Large Geographic Scales Research Articles

Reliability of electric vehicle charging infrastructure: A cross-lingual deep learning approach

Vehicle electrification has emerged as a global strategy to address climate change and emissions externalities from the transportation sector. Deployment of charging infrastructure is needed to accelerate technology adoption; however, managers and policymakers have had limited evidence on the use of public charging stations due to poor data sharing and decentralized ownership across regions. In this article, we use machine learning based classifiers to reveal insights about consumer charging behavior in 72 detected languages including Chinese. We investigate 10 years of consumer reviews in East and Southeast Asia from 2011 to 2021 to enable infrastructure evaluation at a larger geographic scale than previously available. We find evidence that charging stations at government locations result in higher failure rates with consumers compared to charging stations at private points of interest. This evidence contrasts with predictions in the U.S. and European markets, where the performance is closer to parity. We also find that networked stations with communication protocols provide a relatively higher quality of charging services, which favors policy support for connectivity, particularly for underserved or remote areas.

Long term changes in aquaculture influence migration, regional abundance, and distribution of an avian species.

Agricultural development has been causing changes to the environment and the abundance and distribution of avian species. Agriculture is dynamic with changes in products occurring at large scales over relatively short time periods. The catfish aquaculture industry is one such agriculture industry that has undergone dramatic changes over the last 25 years. The double-crested cormorant (Nannopterum auritum) is a piscivorous bird that has an extensive history with the aquaculture industry of Mississippi due to its depredation of cultured catfish. A large-scale monitoring program began in 1989 to estimate the abundance and location of cormorants at every known roost in the primary catfish producing region of the state, regionally known as the Delta. We used this data set to address hypotheses pertaining to cormorant ecology within the Delta over time, particularly in relation to aquaculture. We found that, although the Midwest breeding population of cormorants has been increasing, the abundance of cormorants wintering in the Delta has been decreasing, closely following the decline of aquaculture, suggesting aquaculture area is the primary reason for cormorant inhabitation of the region. We also modeled cormorant presence and abundance at all roost sites to determine what factors most influenced cormorant distribution. Aquaculture area around roosts was a significant predictor of both cormorant presence and abundance. However, the influence of aquaculture area was seasonally dependent, with greater positive influences occurring prior to migration. Lastly, we found peak cormorant abundance in the Delta is occurring 2.14 days earlier each year, which may be indicative of changes to migration phenology. Information gained using this large dataset aids in cormorant damage mitigation and to further our understanding of cormorant ecology. Data indicate changes in agriculture, and potentially climate change, can influence phenology, distribution, and abundance of avian species at large geographic scales.

A Perspective of Decarbonization Pathways in Future Buildings in the United States

The commitment of electrification and decarbonization goals in the United States (U.S.) will significantly change the performance of future buildings. To meet these goals, it is critical to summarize the existing research related to building electrification and decarbonization and discuss future research pathways. This paper provides a perspective on decarbonization pathways of future buildings in the U.S. A critical review of the existing research was conducted, which is divided into three closely linked categories: technologies, economic impacts, and code regulations. Technologies support investments and code regulations while marketing affects the design of building codes and standards. In the meantime, code regulations guide the development of technologies and marketing. Based on the review, future potential research directions for building decarbonization are then discussed. Due to the needs of building decarbonization, future research will be multidisciplinary, conducted at a large geographic scale, and involve a multitude of metrics, which will undoubtedly introduce new challenges. The perspective presented in this paper will provide policy-makers, researchers, building owners, and other stakeholders with a way to understand the impact of electrification and decarbonization of future buildings in the U.S.

Reconstructing mechanisms of extinctions to guide mammal conservation biogeography

AbstractAn emerging research program on population and geographic range dynamics of Australia's mammals illustrates an approach to better understand and respond to geographic range collapses of threatened wildlife in general. In 1788, Europeans colonized an Australia with a diverse and largely endemic mammal fauna, where many species that are now extinct or threatened were common and widespread. Subsequent population declines, range collapses and extinctions were caused by introduced predators and herbivores, altered land use, modified fire regimes and the synergies between these threats. Declines in population and range size continue for many Australian mammals despite legislative protection and conservation interventions. Here, we propose an approach that integrates museum data and other historical records into process‐explicit macroecological models to better resolve mammal distributions and abundances as they were at European arrival. We then illustrate how this integrative approach can identify the likely synergistic mechanisms causing mammal population declines across these and other landscapes. This emerging research approach, undertaken with fine temporal and spatial resolution, but at large geographic scales, will provide valuable insights into the different pathways to, and drivers of, extinction. Such insights may, in turn, underpin conservation strategies based on a process‐explicit understanding of population decline and range collapse under alternative scenarios of impending climate and environmental change. Given that similar information is available for other regional biotas, the approach we describe here can be adapted to conserve threatened wildlife in other regions across the globe.

The potential of lake-source district heating and cooling for European buildings

Lake-source thermal district networks can efficiently supply heating and cooling to buildings and thus save energy and CO2 emissions. However, it remains unclear to which degree they are a sustainable alternative at a larger geographical scale. An evaluation of the potential of developing technically and economically feasible lake-source district systems in Europe was performed in this study, with an integrated spatial explicit techno-economic assessment that accounts for different boundary conditions, such as electricity price, CO2 price and climate change. The feasibility of covering building energy demand near lakes was found to be particularly sensitive to the relationship between capital costs from network design and operational costs from heat pumps, associated electricity consumption and CO2 emissions. Results suggest a European techno-economic potential of 1.9 TWh/y considering only direct cooling and 11.3 TWh/y if thermal networks supply both direct heating and cooling by heat pumps. Respective electricity savings are 0.36 TWh/y and 0.78 TWh/y. An estimated 17% of the cooling demand near European lakes can thus be covered by viable cooling-only lake-source systems. For combined systems, the viable potential is estimated to be 7% of the total combined heating and cooling demand. Lake-source district systems are found to be particularly promising for Italy, Germany, Turkey and Switzerland. The integration of lake-source thermal networks should rarely lead to severe lake water temperature alteration and therefore not limit the techno-economic potential. The introduced methodology allows for a combined evaluation of technological, ecological and economic boundary conditions for using lakes as a source for district heating and cooling. Thereby, a more realistic estimation of their potential implementation becomes possible, enabling informed energy planning for central or decentral system configurations.

Abundance patterns of mammals across Russia explained by remotely sensed vegetation productivity and snow indices

AbstractAimPredicting biodiversity responses to global changes requires good models of species' distributions. Both environmental conditions and human activities determine population density patterns. However, quantifying the relationship between wildlife population densities and their underlying environmental conditions across large geographical scales has remained challenging. Our goal was to explain the abundances of mammal species based on their response to several remotely sensed indices including the Dynamic Habitat Indices (DHIs) and the novel Winter Habitat Indices (WHIs).LocationRussia, the majority of regions.TaxonEight mammal species.MethodsWe estimated average population densities for each species across Russia from 1981 to 2010 from winter track counts. The DHIs measure vegetative productivity, a proxy for food availability. Our WHIs included the duration of snow‐free ground, duration of snow‐covered ground and the start, end and length of frozen season. In models, we included elevation, climate conditions, human footprint index. We parameterized multiple linear regression and applied best‐subset model selection to determine the main factors influencing population density.ResultsThe DHIs were included in some of the top‐twelve models of every species, and in the top model for moose, wild boar, red fox and wolf, so they were important for species at all trophic levels. The WHIs were included in top models for all species except roe deer, demonstrating the importance of winter conditions. The duration of frozen ground without snow and the end of frozen season were particularly important. Our top models performed well for all the species (R2adj 0.43–0.87).Main ConclusionsThe combination of the DHIs and the WHIs with climate and human‐related variables resulted in high explanatory power. We show that vegetation productivity and winter conditions are key drivers of variation in population density of eight species across Russia.

Evaluating individual tree species classification performance across diverse environments

Vegetation species mapping using airborne imaging spectroscopy yields accurate results and is important for advancing conservation objectives and biogeographic studies. As these data become more readily available owing to the upcoming launch of spaceborne imaging spectrometers, it is necessary to understand how these data can be used to consistently classify species across large geographic scales. However, few studies have attempted to map species across multiple ecosystems; therefore, little is known regarding the effect of intra-specific variation on the mapping of a single species across a wide range of environments and among varying backgrounds of other non-target species. To explore this effect, we developed and tested species classification models for Metrosideros polymorpha, a highly polymorphic canopy species endemic to Hawai’i, which is found in a diverse array of ecosystems. We compared the accuracies of support vector machine (SVM) and random forest models trained on canopy reflectance data from each of eight distinct ecosystems (ecosystem-specific) and a universal model trained on data from all ecosystems. When applied to ecosystem-specific test datasets, the ecosystem-specific models outperformed the universal model; however, the universal model retained high (>81%) accuracies across all ecosystems. Additionally, we found that models from ecosystems with broad variation in M. polymorpha canopy traits, as estimated using chemometric equations applied to canopy spectra, accurately predicted M. polymorpha in other ecosystems. While species classifications across ecosystems can yield accurate results, these results will require sampling procedures that capture the intra-specific variation of the target species.

Molecular Epidemiology of Ralstonia pseudosolanacearum Phylotype I Strains in the Southwest Indian Ocean Region and Their Relatedness to African Strains.

The increasing requirement for developing tools enabling fine strain traceability responsible for epidemics is tightly linked with the need to understand factors shaping pathogen populations and their environmental interactions. Bacterial wilt caused by the Ralstonia solanacearum species complex (RSSC) is one of the most important plant diseases in tropical and subtropical regions. Sadly, little, outdated, or no information on its epidemiology is reported in the literature, although alarming outbreaks are regularly reported as disasters. A large set of phylotype I isolates (n = 2,608) was retrieved from diseased plants in fields across the Southwest Indian Ocean (SWIO) and Africa. This collection enabled further assessment of the epidemiological discriminating power of the previously published RS1-MLVA14 scheme. Thirteen markers were validated and characterized as not equally informative. Most had little infra-sequevar polymorphism, and their performance depended on the sequevar. Strong correlation was found with a previous multilocus sequence typing scheme. However, 2 to 3% of sequevars were not correctly assigned through endoglucanase gene sequence. Discriminant analysis of principal components (DAPC) revealed four groups with strong phylogenetic relatedness to sequevars 31, 33, and 18. Phylotype I-31 isolates were highly prevalent in the SWIO and Africa, but their dissemination pathways remain unclear. Tanzania and Mauritius showed the greatest diversity of RSSC strains, as the four DAPC groups were retrieved. Mauritius was the sole territory harboring a vast phylogenetic diversity and all DAPC groups. More research is still needed to understand the high prevalence of phylotype I-31 at such a large geographic scale.

Cross-Hemispheric Genetic Diversity and Spatial Genetic Structure of Callinectes sapidus Reovirus 1 (CsRV1).

The movement of viruses in aquatic systems is rarely studied over large geographic scales. Oceanic currents, host migration, latitude-based variation in climate, and resulting changes in host life history are all potential drivers of virus connectivity, adaptation, and genetic structure. To expand our understanding of the genetic diversity of Callinectes sapidus reovirus 1 (CsRV1) across a broad spatial and host life history range of its blue crab host (Callinectes sapidus), we obtained 22 complete and 96 partial genomic sequences for CsRV1 strains from the US Atlantic coast, Gulf of Mexico, Caribbean Sea, and the Atlantic coast of South America. Phylogenetic analyses of CsRV1 genomes revealed that virus genotypes were divided into four major genogroups consistent with their host geographic origins. However, some CsRV1 sequences from the US mid-Atlantic shared high genetic similarity with the Gulf of Mexico genotypes, suggesting potential human-mediated movement of CsRV1 between the US mid-Atlantic and Gulf coasts. This study advances our understanding of how climate, coastal geography, host life history, and human activity drive patterns of genetic structure and diversity of viruses in marine animals and contributes to the capacity to infer broadscale host population connectivity in marine ecosystems from virus population genetic data.

Heavy metals in influent and effluent from 146 drinking water treatment plants across China: Occurrence, explanatory factors, probabilistic health risk, and removal efficiency

Heavy metals (HMs) in drinking water have drawn worldwide attention due to their risks to public health; however, a systematic assessment of the occurrence of HMs in drinking water treatment plants (DWTPs) at a large geographical scale across China and the removal efficiency, human health risks, and the correlation with environmental factors have yet to be established. Therefore, this study characterised the occurrence patterns of nine conventional dissolved HMs in the influent and effluent water samples from 146 typical DWTPs in seven major river basins across China (which consist of the Yangtze River, the Yellow River, the Songhua River, the Pearl River, the Huaihe River, the Liaohe River and the Haihe River) for the first time and removal efficiency, probabilistic health risks, and the correlation with water quality. According to the findings, a total of eight HMs (beryllium (Be), antimony (Sb), barium (Ba), molybdenum (Mo), nickel (Ni), vanadium (V), cobalt (Co) and titanium (Ti)) were detected, with detection frequencies in influent and effluent water ranging from 2.90 (Mo) to 99.30% (Ba) and 1.40 (Ti) to 97.90% (Ba), respectively. The average concentration range was 0.41 (Be)− 77.36 (Sb) μg/L. Among them, Sb (exceeding standard rate 8%), Ba (2.89%), Ni (21.43%), and V (1.33%) were exceeded the national standard (GB5749–2022). By combining Spearman’s results and redundancy analysis, our results revealed a close correlation among pH, turbidity (TURB), potassium permanganate index (CODMn), and total nitrogen (TN) along with the concentration and composition of HMs. In addition, the concentration of HMs in finished water was strongly affected by the concentration of HMs in raw water, as evidenced by the fact that HMs in surface water poses a risk to the quality of finished water. Metal concentration was the primary factor in assessing the health risk of a single metal, and the carcinogenic risk of Ba, Mo, Ni, and Sb should be paid attention to. In DWTPs, the removal efficiencies of various HMs also vary greatly, with an average removal rate ranging from 16.30% to 95.64%. In summary, our findings provide insights into the water quality and health risks caused by HMs in drinking water.

Nationwide Occurrence and Unexpected Severe Pollution of Fluorescent Brighteners in the Sludge of China: An Emerging Anthropogenic Marker.

Fluorescent brighteners (FBs) are a group of mass-produced dyestuff chemicals that have been extensively used for decades. However, knowledge of their occurrence in municipal wastewater treatment plants on a large geographical scale remains unknown. Herein, we implemented the first nationwide survey for wastewater-derived FBs in sludge across major cities in China. All 25 target FBs were detected in the nationwide sludge. Ionic FBs exhibited much higher concentrations than nonionic FBs. The total sludge concentrations of 25 FBs (∑25FBs) ranged from 7300 to 1,520,000 ng/g, with a median of 35,300 ng/g. A clear geographical distribution of significantly higher concentrations of FBs was found in East and Central China than in West China (p < 0.05). The sludge concentrations of ∑25FBs were correlated well with the gross domestic product (GDP) and population size at the provincial level in China (p < 0.05), demonstrating the significance of anthropogenic impacts on FB levels in urban sludge. The nationwide annual emission of total FBs into sludge in China is estimated to be 835 tons/year, of which 134 tons/year is directly released into sludge-applied soils. Our work highlights another new class of chemicals that significantly contribute to the chemical mixtures in urban sludge and thus require immediate attention.

Small Area Forecasting of Opioid-Related Mortality: Bayesian Spatiotemporal Dynamic Modeling Approach

Opioid-related overdose mortality has remained at crisis levels across the United States, increasing 5-fold and worsened during the COVID-19 pandemic. The ability to provide forecasts of opioid-related mortality at granular geographical and temporal scales may help guide preemptive public health responses. Current forecasting models focus on prediction on a large geographical scale, such as states or counties, lacking the spatial granularity that local public health officials desire to guide policy decisions and resource allocation. The overarching objective of our study was to develop Bayesian spatiotemporal dynamic models to predict opioid-related mortality counts and rates at temporally and geographically granular scales (ie, ZIP Code Tabulation Areas [ZCTAs]) for Massachusetts. We obtained decedent data from the Massachusetts Registry of Vital Records and Statistics for 2005 through 2019. We developed Bayesian spatiotemporal dynamic models to predict opioid-related mortality across Massachusetts' 537 ZCTAs. We evaluated the prediction performance of our models using the one-year ahead approach. We investigated the potential improvement of prediction accuracy by incorporating ZCTA-level demographic and socioeconomic determinants. We identified ZCTAs with the highest predicted opioid-related mortality in terms of rates and counts and stratified them by rural and urban areas. Bayesian dynamic models with the full spatial and temporal dependency performed best. Inclusion of the ZCTA-level demographic and socioeconomic variables as predictors improved the prediction accuracy, but only in the model that did not account for the neighborhood-level spatial dependency of the ZCTAs. Predictions were better for urban areas than for rural areas, which were more sparsely populated. Using the best performing model and the Massachusetts opioid-related mortality data from 2005 through 2019, our models suggested a stabilizing pattern in opioid-related overdose mortality in 2020 and 2021 if there were no disruptive changes to the trends observed for 2005-2019. Our Bayesian spatiotemporal models focused on opioid-related overdose mortality data facilitated prediction approaches that can inform preemptive public health decision-making and resource allocation. While sparse data from rural and less populated locales typically pose special challenges in small area predictions, our dynamic Bayesian models, which maximized information borrowing across geographic areas and time points, were used to provide more accurate predictions for small areas. Such approaches can be replicated in other jurisdictions and at varying temporal and geographical levels. We encourage the formation of a modeling consortium for fatal opioid-related overdose predictions, where different modeling techniques could be ensembled to inform public health policy.

Biogeographic inferences across spatial and evolutionary scales.

The field of biogeography unites landscape genetics and phylogeography under a common conceptual framework. Landscape genetics traditionally focuses on recent-time, population-based, spatial genetics processes at small geographical scales, while phylogeography typically investigates deep past, lineage- and species-based processes at large geographical scales. Here, we evaluate the link between landscape genetics and phylogeographical methods using the western fence lizard (Sceloporus occidentalis) as a model species. First, we conducted replicated landscape genetics studies across several geographical scales to investigate how population genetics inferences change depending on the spatial extent of the study area. Then, we carried out a phylogeographical study of population structure at two evolutionary scales informed by inferences derived from landscape genetics results to identify concordance and conflict between these sets of methods. We found significant concordance in landscape genetics processes at all but the largest geographical scale. Phylogeographical results indicate major clades are restricted to distinct river drainages or distinct hydrological regions. At a more recent timescale, we find minor clades are restricted to single river canyons in the majority of cases, while the remainder of river canyons include samples from at most two clades. Overall, the broad-scale pattern implicating stream and river valleys as key features linking populations in the landscape genetics results, and high degree of clade specificity within major topographic subdivisions in the phylogeographical results, is consistent. As landscape genetics and phylogeography share many of the same objectives, synthesizing theory, models and methods between these fields will help bring about a better understanding of ecological and evolutionary processes structuring genetic variation across space and time.

Strong Genetic Structure and Limited Gene Flow among Populations of the Tropical Seagrass Thalassia hemprichii in the Philippines

Seagrasses are marine angiosperms, and seagrass beds maintain the species diversity of tropical and subtropical coastal ecosystems. For proper understanding, management and conservation of coastal ecosystems, it is essential to understand seagrass population dynamics. Population genetic studies can cover large geographic scales and contribute to a comprehensive understanding of reproductive dynamics and potential dispersal among locations. The clonal and genetic diversity and genetic connectivity of Thalassia hemprichii in the Philippines were estimated by a population genetics approach. The geographic scale of this study has a direct distance of approximately 1600 km. Although high clonal diversity was found in some sites (R = 0.07–1.00), both sexual and asexual reproduction generally maintains separate populations. Genetic diversity is not definitely correlated with latitude, and genetic differentiation is significant in all pairs of sites (FST = 0.026–0.744). Complex genetic structure was found in some regions, even at a fine geographic scale. The migration of fruits and seedlings was elucidated as an infrequent and stochastic event. These results suggest the necessity for the conservation of this species due to a deficiency in migrants from external regions.

Genetic population structure in Norway lobster (Nephrops norvegicus): management regime under panmixia

Abstract Investigations of genetic stock structure sometimes reveal a mismatch between management units and biological units. In Scandinavian waters, Norway lobster (Nephrops norvegicus) is divided into two management units (the Skagerrak–Kattegat and the Norwegian Deep). We have tested the population genetic structure of Nephrops within this region using microsatellite DNA markers, and compared the structure with the present management units. Our study suggests no population genetic structure of Nephrops within the Skagerrak, Kattegat, and Norwegian Deep region, whereas a shallow genetic structure was detected on a larger geographical scale when comparing outgroup samples from Scotland and Iceland. We found indications of sex-biased dispersal as the overall genetic differences were larger for females. Ocean current patterns suggest that Nephrops stocks in the region may be connected by larval drift. The two areas differ in fishing pressure, monitoring, assessment, and regulations, which is an argument for maintaining the present two-areas management regime despite the evidence for one biological population.

Herbarium specimens reveal herbivory patterns across the genus Cucurbita.

Quantifying how closely related plant species differ in susceptibility to insect herbivory is important for understanding the variation in evolutionary pressures on plant functional traits. However, empirically measuring in situ variation in herbivory spanning the geographic range of a plant-insect complex is logistically difficult. Recently, new methods have been developed using herbarium specimens to investigate patterns in plant-insect symbioses across large geographic scales. Such investigations provide insights into how accelerated anthropogenic changes may impact plant-insect interactions that are of ecological or agricultural importance. Here, we analyze 274 pressed herbarium samples to investigate variation in herbivory damage in 13 different species of the economically important plant genus Cucurbita (Cucurbitaceae). This collection is composed of specimens of wild, undomesticated Cucurbita that were collected from across their native range, and Cucurbita cultivars collected from both within their native range and from locations where they have been introduced for agriculture in temperate North America. Herbivory is common on individuals of all Cucurbita species collected throughout their geographic ranges. However, estimates of herbivory varied considerably among individuals, with mesophytic species accruing more insect damage than xerophytic species, and wild specimens having more herbivory than specimens collected from human-managed habitats. Our study suggests that long-term evolutionary changes in habitat from xeric to mesic climates and wild to human-managed habitats may mediate the levels of herbivory pressure from coevolved herbivores. Future investigations into the potential factors that contribute to herbivory may inform the management of domesticated crop plants and their insect herbivores.

Widespread Occurrence and Transport of p-Phenylenediamines and Their Quinones in Sediments across Urban Rivers, Estuaries, Coasts, and Deep-Sea Regions.

p-Phenylenediamines (PPDs) are widely used as antioxidants in tire rubber, and their derived quinone transformation products (PPD-Qs) may pose a threat to marine ecosystems. A compelling example is N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD)-derived quinone, called 6PPD-Q, as the causal toxicant for stormwater-linked acute mortality toward coho salmon. However, the knowledge of the co-occurrences of PPDs and PPD-Qs and their transport from freshwater to oceanic waterbodies on a large geographical scale remains unknown. Herein, we performed the first large-scale survey of these chemicals in sediments across urban rivers, estuaries, coasts, and deep-sea regions. Our results demonstrated that seven PPDs and four PPD-Qs are ubiquitously present in riverine, estuarine, and coastal sediments, and most of them also occur in deep-sea sediments. The most dominant chemicals of concern were identified as 6PPD and 6PPD-Q. Total sedimentary concentrations of PPDs and PPD-Qs presented a clear spatial trend with decreasing levels from urban rivers (medians: 39.7 and 15.2 ng/g) to estuaries (14.0 and 5.85 ng/g) and then toward coasts (9.47 and 2.97 ng/g) and deep-sea regions (5.24 and 3.96 ng/g). Interestingly, spatial variation in the ratios of 6PPD to 6PPD-Q (R6PPD/6PPD-Q) also presented a clear decreasing trend. Our field measurements implied that riverine outflows of PPDs and PPD-Qs may be an important route to transport these tire rubber-derived chemicals to coastal and open oceans.

Local conditions matter: Minimal and variable effects of soil disturbance on microbial communities and functions in European vineyards.

Soil tillage or herbicide applications are commonly used in agriculture for weed control. These measures may also represent a disturbance for soil microbial communities and their functions. However, the generality of response patterns of microbial communities and functions to disturbance have rarely been studied at large geographical scales. We investigated how a soil disturbance gradient (low, intermediate, high), realized by either tillage or herbicide application, affects diversity and composition of soil bacterial and fungal communities as well as soil functions in vineyards across five European countries. Microbial alpha-diversity metrics responded to soil disturbance sporadically, but inconsistently across countries. Increasing soil disturbance changed soil microbial community composition at the European level. However, the effects of soil disturbance on the variation of microbial communities were smaller compared to the effects of location and soil covariates. Microbial respiration was consistently impaired by soil disturbance, while effects on decomposition of organic substrates were inconsistent and showed positive and negative responses depending on the respective country. Therefore, we conclude that it is difficult to extrapolate results from one locality to others because microbial communities and environmental conditions vary strongly over larger geographical scales.

Phylogenetic diversity of stochasticity-dominated predatory myxobacterial community drives multi-nutrient cycling in typical farmland soils

Predatory myxobacteria are keystone taxa in the soil microbial food web that potentially regulate soil microbial community structure and ecosystem functions. However, little is known about the community assembly processes of myxobacteria in typical farmland soils over large geographic scales, in addition to their relationship with soil multi-nutrient cycling. Here, we used high-throughput sequencing techniques and phylogenetic null modeling analysis to investigate the distribution patterns and assembly processes of myxobacteria communities, in addition to interactions between myxobacteria communities and soil multi-nutrient cycling. Anaeromyxobacter (28.5 %) and Haliangium (19.6 %) were the dominant myxobacteria genera in all samples, and myxobacteria community similarities exhibited distinct distance–decay relationships. Stochastic processes (~77.8 %) were the dominant ecological processes driving the assembly of predatory myxobacteria communities over large geographical scales and under three fertilization regimes. Myxobacteria community structure was influenced by geographic factors (location and climate), soil factors (soil pH, soil organic carbon, total nitrogen, and total potassium), and fertilization, with myxobacteria community assembly being more sensitive to geographic factors. Organic-inorganic combined fertilization (NPKM) increased the proportions of deterministic processes in myxobacteria community assembly. Moreover, myxobacteria community assembly and diversity were closely associated with soil multi-nutrient cycling. Hence, myxobacteria phylogenetic α-diversity represented by NTI index is a potential bioindicators for soil multi-nutrient cycling. Overall, our findings comprehensively reveal the mechanisms of assembly of myxobacteria communities in soils over large geographic scales, and provide a theoretical basis for further research on the role of predatory bacteria on soil nutrient cycling in agro-ecosystems.

The monetary value of 16 services protected by the Australian National Biosecurity System: Spatially explicit estimates and vulnerability to incursions

Biosecurity systems protect numerous assets, distributed differentially across space. Focusing on Australia’s 56 natural resource management regions, we generate spatially explicit estimates of the current value of 16 different services generated by assets that are protected by the biosecurity system (hereafter values). Benefit transfer functions are used to generate some values; others are derived from observable market data. Across all regions and services, we estimate an aggregate value of approximately $250b p.a. Nearly 90% of those values are ecosystem service values, associated with Australia’s Natural Capital and more than one-half are services not normally bought or sold in the marketplace (e.g., a subset of cultural and most regulating services). We use insights from the literature, in conjunction with our values, to estimate the potential losses that (a) weeds and (b) invertebrates, could inflict in different regions – hereafter, vulnerabilities (potential $ losses per hectare p.a.). Urban areas are generally more vulnerable than remote areas, and many regions are more vulnerable to invertebrates than weeds, but weed vulnerabilities dominate in several of the large, remote, NRMs across the north, in the ‘outback’ and in the west. Our values can be used to assess the vulnerability of natural capital, and other capitals, to a wide range of other threats and are thus of potential use in numerous policy settings. Our generic approach to considering impacts at large geographic scale (using values and then assessing vulnerabilities) is one that is useful and transferrable to other settings across the world.