions, at least in part, determined spatial variation in seed mass. Black spruce and Jack pine, species with relatively more specific habitat requirements and less plasticity, had more variation in seed mass explained by climate than did the more plastic species white spruce. As traits such as seed mass are related to seedling growth and survival, they potentially influence forest species composition in a changing climate and should be included in future modeling of vegetation shifts.