Find research datasets worth reusing

opencc-zeroJan 2024View details →

Data from: Parasite-mediated changes in host traits alter food web dynamics

Parasites commonly alter the phenotype of their host, thereby influencing competitive and consumer-resource interactions. This could trigger a cascade effect on the dynamics of biological communities, but the role of parasites in ecosystem processes is poorly understood. In this study, we investigate how parasite-induced trait modifications shape the dynamics of a complex lake food web using an allometric trophic network model (ATN). We simulated infections of stage-structured fish host populations via increased maintenance costs and predation risk. Our results show that host trait modifications can significantly impact host demography, with stage-specific biomass declines up to 60%. However, less severely affected host stages buffered these effects and sustained the population. Importantly, host biomass decline altered the dynamics of species interactions and these effects cascaded through the entire community, with biomass changes observed at all trophic levels. Our findings emphasize the importance of incorporating both indirect parasite effects and host life history in ecological network studies for more realistic simulations of community dynamics.

opencc-by-4.0Jan 2024View details →

Elevation differently shapes functional diversity patterns in understory forest communities when considering intraspecific and interspecific trait variability

Datasets used for the analysis done for the paper "Elevation differently shapes functional diversity patterns in understory forest communities when considering intraspecific and interspecific trait variability". Files present are: -Species x Plot (vegetation releveés). -Plot x Environment. -Plot x CWM_inter for Plant height, Leaf area, Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC) using the traits fixed for species, i.e., holding traits constant as the species mean, thus incorporating only turnover. -Plot x CWM_intra for Plant height, Leaf area, Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC) based on an individual by trait matrix, therefore incorporating both turnover and intraspecific trait variation. -Plot x SES-FD_inter (Standard Effect Size Functional Diversity) for Plant height, Leaf area, Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC) using the traits fixed for species, i.e., holding traits constant as the species mean, thus incorporating only turnover. -Plot x SES-FD_intra (Standard Effect Size Functional Diversity) for Plant height, Leaf area, Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC) based on an individual by trait matrix, therefore incorporating both turnover and intraspecific trait variation. All analysis were carried out using the software R version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria, <a href="http://www.R-project.org">http://www.R-project.org</a>) and can be consulted on GitHub https://github.com/AriannaFerrara/Elevation-and-Intraspecific-trait-variability.git

opencc-zeroFeb 2024View details →

funspace: an R package to build, analyze and plot functional trait spaces

Functional trait space analyses are pivotal to describe and compare organisms' functional diversity across the tree of life. Yet, there is no single application that streamlines the many sometimes-troublesome steps needed to build and analyze functional trait spaces. To fill this gap, we propose funspace, an R package to easily handle bivariate and multivariate (PCA-based) functional trait space analyses. The six functions that constitute the package can be grouped in three modules: 'Building and exploring', 'Mapping', and 'Plotting'. The building and exploring module defines the main features of a functional trait space (e.g., functional diversity metrics) by leveraging kernel density-based methods. The mapping module uses general additive models to map how a target variable distributes within a trait space. The plotting module provides many options for creating flexible and high-quality figures representing the outputs obtained from previous modules. We provide a worked example to demonstrate a complete funspace workflow. funspace will provide researchers working with functional traits across the tree of life with an indispensable asset to easily explore: (i) the main features of any functional trait space, (ii) the relationship between a functional trait space and any other biological or non-biological factor that might contribute to shaping species' functional diversity.

opencc-zeroMar 2024View details →

Resources for: Spatio-temporal integrated Bayesian species distribution models reveal lack of broad relationships between traits and range shifts

Aim: Climate change and habitat loss or degradation are some of the greatest threats that species face today, often resulting in range shifts. Species traits have been discussed as important predictors of range shifts, with the identification of general trends being of great interest for conservation efforts. However, studies reviewing relationships between traits and range shifts have questioned the existence of such generalized trends, due to mixed results and weak correlations, as well as analytical shortcomings. The aim of this study was to test this relationship empirically, using analytical approaches that account for common sources of bias when assessing range trends. Location: Tanzania, East Africa. Time period: 1980-1999 and 2000-2020. Major taxa studied: 57 savannah specialist birds found in Tanzania, belonging to 26 families and 11 orders. Methods: We applied recently developed integrated spatio-temporal species distribution models in R-INLA, combining citizen science and bird atlas data to estimate ranges of species, quantify range shifts, and test the predictive power of traditional trait groups, as well as exposure-related and sensitivity traits. We based our study on 40 years of bird observations in East African savannahs, a biome that has experienced increasing climatic and non-climatic pressures over recent decades. We correlated patterns of change with species traits. Results: We find indications of relationships identified by previous research, but low average explanatory power of traits from an ecological perspective, confirming the lack of meaningful general associations. However, our analysis finds compelling species-specific results. Main conclusions: We highlight the importance of individual assessments, while demonstrating the usefulness of our analytical approach for analyses of range shifts.

opencc-by-4.0Mar 2024View details →

EMMA-X GWAS results on S. pimpinellifolium RSA traits - part 2

The results of GWAS run through EMMA-X pipeline, on root system architecture traits of S. pimpinellifolim (wild tomato) exposed to control and salt stress conditions on agar plates. Traits are abbreviated as: aLRG for average lateral root growth rate, aLRL for average lateral root length, aLRLpTRS for the ratio between average lateral root length and total root size. The treatments are abbreviated with C or S for control or 100 mM NaCl treatments. The numbers in file name (0-4) indicate the days post transfer to agar plates containing treatment.

opencc-by-4.0Mar 2024View details →

EMMA-X GWAS results on S. pimpinellifolium RSA traits - part 1

opencc-zeroMar 2024View details →

Fast-slow traits predict competition network structure and its response to resources and enemies

Plants interact in complex networks but how network structure depends on resources, natural enemies, and species resource-use strategy remains poorly understood. Here, we quantified competition networks among 18 plants varying in fast-slow strategy, by testing how increased nutrient availability and reduced foliar pathogens affected intra- and inter-specific interactions. Our results show that nitrogen and pathogens altered several aspects of network structure, often in unexpected ways due to fast and slow-growing species responding differently. Nitrogen addition increased competition asymmetry in slow-growing networks, as expected, but decreased it in fast-growing networks. Pathogen reduction made networks more even and less skewed because pathogens targeted weaker competitors. Surprisingly, pathogens and nitrogen dampened each other's effect. Our results show that plant growth strategy is key to understanding how competition responds to resources and enemies, a prediction from classic theories that has rarely been tested by linking functional traits to competition networks.

opencc-zeroMar 2024View details →

The effect of experimental pollinator decline on pollinator-mediated selection on floral traits

Human-mediated environmental change, by reducing mean fitness, is hypothesized to strengthen selection on traits that mediate interactions among species. For example, human-mediated declines in pollinator populations are hypothesized to reduce mean seed production by increasing the magnitude of pollen limitation and thus strengthen pollinator-mediated selection on floral traits that increase pollinator attraction or pollen transfer efficiency. To test this hypothesis, we measured two female fitness components and six floral traits of Lobelia siphilitica plants exposed to supplemental hand-pollination, ambient open-pollination, or reduced open-pollination treatments. The reduced treatment simulated pollinator decline, while the supplemental treatment was used to estimate pollen limitation and pollinator-mediated selection. We found that plants in the reduced pollination treatment were significantly pollen-limited, resulting in pollinator-mediated selection for taller inflorescences and more vibrant petals, both traits that could increase pollinator attraction. This contrasts with plants in the ambient pollination treatment, where reproduction was not pollen-limited and there was no significant pollinator-mediated selection on any floral trait. Our results support the hypothesis that human-mediated environmental change can strengthen the selection on traits of interacting species and suggest that these traits have the potential to evolve in response to changing environments.

opencc-by-4.0Dec 2015View details →

Fig 1 in Different responses of epigeic beetles to heavy metal contamination depending on functional traits at the family level

Fig 1. Diagram of non-metric multidimensional scaling of beetle assemblages classified to three groups of contamination (square- almost uncontaminated sites, circle- moderately contaminated sites, diamond- highly contaminated sites)

opencc-by-4.0Dec 2015View details →

Fig 2 in Different responses of epigeic beetles to heavy metal contamination depending on functional traits at the family level

Fig 2. Mean total density ± SE of the most frequently occurring groups of beetles in three classes of contaminations along the season (circle- almost uncontaminated sites, square- moderately contaminated sites, triangle- highly contaminated sites).

Figure 8 in Unraveling distributional patterns and life-history traits of a deep-water shrimp Plesionika edwardsii (Decapoda, Pandalidae) under unexploited virgin conditions: a benchmark for fisheries management

Figure 8. Hypothesized life cycle of Plesionika edwardsii in the Azorean region. After the incubation period of shrimp eggs, (1) larvae are released into the water column and (2) juveniles develop in shallow waters. Mature females and males are distributed up to 600 m with a sexual segregation by depth: (3) non-ovigerous females are mainly found up to 200 m, (4) ovigerous females between 200 and 300 m, and (5) males from 400 to 500 m deep. Females are bigger than males, and ovigerous females are bigger than nonovigerous females. A bigger-deeper trend is observed up to 400 m. (6) Long larval stages of P. edwardsii increases its potential for dispersal (Landeira et al., 2009), favoring connectivity and stock homogeneity between adjacent areas.

Figure 5 in Unraveling distributional patterns and life-history traits of a deep-water shrimp Plesionika edwardsii (Decapoda, Pandalidae) under unexploited virgin conditions: a benchmark for fisheries management

Figure 5. Sex ratio of Plesionika edwardsii by depth stratum in the Azorean region during the period 1999–2000.

Figure 2 in Unraveling distributional patterns and life-history traits of a deep-water shrimp Plesionika edwardsii (Decapoda, Pandalidae) under unexploited virgin conditions: a benchmark for fisheries management

Figure 2. Seasonal predicted mean catch per unit effort (CPUE, g trap-1) by depth stratum for males, non-ovigerous and ovigerous females of Plesionika edwardsii in the Azorean region for the period 1999–2000. Light-colored symbols represent raw data. Detailed parameter estimates are in Tab. S4.

Figure 7 in Unraveling distributional patterns and life-history traits of a deep-water shrimp Plesionika edwardsii (Decapoda, Pandalidae) under unexploited virgin conditions: a benchmark for fisheries management

Figure 7. Size at which 50 % of the shrimps are mature (L 50) estimated for Plesionika edwardsii in the Azorean region fitting a logistic curve to the proportion of ovigerous females. Logistic curve was estimated combining all data obtained during the period 1999–2000.

Figure 4 in Unraveling distributional patterns and life-history traits of a deep-water shrimp Plesionika edwardsii (Decapoda, Pandalidae) under unexploited virgin conditions: a benchmark for fisheries management

Figure 4. Seasonal predicted mean cephalothorax length (CL) by depth stratum for males, non-ovigerous and ovigerous females of Plesionika edwardsii in the Azorean region for the period 1999–2000. Light-colored symbols represent raw data. Detailed parameter estimates are in Tab. S4.

Figure 1 in Unraveling distributional patterns and life-history traits of a deep-water shrimp Plesionika edwardsii (Decapoda, Pandalidae) under unexploited virgin conditions: a benchmark for fisheries management

Figure 1. Sampling areas of Plesionika edwardsii in the mid-North Atlantic Ocean, Azorean region (ICES Subdivision 10a2) between 1999 and 2000. Orange dots represent each site sampled by a trap.

Figure 6 in Unraveling distributional patterns and life-history traits of a deep-water shrimp Plesionika edwardsii (Decapoda, Pandalidae) under unexploited virgin conditions: a benchmark for fisheries management

Figure 6. Sex ratio of Plesionika edwardsii by size class in the Azorean region during the period 1999–2000.

Figure 3 in Unraveling distributional patterns and life-history traits of a deep-water shrimp Plesionika edwardsii (Decapoda, Pandalidae) under unexploited virgin conditions: a benchmark for fisheries management

Figure 3. Size frequency distribution of males, non-ovigerous and ovigerous females Plesionika edwardsii in the Azorean region during the period 1999-2000.

opencc-zeroApr 2024View details →

Accounting for nonlinear responses to traits improves range shift predictions

Accurately predicting species' range shifts in response to environmental change is paramount for understanding ecological processes and global change. In synthetic analyses, traits emerge as significant but weak predictors of species' range shifts across recent climate change. These studies assume linear responses to traits, while detailed empirical work often reveals trait responses that are unimodal and contain thresholds or other nonlinearities. We hypothesize that the use of linear modeling approaches fails to capture these nonlinearities and therefore may be under-powering traits to predict range shifts. We evaluate the predictive performance of approaches that can capture nonlinear relationships (ridge-regularized linear regression, support vector regression with linear and nonlinear kernels, and random forests). We apply our models using six multi-decadal range shift datasets for plants, moths, marine fish, birds, and small mammals. We show that nonlinear approaches can perform better than least-squares linear modeling in reproducing historical range shifts. Consistent with expectations, we identify dispersal and climatic niche traits as primary determinants of distribution shifts. Traits identified as important predictors and the direction of trait effects are generally consistent across models but there are notable exceptions. Among important predictors, there are more consistent responses to climatic niches than dispersal ability. Modest improvements in predictability when accounting for nonlinearities and interactions and the overall low amount of variance accounted for by trait predictors suggest limits to trait-based statistical predictive frameworks.