Cognition from genes to ecology: individual differences incognition and its potential role in a social network
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Smith, Brian H.↗
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Results for “ecological network”
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AmeriFlux US-xCL NEON LBJ National Grassland (CLBJ)
This is the AmeriFlux version of the carbon flux data for the site US-xCL NEON LBJ National Grassland (CLBJ). Site Description - The LBJ Grasslands is 16,800 acres of land managed by the US Forest Service under the US Department of Agriculture. There is a rich legacy of land use, ranging back to the mid-19th century. Currently, LBJ Grasslands are used for recreation and hunting, livestock grazing, and fossil fuel extraction. Ongoing ecological monitoring is performed at the site, along with prescribed burning.
Network), NEON (National Ecological Observatory↗
AmeriFlux FLUXNET-1F US-xCL NEON LBJ National Grassland (CLBJ)
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xCL NEON LBJ National Grassland (CLBJ). This is the FLUXNET version of the carbon flux data for the site US-xCL NEON LBJ National Grassland (CLBJ) produced by applying the standard ONEFlux (1F) software. Site Description - The LBJ Grasslands is 16,800 acres of land managed by the US Forest Service under the US Department of Agriculture. There is a rich legacy of land use, ranging back to the mid-19th century. Currently, LBJ Grasslands are used for recreation and hunting, livestock grazing, and fossil fuel extraction. Ongoing ecological monitoring is performed at the site, along with prescribed burning.
Network), NEON (National Ecological Observatory↗
Predicting lake surface water phosphorus dynamics using process-guided machine learning
Phosphorus (P) loading to lakes is degrading the quality and usability of water globally. Accurate predictions of lake P dynamics are needed to understand whole-ecosystem P budgets, as well as the consequences of changing lake P concentrations for water quality. However, complex biophysical processes within lakes, along with limited observational data, challenge our capacity to reproduce short-term lake dynamics needed for water quality predictions, as well as long-term dynamics needed to understand broad scale controls over lake P. Here we use an emerging paradigm in modeling, process-guided machine learning (PGML), to produce a phosphorus budget for Lake Mendota (Wisconsin, USA) and to accurately predict epilimnetic phosphorus over a time range of days to decades. In our implementation of PGML, which we term a Process-Guided Recurrent Neural Network (PGRNN), we combine a process-based model for lake P with a recurrent neural network, and then constrain the predictions with ecological principles. We test independently the process-based model, the recurrent neural network, and the PGRNN to evaluate the overall approach. The process-based model accounted for most of the observed pattern in lake P; however it missed the long-term trend in lake P and had the worst performance in predicting winter and summer P in surface waters. The root mean square error (RMSE) for the process-based model, the recurrent neural network, and the PGRNN was 33.0 μg P L -1 , 22.7 μg P L -1 , and 20.7 μg P L -1 , respectively. All models performed better during summer, with RMSE values for the three models (same order) equal to 14.3 μg P L -1 , 10.9 μg P L -1 , and 10.7 μg P L -1 . Although the PGRNN had only marginally better RMSE during summer, it had lower bias and reproduced long-term decreases in lake P missed by the other two models. For all seasons and all years, the recurrent neural network had better predictions than process alone, with root mean square error (RMSE) of 23.8 μg P L -1 and 28.0 μg P L -1 , respectively. The output of PGRNN indicated that new processes related to water temperature, thermal stratification, and long term changes in external loads are needed to improve the process model. By using ecological knowledge, as well as the information content of complex data, PGML shows promise as a technique for accurate prediction in messy, real-world ecological dynamics, while providing valuable information that can improve our understanding of process.
54 ENVIRONMENTAL SCIENCES↗
Integrated Land Suitability Assessment for Depots Siting in a Sustainable Biomass Supply Chain
A sustainable biomass supply chain would require not only an effective and fluid transportation system with a reduced carbon footprint and costs, but also good soil characteristics ensuring durable biomass feedstock presence. Unlike existing approaches that fail to account for ecological factors, this work integrates ecological as well as economic factors for developing sustainable supply chain development. For feedstock to be sustainably supplied, it necessitates adequate environmental conditions, which need to be captured in supply chain analysis. Using geospatial data and heuristics, we present an integrated framework that models biomass production suitability, capturing the economic aspect via transportation network analysis and the environmental aspect via ecological indicators. Production suitability is estimated using scores, considering both ecological factors and road transportation networks. These factors include land cover/crop rotation, slope, soil properties (productivity, soil texture, and erodibility factor) and water availability. This scoring determines the spatial distribution of depots with priority to fields scoring the highest. Two methods for depot selection are presented using graph theory and a clustering algorithm to benefit from contextualized insights from both and potentially gain a more comprehensive understanding of biomass supply chain designs. Graph theory, via the clustering coefficient, helps determine dense areas in the network and indicate the most appropriate location for a depot. Clustering algorithm, via K-means, helps form clusters and determine the depot location at the center of these clusters. An application of this innovative concept is performed on a case study in the US South Atlantic, in the Piedmont region, determining distance traveled and depot locations, with implications on supply chain design. The findings from this study show that a more decentralized depot-based supply chain design with 3depots, obtained using the graph theory method, can be more economical and environmentally friendly compared to a design obtained from the clustering algorithm method with 2 depots. In the former, the distance from fields to depots totals 801,031,476 miles, while in the latter, it adds up to 1,037,606,072 miles, which represents about 30% more distance covered for feedstock transportation.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
AmeriFlux FLUXNET-1F US-xKA NEON Konza Prairie Biological Station - Relocatable (KONA)
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xKA NEON Konza Prairie Biological Station - Relocatable (KONA). This is the FLUXNET version of the carbon flux data for the site US-xKA NEON Konza Prairie Biological Station - Relocatable (KONA) produced by applying the standard ONEFlux (1F) software. Site Description - Konza Prairie Biological Station (KPBS) was established to provide a "natural laboratory" to conduct ecological research and is located on a 3,487 hectare native tallgrass prairie preserve.
Network), NEON (National Ecological Observatory↗
AmeriFlux FLUXNET-1F US-xKZ NEON Konza Prairie Biological Station (KONZ)
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xKZ NEON Konza Prairie Biological Station (KONZ). This is the FLUXNET version of the carbon flux data for the site US-xKZ NEON Konza Prairie Biological Station (KONZ) produced by applying the standard ONEFlux (1F) software. Site Description - Konza Prairie Biological Station (KPBS) was established to provide a "natural laboratory" to conduct ecological research and is located on a 3,487 hectare native tallgrass prairie preserve. KPBS is a field research station dedicated to conservation, education and long-term ecological research. Over 1,580 scientific papers have been published by scientists conducting studies at KPBS. The study of ecological patterns and processes in native tallgrass prairie ecosystems is the primary subject of research.
Network), NEON (National Ecological Observatory↗
AmeriFlux US-xGR NEON Great Smoky Mountains National Park, Twin Creeks (GRSM)
This is the AmeriFlux version of the carbon flux data for the site US-xGR NEON Great Smoky Mountains National Park, Twin Creeks (GRSM). Site Description - Great Smoky Mountains National Park straddles the ridgeline of the Great Smoky Mountains, the lower section in latitude of the Blue Ridge Mountains, which divides the larger Appalachian Mountain chain. The border between Tennessee and North Carolina runs northeast to southwest through the centerline of the park. Plants and animals common in the country's Northeast have found suitable ecological niches in the park's higher elevations, while southern species find homes in the balmier lower reaches.
Network), NEON (National Ecological Observatory↗
AmeriFlux FLUXNET-1F US-xGR NEON Great Smoky Mountains National Park, Twin Creeks (GRSM)
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xGR NEON Great Smoky Mountains National Park, Twin Creeks (GRSM). This is the FLUXNET version of the carbon flux data for the site US-xGR NEON Great Smoky Mountains National Park, Twin Creeks (GRSM) produced by applying the standard ONEFlux (1F) software. Site Description - Great Smoky Mountains National Park straddles the ridgeline of the Great Smoky Mountains, the lower section in latitude of the Blue Ridge Mountains, which divides the larger Appalachian Mountain chain. The border between Tennessee and North Carolina runs northeast to southwest through the centerline of the park. Plants and animals common in the country's Northeast have found suitable ecological niches in the park's higher elevations, while southern species find homes in the balmier lower reaches.
Network), NEON (National Ecological Observatory↗
AmeriFlux FLUXNET-1F US-xHA NEON Harvard Forest (HARV)
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xHA NEON Harvard Forest (HARV). This is the FLUXNET version of the carbon flux data for the site US-xHA NEON Harvard Forest (HARV) produced by applying the standard ONEFlux (1F) software. Site Description - The Harvard Forest site is comprised of 3,750 acres of land and multiple research facilities; it is the core NEON site for the Northeast region. Harvard Forest is a department of the Faculty of Arts and Sciences of Harvard University. Representative habitats at Harvard Forest include northern, transition, and central forests; marshes, swamps, and conifer-dominated bogs; and forest plantations. Since its inception in 1907, research and education have been the focus of Harvard Forest: the original purpose was to develop a field laboratory for students, a research center in forestry and related disciplines, and a demonstration of practical sustained forestry. Since 1988, Harvard Forest has been a Long-Term Ecological Research site, funded by the National Science Foundation to conduct integrated, long-term studies of forest dynamics.
Network), NEON (National Ecological Observatory↗
Multi‐Omics Analyses Reveal Divergent Molecular Mechanisms Underlying Plant Biomass Conversion by Five Fungi
Fungal plant biomass conversion (FPBC) is of great importance to the global carbon cycle and has been increasingly applied for the production of biofuel and biochemicals from lignocellulose. However, the comprehensive understanding of relevant molecular mechanisms in different fungi remains challenging. Here, we comparatively analyzed the transcriptome, proteome and metabolome profile of four ascomycetes and one basidiomycete fungi during their growth on two common agricultural feedstocks (soybean hulls and corn stover). We revealed strong time‐, substrate‐ and species‐specific responses at multi‐omics levels for the tested fungi, highlighting species‐specific carbon utilization approaches and evolutionary adaptation to environmental niches. Notably, a remarkable expressional diversity of lignocellulose degrading enzymes, sugar transporter and metabolic genes, as well as industrially relevant metabolites were identified across different fungi and cultivation conditions. The findings improves our understanding of complex molecular networks underlying FPBC and fungal ecological roles, offering novel insights that can guide future genetic engineering of fungi for valorization of agriculture waste into value‐added bioproducts.
CAZy↗
SoDaH: the SOils DAta Harmonization database, an open-source synthesis of soil data from research networks, version 1.0
Data collected from research networks present opportunities to test theories and develop models about factors responsible for the long-term persistence and vulnerability of soil organic matter (SOM). Synthesizing datasets collected by different research networks presents opportunities to expand the ecological gradients and scientific breadth of information available for inquiry. Synthesizing these data is challenging, especially considering the legacy of soil data that have already been collected and an expansion of new network science initiatives. To facilitate this effort, here we present the SOils DAta Harmonization database (SoDaH; https://lter.github.io/som-website, last access: 22 December 2020), a flexible database designed to harmonize diverse SOM datasets from multiple research networks. SoDaH is built on several network science efforts in the United States, but the tools built for SoDaH aim to provide an open-access resource to facilitate synthesis of soil carbon data. Moreover, SoDaH allows for individual locations to contribute results from experimental manipulations, repeated measurements from long-term studies, and local- to regional-scale gradients across ecosystems or landscapes. Finally, we also provide data visualization and analysis tools that can be used to query and analyze the aggregated database. The SoDaH v1.0 dataset is archived and available at https://doi.org/10.6073/pasta/9733f6b6d2ffd12bf126dc36a763e0b4 (Wieder et al., 2020).
54 ENVIRONMENTAL SCIENCES↗
Relationship between forest clearing and biophysical factors in tropical environments: Implications for the design of a forest change monitoring approach
The relationship between forest clearing, biophysical factors (e.g, ecological zones, slope gradient, soils), and transportation network in Costa Rica was analyzed. The location of forested areas at four reference datas (1940, 1950, 1961, and 1977) as derived from aerial photography and LANDSAT MSS data was digitilized and entered into a geographically-referenced data base. Ecological zones as protrayed by the Holdridge Life Zone Ecology System, and the location of roads and railways were also digitized from maps of the entire country as input to the data base. Information on slope gradient and soils was digitized from maps of a 21,000 square kilometer area. The total area of forest cleared over four decades are related to biophysical factors was analyzed within the data base and deforestation rates and trends were tabulated. The relatiohship between forest clearing and ecological zone and the influence of topography, sils, and transportation network are presented and discussed.
Sader, S. A.↗
AmeriFlux US-xBL NEON Blandy Experimental Farm (BLAN)
This is the AmeriFlux version of the carbon flux data for the site US-xBL NEON Blandy Experimental Farm (BLAN). Site Description - The Blandy Experimental Farm contains several land use types typically found in rural-suburban landscapes. This mix of land use types is typical and representative in the Middle Atlantic Domain. This site will be under increasing ecological pressure from urbanization within the rapidly growing megapolitan area. The amount of land cover and associated ecosystem processes in each of these land use types is expected to change over time.
Network), NEON (National Ecological Observatory↗
AmeriFlux FLUXNET-1F US-xBL NEON Blandy Experimental Farm (BLAN)
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xBL NEON Blandy Experimental Farm (BLAN). This is the FLUXNET version of the carbon flux data for the site US-xBL NEON Blandy Experimental Farm (BLAN) produced by applying the standard ONEFlux (1F) software. Site Description - The Blandy Experimental Farm contains several land use types typically found in rural-suburban landscapes. This mix of land use types is typical and representative in the Middle Atlantic Domain. This site will be under increasing ecological pressure from urbanization within the rapidly growing megapolitan area. The amount of land cover and associated ecosystem processes in each of these land use types is expected to change over time.
Network), NEON (National Ecological Observatory↗
Islands Within Islands: Bacterial Phylogenetic Structure and Consortia in Hawaiian Lava Caves and Fumaroles
Lava caves, tubes, and fumaroles in Hawai‘i present a range of volcanic, oligotrophic environments from different lava flows and host unexpectedly high levels of bacterial diversity. These features provide an opportunity to study the ecological drivers that structure bacterial community diversity and assemblies in volcanic ecosystems and compare the older, more stable environments of lava tubes, to the more variable and extreme conditions of younger, geothermally active caves and fumaroles. Using 16S rRNA amplicon-based sequencing methods, we investigated the phylogenetic distinctness and diversity and identified microbial interactions and consortia through co-occurrence networks in 70 samples from lava tubes, geothermal lava caves, and fumaroles on the island of Hawai‘i. Our data illustrate that lava caves and geothermal sites harbor unique microbial communities, with very little overlap between caves or sites. We also found that older lava tubes (500–800 yrs old) hosted greater phylogenetic diversity (Faith's PD) than sites that were either geothermally active or younger (<400 yrs old). Geothermally active sites had a greater number of interactions and complexity than lava tubes. Average phylogenetic distinctness, a measure of the phylogenetic relatedness of a community, was higher than would be expected if communities were structured at random. This suggests that bacterial communities of Hawaiian volcanic environments are phylogenetically over-dispersed and that competitive exclusion is the main driver in structuring these communities. This was supported by network analyses that found that taxa (Class level) co-occurred with more distantly related organisms than close relatives, particularly in geothermal sites. Network “hubs” (taxa of potentially higher ecological importance) were not the most abundant taxa in either geothermal sites or lava tubes and were identified as unknown families or genera of the phyla, Chloroflexi and Acidobacteria. These results highlight the need for further study on the ecological role of microbes in caves through targeted culturing methods, metagenomics, and long-read sequence technologies.
59 BASIC BIOLOGICAL SCIENCES↗
Ecology Based Decentralized Agent Management System
The problem of maintaining a desired number of mobile agents on a network is not trivial, especially if we want a completely decentralized solution. Decentralized control makes a system more r e bust and less susceptible to partial failures. The problem is exacerbated on wireless ad hoc networks where host mobility can result in significant changes in the network size and topology. In this paper we propose an ecology-inspired approach to the management of the number of agents. The approach associates agents with living organisms and tasks with food. Agents procreate or die based on the abundance of uncompleted tasks (food). We performed a series of experiments investigating properties of such systems and analyzed their stability under various conditions. We concluded that the ecology based metaphor can be successfully applied to the management of agent populations on wireless ad hoc networks.
Peysakhov, Maxim D.↗
AmeriFlux FLUXNET-1F US-xJE NEON Jones Ecological Research Center (JERC)
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xJE NEON Jones Ecological Research Center (JERC). This is the FLUXNET version of the carbon flux data for the site US-xJE NEON Jones Ecological Research Center (JERC) produced by applying the standard ONEFlux (1F) software. Site Description - This terrestrial relocatable field site is located in the Joseph Jones Ecological Research Center is an 11,000-hectare reserve located within the Lower Coastal Plains and Flatwoods areas in southern Georgia. The Jones site has been managed with low intensity, dormant-season prescribed fires for the past 75 years at a frequency of every 3-4 years.
Network), NEON (National Ecological Observatory↗