Sampling Effort Research Articles

Environmental DNA metabarcoding reflects spatiotemporal fish community shifts in the Scheldt estuary.

Estuarine ecosystems face increasing anthropogenic pressures, necessitating effective monitoring methods to mitigate their impacts on the biodiversity they harbour. The use of environmental DNA (eDNA) based detection methods is increasingly recognized as a promising tool to complement other, potentially invasive monitoring techniques. Integrating such eDNA analyses into monitoring frameworks for large ecosystems is still challenging and requires a deeper understanding of the scale and resolution at which eDNA patterns may offer insights in species presence and community composition space and time. The Scheldt estuary, characterized by its diverse habitats and complex currents, is one of the largest Western European tidal river systems. Until now, it remains challenging to obtain accurate information on fish communities living in and migrating through this ecosystem, consequently confining our knowledge to specific locations. To explore the potential of eDNA based monitoring, we simultaneously combine stow net fishing with eDNA metabarcoding, to assess spatiotemporal shifts in the Scheldt estuary's fish communities. In total, we detected 71 fish species in the estuary using eDNA metabarcoding, partly overlapping with historic fish community data gathered at the different study locations and in contrast to only 42 species using stow net fishing during the same survey period. Community compositions found by both detection methods varied among sampling locations, driven by a clear correlation to the salinity gradient. Limited effects of sampling depth and tide were observed on the eDNA metabarcoding data, allowing a significant reduction of the eDNA sampling effort for future eDNA fish monitoring campaigns in this study system. Our results further demonstrate that seasonal shifts in fish species occurrence can be detected using eDNA metabarcoding. Combining eDNA metabarcoding and stow net fishing further enhances our understanding of this vital waterway's diverse fish populations, allowing a higher resolution and more efficient monitoring strategy.

Assessing Residency and Site Fidelity in Bottlenose Dolphins: A Literature Review and Bibliometric Analysis

Residency and site fidelity are important parameters in population ecology for many species as they indicate the temporal and spatial use for individuals. Although both terms are clearly different, they are used interchangeably due to lack of clarity in their definitions and the ways to assess them, especially in bottlenose dolphins (Tursiops spp.). Individuals with well-defined patterns of residency and site fidelity may be more vulnerable to anthropogenic disturbances; thus, the study of these parameters may help to better assess such impacts. However, interspecific differences and logistical restrictions for the study of dolphins have prevented consensus. We set out to investigate the factors that have influenced measurements of residency and site fidelity in bottlenose and a set of other dolphin species through a retrospective (~30 y: 1990 to 2019) literature review. We found 117 scientific papers with a two-fold increasing trend approximately every 15 years, with 50% published in only four journals. Most of the studies were developed in the United States, followed by Australia and Europe, likely due to strict policies for marine mammal conservation. Author collaboration network analysis showed highly atomized national groups in which North American organizations formed the biggest cluster, followed by Australia, Africa, and Europe. However, large worldwide gaps still exist, possibly because of the heterogeneity in marine mammal sampling efforts and limited information availability in the North Pacific, Central and South America, Africa, Asia, and the Indian Ocean. We found 30 different classification methods in which 12 were based on defined categories. We provide conceptual aid to distinguish between the use of both terms, as well as guidance to tackle the challenge of defining patterns of temporal use due to the variability of thresholds for classifying individuals. A paradigm shift is needed to create comprehensive, standardized, and generalized assessments of residency and site fidelity, which can be compared based on their performance across different populations of bottlenose dolphins around the world.

Bee and butterfly records indicate diversity losses in western and southern North America, but extensive knowledge gaps remain.

Pollinator losses threaten ecosystems and food security, diminishing gene flow and reproductive output for ecological communities and impacting ecosystem services broadly. For four focal families of bees and butterflies, we constructed over 1400 ensemble species distribution models over two time periods for North America. Models indicated disproportionally increased richness in eastern North America over time, with decreases in richness over time in the western US and southern Mexico. To further pinpoint geographic areas of vulnerability, we mapped records of potential pollinator species of conservation concern and found high concentrations of detections in the Great Lakes region, US East Coast, and southern Canada. Finally, we estimated asymptotic diversity indices for genera known to include species that visit flowers and may carry pollen for ecoregions across two time periods. Patterns of generic diversity through time mirrored those of species-level analyses, again indicating a decline in pollinators in the western U.S. Increases in generic diversity were observed in cooler and wetter ecoregions. Overall, changes in pollinator diversity appear to reflect changes in climate, though other factors such as land use change may also explain regional shifts. While statistical methods were employed to account for unequal sampling effort across regions and time, improved monitoring efforts with rigorous sampling designs would provide a deeper understanding of pollinator communities and their responses to ongoing environmental change.

Using Bayesian multispecies models to evaluate fish and invertebrate detection probability and distribution in the hypersaline Bahia Grande tidal basin

AbstractObjectiveIn 2000, the Laguna Atascosa National Wildlife Refuge acquired the Bahia Grande (Texas) management unit, a space that had lain barren and arid for 70 years. A large cooperative partnership launched a restoration project to replenish the basin and recover its original tidal hydrology. In 2005, the construction of a pilot channel successfully restored water throughout the basin, and plans to eventually widen the channel were developed. Our study aims to evaluate an estuarine habitat restoration by assessing ecological drivers and the impacts on species diversity.MethodsWe evaluated species richness, detection/occupancy rates, and species–habitat relationships, and we estimated the sampling effort required to achieve a given level of relative precision if relative abundance was used instead of occupancy to inform future sampling. Sampling gear included bag seines for juvenile life stages and gill nets for capturing subadult and adult life stages. For analysis, we used a Bayesian negative binomial linear mixed‐effects model to evaluate richness–habitat relationships and a hierarchical Bayesian multispecies model to evaluate individual species–habitat relationships, and we calculated the total number of fish captured and relative standard error by gear and sample year to produce a precise estimate of relative abundance.ResultOverall, 29 species were caught between 2018 and 2021. Salinity emerged as a clear driver in the Bahia Grande, as both species richness and individual‐level responses were negatively associated with high salinity values. We found that catch estimated as relative abundance had much variability, as is typical of most survey programs assuming constant detectability, and the number of net sets or seine hauls required to achieve a given level of relative precision varied considerably depending on the species, season, year, and gear type. The most collected species were found in the upper extremes of their salinity tolerances—potentially a unique adaptation to this hypersaline system.ConclusionBaseline data suggest that for the channel widening to be successful, there must be a noticeable increase in suitable habitat characteristics throughout the basin.

Abundance of the northernmost jaguar Panthera onca breeding population

Jaguars are the apex predators of tropical and subtropical ecosystems in the Americas but their conservation is threatened due to habitat loss, poaching, and conflicts over predation. The Northern Jaguar Reserve (NJR) was created by Naturalia A.C. as a project to protect the northernmost jaguar population within an area of 59.3 thousand acres (24.4 ha) of private property. The property also includes other protected species. The present study was conducted to verify the status of this jaguar population in order to evaluate the effectiveness of the NJR, and to contribute to knowledge regarding its ecology. We estimated density using mark-resight and spatially explicit capture-recapture (SERC) models, and evaluated home range through a survey with 56 camera-trap stations over 12 bimonthly periods. In total, we obtained a sampling effort of 40,880 camera-days, registering 2.32 records from 1,000 camera-days. Jaguar density, calculated using the capture-recapture models, ranged from 0.3 to 1.44 indiv./100 km2, while the SERC model estimated a density of between 0.21 and 3.04 indiv./100 km2. The home range was 78.9 km2 for males and 45.1 km2 for females. Long-term population monitoring together with the establishment of Areas Voluntarily Assigned to Conservation, an initiative recently created by the Mexican government, such as the NJR, could be a valid strategy to strengthen jaguar conservation and thereby maintain key ecological processes for other species and their habitat in northwestern Mexico.

Mapping surface sediment characteristics in enclosed shallow‐marine environments using spatially balanced designs and the random forest algorithm

AbstractMapping the sedimentary character of the seafloor in large water‐filled basins is fundamental for understanding landform dynamics to inform research, management, intervention and conservation actions. Seabed mapping methods have undergone considerable development in the last two decades, including the uptake of machine learning approaches for sediment size prediction and classification. However, predictions of surficial sediment characteristics are often hindered by the availability of ground truthing data, their arrangement in space and the modelling approach chosen. Spatially informed sampling designs provide an opportunity to significantly improve the accuracy and uncertainty of predicted sediment distributions. In this study, we apply a machine learning algorithm to predict sediment distributions across Port Phillip Bay, a large (1930 km2) structurally controlled estuary on the southeast coast of Victoria, Australia. Surface sediment samples (n = 252) were collected using a spatially balanced design, ensuring that sampling effort was spread evenly within the embayment with increased sampling intensity placed in more heterogeneous areas. Surficial textural metrics were modelled using the random forest algorithm with bathymetric and hydrodynamic predictor variables. Models highlighted trends in sediment grain size, sorting and composition consistent with predicted wave‐ and current‐induced sediment mobilisation. Model predictions were accurate (normalised‐root mean squared error [NRMSE]: 0.14–0.16); however, standard error was not homogeneous across the study area. Uncertainty maps highlighted areas where additional sampling effort may be needed, including areas where transitional bathymetry impacted surficial sediment character and areas of anthropogenic modifications to the seabed. This study shows the benefits of undertaking spatially informed sample design, block cross‐validation during model fitting and quantifying spatial uncertainty in predictive maps to accurately quantify the fundamental boundary conditions of sediment size. The results of this study are intended to inform local coastal management, including beach renourishment activities. However, approaches outlined are applicable to any study where the seafloor grain size is a fundamental variable in understanding landscape change.

Standardized transect walks outperform pan traps in assessing wild bee community in a Mediterranean protected area (Asinara National Park, Italy)

AbstractThe decline of pollinator insects in various parts of the world has increased the interest in studies on bee sampling. Because pollinator management and conservation policies depend on data representing their communities, knowledge of the systematic bias of sampling methods in relation to surrounding habitat is fundamental. This study examined the performance of standardized transect walks and colored pan traps considering differences in bee species richness, diversity, and composition, and the potential bias due to a different availability of floral sources throughout seasons. The study was conducted in a minor outlying island (Asinara, Italy), a natural park characterized by the prevalence of natural or semi-natural habitats and an Oceanic Pluviseasonal Mediterranean bioclimate. We found that transect and pan trap methods reflected different bee communities based on taxonomic families, genera, and species. In general, the transect method captured more varied samples than pan traps, despite the significantly lower number of individuals captured on transects. Moreover, pan traps captured more bees as floral abundance decreased, whereas transects showed greater bee abundance, richness, and diversity with increasing floral resource availability. In addition, 18 species out of the 68 observed in total were caught exclusively with pan traps, especially in July–October, when transect catches decreased due to substantial bloom reduction. Therefore, alternating the two methods according to season (i.e., transect in late winter-spring and pan trap in summer-autumn) might be the most suitable trade-off to obtain a better representation of the bee community by limiting sampling efforts and the negative impact on bee fauna.

Social interactions generate complex selection patterns in virtual worlds.

Understanding the influence of social interactions on individual fitness is key to improving our predictions of phenotypic evolution. However, we often overlook the different components of selection regimes arising from interactions among organisms, including social, correlational, and indirect selection. This is due to the challenging sampling efforts required in natural populations to measure phenotypes expressed during interactions and individual fitness. Furthermore, behaviours are crucial in mediating social interactions, yet few studies have explicitly quantified these selection components on behavioural traits. In this study, we capitalize on an online multiplayer videogame as a source of extensive data recording direct social interactions among prey, where prey collaborate to escape a predator in realistic ecological settings. We estimate natural and social selection and their contribution to total selection on behavioural traits mediating competition, cooperation, and predator-prey interactions. Behaviours of other prey in a group impact an individual's survival, and thus are under social selection. Depending on whether selection pressures on behaviours are synergistic or conflicting, social interactions enhance or mitigate the strength of natural selection, although natural selection remains the main driving force. Indirect selection through correlations among traits also contributed to the total selection. Thus, failing to account for the effects of social interactions and indirect selection would lead to a misestimation of the total selection acting on traits. Dissecting the contribution of each component to the total selection differential allowed us to investigate the causal mechanisms relating behaviour to fitness and quantify the importance of the behaviours of conspecifics as agents of selection. Our study emphasizes that social interactions generate complex selective regimes even in a relatively simple ecological environment.

Macrofaunal diversity patterns in coastal marine sediments: re-examining common metrics and methods

Complex biodiversity patterns arise in marine systems due to overlapping ecological processes, including organism interactions, resource distribution, and environmental conditions. Despite the importance of documenting these patterns, describing diversity in natural ecosystems remains challenging. Here, we investigate 3 nearshore sub-Arctic sites to describe benthic macroinfaunal taxa and biological traits, with the ultimate aim of determining whether common diversity metrics and typical sampling efforts adequately capture community composition in these systems. First, we assess how diversity relates to sediment depth and examine relationships among commonly used taxonomic and functional diversity indices. Second, using a power analysis, we explore how sampling effort influences the interpretation of diversity patterns in coastal systems. We report significant variation in community composition among sites, even across small spatial scales of km, and find that taxonomically diverse communities do not necessarily correspond to high functional diversity. We further find that although environmental factors such as sediment depth consistently affect macroinfaunal diversity, the direction and magnitude of these relationships are site-dependent. Finally, we demonstrate that typical sampling effort for coastal benthic studies (for example, <5 push cores of ~7 cm diameter) may not capture macroinfaunal community composition adequately, potentially obscuring hotspots in common diversity metrics such as taxonomic or functional richness. However, indices such as Simpson’s diversity may be well-suited to resource-limited studies with restricted sampling capacity. Our results highlight the importance of adopting multi-pronged approaches to biodiversity assessment and determining optimal sample sizes for marine benthic systems, particularly in the context of biodiversity monitoring for conservation purposes.

SNAPSHOT USA 2021: A third coordinated national camera trap survey of the United States.

SNAPSHOT USA is a multicontributor, long-term camera trap survey designed to survey mammals across the United States. Participants are recruited through community networks and directly through a website application (https://www.snapshot-usa.org/). The growing Snapshot dataset is useful, for example, for tracking wildlife population responses to land use, land cover, and climate changes across spatial and temporal scales. Here we present the SNAPSHOT USA 2021 dataset, the third national camera trap survey across the US. Data were collected across 109 camera trap arrays and included 1711 camera sites. The total effort equaled 71,519 camera trap nights and resulted in 172,507 sequences of animal observations. Sampling effort varied among camera trap arrays, with a minimum of 126 camera trap nights, a maximum of 3355 nights, a median 546 nights, and a mean 656 ± 431 nights. This third dataset comprises 51 camera trap arrays that were surveyed during 2019, 2020, and 2021, along with 71 camera trap arrays that were surveyed in 2020 and 2021. All raw data and accompanying metadata are stored on Wildlife Insights (https://www.wildlifeinsights.org/), and are publicly available upon acceptance of the data papers. SNAPSHOT USA aims to sample multiple ecoregions in the United States with adequate representation of each ecoregion according to its relative size. Currently, the relative density of camera trap arrays varies by an order of magnitude for the various ecoregions (0.22-5.9 arrays per 100,000 km2), emphasizing the need to increase sampling effort by further recruiting and retaining contributors. There are no copyright restrictions on these data. We request that authors cite this paper when using these data, or a subset of these data, for publication. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government.

Identifying the generalizable controls on insect associations of native and non-native trees.

Trees growing outside their native geographic ranges often exhibit exceptional growth and survival due in part to the lack of co-evolved natural enemies that may limit their spread and suppress population growth. While most non-native trees tend to accumulate natural enemies over time, it remains uncertain which host and insect characteristics affect these novel associations and whether novel associations follow patterns of assembly similar to those of native hosts. Here, we used a dataset of insect-host tree associations in Europe to model which native insect species are paired with which native tree species, and then tested the model on its ability to predict which native insects are paired with which non-native trees. We show that native and non-native tree species closely related to known hosts are more likely to be hosts themselves, but that native host geographic range size, insect feeding guild, and sampling effort similarly affect insect associations. Our model had a strong ability to predict which insect species utilize non-native trees as hosts, but evolutionarily isolated tree species posed the greatest challenge to the model. These results demonstrate that insect-host associations can be reliably predicted, regardless of whether insect and host trees have co-evolved, and provide a framework for predicting future pest threats using a select number of easily attainable tree and insect characteristics.

Assessing the spatial knowledge gaps of Odonata diversity and conservation in the South American Pampa

Abstract Anthropogenic activities highly threaten neotropical freshwater habitats. Aquatic insects are sensitive to environmental alterations and thus considered under great risk due to such pressures. However, large‐scale gaps regarding the knowledge of the distribution of aquatic insect species remain in the Neotropics, particularly in the South American temperate grasslands (Pampas), hindering the knowledge of hotspots of aquatic insect diversity and the prioritization of conservation areas destined to protect their populations. Here, we review the current knowledge regarding the geographical distribution of Odonata species and use ecological niche models to estimate the areas with the highest potential richness of Odonata species in the Pampas. We also calculate a sampling effort index and interpolate it with maps of protected areas to identify the spatial knowledge gaps regarding their conservation in the region Our compilation of Odonata species records retrieved 237 species for the Pampa. However, Odonata species were recorded in less than 2% of the Pampa. Our findings indicated a higher potential diversity of Odonata in northeastern Argentina, southern Uruguay and southern Brazil. Interpolations of sampling effort index and protected areas showed that 95% of the area potentially rich in Odonata species fall outside protected areas. Our study highlights the shortfall regarding the knowledge of the distribution of Odonata diversity in non‐forest landscapes of the Neotropical region. It also shows that protected areas of the Pampa cover a minor area of the Odonata species range in the region.

COMPOSITION, ABUNDANCE AND DISTRIBUTION OF NON-CICHLID FISH COMMUNITY IN OGBO STREAM AND ITS FLOODPLAIN, ENHWE, DELTA STATE, NIGERIA

A preliminary survey of the composition, abundance and distribution of non-cichlid fish community was carried out at Ogbo stream and its floodplain in Enhwe, Delta StateNigeria. Water samples and fishes were sampled and analyzed using APHA methods and standard fishing gear respectively. The physicochemical parameters revealed distinct values for station 1 (Temperature: 25.63°C, Transparency: 25.09 cm, Sulphate: 7.56 mg/L) and station 2 (Temperature: 23.60 °C, Transparency: 19.90 cm, Sulphate: 6.68 mg/L). Among the parameters, only Temperature, Transparency, and Sulphate exhibited a noteworthy difference (p<0.05) between the two stations. Transparency had a negative correlation with other parameters in Station 1.A total of 725 individual fish species belonging to eight families and genera were sampled. Among the notable findings, Clariidae emerged as the most abundant family, constituting 82.90% of the total relative abundance across both stations. Clarias camerunensisexhibited the highest abundance, comprising 62.20% of the total individuals sampled. Parachanna africanaand Clarias pachynemaalso demonstrated significant presence, contributing 15.00% and 13.20% to the total relative abundance, respectively. ANOVA indicates a significant difference in the composition and abundance of fish species between the stream and floodplain (p < 0.05), emphasizing the influence of habitat-specific factors. The Margalef’s richness (1.67), dominance (0.64), diversity (1.32) and evenness (0.34) index of fishes was higher in the stream than in the floodplains. Magnesium, sulphate, temperature, and transparency were positively correlated to the distribution patterns of Pantodon bucholzi, Clarias jaensis, Phractolaemus ansorgei, and Heterotis niloticusin station 1, with the exception of P. africanaand Polypterus senegalus. There was a negative association between dissolved oxygen, nitrate, pH, and Iron, and the distribution of fishes in station 2. Ogbo stream and its floodplain have low abundance and distribution of fish species. Therefore, it demands for sampling efforts and long-term studies to unravel the checklist of species

Optimal design of electromagnetic field exposure maps in large areas

The mapping of electromagnetic field (EMF) exposure over large areas is a very useful tool for the analysis of epidemiological data and risk assessment. Its production requires a costly measurement process. To optimize the effort and ensure the representativeness of the exposure map, criteria for the selection of the sites to be measured must be established. This paper presents a methodology for conducting EMF exposure maps suitable for risk assessment evaluation in large areas. The proposal combines radio wave propagation criteria and GIS methods to optimize the sampling effort. The design criteria are based on the determination of a rectangular grid of 250 m side and the identification of the emitters within the area under study. Both urban and rural sites are analysed in the proposal and line of sight conditions (LOS) are considered to reduce the number of points required and thus optimize the measurement effort. Depending on the extent and regularity of the surface, the density of measurement points has been estimated to be between 8 and 10 points per square kilometre in the urban area. The proposed methodology has been applied to a case study of a 2.8 km2 urban area within a 35.11 km2 municipality, obtaining an average point density of 9.64 points/km2 in the urban area. The differences in exposure depending on the application of the criteria have been analysed by means of the statistical values of the sets and the subtraction of the maps generated using kriging techniques. According to our results, if LOS measurements are not properly incorporated, the mean value of the EMF is underestimated in the area under study.

No optimal spatial filtering distance for mitigating sampling bias in ecological niche models

AbstractAimThe continuous development of statistical tools applied to ecology has contributed to great advances for modelling species' niches and distributions from opportunistic observations. However, as these observations are subject to biases caused by spatial variation in sampling effort, ecological niche models (ENMs) are also frequently biased. Among several bias correction methods that have been proposed, spatial filtering—imposing a minimum distance between occurrences—is widely used, yet lacks clear guidelines for choosing the filtering distance. Here, we aimed to explore the impact of spatial filtering distances on the performance of ENMs.LocationEurope.TaxonVirtual species.MethodsWe applied ENMs to two virtual species with contrasting levels of specialisation, across a spectrum of modelling conditions, bias types and sample sizes.ResultsModels applied to the specialist species had on average a lower performance than those applied to the generalist species. Using a biased sample reduced model performance, especially when the bias was strong, and when the sample size was large. In many cases, spatial filtering failed to improve model performance or even reduced it. We did find an improvement for the generalist species modelled with large and strongly biased datasets. However, there was no optimal filtering distance, as this improvement was linearly and positively associated with filtering distance. Moreover, because the initial bias was strong and the filtered dataset became very small, the resulting models had only very low accuracy.Main ConclusionsOur results suggest that there is no optimal filtering distance for dealing with sampling bias in ENMs, and that spatial filtering never improves model performance enough to draw accurate predictions. We therefore recommend spatial filtering to be employed cautiously, only when enough data are available, and bearing in mind that its effectiveness remains highly uncertain.

Plantation forestry of Alder-leaf Birch (Betula alnoides) affects composition but not interactions of mixed-species bird flocks in southwestern China

Human disturbance impacts mixed-species bird flocks (“flocks”). Unfortunately, the impact on flocks by one large-scale disturbance, plantation forestry, has remained little explored. We examined how plantation forestry of a widespread yet understudied timber species, Alder-leaf Birch (Betula alnoides, “birch”), affects the composition and interactions of flocks in the Indo-Burma biodiversity hotspot in southwestern China. We conducted transect surveys to sample flocks in birch plantations and natural forests of two age classes (mature and young). While flock size and species richness per flock were similar across land-use types, rarefied species richness accounting for unequal sampling effort was noticeably higher in mature forests. Furthermore, flock composition differed across land-use types, with differences related to species' morphological characteristics, dietary preferences, and foraging substrates. Specifically, mature forests supported flock participants with large bodies, poor dispersal ability, and a fruit-eating diet. Birch plantations offered equal support to invertivores as both natural forests, and additional support to bark foragers. Lastly, interactions among flocking species quantified by social network metrics were similar across land-use types, suggesting that birch plantations perserved the flocking behavior itself. Our study reveals the conservation potential of birch plantations in supporting invertivorous birds and preserving interactions in flocks. More importantly, it highlights the irreplaceability of mature forests because of their unique species composition. We recommend promoting birch planting without compromising local economies and protecting remnant mature forests through education programs and continued research.

Insect floral visitors of thermo-Mediterranean shrubland maquis (Ajaccio, Corsica, France).

The Mediterranean Region represents a biodiversity hotspot with a high rate of endemism. In its western part, Corsica Island is notable in terms of biodiversity due to its large surface and its large range of habitats from seaside to alpine biotopes. Amongst diverse groups, insects, notably the main orders of pollinators composed of Coleoptera, Hymenoptera, Diptera and Lepidoptera, represent a good part of the insular richness. Our sampling effort focused on the insects from these four orders visiting flowers in a characteristic thermo-Mediterranean vegetation. Our database is an insight into the Corsican floral visitor biodiversity from three sites separated by a few kilometres in the region of Ajaccio during 13 months over two successive years. In total, 4012 specimens were sampled and 252 species or morpho-species identified from 133 genera and 47 families. Beetles were by far the most abundant order representing about 54% of the sampled specimens. The most diverse order was the Hymenoptera representing 39% of the species. Our continuous survey showed that these orders are temporally dynamic both between years and between seasons in terms of abundance and diversity.

Managing Uncertainty in Urban Road Traffic Emissions Associated with Vehicle Fleet Composition: From the Perspective of Spatiotemporal Sampling Coverage

With pronounced differences in emission factors among vehicle types and marked spatiotemporal heterogeneity of vehicle fleet composition, extrapolating fleet composition from insufficient sample hour periods and road segments will introduce significant uncertainty in calculating regional daily road traffic emissions. We proposed a framework to manage uncertainty in urban road traffic emissions associated with vehicle fleet composition from the perspective of spatiotemporal sampling coverage. Initially, the respective relationships of the temporal and spatial sampling coverages of fleet composition with the resulting regional daily road traffic emission uncertainties were determined, using the core area of a typical small and medium-sized city in China with the widely-used International Vehicle Emissions (IVE) model as example. Subsequently, function models were developed to explore the determination of the spatiotemporal sampling coverage of fleet composition. These results of emission uncertainties and function models implied that gases with larger emission factor discrepancies between vehicle types, such as NOx, required greater spatiotemporal sampling coverage than gases with smaller discrepancies, such as CO2, under the same uncertainties target. Therefore, sampling efforts should be prioritized for gases with larger emission factor discrepancies. Additionally, increasing sampling coverage in one dimension (either spatial or temporal) can reduce the minimum required coverage in the other dimension. To further reduce uncertainty, enhancing both spatial and temporal sampling coverage of the fleet composition is more effective than enhancing one type of coverage alone. The framework and results proposed in this work can reduce the uncertainty of emissions calculations caused by insufficient sampling coverage and contribute to more accurate transport emission reduction policy formulation.

Towards accurate spatial prediction of Glossina pallidipes relative densities at country-scale in Kenya

Vector-borne diseases, like those transmitted by tsetse flies, pose a significant global public health threat. Reducing vector populations is a promising strategy for disease control, especially in the case of tsetse-transmitted African trypanosomiasis. However, the cost-effective implementation of large-scale vector surveillance and control measures face challenges due to the lack of spatially explicit and reliable maps identifying vector hotspots. In this study, we assessed the accuracy of predicting Glossina pallidipes relative densities across Kenya by linking constrained in-situ tsetse catch data from 660 traps across three Kenyan regions with readily available gridded satellite information (human population, land cover, soil properties, elevation, precipitation, and land surface temperature) using a classical random forest algorithm. To enhance predictive performance, we employed two feature elimination techniques specifically designed for machine learning algorithms, i.e., Recursive Feature Elimination (RFE) and Variable Selection Using Random Forests (VSURF). For each set of retained variables, we trained a Random Forest model using a spatial cross-validation technique. Our findings showed that tsetse fly relative densities decreased with mean annual precipitation, and soil moisture, and conversely increased with higher tree cover. Based on the cross-validated R2, 41% of the spatial variability in relative densities of tsetse flies could be explained. For spatial extrapolation, only the set of predictors retained by VSURF closely matched known tsetse fly distributions in Kenya. This more accurate performance of VSURF may be attributed to its approach of assessing variables for both importance and their contribution to reducing prediction error. Our study demonstrates the potential of using a random forest method to upscale tsetse relative abundance predictions to the national level. However, the reliability of the current extrapolated map remains uncertain. We recommend: 1) increasing tsetse fly sampling efforts, particularly in the data-limited northern and eastern regions of Kenya, and 2) developing a more precise and accurate land cover map with classes that directly associate with known habitat characteristics of the target tsetse species.

Assessing water diversion impacts on the fish community size structure in headwater stream stretches

AbstractWater diversion for hydropower plants is one of the leading causes of habitat alteration and biotic homogenization. The impacts of small hydropower plants on fish communities are usually assessed using taxonomic composition and structure indicators. Size-based indicators are useful tools to evaluate the effects of environmental factors and anthropogenic perturbations on riverine ecosystems. In this study, we investigated the impact of water diversion on fish community body size structure in 16 small hydropower plants in the upper Ter River basin (NE Iberian Peninsula). We tested the use of multiple size-based metrics under different sampling intensities (one- vs. four-pass electrofishing) and compared control vs. diverted stream stretches. Results revealed that water diversion had a negative effect on fish community average and median length, while size spectrum and size diversity metrics showed no responses to the impact. Altitude was positively related with body size metrics and was the strongest natural driver affecting them. Moreover, we found that all the size-based metrics exhibited consistent values under different sampling efforts. Our findings suggest that size-based metrics could be useful indicators for bioassessment of river flow alteration and that one-pass electrofishing was robust enough to characterize the stream fish community size structure in our study.