Find research datasets worth reusing

openCC0Mar 2018View details →

Effects of Salicaceae species litter type and moisture at 10 paired wetland by upland plots:Specialization, maintenance of diversity and ecosystem consequences of growth defense trade-offs in a model system: the hyper-diverse willow communities of Cedar Creek

Cedar Creek includes a diversity of habitats, which support an astonishing number of species (15) from a single evolutionary lineage: the willow family (Salicaceae). The physiological tolerances and abiotic mechanisms that maintain natural diversity in this hyper-diverse system are beginning to be understood; the role of biotic interactions, however, remains a major gap in understanding. We hypothesize that insect herbivory plays a critical role in niche partitioning, providing an important explanation for high willow diversity. Using a replicated series of common gardens and insect herbivore manipulations in resource rich and resource poor habitats, we are testing for evolved trade-offs between defense investment and growth rate. We expect specialized plant syndromes to emerge along the continuum from ???herbivore escape??? via fast growth in high resource environments to ???anti-herbivore protection??? via heavy investment in defense in low resource environments. Evolved growth/defense strategies that promote diversity are also likely to have ecosystem consequences due to foliar chemical influences on decomposition and the composition and diversity of the insect communities they support. The proposed research takes advantage of natural diversity, providing an important model system at Cedar Creek.

openCC0Mar 2018View details →

Initial Salicaceae species litter chemistry:Specialization, maintenance of diversity and ecosystem consequences of growth defense trade-offs in a model system: the hyper-diverse willow communities of Cedar Creek

openCC0Oct 2020View details →

2012 growing season water table depth in common gardens:Specialization, maintenance of diversity and ecosystem consequences of growth defense trade-offs in a model system, the hyper-diverse willow communities of Cedar Creek

openCC0Oct 2020View details →

Percent carbon and nitrogen in leaf tissue:Specialization, maintenance of diversity and ecosystem consequences of growth defense trade-offs in a model system, the hyper-diverse willow communities of Cedar Creek

opencc-by-4.0Jul 2020View details →

Training data for "Apply modeling on population or community data to see effect of year, habitat or site on species abundance"

Datasets for the "Apply modeling on population or community data to see effect of year, habitat or site on species abundance" Galaxy for ecology tutorial

opencc-zeroAug 2020View details →

Mobilisation of data to stakeholder communities: Bridging the research-practice gap using a commercial shellfish species model

Knowledge mobilisation is required to "bridge the gap" between research, policy and practice. This activity is dependent on the amount, richness and quality of the data published. To understand the impact of a changing climate on commercial species, stakeholder communities require better knowledge of their past and current situations. The common cockle (Cerastoderma edule) is an excellent model species for this type of analysis, as it is well-studied due to its cultural, commercial and ecological significance in west Europe. Recently, C. edule harvests have decreased, coinciding with frequent mass mortalities, due to factors such as a changing climate and diseases. In this study, macro and micro level marine historical ecology techniques were used to create datasets on topics including: cockle abundance, spawning duration and harvest levels, as well as the ecological factors impacting those cockle populations. These data were correlated with changing climate and the Atlantic Multidecadal Oscillation (AMO) index to assess if they are drivers of cockle abundance and harvesting. The analyses identified the key stakeholder communities involved in cockle research and data acquisition. It highlighted that data collection was sporadic and lacking in cross-national/stakeholder community coordination. A major finding was that local variability in cockle populations is influenced by biotic (parasites) and abiotic (temperature, legislation and harvesting) factors, and at a global scale by climate (AMO Index). This comprehensive study provided an insight into the European cockle fishery but also highlights the need to identify the type of data required, the importance of standardised monitoring, and dissemination efforts, taking into account the knowledge, source, and audience. These factors are key elements that will be highly beneficial not only to the cockle stakeholder communities but to other commercial species.

opencc-by-4.0Nov 2020View details →

Contrasting aerosol effects on longwave cloud forcing in South East Asia and Amazon simulated with Community Atmosphere Model version 5.3

Aerosols modify cloud microphysical and radiative properties and thus impact the shortwave (SW) and longwave cloud forcing (LWCF). This study first reports the finding of contrasting aerosol effects on LWCF in South East Asia and Amazon in the Community Atmosphere Model version 5.3 (CAM5.3), which corresponds to the sum of LW indirect and semi-direct effects investigated in Ghan et al., (2012). A series of numerical experiments is conducted to decompose the complex aerosol effects on LWCF. Our analysis indicates that the cooling (negative aerosol effects on LWCF) in Amazon is due mainly to the aerosol effects on warm clouds and the inhibition of vertical motion by the aerosol-induced radiative cooling. In contrast, the warming (positive aerosol effects on LWCF) in South East Asia is due mainly to the aerosol effect on homogeneous freezing, thus reducing the ice particle size and prolonging the existence of ice cloud. Our results emphasize that a comprehensive analysis of integrated aerosol effects on both warm and ice clouds is necessary for better understanding the aerosol effects on LWCF.

opencc-zeroDec 2014View details →

Data from: A hierarchical distance sampling model to estimate abundance and covariate associations of species and communities

Distance sampling is a common survey method in wildlife studies, because it allows accounting for imperfect detection. The framework has been extended to hierarchical distance sampling (HDS), which accommodates the modelling of abundance as a function of covariates, but rare and elusive species may not yield enough observations to fit such a model. We integrate HDS into a community modelling framework that accommodates multi-species spatially replicated distance sampling data. The model allows species-specific parameters, but these come from a common underlying distribution. This form of information sharing enables estimation of parameters for species with sparse data sets that would otherwise be discarded from analysis. We evaluate the performance of the model under varying community sizes with different species-specific abundances through a simulation study. We further fit the model to a seabird data set obtained from shipboard distance sampling surveys off the East Coast of the USA. Comparing communities comprised of 5, 15 or 30 species, bias of all community-level parameters and some species-level parameters decreased with increasing community size, while precision increased. Most species-level parameters were less biased for more abundant species. For larger communities, the community model increased precision in abundance estimates of rarely observed species when compared to single-species models. For the seabird application, we found a strong negative association of community and species abundance with distance to shore. Water temperature and prey density had weak effects on seabird abundance. Patterns in overall abundance were consistent with known seabird ecology. The community distance sampling model can be expanded to account for imperfect availability, imperfect species identification or other missing individual covariates. The model allowed us to make inference about ecology of species communities, including rarely observed species, which is particularly important in conservation and management. The approach holds great potential to improve inference on species communities that can be surveyed with distance sampling.

opencc-zeroDec 2014View details →

Data from: Auxotrophy and intra-population complementary in the 'interactome' of a cultivated freshwater model community

Microorganisms are usually studied either in highly complex natural communities or in isolation as monoclonal model populations that we manage to grow in the laboratory. Here, we uncover the biology of some of the most common and yet-uncultured bacteria in freshwater environments using a mixed culture from Lake Grosse Fuchskuhle. From a single shotgun metagenome of a freshwater mixed culture of low complexity, we recovered four high-quality metagenome-assembled genomes (MAGs) for metabolic reconstruction. This analysis revealed the metabolic interconnectedness and niche partitioning of these naturally dominant bacteria. In particular, vitamin- and amino acid biosynthetic pathways were distributed unequally with a member of Crenarchaeota most likely being the sole producer of vitamin B12 in the mixed culture. Using coverage-based partitioning of the genes recovered from a single MAG intrapopulation metabolic complementarity was revealed pointing to 'social' interactions for the common good of populations dominating freshwater plankton. As such, our MAGs highlight the power of mixed cultures to extract naturally occurring 'interactomes' and to overcome our inability to isolate and grow the microbes dominating in nature.

opencc-zeroDec 2015View details →

Data from: Recasting the dynamic equilibrium model through a functional lens: the interplay of trait-based community assembly and climate

1. According to the dynamic equilibrium hypothesis (DEH), plant species richness is locally controlled by productivity and disturbance. Given that regional conditions widely affect local environmental variables such as soil nutrient availability, the DEH predictions could be improved by considering how climate influences local controls of species richness. Further, a trait-based approach to community assembly has the potential to reveal a deeper, mechanistic understanding of species richness variation across environments. Here we bring together DEH and trait-based community assembly expectations to examine if and how local relationships between diversity, disturbance and productivity are affected by habitat filtering and regional climate. 2. We specifically tested how gradients of local nutrient availability and disturbance intensity interact with climatic conditions to drive the species richness of grassland communities. Further, we recast the DEH through a functional lens by exploring how disturbance-diversity and nutrient availability-diversity relationships are shaped by the functional space occupied by species in a community and species packing within this functional space. 3. The functional space occupied by co-occurring species and the way they are functionally packed are quantified using multi-trait indices calculated with five core plant functional traits. Working with grassland communities spread across differing regional climatic conditions, we used mixed models to test if the variation in taxonomic and functional metrics corresponded to the dynamic equilibrium model's predictions as well as to determine the relationship between those metrics. 4. Contrary to the expectations based on the relation between species richness and the functional components considered, taxonomic and functional metrics did not vary in accordance along environmental gradients. Climate strongly interacted with the local environment to modulate local diversity patterns, sometimes even inversing a given trend and falsifying the DEH predictions. 5. Synthesis. Our findings quantitatively highlight the interplay between regional and local environmental gradients in driving community assembly. We demonstrate that, depending on climatic conditions, observed patterns of both taxonomic and functional community composition can be opposite to expected productivity-diversity and disturbance-diversity relationships. This emphasizes the relevance of multi-faceted studies of biodiversity and the need for a more systematic quantification of regional controls in community assembly studies.

opencc-zeroDec 2016View details →

Data from: Multiresponse algorithms for community-level modeling: review of theory, applications, and comparison to species distribution models

1.Community-level models (CLMs) consider multiple, co-occurring species in model fitting and are lesser known alternatives to species distribution models (SDMs) for analyzing and predicting biodiversity patterns. CLMs simultaneously model multiple species, including rare species, while reducing overfitting and implicitly considering drivers of co-occurrence. Many CLMs are direct extensions of well-known SDMs and therefore should be familiar to ecologists. However, CLMs remain underutilized, and there have been few tests of their potential benefits and no systematic reviews of their assumptions and implementations. Here we review this emerging field and provide examples in R to fit common CLMs. Our goal is to introduce CLMs to a broader audience, and discuss their attributes, benefits, and limitations relative to SDMs. 2.We review i) statistical implementations and applications of CLMs, ii) their advantages and limitations, and iii) comparative analyses of CLMs and SDMs. We also suggest directions for future research. 3.We identify seven CLM algorithms with similar data structures and predictive outputs as SDMs that should be most accessible to ecologists familiar with species-level modeling, including five methods that predict assemblage composition and individual species distributions and two methods that model compositional turnover along environmental gradients. CLMs have been applied to numerous taxa, regions, and spatial scales, and a variety of topics (e.g., studying drivers of community structure or assessing relationships between community composition and functional traits). Studies suggest that the relative benefits of CLMs and SDMs may be case specific, especially in terms of predicting species distributions and community composition. However, CLMs may offer advantages in terms of computational efficiency, modeling rare species, and projecting to no-analog climates. A major shortcoming of CLMs is their reliance on presence-absence community composition data. 4.Studies are needed to assess the relative merits of SDMs and CLMs, and different CLM algorithms, with a focus on three key areas: i) under which circumstances CLMs improve predictions for rare species, ii) how CLMs perform under different community compositions (e.g. relative abundance of rare vs. common species), including the extent to which co-occurrence patterns are structured by biotic interactions, and iii) ability to project across time/space.

opencc-zeroJun 2021View details →

Data from: Achieving a step change in the tuberculosis epidemic through comprehensive community-wide intervention: A model-based analysis

Background: Global progress towards reducing tuberculosis (TB) incidence and mortality has consistently lagged behind World Health Organization targets leading to a perception that large reductions in TB burden cannot be achieved. However, several recent and historical trials suggest that intervention efforts that are comprehensive and focused can have substantial epidemiological impact. We aimed to quantify the potential epidemiological impact of an intensive but realistic, community-wide campaign utilizing existing tools, and designed to achieve a "step change" in TB burden. Methods: We developed a compartmental model of tuberculosis transmission in a mid-sized city in India, the country with the greatest absolute burden of TB worldwide. We modeled the impact of a campaign comprising one-time community-wide screening with treatment for TB disease and preventive therapy for latent TB infection (LTBI). This one-time intervention was followed by strengthening of tuberculosis-related health system achieved by leveraging the one-time campaign. We estimated the tuberculosis cases and deaths that could be averted over 10 years using this comprehensive approach and assessed the contributions of individual components of the intervention. Results: A campaign that successfully screened 70% of the adult population for active and latent tuberculosis and subsequently reduced diagnostic and treatment delays and unsuccessful treatment outcomes by 50% was projected to avert 7,800 (95% range: 5,450 – 10,200) cases and 1,710 (1,290 – 2,180) tuberculosis-related deaths per 1 million population over 10 years. Of the total averted deaths, 33.5% (28.2 – 38.3) were attributable to inclusion of preventive therapy and 52.9% (48.4 - 56.9) to health system strengthening. Conclusions: A one-time, community-wide mass campaign, comprehensively designed to detect, treat, and prevent tuberculosis with currently existing tools can have meaningful and long-lasting epidemiological impact. Successful treatment of LTBI is critical to achieving this result. Health system strengthening is essential to any effort to transform the TB response.

opencc-by-4.0Dec 2019View details →

Community Radiative Transfer Model binary files

The Community Radiative Transfer Model (CRTM) is a JCSDA developed and distributed community model. It is used within the JCSDA JEDI framework, but is also a commonly used stand-alone radiative transfer model used across various federal agencies, research organizations, and universities. CRTM is licensed under the Creative Commons Zero license, and is fully within the public domain, including the dataset to be hosted here. The present dataset is the "binary files" that are used within the CRTM to enable it to compute clear-sky transmittances for various satellite sensors. There will be either 1 "tarball" file (tar.gz) with a total size of approximately 6 GB or less, or a structured directory consisting of 4139 files binary files consisting of big endian, little endian, netCDF3/4, pdf, and assorted binary assets totaling no more than 10GB (uncompressed). There will be occasion to add individual files, but no more than a weekly occurrence in general.

opencc-by-4.0Dec 2021View details →

Data for "Improvements in wintertime surface temperature variability in the Community Earth System Model version 2 (CESM2) related to the representation of snow density"

This dataset contains all the postprocessed data required to reproduce the figures in the publication Simpson et al (2022) "Improvements in wintertime surface temperature variability in the Community Earth System Model version 2 (CESM2) related to the representation of snow density", in the Journal of Advances in Modelling the Earth System.

opencc-zeroJan 2022View details →

Agent‐based modeling of the effects of forest dynamics, selective logging, and fragment size on epiphyte communities

Forest canopies play a crucial role in structuring communities of vascular epiphytes by providing substrate for colonization, by locally varying microclimate, and by causing epiphyte mortality due to branch or tree fall. However, as field studies in the three-dimensional habitat of epiphytes are generally challenging, our understanding of how forest structure and dynamics influence the structure and dynamics of epiphyte communities is scarce. Mechanistic models can improve our understanding of epiphyte community dynamics. We present such a model that couples dispersal, growth, and mortality of individual epiphytes with substrate dynamics, obtained from a three-dimensional functional-structural forest model, allowing the study of forest-epiphyte interactions. After validating the epiphyte model with independent field data, we performed several theoretical simulation experiments to assess how (1) differences in natural forest dynamics, (2) selective logging, and (3) forest fragmentation could influence the long-term dynamics of epiphyte communities. The proportion of arboreal substrate occupied by epiphytes (i.e. saturation level) was tightly linked with forest dynamics and increased with decreasing forest turnover rates. While species richness was, in general, negatively correlated with forest turnover rates, low species numbers in forests with very low turnover rates were due to competitive exclusion when epiphyte communities became saturated. Logging had a negative impact on epiphyte communities, potentially leading to a near-complete extirpation of epiphytes when the simulated target diameters fell below a threshold. Fragment size had no effect on epiphyte abundance and saturation level but correlated positively with species numbers. Synthesis: The presented model is a first step towards studying the dynamic forest-epiphyte interactions in an agent-based modelling framework. Our study suggests forest dynamics as key factor in controlling epiphyte communities. Thus, both natural and human-induced changes in forest dynamics, e.g. increased mortality rates or the loss of large trees, pose challenges for epiphyte conservation.

opencc-by-4.0Dec 2020View details →

Figure 7 in Spatiotemporal patterns in marine fish and cephalopods communities across scales: using an autoregressive spatiotemporal clustering model. A study of fish and cephalopods of the Eastern English Channel

Figure 7. – Eastern English Channel spatial community from low (blue) to high (red) median densities of numbers/ km2 in log scale are mapped, S522c1 (A), S522c2 (B).

opencc-by-4.0Dec 2020View details →

Figure S3 in Spatiotemporal patterns in marine fish and cephalopods communities across scales: using an autoregressive spatiotemporal clustering model. A study of fish and cephalopods of the Eastern English Channel

Figure S3. – Eastern English Channel spatial community from low (blue) to high (red) median densities of numbers/km2 in log scale are mapped, S782c1 (A), S782c2 (B), S1043sc1 (C), S1043sc2 (D), S1043sc3 (E).