Intensive Field Sampling Research Articles

Leaf-cutting ants’ distribution in an elevation gradient in central Argentina

ABSTRACT Leaf-cutting ants are among the most prominent herbivores in neotropical forests and savannas, and Argentina represents the southern limit of their distribution. Despite their importance, few systematic studies analyze the presence and distribution of leaf-cutting ants in Argentina. Our aim was to describe, through an intensive field sampling, the leaf-cutting ant species present in the central Argentine mountains and analyze their distribution along the elevation gradient. We collected ants from 69 nests in 56 out of the 250 plots visited along the study elevation gradient (400–2700 m above sea level) in seven different habitats, from forests to rocky areas. We found six species. The most frequent were Acromyrmex lobicornis and Acromyrmex crassispinus, while Acromyrmex heyeri, Amoimyrmex silvestrii, Amoimyrmex striatus, and Amoimyrmex bruchi were far less frequent. The species distributed at the highest elevation was A. lobicornis (1223 to 2163 m a.s.l.), showing significant differences with the other species. We found leaf-cutting ants in all habitats, with a higher presence in grazing lawns, shrublands, and exotic forests. Our results indicate that leaf-cutting ants are present in most of the mountain range, as the area above their upper limit of distribution represents less than 5% of the total mountain area.

A new species of Ctenomys (Rodentia, Ctenomyidae) from the pre-Andean regions of Mendoza Province, Argentina

Abstract The genus Ctenomys (Rodentia: Hystricomorpha) includes an impressive diversity of species, all of which have evolved in southern South America. The number of recognized species is currently approaching 70. During the last few decades, taxonomic revisions and new field collections have resulted in both the description of new species and the synonymization of others, suggesting that much of the alpha taxonomy of Ctenomys remains unresolved, particularly when considering the vast areas of distribution that are still unsampled. Both phylogeographic patterns and the fossil record suggest that the Andean Cordillera has played a critical role in the diversification of the genus. Building upon recent, intensive field sampling in the Andean and pre-Andean regions of southern Mendoza Province, I integrated molecular and morphological data to evaluate the taxonomic status of populations of Ctenomys in this region. These analyses revealed a taxonomically-diverse Ctenomys assemblage within which here I provide the description for a new species. Available data indicate that this new species is endemic to southern portions of Mendoza Province, a geographic region that represents the confluence of 3 lineages ‘magellanicus,’ ‘maulinus,’ and ‘mendocinus,’ and that it is thus an area of particular importance for the conservation of these rodents.

Characterization of naturally occurring radioactive material dynamics in community water systems using groundwater from Ganghwa Island, Republic of Korea

Understanding the temporal behaviors of naturally occurring radioactive materials is important for the maintenance of community water supply systems for drinking groundwater on islands and in mountainous areas. Intensive field sampling in the Republic of Korea to characterize temporal variation in 238U concentration and 222Rn activity was performed for three community water systems on Ganghwa Island for ten years (2012–2022). 222Rn, a dissolved gas in groundwater, tended to decrease in activity as water moved from the source through community water systems, but no such trend was observed in 238U concentration. 238U and 222Rn behaviors in time series data for different CWSs reflected different geochemical processes and were differently classified accordingly. In particular, the 238U and 222Rn at points GJ and YH shows the signature of weathering: accompaniment by variation in pH and dissolved oxygen. In other time series, the 238U and 222Rn behavior shows the signature of cation exchange by seawater intrusion: accompaniment by dramatic variation in electrical conductivity. Random forest regression models developed to estimate the 238U concentration and 222Rn activity in groundwater boreholes exhibited reasonable threshold classification accuracy. The optimized threshold structure for 238U concentration and 222Rn activity variation with respect to the water quality variable of greatest statistical importance in each community water system random forest regression model corresponded to the geochemical process controlling the behavior of 238U and 222Rn in that groundwater borehole. Therefore, more intensive field sampling, covering the full data range that could emerge at each groundwater borehole, can aid in enhancing the accuracy of estimation of 238U concentration and 222Rn activity. Furthermore, the use of an in situ groundwater monitoring system in a random forest regression model facilitates the effective management of community water systems in the face of risk posed by naturally occurring radioactive materials.

Characterization of seasonal behaviors of naturally occurring radioactive materials in a groundwater borehole using an in situ monitoring system

Understanding the temporal behaviors of naturally occurring radioactive materials is important for safeguarding groundwater as a secure water resource for drinking, agriculture, and industry usage. This study reports the vertical profiles of 238U concentration and 222Rn activity and the management of in situ monitoring systems during intensive field sampling of a national groundwater-monitoring borehole for seven years (2015–2021). The aim was to capture the seasonal characteristics of the 238U concentrations and 222Rn activity. Both factors were low in the rainy season and high in the winter season, reflecting the dilution effect of rainfall recharge. The 238U and 222Rn behaviors were associated with water–rock interactions of calcite dissolution in fracture zones filled with carbonate minerals. Furthermore, multilayer perceptron models estimated the 238U concentration and 222Rn activity with reasonable regression and classification accuracy. Hydrometeorological indicators (temperature and groundwater-level fluctuations) were more important estimators of 238U concentration and 222Rn activity than geochemical process indicators. The regression accuracy performance was higher at deeper sampling depths, where seasonality in the 238U and 222Rn behaviors dominated. From the predicted distributions of 238U concentrations and 222Rn activities, we could estimate the ranges of 238U concentrations and 222Rn activities emerging from groundwater boreholes. High exposure threats from 238U and 222Rn during groundwater usage were found in the winter season. When the multilayer perceptron models use the entire in situ monitoring data at refined temporal resolution, we can quickly determine the naturally occurring radioactive materials and further develop the national groundwater-monitoring borehole equipped with the in-situ monitoring system, supplementing the occasionally obtained field-measurement data.

Daily activity patterns and body temperature of the Oriental migratory locust, Locusta migratoria manilensis (Meyen), in natural habitat.

Current pest management techniques would benefit from understanding the behavioural rhythms of the target pest and its body temperature, a critical aspect not well studied and potentially limiting the effectiveness of biopesticides under natural conditions. This study aims 1) to understand under natural conditions the behavioural patterns of different stages of hoppers and adults of Locusta migratoria manilensis and 2) to identify the environmental factors modulating their body temperature through field observation. We carried out an intensive field sampling in two of the main locust breeding regions in China, recording the body temperature (day and night), morphological traits (stage, sex and size) and microhabitat of 953 individuals. The results revealed that locusts preferred the ground as their main activity subhabitat, particularly for hoppers. Adults tended to move upper in the reed canopy at two peaks (10-11h and 14-15h). Locusts body temperature during daytime increased with development stage and size, while the opposite pattern occurred during night time. Entompathogenic fungi are more effective if the body temperature of the target pest is in a proper range without too high or too low. Application of biopesticides should focus on younger locusts spraying in the morning or at dusk as the locusts have lower body temperatures.

Modelling the location of interglacial microrefugia for cold-adapted species

Rhododendron tomentosum is a vascular plant common in northern regions of Europe, Asia and North America. In central Europe, this species is considered a glacial relict. In recent years, systematic floristic mapping of the distribution of this species in the Bohemian Switzerland National Park has revealed that this rare and highly sensitive species is strongly associated with a specific type of habitat. Rhododendron tomentosum adapted to environmental changes throughout the Holocene: soil acidification, repeated fires and negative effect of forestry on species composition. To identify the survival mechanisms of R. tomentosum, suitable sites in well-preserved parts of a sandstone landscape with assumed minimal human influence were selected. Based on data from intensive field sampling and a set of environmental variables for the whole area of the National Park, habitat suitability maps for R. tomentosum were developed. These maps were then combined with the palaeoecological data and used to identify sources of pollen with greater precision and extend the knowledge of the potential distribution of R. tomentosum outside the intensively sampled areas. Palaeoecological data was particularly useful for reconstructing the past population dynamics of R. tomentosum. The results indicate the long-term stability of sites suitable for this species, supported by locally diversified vegetation development in sandstone areas. This research could therefore provide the first direct evidence of the persistence of R. tomentosum micropopulations throughout a large part of the Holocene.

Effects of Afforestation on Soil Carbon and Nitrogen Accumulation Depend on Initial Soil Nitrogen Status

AbstractLong‐term carbon (C) sequestration in terrestrial vegetation and soil is mediated by soil nitrogen (N) supply. Afforestation is regarded as a global‐scale solution to climate change; thus, resolving the role of N in either facilitating or reducing the long‐term C benefits of this practice has essential implications to maximize its C sink potential. The impacts of afforestation on soil C, N, and their stoichiometric ratio have been widely explored but what regulates these impacts remains unclear at regional and global scales. In this study, we conducted an intensive field sampling investigation including 610 pairs of afforested and control plots in northern China and extensively compiled a global data set containing 211 afforested‐control pairs worldwide to evaluate responses of soil N concentrations and C:N ratios to afforestation and further explored their major regulator. We identified a soil N threshold, the inflection point where afforestation changes from increasing to decreasing soil C and N, which was 0.86 (95% CI: 0.81–0.91) kg N m−2 in 0–1 m depth. Changes in soil C:N ratios with afforestation were mediated by initial relative abundance of soil C and N and types of mycorrhiza associated with planted trees. Increases in soil C:N were mostly driven by trees with ectomycorrhizal associations but did not change for those associated with arbuscular mycorrhizal fungi. These results provide a data‐based understanding on soil C and N dynamics following afforestation and its underlying mechanisms and further highlight the importance of site selection based on initial soil properties in future afforestation.

Significance of sources and size distribution on calibration of low-cost particle sensors: Evidence from a field sampling campaign

Low-cost sensors (LCS) are gathering the interest of researchers and monitoring agencies worldwide due to their compact size and economic feasibility. However, the data recorded by LCS is often of low quality owing to its calibration dependencies and biases. An intensive field sampling campaign was conducted at five sites inside the IIT Bombay campus to understand the fundamental issues associated with LCS. PA-II and OPC-N2 LCS were collocated with BAM-1020 and OPS- 3330 at the sampling locations for inter-comparison. LCS shows a good correlation with BAM-1020 at sites where the contributing sources produce more particles in the 1–2.5 μm size range than particles in below 1 μm (PM1) and 2.5–10 μm size range. The performance decreased with an increase in mass fractions of PM1 and PM10. The overall performance of both PA-II (R2 = 0.72) and OPC-N2 (R2 = 0.73) are comparable. Both PA-II and OPC-N2 have substandard performance with R2 in the range of 0.30–0.39 and 0.42–0.53 at the construction and main gate site respectively. Comparing the two calibration approaches used in this study indicates the importance of including size distribution parameters in the calibration of LCS. The calibration models were developed for each site and were compared with the general model developed for PA-II and OPC-N2. Results indicate that the site-specific models are in better agreement with the reference instrument than the general calibration model. The number concentration recorded by PA-II was poorly correlated with OPS-3330, especially for particles >1 μm and vice versa for OPC-N2. The particle count for PM > 2.5 μm recorded by PA-II is predominantly zero, which is inconsistent with the mass concentration data recorded by the sensor. The size distribution results indicate that LCS assumes a universal monotonically decreasing function of number concentration with respect to the particle diameter. It is one of the critical problems with LCS measurements as any error in the number measurement is increased 3-fold in the mass conversion. This study shows the need for site-specific robust calibration of LCS based on the particle size distribution and provides a direction in their development.

Probability of cultivating Se-rich maize in Se-poor farmland based on intensive field sampling and artificial neural network modelling

Selenium (Se) is a necessary micronutrient for humans, and its supplementation from crop grains is important to address the ubiquitous Se deficiency in people worldwide. Se uptake by crops largely depend on soil bioavailable Se rather than soil total Se content, which provides possibilities to explore the Se-rich crops in Se-poor area. Here, the possibility of cultivating Se-rich maize grains in Se-poor farmland was tested based on intensive field sampling and mathematical modelling. Sampling was conducted at county scale, and a total of 7779 topsoil samples and 109 maize samples with paired rhizosphere soils samples were collected. Results showed that although the soil Se content in the study county from southwestern China was at a low level (0.01–2.75 mg kg−1), 54.1% of the maize grain samples satisfied the standard for Se-rich products (0.02–0.30 mg kg−1). Soil organic matter, iron oxide, and phosphorus levels were correlated negatively with Se bioconcentration factor (BCF) of maize grain. Compared with the multivariate linear regression model, the artificial neural network (ANN) model was more accurate and reliable in predicting maize Se BCF. Prediction using the ANN model showed that 22.7% of the county's farmland was suitable for cultivating naturally Se-rich maize, which increased 21.3% growing areas than that from cultivation based on simply soil total Se. This study provided a new methodological framework for natural Se-rich maize production and verified the probability of cultivating naturally Se-rich maize in Se-poor farmland.

Assessing tiger corridor functionality with landscape genetics and modelling across Terai-Arc landscape, India

India led the global tiger conservation initiatives and has doubled its wild tiger population to 2967 (2603–3346) since 2006. As the extant habitats are shrinking continuously, the persistence of these growing populations can only be ensured through focused landscape-scale conservation planning across all the existing tiger landscapes of Indian. We used intensive field-sampling, genetic analyses and GIS modelling to investigate tiger population structure, source-recipient dynamics and functionality of the existing corridors across the Indian part of Terai-Arc landscape (TAL). Using a 13 microsatellite marker panel we identified 219 individual tigers across Indian TAL. Further genetic analyses revealed three weakly, but significantly differentiated tiger subpopulations, termed as ‘Tiger Genetic Blocks (TGBs)’. Genetic migrant detection and gene flow analyses distinguished seven source and 10 recipient areas within this landscape. Circuitscape analyses ascertained total 19 (10 high, three medium and six low conductance) corridors across this landscape, of which 10 require immediate conservation attention. Overall, the tiger populations residing in the western, central and eastern TAL still maintain functional connectivity through these corridors. We suggest urgent management plan involving habitat recovery and protection of ~ 2700 sq. km. identified area to establish landscape connectivity. Further, mitigation measures associated with ongoing linear infrastructure developments and transboundary coordination with Nepal will ensure habitat and genetic connectivity and long-term sustainability of tigers in this globally important landscape.

Citellinema (Nematoda: Heligmosomidae) from North America with descriptions of 2 new species from the red squirrel Tamiasciurus hudsonicus and 1 from the Canadian woodchuck, Marmota monax.

Citellinema Hall, 1918 includes 6 valid species of gastrointestinal nematodes of sciurids. Two species occur in the Palearctic and 4 in the Nearctic, 3 of which occur minimally across Colorado, Idaho and Oregon and 1, Citellinema bifurcatum, has a wide distribution across North America. Members of the genus are didelphic, possess a cephalic vesicle, a terminal spine-like process in females and feature robust spicules, consisting of a proximal end fused and semicylindrical shaft connected to a lamina supported by 2 terminal filiform processes. Typically, the size of the spicules is used to differentiate species. As part of the Beringian Coevolution Project, specimens provisionally identified as C. bifurcatum were collected through intensive field sampling of mammals and associated parasites from across localities spanning the Holarctic. These specimens revealed considerable genetic variability at both mitochondrial and nuclear loci, supporting the identification of deeply divergent clades. Examination of these new specimens, along with the holotypes of C. bifurcatum and Citellinema quadrivittati indicates that Citellinema monacis (previously synonymized with C. bifurcatum) should be resurrected and 3 additional species described. We suggest that the apparent bifurcated nature of the spicule should be considered a generic diagnostic trait, while the proportional length of the lamina relative to that of the spicule is used as a specific character. We demonstrate the critical need for continued inventory of often poorly known assemblages of hosts and parasites, contributing to a growing baseline of archival specimens, collections and information that make explorations of faunal structure and diversity possible.

How do accuracy and model agreement vary with versioning, scale, and landscape heterogeneity for satellite-derived vegetation maps in sagebrush steppe?

Maps of the distribution and abundance of dominant plants derived from satellite data are essential for ecological research and management, particularly in the vast semiarid shrub-steppe. Appropriate application of these maps requires an understanding of model accuracy and precision, and how it might vary across space, time, and different vegetation types. For a 113 k Ha burn area, we compared modeled maps of different vegetation cover types created from satellite data to ‘benchmark” models based on intensive field sampling (∼1500–2000 plots resampled annually for 5 years) for three new satellite-derived models: USDA Rangeland Analysis Platform (RAP), the USGS Rangeland Condition Monitoring Assessment and Projection (RCMAP), and USGS fractional estimate of exotic annual grass cover (USGS-fractional-EAG). We assessed out-of-sample point accuracy and asked if and how accuracy changed each year due to vegetation shifts, new images, and model improvements (i.e. model versions). We also assessed how map agreement between satellite-based and field-based models changed with scale of application, topography, and time since fire.Accuracy and map agreement varied considerably among the vegetation types and across time and space (r2 ranging from 0 to 0.53), and some of the variability was predictable. All models tended to over or underestimate cover when field-measured cover was relatively low or high, respectively, i.e. a “false moderating effect”. Accuracy was greater and improved with newer versions of RAP (+0.05 to 0.29 r2) compared to RCMAP and USGS fractional model estimates, and in some cases was greater than field-based models. Variability in map agreement tended to decrease with larger areas sampled (particularly in areas >12 km), and this scale dependency was more evident in RAP and USGS-fractional-EAG models. Creating a “fair” basis for comparison of spatial models of low-statured semiarid vegetation derived from satellite compared to field data is not trivial because scaling the field data to the scale of large satellite pixels (or downscaling satellite-based models to field scale) requires modeling and associated model uncertainty. Accuracy can vary considerably and understanding the variation can help guide application of the models to the appropriate time, place, and variables.

Probability of Cultivating Se-Rich Maize in Se-Poor Farmland Based on Intensive Field Sampling and Artificial Neural Network Modelling

Probability of Cultivating Se-Rich Maize in Se-Poor Farmland Based on Intensive Field Sampling and Artificial Neural Network Modelling

Strain Diversity and Spatial Distribution Are Linked to Epidemic Dynamics in Host Populations.

AbstractThe inherently variable nature of epidemics renders predictions of when and where infection is expected to occur challenging. Differences in pathogen strain composition, diversity, fitness, and spatial distribution are generally ignored in epidemiological modeling and are rarely studied in natural populations, yet they may be important drivers of epidemic trajectories. To examine how these factors are linked to epidemics in natural host populations, we collected epidemiological and genetic data from 15 populations of the powdery mildew fungus, Podosphaera plantaginis, on Plantago lanceolata in the Åland Islands, Finland. In each population, we tracked spatiotemporal disease progression throughout one epidemic season and coupled our survey of infection with intensive field sampling of the pathogen. We found that strain composition varied greatly among populations in the landscape. Within populations, strain composition was driven by the sequence of strain activity: early-active strains reached higher abundances, leading to consistent strain compositions over time. Co-occurring strains also varied in their contribution to the growth of the local epidemic, and these fitness inequalities were linked to epidemic dynamics: a higher proportion of hosts became infected in populations containing strains that were more similar in fitness. Epidemic trajectories in the populations were also linked to strain diversity and spatial dynamics: higher infection rates occurred in populations containing higher strain diversity, while spatially clustered epidemics experienced lower infection rates. Together, our results suggest that spatial and/or temporal variation in the strain composition, diversity, and fitness of pathogen populations are important factors generating variation in epidemiological trajectories among infected host populations.

Intensive field sampling increases the known extent of carbon-rich Amazonian peatland pole forests

Peatland pole forest is the most carbon-dense ecosystem in Amazonia, but its spatial distribution and species composition are poorly known. To address this knowledge gap, we quantified variation in the floristic composition, peat thickness, and the amount of carbon stored above and below ground of 102 forest plots and 53 transects in northern Peruvian Amazonia. This large dataset includes 571 ground reference points of peat thickness measurements across six ecosystem types. These field data were also used to generate a new land-cover classification based on multiple satellite products using a random forest classification. Peatland pole forests are floristically distinctive and dominated by thin-stemmed woody species such as Pachira nitida (Malvaceae), Platycarpum loretense (Rubiaceae), and Hevea guianensis (Euphorbiaceae). In contrast, palm swamps and open peatlands are dominated by Mauritia flexuosa (Arecaceae). Peatland pole forests have high peat thickness (274 ± 22 cm, mean ± 95% CI, n = 184) similar to open peatlands (282 ± 46 cm, n = 46), but greater than palm swamps (161 ± 17 cm, n = 220) and seasonally-flooded forest, terra firme, and white-sand forest where peat is rare or absent. As a result, peatland pole forest has exceptional carbon density (1,133 ± 93 Mg C ha−1). The new sites expand the known distribution of peatland pole forest by 61% within the Pastaza-Marañón Foreland basin, mainly alongside the Tigre river, to cover a total of 7540 km2 in northern Peruvian Amazonia. However, only 15% of the pole forest area is within a protected area, whilst an additional 26% lies within indigenous territories. The current low levels of protection and forest degradation but high threat from road paving projects makes the Tigre river basin a priority for conservation. The long-term conservation of peatland pole forests has the potential to make a large contribution towards international commitments to mitigate climate change.

Exploring the Contemporary Relationship between Predator and Prey in a Significant, Reintroduced Lahontan Cutthroat Trout Population

AbstractLahontan Cutthroat Trout (LCT) Oncorhynchus clarkii henshawi have experienced some of the most marked reductions in abundance and distribution among Cutthroat Trout subspecies. The population of LCT in Pyramid Lake, Nevada has returned from the brink of extirpation, and although it is highly managed via stocking, the population is thriving and has recently started to reproduce naturally. Our objectives were to determine (1) whether predator and prey remain tightly coupled, (2) whether LCT are food limited, and (3) the status of the LCT population with regard to the potential prey‐based contemporary carrying capacity. We used a multifaceted approach, including intensive field sampling of fish, bioenergetics modeling, cohort reconstruction, and comparisons of prey availability to consumption. We estimated that the average population of LCT in Pyramid Lake is 1.2 million, average annual stocking is 650,000, and the number of fish angled ranges from 5,000 to 14,000 per year, with a 90% release rate. Driven by seasonal and size variation in consumption, individual annual consumption by LCT varied from 667 to 992 g/year for small LCT (200–400 mm TL) and from 2,388 to 3,057 g/year for large LCT (>400 mm TL). Lahontan Cutthroat Trout are consuming, on average, 14–63% of the standing crop of Tui Chub Siphateles bicolor annually, indicating that LCT are currently not exceeding their prey‐based carrying capacity. The LCT in Pyramid Lake remain tightly coupled to their primary native prey, Tui Chub, despite considerable changes to the ecosystem; therefore, managing for a robust population of LCT translates largely to managing for forage fish. This supply‐versus‐demand issue is of particular concern for Pyramid Lake given that the density of Tui Chub may be declining concordant with declining lake elevation. Given the conservation importance of this LCT population, careful monitoring is critical; however, “predation inertia” indicates that effective short‐term management in response to fluctuations in forage fishes is likely possible.

Bulk and pipe wall chlorine degradation kinetics in three water distribution systems

ABSTRACT This paper presents a methodology to estimate free residual chlorine concentrations (FRCC) in full-scale water distribution system (WDS) using different degradation kinetics according to pipe material, age and diameter. Intensive field sampling campaigns and laboratory-scale tests were carried out to estimate total and bulk volume FRCC in three WDS. Bulk kinetic constants were estimated for water temperatures typical of different seasons in the Quebec City area (Canada). With field-measured FRCC at all sampling sites and an estimation of travel times through the use of a hydraulic model, total, bulk and pipe wall kinetic constants were obtained with ranges of 10.2 to 130.4, 4.1 to 43.8 and 8.5 to 114.9 10−3/h, respectively. Pipe wall kinetics tend to dominate the total degradation process for older grey and ductile cast-iron pipes, followed by newer ductile iron pipes and then PVC and pre-stressed concrete pipes (mostly installed from 1990). The developed methodology and results will be useful to improve the prediction of FRCC through hydraulic and water quality modelling.

A Self-Powered, Real-Time, LoRaWAN IoT-Based Soil Health Monitoring System

Typical soil health assessment requires intensive field sampling and laboratory analysis. Although this approach yields accurate results, it can be costly and labor intensive and not suitable for continuous tracking of soil properties. Advances in soil sensor and wireless technologies are poised to replace physical sampling and offline measurement with in-field monitoring. This article reports the development, deployment, and validation of an Internet-of-Things (IoT) system for continuous monitoring of soil health. The end nodes of the proposed system, called soil health monitoring units (SHMUs), are solar powered and can be installed on a field for extended periods of time. Each SHMU transmits soil temperature, moisture, electrical conductivity, carbon dioxide (CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ), and geolocation data wirelessly using long-range wide-area network (LoRaWAN) radio technology. Data are received by a LoRaWAN gateway, which uploads it to a server for long-term storage and analysis. Users can view acquired data through a Web-based dashboard. The following significant experiments were carried out to validate the developed system: 1) a network consisting of eight SHMUs was deployed at an agricultural field site for several weeks and soil health metrics were analyzed using the soil health dashboard; 2) the flexibility of the system was demonstrated by the addition of an extra CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> sensor allowing an additional variable directly linked to soil health to be recorded; 3) a wireless communication range of 3422 m was estimated at a transmission power of 10 dBm by deploying the developed system on a large field; 4) the average current consumption of a SHMU (including its associated sensors) was estimated to be 13 mA, at this rate, the onboard Li-ion battery is able to sustain a SHMU for several days; and 5) a 7 cm ×6.5 cm solar panel was able to fully charge the onboard battery in 14 days while supplying power to the SHMU.

Slope Stability Analysis for Deterministic Shallow Landslide Assessment and Mapping: A Case Study in Kibawe, Bukidnon

The slope’s stability in mountainous or hilly region is significantly important for the safety and protection of the people and the environment. Intensive field sampling was carried out in the study sites at Kibawe, Bukidnon, Philippines and soil samples were subjected to laboratory tests. The study applied the deterministic method through slope stability analysis to calculate the factor of safety (FOS) for landslide assessment. It also used Geographic Information System (GIS) particularly the ArcGIS software for FOS mapping. The results revealed that the study sites have mostly inorganic but highly expansive fine-grained soils. The values of the FOS varied in each steady-state condition. For fully-saturated and dry conditions, the values ranged from 1.54-9.98 and 1.94-12.66, respectively. For partially-saturated condition where m = 0.75, m = 0.5 and m = 0.25, the values of FOS ranged from 1.65-10.65; 1.74-11.32; and 1.84- 11.99, respectively. In general, the FOS values signified that the study area was stable against sliding; however, there was a considerable decrease in FOS values when the slope changed from completely dry to fully-saturated condition. The created set of FOS maps lay out a visual impression and the variation of slope stability condition in the study area. The findings provide a baseline reference study for the area’s slope stability that is essential in planning or further assessment of the study area. Furthermore, this can be directly used by the local government for land-use planning and future development.

Core and Differentially Abundant Bacterial Taxa in the Rhizosphere of Field Grown Brassica napus Genotypes: Implications for Canola Breeding.

Modifying the rhizosphere microbiome through targeted plant breeding is key to harnessing positive plant–microbial interrelationships in cropping agroecosystems. Here, we examine the composition of rhizosphere bacterial communities of diverse Brassica napus genotypes to identify: (1) taxa that preferentially associate with genotypes, (2) core bacterial microbiota associated with B. napus, (3) heritable alpha diversity measures at flowering and whole growing season, and (4) correlation between microbial and plant genetic distance among canola genotypes at different growth stages. Our aim is to identify and describe signature microbiota with potential positive benefits that could be integrated in B. napus breeding and management strategies. Rhizosphere soils of 16 diverse genotypes sampled weekly over a 10-week period at single location as well as at three time points at two additional locations were analyzed using 16S rRNA gene amplicon sequencing. The B. napus rhizosphere microbiome was characterized by diverse bacterial communities with 32 named bacterial phyla. The most abundant phyla were Proteobacteria, Actinobacteria, and Acidobacteria. Overall microbial and plant genetic distances were highly correlated (R = 0.65). Alpha diversity heritability estimates were between 0.16 and 0.41 when evaluated across growth stage and between 0.24 and 0.59 at flowering. Compared with a reference B. napus genotype, a total of 81 genera were significantly more abundant and 71 were significantly less abundant in at least one B. napus genotype out of the total 558 bacterial genera. Most differentially abundant genera were Proteobacteria and Actinobacteria followed by Bacteroidetes and Firmicutes. Here, we also show that B. napus genotypes select an overall core bacterial microbiome with growth-stage-related patterns as to how taxa joined the core membership. In addition, we report that sets of B. napus core taxa were consistent across our three sites and 2 years. Both differential abundance and core analysis implicate numerous bacteria that have been reported to have beneficial effects on plant growth including disease suppression, antifungal properties, and plant growth promotion. Using a multi-site year, temporally intensive field sampling approach, we showed that small plant genetic differences cause predictable changes in canola microbiome and are potential target for direct and indirect selection within breeding programs.