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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network and Analysis of Complementarity with Existing Ecological Networks

Abstract Studies conducted at sites across ecological research networks usually strive to scale their results to larger areas, trying to reach conclusions that are valid throughout larger enclosing regions. Network representativeness and constituency can show how well conditions at sampling locations represent conditions also found elsewhere and can be used to help scale-up results over larger regions. Multivariate statistical methods have been used to design networks and select sites that optimize regional representation, thereby maximizing the value of datasets and research. However, in networks created from already established sites, an immediate challenge is to understand how well existing sites represent the range of environments in the whole area of interest. We performed an analysis to show how well sites in the USDA Long-Term Agroecosystem Research (LTAR) Network represent all agricultural working lands within the conterminous United States (CONUS). Our analysis of 18 LTAR sites, based on 15 climatic and edaphic characteristics, produced maps of representativeness and constituency. Representativeness of the LTAR sites was quantified through an exhaustive pairwise Euclidean distance calculation in multivariate space, between the locations of experiments within each LTAR site and every 1 km cell across the CONUS. Network representativeness is from the perspective of all CONUS locations, but we also considered the perspective from each LTAR site. For every LTAR site, we identified the region that is best represented by that particular site—its constituency—as the set of 1 km grid locations best represented by the environmental drivers at that particular LTAR site. Representativeness shows how well the combination of characteristics at each CONUS location was represented by the LTAR sites’ environments, while constituency shows which LTAR site was the closest match for each location. LTAR representativeness was good across most of the CONUS. Representativeness for croplands was higher than for grazinglands, probably because croplands have more specific environmental criteria. Constituencies resemble ecoregions but have their environmental conditions “centered” on those at particular existing LTAR sites. Constituency of LTAR sites can be used to prioritize the locations of experimental research at or even within particular sites, or to identify the extents that can likely be included when generalizing knowledge across larger regions of the CONUS. Sites with a large constituency have generalist environments, while those with smaller constituency areas have more specialized environmental combinations. These “specialist” sites are the best representatives for smaller, more unusual areas. The potential of sharing complementary sites from the Long-Term Ecological Research (LTER) Network and the National Ecological Observatory Network (NEON) to boost representativeness was also explored. LTAR network representativeness would benefit from borrowing several NEON sites and the Sevilleta LTER site. Later network additions must include such specialist sites that are targeted to represent unique missing environments. While this analysis exhaustively considered principal environmental characteristics related to production on working lands, we did not consider the focal agronomic systems under study, or their socio-economic context.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Microbial Community Structure and Ecological Networks during Simulation of Diatom Sinking

Microbial-mediated utilization of particulate organic matter (POM) during its downward transport from the surface to the deep ocean constitutes a critical component of the global ocean carbon cycle. However, it remains unclear as to how high hydrostatic pressure (HHP) and low temperature (LT) with the sinking particles affects community structure and network interactions of the particle-attached microorganisms (PAM) and those free-living microorganisms (FLM) in the surrounding water. In this study, we investigated microbial succession and network interactions in experiments simulating POM sinking in the ocean. Diatom-derived 13C- and 12C-labeled POM were used to incubate surface water microbial communities from the East China Sea (ECS) under pressure (temperature) of 0.1 (25 °C), 20 (4 °C), and 40 (4 °C) MPa (megapascal). Our results show that the diversity and species richness of the PAM and FLM communities decreased significantly with HHP and LT. Microbial community analysis indicated an increase in the relative abundance of Bacteroidetes at high pressure (40 MPa), mostly at the expense of Gammaproteobacteria, Alphaproteobacteria, and Gracilibacteria at atmospheric pressure. Hydrostatic pressure and temperature affected lifestyle preferences between particle-attached (PA) and free-living (FL) microbes. Ecological network analysis showed that HHP and LT enhanced microbial network interactions and resulted in higher vulnerability to networks of the PAM communities and more resilience of those of the FLM communities. Most interestingly, the PAM communities occupied most of the module hubs of the networks, whereas the FLM communities mainly served as connectors of the modules, suggesting their different ecological roles of the two groups of microbes. These results provided novel insights into how HHP and LT affected microbial community dynamics, ecological networks during POM sinking, and the implications for carbon cycling in the ocean.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Long-term excess nitrogen fertilizer increases sensitivity of soil microbial community to seasonal change revealed by ecological network and metagenome analyses

Nitrogen (N) fertilizer has often been generously applied to increase crop biomass yield. Although the influences of inorganic N fertilizer on soil microbial communities have been widely studied, the effect of N fertilizer on microbial co-occurrence networks and its metagenome is largely unknown. Further, seasonal changes in microbial community responses to N addition have rarely been reported. In this study, three N fertilizer rates (0, 56, 196 kg N/ha) were applied annually in switchgrass (Panicum virgatum L.) grown for bioenergy production in the upper Midwest, USA. The soil microbiome was affected by both fertilizer and low pH in the 7th year of fertilization treatments. The microbial community structures were relatively stable during the growing season for each N fertilizer rate. However, the excess N fertilizer (196N) increased the seasonal variation of bacterial and fungal communities. Network analysis showed that the microbial interactions at the 196N treatment were more intense, with decreased bacteria-fungal interactions compared to 56N and 0N. Furthermore, this suggests that the microbial community became more sensitive to environmental change under the influence of long-term excess N fertilizer. Metagenomic analysis showed that the long-term excess N fertilizer promoted many metabolic processes, especially carbohydrate and amino acid related metabolism and Archaea mediated ammonia oxidation. However, N fertilizer also reduced many other traits, especially N 2 fixation and signal transduction, the latter of which may contribute to the decreased interactions between bacteria and fungi.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Phylogenetic structure of specialization: A new approach that integrates partner availability and phylogenetic diversity to quantify biotic specialization in ecological networks

Abstract Biotic specialization holds information about the assembly, evolution, and stability of biological communities. Partner availabilities can play an important role in enabling species interactions, where uneven partner availabilities can bias estimates of biotic specialization when using phylogenetic diversity indices. It is therefore important to account for partner availability when characterizing biotic specialization using phylogenies. We developed an index, phylogenetic structure of specialization (PSS), that avoids bias from uneven partner availabilities by uncoupling the null models for interaction frequency and phylogenetic distance. We incorporate the deviation between observed and random interaction frequencies as weights into the calculation of partner phylogenetic α‐diversity. To calculate the PSS index, we then compare observed partner phylogenetic α‐diversity to a null distribution generated by randomizing phylogenetic distances among the same number of partners. PSS quantifies the phylogenetic structure (i.e., clustered, overdispersed, or random) of the partners of a focal species. We show with simulations that the PSS index is not correlated with network properties, which allows comparisons across multiple systems. We also implemented PSS on empirical networks of host–parasite, avian seed‐dispersal, lichenized fungi–cyanobacteria, and hummingbird pollination interactions. Across these systems, a large proportion of taxa interact with phylogenetically random partners according to PSS, sometimes to a larger extent than detected with an existing method that does not account for partner availability. We also found that many taxa interact with phylogenetically clustered partners, while taxa with overdispersed partners were rare. We argue that species with phylogenetically overdispersed partners have often been misinterpreted as generalists when they should be considered specialists. Our results highlight the important role of randomness in shaping interaction networks, even in highly intimate symbioses, and provide a much‐needed quantitative framework to assess the role that evolutionary history and symbiotic specialization play in shaping patterns of biodiversity. PSS is available as an R package at https://github.com/cjpardodelahoz/pss .

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2004

Southeast Ecological Observatory Network (SEEON) Workshop on Ecological Sensors and Information Technology. Report on Second SEEON Workshop

A fundamental goal of the new National Science Foundation (NSF) initiative National Ecological Observatory Network (NEON) is to provide timely and broad access to the ecological data collected at NEON sites. Information management and data collection will be critical components to achieving this goal and a successful NEON implementation. The Southeast Ecological Observatory Network (SEEON) working group recognized the importance of information management and sensor technology in its first planning workshop and recommended that interested parties in the region come together to discuss these subjects in the context of the needs and capabilities of a southeast regional ecological observatory network. In February 2004, 28 participants from 14 organizations including academic institutions, state and federal agencies, private and non-profit entities convened at the Space Life Sciences Laboratory (SLSL) at the Kennedy Space Center, Florida for two days of presentations and discussions on ecological sensors and information management. Some of the participants were previously involved in the first SEEON workshop or other meetings concerned with NEON, but many were somewhat new to the NEON community. Each day focused on a different technical component, i.e. ecological sensors the first day and cyber-infrastructure the second day, and were structured in a similar manner. The mornings were devoted to presentations by experts to help stimulate discussions on aspects of the focal topic held in the afternoon. The formal and informal discussions held during the workshop succeeded in validating some concerns and needs identified in the first SEEON workshop, but also served to bring to light other questions or issues that will need to be addressed as the NEON planning and design stages move forward. While the expansion of the SEEON community meant that some of the presentation and discussion time was needed to help bring the newcomers up to speed on the goals, objectives and current status of the various NEON efforts, the additional perspectives and technical expertise included in this workshop helped fuel some valuable interdisciplinary discussions that will need to continue to bring SEEON and NEON to fruition. Participants agreed that continued discussions of SEEON are needed , to keep up the momentum and that the southeast region must continue to be represented at the national level. It is vital that the all'the regions continue to push things forward for NEON to succeed.

Jones, Lori N.↗
NASA NTRS2019

The Terrestrial Organism and Biogeochemistry Spatial Sampling Design for the National Ecological Observatory Network

The National Ecological Observatory Network (NEON) seeks to facilitate ecological prediction at a continental scale by measuring processes that drive change and responses at sites across the United States for thirty years. The spatial distribution of observations of terrestrial organisms and soil within NEON sites is determined according to a “design‐based” sample design that relies on the randomization of sampling locations. Development of the sample design was guided by high‐level NEON objectives and the multitude of data products that will be subjected to numerous analytical approaches to address the causes and consequences of ecological change. A requirement framework permeates the NEON design, ensuring traceability from each facet of the design to the high‐level requirements that make the NEON mission statement actionable. Requirements were developed for the terrestrial sample design to guide the key components of the design: Randomizing the sample locations ensures the unbiased collection of data, is appropriate for organisms and soil, and provides data suitable for a variety of analyses. Stratification increases efficiency and allows sampling to focus on those parts of the landscape measured by other NEON observation platforms. Attention to the sample size and spatial plot allocation ensures that data products will be sufficient to inform questions asked of the data and the NEON objectives. Establishing a framework with the capacity for re‐evaluate and design iteration allows for adaption to unexpected challenges and optimization of the sample design based on early data returns. The utility of the NEON sampling design is highlighted by its application across terrestrial systems. The data generated from this unique design will be used to quantify patterns in: the abundance and diversity of small mammals, breeding birds, insects, and soil microbes; vegetation structure, biomass, productivity, and diversity; and soil biogeochemistry.

National Ecological Observatory Network↗
DOE OSTI2024

The Interplay of Binary and Quantitative Structure on the Stability of Mutualistic Networks

Synopsis Understanding how the structure of biological systems impacts their resilience (broadly defined) is a recurring question across multiple levels of biological organization. In ecology, considerable effort has been devoted to understanding how the structure of interactions between species in ecological networks is linked to different broad resilience outcomes, especially local stability. Still, nearly all of that work has focused on interaction structure in presence-absence terms and has not investigated quantitative structure, i.e., the arrangement of interaction strengths in ecological networks. We investigated how the interplay between binary and quantitative structure impacts stability in mutualistic interaction networks (those in which species interactions are mutually beneficial), using community matrix approaches. We additionally examined the effects of network complexity and within-guild competition for context. In terms of structure, we focused on understanding the stability impacts of nestedness, a structure in which more-specialized species interact with smaller subsets of the same species that more-generalized species interact with. Most mutualistic networks in nature display binary nestedness, which is puzzling because both binary and quantitative nestedness are known to be destabilizing on their own. We found that quantitative network structure has important consequences for local stability. In more-complex networks, binary-nested structures were the most stable configurations, depending on the quantitative structures, but which quantitative structure was stabilizing depended on network complexity and competitive context. As complexity increases and in the absence of within-guild competition, the most stable configurations have a nested binary structure with a complementary (i.e., anti-nested) quantitative structure. In the presence of within-guild competition, however, the most stable networks are those with a nested binary structure and a nested quantitative structure. In other words, the impact of interaction overlap on community persistence is dependent on the competitive context. These results help to explain the prevalence of binary-nested structures in nature and underscore the need for future empirical work on quantitative structure.

Zoology↗
DOE OSTI2025

Foliar element determination from field survey in association with the National Ecological Observatory Network Airborne Observation Platform survey, East River, Colorado 2018

The purpose of this dataset is to support research aimed at understanding the coupling between hydrologic and biogeochemical processes at watershed scale, particularly the relationship between aboveground vegetation characteristics and subsurface soil properties. These data are intended to inform and calibrate models of catchment-scale biogeochemical fluxes, including rock-derived nutrient cycling, and they were procured to address the following questions: (1) What is the distribution of vegetation characteristics across the study catchments? (2) Are foliar concentrations of rock-derived nutrients related to underlying lithology and soil availability, or are these signals masked by biotic nutrient cycling and retention processes?This data package contains foliar elemental data collected during the 2018 National Ecological Observatory Networks (NEON) Airborne Observation Platform (AOP) imaging spectroscopy and lidar surveys in Gunnison County, Colorado. Folair samples were collected across the East River, Washington Gulch, Slate River, and Coal Creek watersheds and contain a mixture of vegetation including meadow, shrub, and tree foliar samples. The samples were processed using aqua regia digestion and analyzed for elemental determination on inductively coupled plasma optical emission spectrometry (ICP-OES).The data package includes: (1) raw foliar elemental data files in CSV and PDF formats, (2) quality control certificates in PDF format, and (3) an aggregated CSV file containing all elemental measurements compiled across samples. No specialized software is required to access or use these files.

2018 National Ecological Observatory Network Campa↗
DOE OSTI2023

Relationship between isotope ratios in precipitation and stream water across watersheds of the National Ecological Observation Network

The timescales associated with precipitation moving through watersheds reveal processes that are critical to understanding many hydrologic systems. Measurements of environmental stable water isotope ratios (δ 2 H and δ 18 O) have been used as tracers to study hydrologic timescales by examining how long it takes for incoming precipitation tracers become stream discharge, yet limited measurements both spatially and temporally have bounded macroscale evaluations so far. Here in this observation driven study across North American biomes within the National Ecological Observation Network (NEON), we examined δ 18 O and δ 2 H stable water isotope in precipitation (δP) and stream water (δQ) at 26 co-located sites. With an average 54 precipitation samples and 139 stream water samples per site collected over 2014–2022, assessment of local meteoric water lines and local stream water lines showed geographic variation across North America. Taking the ratio of estimated seasonal amplitudes of δP and δQ to calculate young water fractions (F yw ), showed a Fyw range from 1% to 93% with most sites having F yw below 20%. Calculate d mean transit times (MTT) based on a gamma convolution model showed a MTT range from 0.10 to 13.2 years, with half of the sites having MTT estimates lower than 2 years. Significant correlations were found between the F yw and watershed area, longest flow length, and the longest flow length/slope. Significant correlations were found between MTT and site latitude, longitude, slope, clay fraction, temperature, precipitation magnitude, and precipitation frequency. The significant correlations between water timescale metrics and the environmental characteristics we report share some similarities with those reported in prior studies, demonstrating that these quantities are primarily driven by site or area specific factors. The analysis of isotope data presented here provides important constraints on isotope variation in North American biomes and the timescales of water movement through NEON study sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climate warming enhances microbial network complexity and stability

Unravelling the relationships between network complexity and stability under changing climate is a challenging topic in theoretical ecology that remains understudied in the field of microbial ecology. Here, we examined the effects of long-term experimental warming on the complexity and stability of molecular ecological networks in grassland soil microbial communities. Warming significantly increased network complexity, including network size, connectivity, connectance, average clustering coefficient, relative modularity and number of keystone species, as compared with the ambient control. Molecular ecological networks under warming became significantly more robust, with network stability strongly correlated with network complexity, supporting the central ecological belief that complexity begets stability. Furthermore, warming significantly strengthened the relationships of network structure to community functional potentials and key ecosystem functioning. Furthermore, these results indicate that preserving microbial ‘interactions’ is critical for ecosystem management and for projecting ecological consequences of future climate warming.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

The Plant Phenology Monitoring Design for the National Ecological Observatory Network

Phenology is an integrative science that comprises the study of recurring biological activities or events. In an era of rapidly changing climate, the relationship between the timing of those events and environmental cues such as temperature, snowmelt, water availability, or day length are of particular interest. This article provides an overview of the observer-based plant phenology sampling conducted by the U.S. National Ecological Observatory Network (NEON), the resulting data, and the rationale behind the design. Trained technicians will conduct regular in situ observations of plant phenology at all terrestrial NEON sites for the 30-yr life of the observatory. Standardized and coordinated data across the network of sites can be used to quantify the direction and magnitude of the relationships between phenology and environmental forcings, as well as the degree to which these relationships vary among sites, among species, among phenophases, and through time. Vegetation at NEON sites will also be monitored with tower-based cameras, satellite remote sensing, and annual high-resolution airborne remote sensing. Ground-based measurements can be used to calibrate and improve satellite-derived phenometrics. NEON's phenology monitoring design is complementary to existing phenology research efforts and citizen science initiatives throughout the world and will produce interoperable data. By collocating plant phenology observations with a suite of additional meteorological, biophysical, and ecological measurements (e.g., climate, carbon flux, plant productivity, population dynamics of consumers) at 47 terrestrial sites, the NEON design will enable continental-scale inference about the status, trends, causes, and ecological consequences of phenological change.

phenology↗
DOE OSTI2021

State changes: insights from the U.S. Long Term Ecological Research Network

Understanding the complex and unpredictable ways ecosystems are changing and predicting the state of ecosystems and the services they will provide in the future requires coordinated, long-term research. This paper is a product of a U.S. National Science Foundation funded Long Term Ecological Research (LTER)network synthesis effort that addressed anticipated changes in future populations and communities. Each LTER site described what their site would look like in50 or 100 yr based on long-term patterns and responses to global change drivers in each ecosystem. Common themes emerged and predictions were grouped into state change, connectivity, resilience, time lags, and cascading effects. Here, we report on the “state change” theme, which includes examples from the Georgia Coastal (coastal marsh), Konza Prairie (mesic grassland), Luquillo(tropical forest), Sevilleta (arid grassland), and Virginia Coastal (coastal grassland) sites. Ecological thresholds(the point at which small changes in an environmental driver can produce an abrupt and persistent state change in an ecosystem quality, property, or phenomenon) were most commonly predicted. For example, in coastal ecosystems, sea-level rise and climate change could convert salt marsh to mangroves and coastal barrier dunes to shrub thicket. Reduced fire frequency has converted grassland to shrubland in mesic prairie, whereas overgrazing combined with drought drive shrub encroachment in arid grasslands. Lastly, tropical cloud forests are susceptible to climate-induced changes in cloud base altitude leading to shifts in species distributions. Overall, these examples reveal that state change is a likely outcome of global environmental change across adverse range of ecosystems and highlight the need for long-term studies to sort out the causes and consequences of state change. The diversity of sites within the LTER network facilitates the emergence of overarching concepts about state changes as an important driver of ecosystem structure, function, services, and futures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Belowground cross-trophic networks impact CH4 and CO2 emissions in degraded alpine peatlands

Belowground organisms forming complex cross-trophic ecological networks are essential for maintaining peatland carbon stability and energy flow. However, how peatland degradation affects the biodiversity and cross-trophic ecological networks of soil communities remains poorly understood. Here, we examined the degradation effects on soil prokaryotes (i.e., bacteria, archaea), fungi and nematodes in alpine peatlands on the eastern Tibetan Plateau, characterized by varying water table depths (indicating degradation levels). We found that peatland degradation, accompanied by significant shifts in soil moisture and pH (P < 0.05), reduced the taxonomic richness and phylogenetic diversity of prokaryotes, fungi, and nematodes, particularly in deeper soil layers (20–50 cm). Crucially, peatland degradation weakened potential cross-trophic interactions within bipartite networks of prokaryotes-nematodes and fungi-nematodes, resulting in less than 6.5 %–28.8 % of unchanged modules. Degradation-induced changes in soil moisture and pH were identified as primary drivers of biodiversity loss and network restructuring. Furthermore, such changes of belowground cross-trophic networks (particularly prokaryote-nematode) were significantly correlated with greenhouse gas emissions, such as decreased CO2 emissions, maintained CH4 emissions (leading to a higher CH4/CO2 ratio in deep layers), and reduced temperature sensitivity (Q10) of soil respiration. These findings underscore the critical need to protect soil biodiversity and cross-trophic networks in peatlands, particularly under the threat of climate change, to preserve peatland carbon stocks and maintain ecosystem stability. Our findings highlight that belowground cross-trophic networks are pivotal to decipher soil carbon dynamics of degraded peatlands and project the fate of peatland carbon stocks under future climate change scenarios.

Cross-trophic networks↗
NASA NTRS2020

Exploring Carbon Mineral Systems: Recent Advances in C Mineral Evolution, Mineral Ecology, and Network Analysis

Large and growing data resources on the spatial and temporal diversity and distribution of the more than 400 carbon-bearing mineral species reveal patterns of mineral evolution and ecology. Recent advances in analytical and visualization techniques leverage these data and are propelling mineralogy from a largely descriptive field into one of prediction within complex, integrated, multidimensional systems. These discoveries include: (1) systematic changes in the character of carbon minerals and their networks of coexisting species through deep time; (2) improved statistical predictions of the number and types of carbon minerals that occur on Earth but are yet to be discovered and described; and (3) a range of proposed and ongoing studies related to the quantification of network structures and trends, relation of mineral “natural kinds” to their genetic environments, prediction of the location of mineral species across the globe, examination of the tectonic drivers of mineralization through deep time, quantification of preservational and sampling bias in the mineralogical record, and characterization of feedback relationships between minerals and geochemical environments with microbial populations. These aspects of Earth’s carbon mineralogy underscore the complex coevolution of the geosphere and biosphere and highlight the possibility for scientific discovery in Earth and planetary systems.

Carbon↗
DOE OSTI2024

Ecologically inspired metrics for transitioning to a sustainable and resilient circular economy with application to multilayer plastic films

Current Circular Economy (CE) frameworks applied to product chains exhibit notable shortcomings. These include neglecting the resilience and robustness of design, requiring detailed economic and environmental data for impact assessment, and relying on qualitative rather than quantitative metrics capturing certain CE design aspects. In the current contribution, we addressed these shortcomings by developing an Ecologically inspired (Eco-inspired) Framework using the mathematical foundations of Ecological Network Analysis (ENA). While ENA metrics have previously found application in designing circular economies, particularly in Industrial Symbiosis (IS) networks, our adaptation tailors these metrics for use in product-level CE, recognizing the inherent distinctions between product-level CE and IS. Our Eco-inspired Framework comprises three key categories to provide holistic and granular-level metrics for designing product-level CE. The first set of metrics assesses circularity and resource efficiency. The second set gauges network intensity and robustness as complementary indicators ensuring a CE is both sustainable and resilient. The third group of metrics evaluates enhancement potential of CE strategies through introducing quantitative metrics for measuring the degree of closed-loop strategies and average circularity level of a CE design. The three comprehensive set of indicators within the Eco-inspired Framework uniquely captures various facets of circular design, whether originating from technological innovations and recovery improvement at the end of life (EoL), shifts in human consumption patterns, alterations in product design, or changes in business models. The framework’s application is tested in designing a CE for multilayer Polyethylene-Polyamide (PE-PA) films. Using the Eco-inspired Framework, we identified the best strategy for designing a resilient and sustainable CE for PE-PA films. A diverse set of EoL strategies along with a reduction in product consumption can improve circularity and resilience by 650% and 255%, respectively, and mitigate greenhouse gas emissions by 90%. The framework minimizes trade-offs between sustainability and circularity goals and offers insights on how to enhance each strategy for achieving a resilient and sustainable CE for products.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Design methodologies and engineering applications for ecosystem biomimicry: an interdisciplinary review spanning cyber, physical, and cyber-physical systems

Abstract Ecosystem biomimicry is a promising pathway for sustainable development. However, while typical form- and process-level biomimicry is prevalent, system-level ecosystem biomimicry remains a nascent practice in numerous engineering fields. This critical review takes an interdisciplinary approach to synthesize trends across case studies, evaluate design methodologies, and identify future opportunities when applying ecosystem biomimicry to engineering practices, including cyber systems (CS), physical systems (PS), and cyber-physical systems (CPS). After systematically sourcing publications from major databases, the papers were first analyzed at a meta level for their bibliographic context and for statistical correlations among categorical variables. Then, we investigated deeper into the engineering applications and design methodologies. Results indicate that CPS most frequently mimic organisms and ecosystems, while CS and PS frequently mimic populations-communities and molecules-tissues-organ systems, respectively (statistically highly significant). An indirect approach is most often used for mimicry at organizational levels from populations to ecosystems, while a direct approach frequently suits levels from molecules to organisms (highly significant). Dominant themes across engineering applications include symbiotic organism search algorithms for CS and ecological network analysis for CPS, while PS are highly diverse. For design methodologies, this work summarizes and details ten well-documented biomimetic process models among literature, which addresses an outdated concern for a lack of systematic methods for ecosystem biomimicry. In addition to the Biomimetics Standard ISO 18458, these methods include the Natural Step and Techno-Ecological Synergy framework, among others. Further, the analyses revealed future opportunities from less utilized design methods (e.g. interdisciplinary teams tackling indirect, ecosystem-level projects) to well-established engineering concepts ready for technological advancement (e.g. implementing membrane computing for physical applications). For future studies, this review provides a comprehensive reference for ecosystem biomimetic design practices and application opportunities across multiple engineering domains.

42 ENGINEERING↗