Human Influence Research Articles

Indigenous and colonial influences on Amazonian forests

Societal Impact StatementGlobal climate models that incorporate carbon sources and sinks usually consider that forest uptake of carbon is in a state of equilibrium. Both historical and paleoecological records suggest that this is commonly not the case for Amazonia. Here, the impacts of colonial practices on Amazonian Indigenous peoples and forests are reviewed. Human activities affect forests' successional stages, trajectories, and species composition. By increasing the spatial coverage of paleoecological records that focus on pre‐ and post‐Columbian periods, the long‐term interactions between humans and Amazonian forests and their role in affecting Earth's climate may be better understood.SummaryLegacy effects left by the activities of Indigenous people in Amazonia are well known. Although severe, widespread, and recently occurring, the impacts left post‐1492 CE have been less investigated. We review the impact of colonial practices on Indigenous peoples and Amazonian forests. We suggest that forests comprise the sum of their past events, in a mosaic of different cumulative successional trajectories depending on the type, frequency, intensity, and timing of human influence. In regions with a history of minimal human influence, old‐growth species sensitive to fire would be the dominant landscape. In regions with high pre‐Columbian and low colonial influence, old‐growth forests carrying pre‐Columbian ecological legacies would be prevalent. Regions occupied by Indigenous groups post‐1492 CE would also carry similar ecological legacies. In regions influenced by the Jesuits, mid‐successional forests are expected to be enriched with cacao trees. In regions of latex extraction during the rubber boom, mid‐growth forests would present high abundances of early and mid‐successional species and depletion of some species. In deforested areas, we expect early successional forests with influence of exotic useful species. This patchwork of history probably plays a large role in shaping today's forests, and the biodiversity and carbon dynamics documented within them. Paleoecological work focusing on the last millennium, although scarce, has the potential to detect these mosaics of past human influence, and they should be considered when estimating forest ages and successional stages across the basin.

Dune behavior in the Source Area of the Yellow River under climate changes observed from various remote sensing datasets

Sand dunes are a landscape feature with a quick response time to climate change and human influences (e.g. grazing, greening projects, and fixation structures). Their migration rates and their development can help to gather information about changing environmental conditions over time. The Source Area of the Yellow River (SAYR), located upon the Tibetan Plateau, is highly complex with topographical, hydrological, and climatological influences on active dunes, making it a good study area for these interactions. Based on remote sensing datasets, spanning the last 54 years, 415 dunes were mapped for migration rate calculations. Further, climate data from ERA-5 reanalysis and a local climate station was used to assess their changes within a changing climate. Generally, dune migration rates are rather slow with an average of 3.62 m y-1. In accordance, the averaged resultant drift potential (RDP) values are lower than 10 m3/s−3(−|-). Further, we assessed the density development of the main active barchan dune field in direct premise of the Yellow River. Throughout the past 54 years, we observed the emergence of more than 5 new barchans per square kilometer. This increase is likely attributed to higher sand flux from the Yellow River, which has resulted from increased discharge due to declining snowfall and rising precipitation levels.

Effects of an extreme weather event over reproduction and survival of Great Tits (Parus major) in eastern Spain

AbstractThe frequency of extreme climatic and weather events has increased since 1950 due to global changes induced by human influence. These events can have significant impacts at the individual, population, and community levels across various taxonomic groups. They can be particularly detrimental to bird populations during their breeding season, affecting specific breeding parameters. This study originated from an exceptionally rare breeding season of a resident Great Tit population recorded in spring 2002 when an unusual mortality of nestlings was observed. We quantified weather conditions (temperature, rainfall) from the end of April, a few days before we started detecting failed nests, and compared them with previous and subsequent years. In early May, when many pairs were incubating or caring for newly hatched chicks, we detected unusually low ambient temperatures and unusually high rainfall. This event likely caused that many first clutches failed completely, and that, compared with previous and subsequent years, fledging and breeding success was relatively low in those which were successful. There was also an increased proportion of replacement clutches that year. Anyway, the overall production of fledglings per breeding pair over the breeding season was 2.39, lower than other years. Although recruitment rate in 2003 was similar to other years, the lower production of fledglings in 2002 probably resulted in a decrease in the number of breeding pairs in the following years.

EVALUATION OF THE CARBON FOOTPRINT IN THE TREATMENT OF URBAN WASTEWATER IN THE CANARY ISLANDS (SPAIN)

ABSTRACT: Wastewater treatment plants play an important role within the urban water cycle to prevent the natural water environment and human health from being negatively affected by human activities. However, wastewater treatment processes, such as effluent discharge and indirect emissions resulting from energy or chemical production, also negatively affect the environment. Footprints have been used to track human influence on the environment in different areas of interest and have been applied to assess the sustainability of wastewater treatment plants. In this article, a comprehensive review of footprint assessment was investigated to evaluate the wastewater treatment process in wastewater treatment plants. The review showed that carbon footprinting was used to assess the sustainability of WWTPs, and that other footprint assessment applications (such as nitrogen and phosphorus footprinting) were also introduced to assess eutrophication of water bodies. To promote the application of footprint assessment, this article regulates the study objectives, frameworks, system boundaries, data processing methods, and the resulting interpretation process. The pros and cons of the footprint assessments were discussed and investigated in detail, examining the CO2 production on each island of the Canary archipelago, and several suggestions were proposed to improve the footprint assessments. Analysis of footprint assessments at different wastewater treatment plants revealed that wastewater treatment technologies and scales had a significant impact on footprints. Furthermore, research hotspots identified using a keyword network diagram showed that the water-carbon-energy nexus was a promising direction for future studies. The purpose of the study is to improve the reduction of the carbon footprint both at the level of direct and indirect emissions factors using new tools and methodologies. Key Words: Footprint; Waste water; Canary Islands

OPC-Pod: A New Sensor Payload to Measure Aerosol Particles for Small Uncrewed Aircraft Systems

Abstract Atmospheric aerosols affect human health and influence atmospheric and biological processes. Dust can be transported long distances in the atmosphere, and the mechanisms that influence dust transport are not fully understood. To improve the data base for numerical models that simulate dust transport, measurements are needed that cover both the vertical distribution of the dust and its size distribution. In addition to measurements with crewed aircraft, uncrewed aircraft systems (UAS) provide a particularly suitable platform for this purpose. In this paper we present the OPC-Pod, a payload for the small fixed-wing UAS of the type MASC-3 for aerosol particle measurements. The OPC-Pod is based on the optical particle counter (OPC) OPC-N3 (Alphasense, UK), modified by the addition of a dryer and a passive aspiration system. Based on field tests with a reference instrument in Mannheim, Germany, wind tunnel tests and a comparison measurement with the UAS-mounted aerosol particle measurement system UCASS during a dust event over Cyprus, we show that the OPC-Pod can measure particle number concentrations in the range 0.66 - 31 μm as well as particle size distributions. The agreement of ther OPC-Pod with UCASS is good. Both instruments resolve a vertical profile of the Saharan dust event, with a prominent dust layer between 1500 m and 2800 m above sea level, with particle number concentrations up to 35 cm−3 for particles between 0.66 - 31 μm.

Evaluating the impact of historical climate and early human groups in the Araucaria Forest of eastern South America

It has been hypothesized that the Araucaria Forest in southern Brazil underwent expansions in the past, driven either by human groups or by climate fluctuations of the Holocene and Pleistocene. Fossil pollen records of the Paraná pine Araucaria angustifolia, a dominant tree in that forest, provide some insights into when those may have occurred. Still, the timing of those expansions has never been estimated. To infer past range shifts and shed light on their main drivers, we employed next‐generation DNA sequencing (ddRADseq), machine learning, and a comprehensive database of fossil pollen records into a study of historical demographic inference and paleo‐distribution modeling of the Paraná pine. We found that A. angustifolia comprises two populations expanding at different times: one in the Mantiqueira mountain chain, the other in the southern Brazilian plateau. The southern population began to expand during the Last Glacial Period ~ 70 kya, long before human arrival in South America. Still, genetic analyses support that humans later impacted this population, resulting in lower genetic diversity, higher inbreeding, and high levels of gene flow over large distances with a weak pattern of isolation‐by‐distance. It is possible this resulted from human influence on seed dispersal and germination on the southern Brazilian plateau. The Mantiqueira population, in contrast, expanded only recently (~ 3 kya). This timing coincides with Holocene climatic changes and human settlements established further south, although, to date, there is little archeological evidence of human impact in the Mantiqueira. In addition, multitemporal species distribution models built from a combination of present‐day and pollen records infer a range expansion of the Araucaria Forest during glacial times until the cold humid HS1 event (~ 16 kya), when the forest was most widespread, with no evidence of glacial refugia. The combination of genomic and spatial analyses suggests that both human and climatic controls played a role in the dynamics of the Araucaria Forest.

Anthropogenic influence on the extremely low September sea ice and hot summer of 2020 over the arctic and its future risk of occurrence

During 2020, the Arctic is marked by extremely low sea ice coverage and hot climate. September Sea Ice Extent (SIE) was about 2.3 million km2 below the 1979–2014 mean and the 2nd lowest on the 1979–2020 record, while regional summer (June–August, JJA) mean 2 m air temperature (TAS) was about 1.3 °C above the 1979–2014 mean and was the hottest on record at the time. Locally, September Sea Ice Concentration (SIC) was approximately 70% lower and JJA TAS can be as much as 6.0 °C higher than the 1979–2014 mean. Although the proximate cause for the extreme event was the continuously favorable atmospheric circulation patterns, wind conditions and ice-albedo feedback, the main objective of this paper is probabilistic extreme event attribution studies to assess the anthropogenic influence. Based on the CMIP6 multi-model ensemble products, modeled long-term trends of Arctic sea ice and TAS are consistent with observed trends when including anthropogenic forcing or greenhouse gas (GHG) forcing, while cannot exhibit observed trends with only aerosol or natural forcing. Further analysis reveals that human influence including GHG forcing has substantially increased the probability of occurrence of the 2020-like extreme events, which are rare in aerosol-only or natural-only forcing. The frequencies of 2020-like low SIC increase by 19 times with all forcing and 16 times with GHG forcing than with natural forcing. Future climate simulations under different Shared Socioeconomic Pathway (SSP) scenarios of SSP126, SSP245 and SSP585 show that the 2020-like extreme event that is currently considered rare is projected to become the norm and almost occur 1-in-1 year beyond 2041–2060. The probabilities will be approximately in the range of 0.85–1.00 for SIC and 0.76–0.99 for TAS from low emission of SSP126 to high emission of SSP585.

Impact of Fine Sediment on Benthic Macroinvertebrates Communities of Freshwater Ecosystem: A Review

The freshwater environment in Ethiopia is exposed to severe human influence because of fast population growth and other factors. Anthropogenic activities in developing countries such as river regulation and pollution have a potentially negative cumulative impact on water quantity and quality of the rivers and wetlands, hence negatively impacting benthic invertebrates and fishes. This review aims to identify the impacts of fine sediment on the community of benthic macroinvertebrates, and freshwater food webs, and to assess the response of benthic invertebrates to fine sediment pollution. Literature review was used as a methodology.  Fine segment load on the freshwater ecosystem from both point and nonpoint sources may directly/indirectly alter the macroinvertebrate communities. Organic and inorganic contaminants as well as other sediment variables (sediment grain size, total organic carbon, nutrients, etc.) were affecting the community composition of benthic invertebrates. However, habitat features like the number of supplements or the silt grain measure clarify the variation in macroinvertebrate indices and metrics. The impact of metals and, to a lesser extent, organic contaminants may also be significant. Benthic macroinvertebrates are commonly used indicators of river ecological conditions that can be adversely affected by fine sediment loads. Sedimentation can change the suitability of the substrate for some taxa, increase macroinvertebrate drift, and affect respiration and feeding. To conclude, excessive fine sediment severely alters the structure and function of macroinvertebrates. At the regional and national levels, different governmental and non-governmental organizations, research institutions, and policy makers are recommended to take responsibility for reducing sediment discharge to the freshwater ecosystem by applying different conservation measures of benthic macroinvertebrates.

Global patterns of human-wildlife spatial associations and implications for differentiating conservation strategies.

Understanding the global patterns of human and wildlife spatial associations is essential for pragmatic conservation implementation, yet analytical foundations and indicator-based assessments that would further this understanding are lacking. We integrated the global distributions of 30,664 terrestrial vertebrates and human pressures to map human-nature index (HNI) categories that indicate the extent and intensity of human-wildlife interactions. Along the 2 dimensions of biodiversity and human activity, the HNI allowed placement of terrestrial areas worldwide in one of 4 HNI categories: anthropic (human-dominated areas), wildlife-dominated (little human influence and rich in wildlife), co-occurring (substantial presence of humans and wildlife), and harsh-environment (limited presence of humans and wildlife) areas. The HNI varied considerably among taxonomic groups, and the leading driver of HNI was global climate patterns. Co-occurring regions were the most prevalent (35.9%), and wildlife-dominated and anthropic regions encompassed 26.45% and 6.50% of land area, respectively. Our results highlight the necessity for customizing conservation strategies to regions based on human-wildlife spatial associations and the distribution of existing protected area networks. Human activity and biodiversity should be integrated for complementary strategies to support conservation toward ambitious and pragmatic 30×30 goals.

A framework for understanding the human experience of nature through cognitive mapping.

Human behavior is a key driver of the biodiversity crisis, and addressing it requires changing individual choices and actions. Yet, the same processes that imperil biodiversity (e.g., urbanization) also alienate people from the experience of nature, eroding care for the natural world. Although averting this extinction of experience is increasingly recognized as a major contemporary conservation challenge, understanding of what constitutes nature experience remains elusive and few empirical studies have explored it directly. Most researchers have used nature interactions as a stand-in for experience, even though experience extends beyond interactions. We aimed to determine what constitutes the experience of nature and to propose a holistic, empirically derived framework that incorporates the multiple dimensions and components of the experience of nature. Using a mixed-method approach across 3 countries (the United States, Switzerland, and Israel), we conducted a multistage, conceptual content, cognitive mapping (3CM) exercise with 106 participants. This methodology included developing a prompt to capture participants' perceptions of nature experiences and subsequently refining and organizing their input into distinct components and underlying dimensions through an iterative engagement process. Beyond multisensory interactions with nature, experience of nature consisted of 2 dimensions: the circumstances in which interactions occur and the internal responses that encompass various cognitive, affective, and restorative benefits associated with nature interactions. These 3 dimensions had 33 components that occurred consistently across participants in the 3 countries. Frequently mentioned components included seeing animals, landscapes, or scenery; lack of human influence; weather conditions; relaxing, recharging; feeling good; and awe for nature. Fear and nature experienced at home were the least mentioned components. Together, our results showed that nature experience is a combination of nature interactions, circumstances, and internal responses. The emphasized components underscore the significance of offering access to extensive, less human-influenced natural spaces. This in turn can foster a profound nature experience, cultivating feelings of connectedness and care for nature.

The ecological value of Neotropical forest landscapes through a multicriteria approach employing spatial models

Ecological value (EV) is a term used to characterize the biotic or abiotic elements of a landscape, excluding human influence. Significant criteria for EV estimation can be grouped into two categories: ecological properties (biodiversity and vulnerability) and functional/structural features (fragmentation, connectivity, and resilience). While various methodological frameworks exist for estimating these criteria, few studies integrate all five criteria, and even fewer compare their results with fieldwork data. The objective of this study was to devise a novel spatial modelling tool for EV estimation based on biodiversity, vulnerability, fragmentation, connectivity, and resilience, utilizing data from Neotropical montane forests in west-central Mexico. The model incorporated data on (i) biodiversity and vulnerability estimated through ecological niche models, (ii) fragmentation and connectivity using landscape spatial patterns, and (iii) resilience estimated through the inverse of the vegetation sensitivity index. The results were then compared with fieldwork data. Natural protected areas within the Neotropical montane forests of west-central Mexico exhibited high EVs; however, a substantial portion of these forests lack legal protection. In terms of vegetation types, cloud and semideciduous forests exhibited the highest EV, emphasizing the urgent need for legal protection of these vital ecosystems. The comparison process demonstrated a moderate to high correlation in some criteria between the spatial and fieldwork data, indicating that the spatial model robustly captured the landscape spatial patterns. The spatial modelling tool proposed in this study is not only practical but also reproducible and applicable globally. Its efficacy lies in combining ecological properties with the functional and structural features of the landscape, making it particularly suitable for delineating protected natural areas and contributing to landscape planning efforts.

Case study analysis of innovative producers toward sustainable integrated crop-livestock systems: trajectory, achievements, and thought process

Integrated crop-livestock systems (ICLS) are more complex to properly manage than specialized farming systems due to multiple interactions between crops, livestock, and grassland. Despite individual and structural barriers to adopting sustainable ICLS, some innovative producers have successfully conducted integrated production practices. In this context, a research gap exists in understanding the motivations and incentives for transitioning to such systems. This study aims to address ICLS adoption barriers by analyzing the trajectory, achievements, and thought processes of 15 producers practicing ICLS. Our objectives were to (1) highlight producers’ perceptions of ICLS levers and barriers and (2) identify turning point factors that enabled producers to overcome the barriers. We used a unique set of cases in three continental regions (southern Brazil, the northern Great Plains region in the United States, and southern France) and conducted semi-structured interviews. Interviewees emphasized that ICLS imply dealing with barriers ranging from mindset change to operational adaptations, but they also emphasized the rewarding nature of ICLS when properly managed. All their trajectories had important turning points, such as programs or initiatives, human influence, and broader social and economic reasons that resulted in shifts in their production practices and thought processes. The cases also highlighted that integrating crops and livestock positively impacted family producers’ business outcomes, soil health, and livelihood options. Still, individual barriers, including operational management, and structural barriers, including stakeholder awareness and commitment, must be overcome. Encouraging initiatives that offer a systemic approach and promote knowledge exchange can address part of ICLS adoption barriers. Initiatives must embrace a broader innovation ecosystem, having extension teams in close contact with researchers and stakeholders to assist producers in providing support for a more sophisticated level of management that ICLS require. Overall, we found commonalities in consciousness and proactiveness in remarkable cases that could inspire broader sustainability transitions.

Impacts of climate variations and human influences on groundwater recharge in the semi-arid Trarza aquifer (SW Mauritania)

Impacts of climate variations and human influences on groundwater recharge in the semi-arid Trarza aquifer (SW Mauritania)

Intellectual Development Diagnostics in Athletes with Intellectual and Physical Disabilities

In the article the diagnostic so intellectual development in athletes with intellectual and physical disabilities discussed. Any child from the age of 8 and any person with intellectual disabilities can train and participate in Special Olympics competitions. It has been determined that this must meet the criteria for delayed or impaired intellectual development based on the standard indicator - the IQ score, other indicators, medical examination report and doctor’s permission. The purpose of the article is to substantiate the methodology for diagnosing athletes with intellectual and physical disabilities that adhere to existing international rules for specific sports. To effectively implement the classification in the competitive process of paralympians, human factor influence on classification results should be minimized. One of the key figures in the classification process is the classifier. This classifier allows assessing the level of preserve debilities of athletes and determines the outcome of athletes’ classification. This imposes strict requirements both on the moral qualities of the classifier and on his her level of professionals kill. The diagnostics of intellectual development is carried out according to the criteria established by the World Health Organization, the International Classification of Diseases, using the Wechsler Intelligence Scale methodology (WAIS, WISC). The level of social adaptation and adaptive behavior disorders are determined by a special set of socially significant indicators. They are defined in specially designed questionnaire forms A, B, C. The internationally recognized Vineland Adaptive Behavior Scale (VABS) is also used. The total quantitative data from forms A, B, C to determine the overall level of adaptive behavior is or dersisused and calculated as the arithmetic mean.

The Impact of Imperfect XAI on Human-AI Decision-Making

Explainability techniques are rapidly being developed to improve human-AI decision-making across various cooperative work settings. Consequently, previous research has evaluated how decision-makers collaborate with imperfect AI by investigating appropriate reliance and task performance with the aim of designing more human-centered computer-supported collaborative tools. Several human-centered explainable AI (XAI) techniques have been proposed in hopes of improving decision-makers' collaboration with AI; however, these techniques are grounded in findings from previous studies that primarily focus on the impact of incorrect AI advice. Few studies acknowledge the possibility of the explanations being incorrect even if the AI advice is correct. Thus, it is crucial to understand how imperfect XAI affects human-AI decision-making. In this work, we contribute a robust, mixed-methods user study with 136 participants to evaluate how incorrect explanations influence humans' decision-making behavior in a bird species identification task, taking into account their level of expertise and an explanation's level of assertiveness. Our findings reveal the influence of imperfect XAI and humans' level of expertise on their reliance on AI and human-AI team performance. We also discuss how explanations can deceive decision-makers during human-AI collaboration. Hence, we shed light on the impacts of imperfect XAI in the field of computer-supported cooperative work and provide guidelines for designers of human-AI collaboration systems.

About the Assessment of Group aspects of the Human factor influence on Safety of Technical systems

About the Assessment of Group aspects of the Human factor influence on Safety of Technical systems

Anthropogenic influence on altitudinally amplified temperature change in the Tibetan Plateau

As the highest plateau on the Earth, the Tibetan Plateau (TP) has experienced rapid warming in the last decades, affecting natural ecosystem and water resources extending far beyond the plateau itself. A distinctive characteristic known as elevation-dependent warming (EDW) in the high mountain regions was particularly pronounced in the TP, whereby the magnitude of temperature warming was amplified with increasing altitudes. Different mechanisms have been proposed to explain this phenomenon, however, the link between the root cause of warming, human activities, and the EDW remains poorly understood. Here we used the homogenized observation and simulations by the newest climate models to discern human influence on both mean and extreme temperatures within the region. An optimal fingerprinting method was applied in a vertical space rather than in traditional horizontal space. We found that the long-term trends in mean and extreme temperature amplified with increasing elevation, with larger magnitude of trends at higher elevations. The response to external forcing, primarily driven by human activities, was robustly detected in altitudinal amplification of temperature increase, providing clear evidence of human causes of EDW. As warming increases, the EDW in the region will continue, with more pronounced EDW corresponding to larger magnitude of warming under a high emission scenario. These findings mark the first evidence of human influence on temperature across different vertical altitudes of climate system.

OccTest: An integrated approach for quality control of species occurrence data

AbstractAimSpecies occurrence data are valuable information that enables one to estimate geographical distributions, characterize niches and their evolution, and guide spatial conservation planning. Rapid increases in species occurrence data stem from increasing digitization and aggregation efforts, and citizen science initiatives. However, persistent quality issues in occurrence data can impact the accuracy of scientific findings, underscoring the importance of filtering erroneous occurrence records in biodiversity analyses.InnovationWe introduce an R package, occTest, that synthesizes a growing open‐source ecosystem of biodiversity cleaning workflows to prepare occurrence data for different modelling applications. It offers a structured set of algorithms to identify potential problems with species occurrence records by employing a hierarchical organization of multiple tests. The workflow has a hierarchical structure organized in testPhases (i.e. cleaning vs. testing) that encompass different testBlocks grouping different testTypes (e.g. environmental outlier detection), which may use different testMethods (e.g. Rosner test, jacknife,etc.). Four different testBlocks characterize potential problems in geographic, environmental, human influence and temporal dimensions. Filtering and plotting functions are incorporated to facilitate the interpretation of tests. We provide examples with different data sources, with default and user‐defined parameters. Compared to other available tools and workflows, occTest offers a comprehensive suite of integrated tests, and allows multiple methods associated with each test to explore consensus among data cleaning methods. It uniquely incorporates both coordinate accuracy analysis and environmental analysis of occurrence records. Furthermore, it provides a hierarchical structure to incorporate future tests yet to be developed.Main conclusionsoccTest will help users understand the quality and quantity of data available before the start of data analysis, while also enabling users to filter data using either predefined rules or custom‐built rules. As a result, occTest can better assess each record's appropriateness for its intended application.

Human influence on the recent weakening of storm tracks in boreal summer

Anthropogenic warming can alter large-scale circulation patterns in the atmosphere, which could have serious consequences for regional climate impacts and extreme weather. Observed thermodynamic changes in boreal extratropics have been attributed to human emissions with high confidence, but most circulation changes have not. In particular, not only that in the previous suite of climate models most models do not capture the recent boreal summer storm tracks weakening, but also a quantification of the role of human emissions in the recent storm tracks weakening has not been conducted to date. Here we use the latest suite of climate models, which are found to adequately capture the recent storm tracks weakening, and show that this weakening is attributable to anthropogenic emissions. Human emissions have resulted in more-rapid warming of the high latitudes, and the associated reduction in poleward temperature gradient has weakened the storms. The physical consistency between models and reanalyses increases our confidence in the projected weakening, which presents regional risks including hot-dry extremes in summer.

A network approach for multiscale catchment classification using traits

Abstract. The classification of river catchments into groups with similar biophysical characteristics is useful to understand and predict their hydrological behavior. The increasing availability of remote sensing and other large-scale geospatial datasets has enabled the use of advanced data-driven approaches to classify catchments using traits such as topography, geology, climate, land cover, land use, and human influence. Unsupervised clustering algorithms based on the Euclidean distance are commonly used for trait-based classification but are not suitable for highly dimensional data. In this study we present a new network-based method for multi-scale catchment classification, which can be applied to large datasets and used to determine the traits associated with different catchment groups. In this framework, two networks are analyzed in parallel: the first being where the nodes are traits and the second being where the nodes are catchments. In both cases, edges represent pairwise similarity, and a network cluster detection algorithm is used for the classification. The trait network is used to investigate redundancy in the trait data and to condense this information into a small number of interpretable categories. The catchments network is used to classify the catchments into clusters and to identify representative catchments for the different groups using the degree centrality metric. We apply this method to classify 9067 river catchments across the contiguous United States at both regional and continental scales using 274 non-categorical traits. At the continental scale, we identify 25 interpretable trait categories and 34 catchment clusters of sizes greater than 50. We find that catchments with similar trait categories are typically located in the same region, with different spatial patterns emerging among clusters dominated by natural and anthropogenic traits. We also find that the catchment clusters exhibit distinct hydrological behavior based on an analysis of streamflow indices. This network approach provides several advantages over traditional means of classification, including better separation of clusters, the use of alternate similarity metrics that are more suitable for highly dimensional data, and reducing redundancy in the trait information. The paired catchment–trait networks enable analysis of hydrological behavior using the dominant trait categories for each catchment cluster. The approach can be used at multiple spatial scales since the network topologies adjust automatically to reflect the trait patterns at the scale of investigation. Finally, the representative catchments identified as hub nodes in the network can be used to guide transferable observational and modeling strategies. The method is broadly applicable beyond hydrology for classification of other complex systems that utilize different types of trait datasets.