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FIG. 2 in Changes in functional and taxonomic diversity and composition of corticolous lichens in an altitudinal gradient in Colombia
FIG. 2. — Number of species of the lichen families with higher diversity at each locality in the Chocó region of Valle del Cauca, Colombia.
FIG. 6 in Changes in functional and taxonomic diversity and composition of corticolous lichens in an altitudinal gradient in Colombia
FIG. 6. — Community Weighted Means (CWMs) of functional lichen traits along the altitudinal gradient in the Chocó region of Valle del Cauca, Colombia: A, crustose thallus; B, crustose thallus by microhabitat; C, foliose thallus; D, fruticose thallus; E, fruticose thallus by microhabitat; F, rhizines by microhabitat; G, cyanobacterial photobiont; H, vegetative propagules; I, ascoma; J, ascospore septation (septate, muriform and simple); K, thickness of the ascospore wall; L, size of the ascospores.
FIG. 7 in Changes in functional and taxonomic diversity and composition of corticolous lichens in an altitudinal gradient in Colombia
FIG. 7. — Functional diversity along the altitudinal gradient: A, relative Rao Index; B, functional Dominance.
FIG. 4 in Changes in functional and taxonomic diversity and composition of corticolous lichens in an altitudinal gradient in Colombia
FIG. 4. — Scatter plot for the alpha lichen diversity and tree density ratio in each study site in the Chocó region of Valle del Cauca, Colombia.
Frugivore-mediated seed dispersal in fragmented landscapes: Compositional and functional turnover from forest to matrix
<p>Seed dispersal by frugivores is a fundamental function for plant community dynamics in fragmented landscapes, where forest remnants are typically embedded in a matrix of anthropogenic habitats. Frugivores can mediate both connectivity among forest remnants and plant colonization of the matrix. However, it remains poorly understood how frugivore communities change from forest to matrix due to the loss or replacement of species with traits that are less advantageous in open habitats, and whether such changes ultimately influence the composition and traits of dispersed plants via species interactions. Here, we close this gap by using a unique dataset of seed-dispersal networks that were sampled in forest patches and adjacent matrix habitats of seven fragmented landscapes across Europe. We found a similar diversity of frugivores, plants and interactions contributing to seed dispersal in forest and matrix, but a high turnover (replacement) in all these components. The turnover of dispersed seeds was smaller than that of frugivore communities because different frugivore species provided complementary seed dispersal in forest and matrix. Importantly, the turnover involved functional changes towards larger and more mobile frugivores in the matrix, which dispersed taller, larger-seeded plants with later fruiting periods. Our study provides a trait-based understanding of frugivore-mediated seed dispersal through fragmented landscapes, uncovering non-random shifts that can have cascading consequences for the composition of regenerating plant communities. Our findings also highlight the importance of forest remnants and frugivore faunas for ecosystem resilience, demonstrating a high potential for passive forest restoration of unmanaged lands in the matrix.</p>
Frugivore-mediated seed dispersal in fragmented landscapes: Compositional and functional turnover from forest to matrix
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Drivers of plant diversity, community composition, functional traits and soil processes along an alpine gradient in the central Chilean Andes
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Data from: Functional regulation of aquaporin dynamics by lipid bilayer composition
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Selection on convergent functional traits drives compositional divergence in a tallgrass prairie restoration experiment
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Data from: Multiple sclerosis-associated changes in the composition and immune functions of spore-forming bacteria
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Plant Species Composition percent cover:Nutrient Network: A cross-site investigation of bottom-up control over herbaceous plant community dynamics and ecosystem function.
This experiment is one implementation of a globally distributed experiment, known as the Nutrient Network. At Cedar Creek, as in over 70 other sites in grasslands around the world, the experiment aims to describe impacts of increased nutrients (nitrogen, phosphorus, potassium, sulfur and other metals) and decreased herbivory (removal of mammals by fencing). Two overarching questions are being explored with these manipulations: 1. To what extent are plant production and diversity co-limited by multiple nutrients in herbaceous-dominated communities? 2. Under what conditions do grazers or fertilization control plant biomass, diversity, and composition? By utilizing identical protocols at diverse grassland sites around the world, NutNet aims to uncover both the generalities in ecosystem functioning, and the contingencies or differences which can obscure those common mechanisms. In addition to the standard NutNet protocol, e247 includes an additional low Nitrogen gradient (1 gram Nitrogen per meter squared per year and 5 grams Nitrogen per meter squared per year in addition to the standard 10 grams Nitrogen per meter squared per year).
Species composition and plant functional traits on Hog and Metompkin Islands, VA 2016-2017
Physical characteristics (soil salinity, elevation, distance from shoreline) and biological parameters (species composition, cover, biomass, and functional traits) were measured for plants on Hog Island (Northampton Co. VA) and Metompkin Island (Accomack County, VA). Physical parameters were measured during 2016. Plant biomass, species composition, percent cover, and functional traits were measured in 2017. Data Table 1: Environmental and geographic data on Hog and Metompkin Islands, VA 2016 Data Table 2: Species composition and aboveground plant functional traits on Hog and Metompkin Islands, VA 2017 Data Table 3: Vegetative biomass on Hog and Metompkin Islands, VA 2017 Data Table 4: Plot-level root functional traits on Hog and Metompkin Islands, VA 2017 Data Table 5: Latitude-longitude coordinates of plots on Hog and Metompkin Islands, VA 2016-2017
Data for "Decreasing snow cover alters functional composition and diversity of Arctic tundra"
<p>This page links to the data and code associated with the publication Niittynen et al. (2020) "<strong>Decreasing snow cover alters functional composition and diversity of Arctic tundra</strong>" published in PNAS ( <a href="https://doi.org/10.1073/pnas.2001254117">https://doi.org/10.1073/pnas.2001254117</a> ). The species data contain cover values of 200 vascular plant species recorded in 1325 study sites in Rastigaisa area in Northern Norway. The trait data includes species level median trait values for the 200 species calculated from records extracted from public databases for seven plant functional traits and community weighted means of these traits calculated for all the 1325 study sites. The environmental data contain six spatially continuous predictors used in the species level models. The data and analyses are described in the linked publication.</p>
Data from: Shifts in plant functional composition following long-term drought in grasslands
1. Plant traits can provide unique insights into plant performance at the community scale. Functional composition, defined by both functional diversity and community-weighted trait means (CWMs), can affect the stability of aboveground net primary production (ANPP) in response to climate extremes. Further complexity arises, however, when functional composition itself responds to environmental change. The duration of climate extremes, such as drought, is expected to increase with rising global temperatures; thus, understanding the impacts of long-term drought on functional composition and the corresponding effect that has on ecosystem function could improve predictions of ecosystem sensitivity to climate change. 2. We experimentally reduced growing season precipitation by 66% across six temperate grasslands for four years and measured changes in three indices of functional diversity (functional dispersion, richness, and evenness), community-weighted trait means, and phylogenetic diversity (PD). Specific leaf area (SLA), leaf nitrogen content (LNC) and (at most sites) leaf turgor loss point (πTLP) were measured for species cumulatively representing ~90% plant cover at each site. 3. Long-term drought led to increased community functional dispersion in three sites, with negligible effects on the remaining sites. Species re-ordering following the mortality/senescence of dominant species was the main driver of increased functional dispersion. The response of functional diversity was not consistently matched by changes in phylogenetic diversity. Community-level drought strategies (assessed as CWMs) largely shifted from drought tolerance to drought avoidance and/or escape strategies, as evidenced by higher community-weighted πTLP, SLA, and LNC. Lastly, ecosystem drought sensitivity (i.e. relative reduction in ANPP) was positively correlated with community-weighted SLA and negatively correlated with functional diversity. 4. Synthesis: Increased functional diversity following long-term drought may stabilize ecosystem functioning in response to future drought. However, shifts in community-scale drought strategies may increase ecosystem drought sensitivity, depending on the nature and timing of drought. Thus, our results highlight the importance of considering both functional diversity and abundance-weighted traits means of plant communities as their collective effect may either stabilize or enhance ecosystem sensitivity to drought.
Meta-analysis on pulse disturbances reveals differences in functional and compositional recovery across ecosystems
Most ecosystems are affected by anthropogenic or natural pulse disturbances, which alter the community composition and functioning for a limited period of time. Whether and how quickly communities recover from such pulses is central to our understanding of biodiversity dynamics and ecosystem organization, but also to nature conservation and management. Here, we present a meta-analysis of 508 (semi-)natural field experiments globally distributed across marine, terrestrial and freshwater ecosystems. We found recovery to be significant yet incomplete. At the end of the experiments, disturbed treatments resembled controls again when considering abundance (94%), biomass (82%), and univariate diversity measures (88%). Most disturbed treatments did not further depart from control after the pulse, indicating that few studies showed novel trajectories induced by the pulse. Only multivariate community composition on average showed little recovery: disturbed species composition remained dissimilar to the control throughout the experiment. Still, when experiments showed a higher compositional stability, they tended to also show higher functional stability. Recovery was more complete when systems had high resistance, whereas resilience and resistance were negatively correlated. The overall results were highly consistent across studies, but significant differences between ecosystems and organism groups appeared. Future research on disturbances should aim to understand these differences, but also fill obvious gaps in the empirical assessments for regions (especially the tropics), ecosystems and organisms. In summary, we provide general evidence that (semi-)natural communities can recover from pulse disturbances, but compositional aspects are more vulnerable to long-lasting effects of pulse disturbance than the emergent functions associated to them.
Data from: Tropical deforestation reduces plant mating quality by shifting the functional composition of pollinator communities
<p>Deforestation can impact the quality of pollen received by target plants (<i>i.e., </i>delivery of incompatible pollen, self-pollen, or pollen from closely related individuals). Such reductions in plant mating quality may be direct, when deforestation reduces plant population size and the availability of pollen donors, or indirect, when decreased mating quality results, for example, from shifts in the composition of the pollinator community. As most flowering plants depend on animal pollinators for reproduction, there is a need to understand the direct and indirect links between deforestation, pollinator community composition, and plant mating quality.</p> <p>We quantified the direct, pollen-donor-mediated and indirect, pollinator-mediated effects of deforestation on mating quality in <i>Heliconia tortuosa</i>, a tropical herb pollinated by low- and high-mobility hummingbirds. We used a confirmatory path analysis to test the hypothesis that deforestation (amount of forest cover and forest patch size) influenced mating quality (haplotype diversity of pollen pools, outcrossing, and biparental inbreeding) directly and indirectly through functional shifts in the composition of pollinator communities (proportion of high-mobility hummingbirds).</p> <p>We found that deforestation triggered functional shifts in the composition of pollinator communities, as the proportion of high-mobility hummingbirds increased significantly with the amount of forest cover and forest patch size. The composition of the pollinator community affected mating quality, as the haplotype diversity of pollen pools increased significantly with the proportion of high-mobility hummingbirds, while biparental inbreeding decreased significantly. Although we did not detect any significant direct, pollen-donor-mediated effects of deforestation on mating quality, reductions in the amount of forest cover and forest patch size resulted in functional shifts that filtered out high-mobility hummingbirds from the pollinator community, thereby reducing mating quality indirectly.</p> <p><i>Synthesis. </i>Deforestation primarily influenced plant mating quality through a cascading effect mediated by functional shifts in the composition of the pollinator community. Our results indicate that plant mating quality strongly depends on the composition of local pollinator communities. Functional shifts that filter out highly mobile and effective pollinators may reduce the transfer of genetically diverse pollen loads from unrelated plants. Such shifts may have pronounced effects on plant population dynamics and disrupt genetic connectivity.</p>
Data from: Parallel changes in gut microbiome composition and function during colonization, local adaptation and ecological speciation
<p>The processes of local adaptation and ecological speciation are often strongly shaped by biotic interactions such as competition and predation. One of the strongest lines of evidence that biotic interactions drive evolution comes from repeated divergence of lineages in association with repeated changes in the community of interacting species. Yet, relatively little is known about the repeatability of changes in gut microbial communities and their role in adaptation and divergence of host populations in nature. Here we utilize three cases of rapid, parallel adaptation and speciation in freshwater threespine stickleback to test for parallel changes in associated gut microbiomes. We find that features of the gut microbial communities have shifted repeatedly in the same direction in association with parallel divergence and speciation of stickleback hosts. These results suggest that changes to gut microbiomes can occur rapidly and predictably in conjunction with host evolution, and that host-microbe interactions might play an important role in host adaptation and diversification.</p>
Data from: Do temperate tree species diversity and identity influence soil microbial community function and composition?
Studies of biodiversity-ecosystem function in treed ecosystems have generally focused on aboveground functions. The present study investigates inter-trophic links between tree diversity and soil microbial community function and composition.We examined how microbial communities in surface mineral soil responded to experimental gradients of tree species richness (SR), functional diversity (FD), community-weighted mean trait value (CWM) and tree identity. The site was a 4-yr-old common garden experiment near Montreal, Canada, consisting of deciduous and evergreen tree species mixtures. Microbial community composition, community-level physiological profiles (CLPP) and respiration were evaluated using phospholipid fatty acid (PLFA) analysis and the MicroRespTM system, respectively. The relationship between tree species richness and glucose induced respiration (GIR), basal respiration (BR), metabolic quotient (qCO2) followed a positive but saturating shape. Microbial communities associated with species mixtures were more active (basal respiration (BR)), with higher biomass (glucose induced respiration (GIR)), and used a greater number of carbon sources than monocultures. Communities associated with deciduous tree species used a greater number of carbon sources than those associated with evergreen species, suggesting a greater soil carbon storage capacity. There were no differences in microbial composition (PLFA) between monocultures and SR mixtures. The FD and the CWM of several functional traits affected both BR and GIR. In general, the CWM of traits had stronger effects than did FD, suggesting that certain traits of dominant species have more effect on ecosystem processes than does FD. Both the functions of GIR and BR were positively related to aboveground tree community productivity. Both tree diversity (SR) and identity (species and functional identity – leaf habit) affected soil microbial community respiration, biomass and composition. For the first time, we identified functional traits related to life history strategy, as well as root traits that influence another trophic level, soil microbial community function, via effects on BR and GIR.
Data from: Functional traits and community composition: a comparison among community-weighted means, weighted correlations, and multilevel models
1. Of the several approaches that are used to analyze functional trait-environment relationships, the most popular is community-weighted mean regressions (CWMr) in which species trait values are averaged at the site level and then regressed against environmental variables. Other approaches include model-based methods and weighted correlations of different metrics of trait-environment associations, the best known of which is the fourth-corner correlation method. 2. We investigated these three general statistical approaches for trait-environment associations: CWMr, five weighted correlation metrics (Peres-Neto et al. 2017), and two multilevel models (MLM) using four different methods for computing p-values. We first compared the methods applied to a plant community dataset. To determine the validity of the statistical conclusions, we then performed a simulation study. 3. CWMr gave highly significant associations for both traits, while the other methods gave a mix of support. CWMr had inflated type I errors for some simulation scenarios, implying that the significant results for the data could be spurious. The weighted correlation methods had generally good type I error control but had low power. One of the multilevel models, that from Jamil et al. (2013), had both good type I error control and high power when an appropriate method was used to obtain p-values. In particular, if there was no correlation among species in their abundances among sites, a parametric bootstrap likelihood ratio test (LRT) gave the best power. When there was correlation among species in their abundances, a conditional parametric LRT had correct type I errors but had lower power. 4. There is no overall best method for identifying trait-environment associations. For the simple task of testing, one-by-one, associations between single environmental variables and single traits, the weighted correlations with permutation tests all had good type I error control, and their ease of implementation is an advantage. For the more complex task of multivariate analyses and model fitting, and when high statistical power is needed, we recommend MLM2 (Jamil et al. 2013); however, care must be taken to ensure against inflated type I errors. Because CWMr exhibited highly inflated type I error rates, it should always be avoided. 2. We investigated these three general statistical approaches for trait-environment associations: CWMr, five weighted correlation metrics (Peres-Neto et al. 2017), and two multilevel models (MLM) using five different methods for computing p-values. We first compared the methods applied to a plant community dataset. To determine the validity of the statistical conclusions, we then performed a simulation study. 3. CWMr gave highly significant associations for both traits, while the other methods gave a mix of support. CWMr had inflated type I errors for some simulation scenarios. The weighted correlation methods had generally good type I error control but had low power. One of the multilevel models, that from Jamil et al. (2013), had both good type I error control and high power when an appropriate method was used to obtain p-values. In particular, if there was no correlation among species in their abundances among sites, a parametric bootstrap likelihood ratio test (LRT) gave the best power. When there was correlation among species in their abundances, a conditional parametric LRT had correct type I errors but suffered from low power. 4. There is no overall best method for identifying trait-environment associations. For the simple task of testing, one-by-one, associations between single environmental variables and single traits, the weighted correlations with permutation tests all had good type I error control, and their ease of implementation is an advantage. For the more complex task of multivariate analyses and model fitting, and when high statistical power is needed, we recommend MLM2 (Jamil et al. 2013); however, care must be taken to ensure against inflated type I errors. Because CWMr exhibited highly inflated type I error rates, it should be avoided.
Dataset for paper "Interpreting the shifts in forest structure, plant community composition, diversity, and functional identity by using remote sensing-derived wildfire severity"
<p>Interpreting the shifts in forest structure, plant community composition, diversity, and functional identity by using remote sensing-derived wildfire severity . New collected data</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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