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14 results for “trait-based model”
Improving landscape-scale productivity estimates by integrating trait-based models and remotely-sensed foliar-trait and canopy-structural data
Assessing the impacts of anthropogenic degradation and climate change on global carbon cycling is hindered by a lack of clear, flexible, and easy-to-use productivity models along with scarce trait and productivity data for parameterizing and testing those models. We provide a simple solution: a mechanistic framework (RS-CFM) that combines remotely-sensed foliar-trait and canopy-structural data with trait-based metabolic theory to efficiently map productivity at large spatial scales. We test this framework by quantifying net primary productivity (NPP) at high-resolution (0.01-ha) in hyper-diverse Peruvian tropical forests (30,040 hectares) along a 3,322-m elevation gradient. Our analysis captures hotspots and elevational shifts in productivity more accurately and in greater detail than alternative empirical- and process-based models that use plant functional types. This result exposes how high-resolution, location-specific variation in traits and light competition drive variability in productivity, opening up possibilities to fully harness remote sensing data and reliably scale up from traits to map global productivity in a more direct, efficient, and cost-effective manner.
Improving landscape-scale productivity estimates by integrating trait-based models and remotely-sensed foliar-trait and canopy-structural data
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Experimental evidence of warming-induced disease emergence and its prediction by a trait-based mechanistic model
<p>Predicting the effects of seasonality and climate change on the emergence and spread of infectious disease remains difficult, in part because of poorly understood connections between warming and the mechanisms driving disease. Trait-based mechanistic models combined with thermal performance curves arising from the Metabolic Theory of Ecology (MTE) have been highlighted as a promising approach going forward; however, this framework has not been tested under controlled experimental conditions that isolate the role of gradual temporal warming on disease dynamics and emergence. Here, we provide experimental evidence that a slowly warming host – parasite system can be pushed through a critical transition into an epidemic state. We then show that a trait-based mechanistic model with MTE functional forms can predict the critical temperature for disease emergence, subsequent disease dynamics through time, and final infection prevalence in an experimentally warmed system of <i>Daphnia </i>and a microsporidian parasite. Our results serve as a proof of principle that trait-based mechanistic models using MTE sub-functions can predict warming-induced disease emergence in data-rich systems – a critical step towards generalizing the approach to other systems.</p>
Data: Trait-based food web model reveals the underlying mechanisms of biodiversity-ecosystem functioning relationships
<p>Data and code related to 'Trait-based food web model reveals the underlying mechanisms of biodiversity-ecosystem functioning relationships' to reproduce figures and analyses.</p>
Data from: Does trait-based joint species distribution modelling reveal the signature of competition in stream macroinvertebrate communities?
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Experimental evidence of warming-induced disease emergence and its prediction by a trait-based mechanistic model
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Data: Experimental evidence of warming-induced disease emergence and its prediction by a trait-based mechanistic model
<p>Predicting the effects of seasonality and climate change on the emergence and spread of infectious disease remains difficult, in part because of poorly understood connections between warming and the mechanisms driving disease. Trait-based mechanistic models combined with thermal performance curves arising from the Metabolic Theory of Ecology (MTE) have been highlighted as a promising approach going forward; however, this framework has not been tested under controlled experimental conditions that isolate the role of gradual temporal warming on disease dynamics and emergence. Here, we provide experimental evidence that a slowly warming host – parasite system can be pushed through a critical transition into an epidemic state. We then show that a trait-based mechanistic model with MTE functional forms can predict the critical temperature for disease emergence, subsequent disease dynamics through time, and final infection prevalence in an experimentally warmed system of <i>Daphnia </i>and a microsporidian parasite. Our results serve as a proof of principle that trait-based mechanistic models using MTE sub-functions can predict warming-induced disease emergence in data-rich systems – a critical step towards generalizing the approach to other systems.</p>
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.
Data from: Trait-based modeling of multi-host pathogen transmission: plant-pollinator networks
Epidemiological models for multi-host pathogen systems often classify individuals taxonomically and use species-specific parameter values, but in species-rich communities, that approach may require intractably many parameters. Trait-based epidemiological models offer a potential solution, but have not accounted for within-species trait variation or between-species trait overlap. Here, we propose and study trait-based models with host and vector communities represented as trait distributions without regard to species identity. To illustrate this approach, we develop SIS models for disease spread in plant-pollinator networks with continuous trait distributions. We model trait-dependent contact rates in two common scenarios: nested networks, and specialized plant-pollinator interactions based on trait matching. We find that disease spread in plant-pollinator networks is impacted the most by selective pollinators, universally attractive flowers, and co-specialized plant-pollinator pairs. When extreme pollinator traits are rare, pollinators with common traits are most important for disease spread, whereas when extreme flower traits are rare, flowers with uncommon traits impact disease spread the most. Greater nestedness and specialization both typically promote disease persistence. Given recent pollinator declines caused in part by pathogens, we discuss how trait-based models could inform conservation strategies for wild and managed pollinators. Furthermore, while we have applied our model to pollinators and pathogens, its framework is general and can be transferred to any kind of species interactions, in any community.
Supplemental data for "Patterns of West Nile virus in the Northeastern United States using negative binomial and mechanistic trait-based models"
<p>Supplemental data files for "Patterns of West Nile virus in the Northeastern United States using negative binomial and mechanistic trait-based models"</p> <p><strong>S1 Table File.</strong> A table containing the probability of obtaining a result of 0 WNV cases in 20 years based on the group-estimated negative binomial model for each county with no cases reported.</p> <p><strong>S2 Table File.</strong> A table containing the county temperature inputs used in this study, and the associated relative R0 predictions</p> <p><strong>S3. Table File.</strong> A table containing the negative binomial probabilities by county, including group identity and group populations.</p>
Data from: Intraspecific trait variation increases species diversity in a trait-based grassland model
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Data from: Trait-based modeling of multi-host pathogen transmission: plant-pollinator networks
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Data: Experimental evidence of warming-induced disease emergence and its prediction by a trait-based mechanistic model
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Data from: Recasting the dynamic equilibrium model through a functional lens: the interplay of trait-based community assembly and climate
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.