Reliable Distribution Data Research Articles

The riverscape on a chip: High-throughput qPCR enables basin-wide fishery assessments

To achieve reliable detection of environmental DNA from multiple species, a method which combines the specificity of single-taxon assays with the broad taxonomic coverage of metabarcoding is needed. High-throughput quantitative PCR (HT-qPCR) has emerged as one such method that holds particular promise for ecological applications. Here, we present the development and validation of a HT-qPCR biochip (i.e., biochip) protocol for a suite of western North American fishes with high cultural, economic, and ecological significance. Coupling this biochip with systematically distributed eDNA samples collected by citizen scientists, we evaluated the distribution of multiple species throughout a large river basin in the U.S. Pacific Northwest. Patterns of detection using the biochip were comparable to those using single-taxon qPCR (ST-qPCR; mean concordance = 0.917), despite the biochip using 90% less DNA per taxon and reducing costs by an estimated 40%. Comparisons between biochip results and distributions derived from conventional methods demonstrate that this approach not only offers more reliable and high-resolution distribution data for these species but also achieves this more efficiently than traditional sampling methods.

A new threshold selection method for species distribution models with presence-only data: Extracting the mutation point of the P/E curve by threshold regression.

Selecting thresholds to convert continuous predictions of species distribution models proves critical for many real-world applications and model assessments. Prevalent threshold selection methods for presence-only data require unproven pseudo-absence data or subjective researchers' decisions. This study proposes a new method, Boyce-Threshold Quantile Regression (BTQR), to determine thresholds objectively without pseudo-absence data. We summarize that the mutation point is a typical shape feature of the predicted-to-expected (P/E) curve after reviewing relevant articles. Analysis based on source-sink theory suggests that this mutation point may represent a transition in habitat types and serve as an appropriate threshold. Threshold regression is introduced to accurately locate the mutation point. To validate the effectiveness of BTQR, we used four virtual species of varying prevalence and a real species with reliable distribution data. Six different species distribution models were employed to generate continuous suitability predictions. BTQR and nine other traditional methods transformed these continuous outputs into binary results. Comparative experiments show that BTQR has advantages in terms of accuracy, applicability, and consistency over the existing methods.

Environmental DNA Detects Remaining Populations of Endangered Stream Salmon (Sichuan Taimen: Hucho bleekeri Kimura Salmonidae) in the Qinling Mountains

Sichuan taimen (Hucho bleekeri Salmonidae) populations are declining, and the status of remnant populations in the Qinling Mountains is poorly known. In this study, eDNA and creel netting were used to estimate the distributions of Sichuan taimen in two upper tributaries of the Hanjiang River. A qPCR assay was applied to detect the eDNA of H. bleekeri, and the presence of Sichuan taimen in the Taibai River, but not in the Xushui River, was confirmed. Sampling during summer achieved a relatively higher detection rate. The utility of eDNA techniques for detecting low-density Sichuan taimen was demonstrated in intricate stream ecosystems. The eDNA method can increase the efficiency of the management of endangered freshwater species, such as Sichuan taimen, by providing reliable distribution data.

The taxonomy and conservation status of Isoetes (Isoetaceae; Lycopodiopsida) in India

ABSTRACT In many cases over the years the diversity of Isoetes in India has been defined by inconsistent morphological analyses and questionable data. This has resulted in substantial confusion, dramatically different taxonomic interpretations and a low level of global acceptance. That in turn has prevented the reliable determination of conservation priorities. The present study reviews the most reliable morphological, distributional and cytological Indian data available with techniques and standards that have guided successful taxonomic investigations of Isoetes elsewhere in the world. This results in the enumeration of nine readily distinguishable species for India. One named hybrid is also discussed as is the probable occurrence of other unnamed hybrids. All Indian Isoetes species except I. coromandelina subsp. coromandelina are endemic. Two possible but unresolved taxa are also discussed. A clearer determination of the highest national priorities for Isoetes conservation has resulted. Most Indian taxa are rare, some qualifying as Endangered and others probably being extinct. Suggestions for conservation strategies and actions to protect and sustain vulnerable Isoetes species and their habitats are offered.

Designing an optimal sampling strategy for a national level invasive alien plant assessment: A South African case study

The availability of accurate spatial distribution data of invasive alien plant (IAP) species is a shortcoming in most programmes and strategies that deal with biological invasions. Such data are required at the relevant spatial and temporal scales to assist decision making ranging from high level policy to local level implementation and the assessment of biological invasion status as part of the monitoring of the range and abundance of invasive species’ indicators. Because the complete inventories of IAPs are not feasible due to budget constraints, sampling of a representative proportion is necessary. The selection of an adequate sampling design is critical to ensure cost effective assessments that will also result in accurate and reliable IAP distribution data across extensive and environmental varying landscapes. This paper presents the development of an objective and scientifically accurate monitoring system at a regional level for major invaders for an extensive area such as South Africa by comparing three standard statistical sampling strategies, namely, simple random, systematic and proportionally stratified sampling. The comparison is based on the prediction accuracy of the three designs and their sensitivity to sample size. Sampling was repeated in simulations for each of the sampling designs based on an incremental increase in sampling intensity and compared to an actual field survey result. A generalised linear model was used to predict how accurately the distribution and density of species were reflected by the different sampling designs. Comparisons show that the proportionally stratified design provides the most precise results, followed by systematic and finally random sampling. Further sampling simulations showed that a proportionally stratified design at a national level requires approximately 61 000 sample points to be able to detect IAP species’ distribution and distinguish between IAP density levels of five percent and more with a maximum coefficient of variation of 15% at a specified cost threshold of R10 million (600000 €).

Mapping the drivers of parasitic weed abundance at a national scale: a new approach applied to Striga asiatica in the mid‐west of Madagascar

AbstractThe parasitic weed genus Striga causes huge losses to crop production in sub‐Saharan Africa, estimated to be in excess of $7 billion per year. There is a paucity of reliable distribution data for Striga; however, such data are urgently needed to understand current drivers, better target control efforts, as well as to predict future risks. To address this, we developed a methodology to enable rapid, large‐scale monitoring of Striga populations. We used this approach to uncover the factors that currently drive the abundance and distribution of Striga asiatica in Madagascar. Two long‐distance transects were established across the middle‐west region of Madagascar in which S. asiatica abundance in fields adjacent to the road was estimated. Management, crop structure and soil data were also collected. Analysis of the data suggests that crop variety, companion crop and previous crop were correlated with Striga density. A positive relationship between within‐field Striga density and the density of the nearest neighbouring fields indicates that spatial configuration and connectivity of suitable habitats is also important in determining Striga spread. Our results demonstrate that we are able to capture distribution and management data for Striga density at a landscape scale and use this to understand the ecological and agronomic drivers of abundance. The importance of crop varieties and cropping patterns is significant, as these are key socio‐economic elements of Malagasy cropping practices. Therefore, they have the potential to be promoted as readily available control options, rather than novel technologies requiring introduction.

Plant distribution data for the Czech Republic integrated in the Pladias database

Research on the Czech flora has a long tradition and yielded a large number of records on the occurrence of plants. Several independent electronic databases were established during the last three decades in order to collect and manage these records. However, this fragmentation and the different characteristics of each database strongly limit the utilization and analyses of plant distribution data. Solving these problems was one of the aims of the Centre of Excellence PLADIAS (Plant Diversity Analysis and Synthesis. 2014-2018). which is also the source of the name of the central database of the project: Pladias - Database of the Czech Flora and Vegetation (www.pladias.cz). We developed an occurrence module as a part of the Pladias database in order to integrate species occurrence data on vascular plants in the Czech Republic for use in pure and applied research. In this paper, we present a description of the structure of this database, data handling and validation, creation of distribution maps based on critically evaluated records as well as descriptions of the original databases and explorative analyses of spatiotemporal and taxonomic coverage of the integrated occurrence data. So far we have integrated more than 13 million records of almost 5 thousand taxa (species, subspecies, varieties and hybrids). which came from five large national databases. seven regional projects and records collected within the PLADIAS project. The Pladias database is now the largest set of data on vascular plant occurrence in the Czech Republic, which is subject to continuous quality control. Analyses of this database pointed to differences in spatial and taxonomic coverage of the source datasets. However, it also showed that the targeted effort of experts focused on validating existing records, as well as the collection of new data is still necessary in order to obtain reliable distribution data for individual species.

The development of real-time PCR assays for species and sex identification of three sympatric deer species from noninvasive samples

Reliably identifying the species occupying an area is an essential part of any wildlife conservation study or sustainable management plan, especially when dealing with a harvested species such as deer. Traditional deer monitoring techniques such as faecal standing crop or faecal accumulation rate estimates cannot accurately identify deer species based on pellet morphology where more than one deer species is present. This study presents real-time PCR assays for the identification of fallow deer (Dama dama), red deer (Cervus elaphus), and sika deer (Cervus nippon) species from pellet samples, and real-time PCR sex determining assays to amplify the ZFX and SRY gene of all three deer species. These assays successfully identified tissue and faecal pellets of all three species with no cross species amplification. Sex determination was successful from both tissue and faecal pellets samples, with the assays amplifying as little as 4 pg of nDNA, making them suitable for use with the often poor quality and low quantity DNA found in noninvasive samples. Application of these assays will provide reliable species presence and distribution data not possible with traditional methods as well as valuable information on sex ratios which can inform sustainable wildlife management and harvest strategies.

ConR: An R package to assist large-scale multispecies preliminary conservation assessments using distribution data.

The Red List Categories and the accompanying five criteria developed by the International Union for Conservation of Nature (IUCN) provide an authoritative and comprehensive methodology to assess the conservation status of organisms. Red List criterion B, which principally uses distribution data, is the most widely used to assess conservation status, particularly of plant species. No software package has previously been available to perform large‐scale multispecies calculations of the three main criterion B parameters [extent of occurrence (EOO), area of occupancy (AOO) and an estimate of the number of locations] and provide preliminary conservation assessments using an automated batch process. We developed ConR, a dedicated R package, as a rapid and efficient tool to conduct large numbers of preliminary assessments, thereby facilitating complete Red List assessment. ConR (1) calculates key geographic range parameters (AOO and EOO) and estimates the number of locations sensu IUCN needed for an assessment under criterion B; (2) uses this information in a batch process to generate preliminary assessments of multiple species; (3) summarize the parameters and preliminary assessments in a spreadsheet; and (4) provides a visualization of the results by generating maps suitable for the submission of full assessments to the IUCN Red List. ConR can be used for any living organism for which reliable georeferenced distribution data are available. As distributional data for taxa become increasingly available via large open access datasets, ConR provides a novel, timely tool to guide and accelerate the work of the conservation and taxonomic communities by enabling practitioners to conduct preliminary assessments simultaneously for hundreds or even thousands of species in an efficient and time‐saving way.

AR-RRNS: Configurable reliable distributed data storage systems for Internet of Things to ensure security

Benefits of Internet of Things and cloud–fog-edge computing are associated with the risks of confidentiality, integrity, and availability related with the loss of information, denial of access for a long time, information leakage, conspiracy and technical failures. In this article, we propose a configurable, reliable, and confidential distributed data storage scheme with the ability to process encrypted data and control results of computations. Our system utilizes Redundant Residue Number System (RRNS) with new method of error correction codes and secret sharing schemes. We introduce the concept of an approximate value of a rank of a number (AR), which allows us to reduce the computational complexity of the decoding from RNS to binary representation, and size of the coefficients. Based on the properties of the approximate value and arithmetic properties of RNS, we introduce AR-RRNS method for error detection, correction, and controlling computational results. We provide a theoretical basis to configure probability of information loss, data redundancy, speed of encoding and decoding to cope with different objective preferences, workloads, and storage properties. Theoretical analysis shows that by appropriate selection of RRNS parameters, the proposed scheme allows not only increasing safety, reliability, and reducing an overhead of data storage, but also processing of encrypted data.

An irreplaceability map for Tasmanian priority plant species

There is a strong need to map the relative importance of areas for nature conservation both inside and outside reserves, given increasing development pressures and ongoing threats to biodiversity. Nature conservation importance has typically been established using iterative or optimising systems which select areas to achieve explicit targets. Irreplaceability has been a concept used in many of these analyses. We calculated rarity-weighted richness values (irreplaceability scores) from reliable distributional data for all vascular plant species of conservation importance in one square kilometre grid cells covering the State of Tasmania, Australia. The spatial patterns of scores on the irreplaceability index were not strongly related to data collection intensity. Thus, our scores were reliable for most parts of the State, irrespective of survey effort, except where there were no or little survey data. Irreplaceability scores were high in places with concentrations of local endemics, on mountains with persistent snow cover, along the northern part of the coast and on the Bass Strait islands.

Downscaling of AMSR-E soil moisture with MODIS products using machine learning approaches

Passive microwave remotely sensed soil moisture products, such as Advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR-E) data, have been routinely used to monitor global soil moisture patterns. However, they are often limited in their ability to provide reliable spatial distribution data for soil moisture due to their coarse spatial resolutions. In this study, three machine learning approaches—random forest, boosted regression trees, and Cubist—were examined for the downscaling of AMSR-E soil moisture (25 × 25 km) data over two regions (South Korea and Australia) with different climatic characteristics using moderate resolution imaging spectroradiometer products (1 km), including surface albedo, land surface temperature (LST), Normalized Difference Vegetation Index, Enhanced Vegetation Index, Leaf Area Index, and evapotranspiration (ET). Results showed that the random forest approach was superior to the other machine learning models for downscaling AMSR-E soil moisture data in terms of the correlation coefficient [r = 0.71/0.84 (South Korea/Australia) for random forest, 0.75/0.77 for boosted regression trees, and 0.70/0.61 for Cubist] and root-mean-square error (RMSE = 0.049/0.057, 0.052/0.078, and 0.051/0.063, respectively) through cross-validation. The ET and LST were identified as the most influential among the six input parameters when estimating AMSR-E soil moisture for South Korea, while ET, albedo, and LST were very useful for Australia. In overall, the downscaled soil moisture with 1 km resolution yielded a higher correlation with in situ observations than the original AMSR-E soil moisture data. The latter appeared higher than the downscaled data in forested areas, possibly due to the overestimation of soil moisture by passive microwave sensors over forests, which implies that downscaling can mitigate such overestimation of soil moisture.

Citizen science data as an efficient tool for mapping protected saproxylic beetles

Global change imposes rapid assessments to obtain reliable and updated distribution data to implement conservation measures. This task is undoubtedly unaffordable for numerous invertebrate species, both in terms of time and economic resources, because they are often elusive, detectable life stages are present for a restricted time and ecological data are scarce. Citizen science might be able to provide a large number of records and these data might facilitate the evaluation of extinction risks. Large saproxylic beetles represent an ideal group to assess the potential of citizen science to map distributions on a large scale geographic distribution. The data presented were collected during a citizen science program developed within the LIFE Project “Monitoring of Insects with Public Participation”, which used a website and a mobile app to involve citizens. We selected three pan European species protected under the Habitats Directive: Lucanus cervus, Morimus asper/funereus and Rosalia alpina, and we compared the data gathered by the citizen science project with distributional data from the official national species inventory. For all species we found a low overlap of occupied cells and the integration of the two datasets resulted in an increase in the distributional ranges of up to one third. Furthermore, taking into account the time frame of data collection, we found that the extent of occurrence obtained in 10years of records present in the national dataset was comparable to data collected in only two years of the citizen science data project. Similar results were obtained for the estimates of spatial parameters for the IUCN Red List assessment. Our study shows the potential and the efficacy of citizen science projects as rapid tools to provide reliable distributional data for neglected species of high conservation priority.

Distributional modeling of Mantophasmatodea (Insecta: Notoptera): a preliminary application and the need for future sampling

Insects are the most diverse animal group, with remarkable and critical ecological roles, but the understanding of the taxonomic diversity, distribution, and biology of the overwhelming majority of lineages remains in its incipient stages. One means of addressing the lack of reliable distributional data for many groups is to predict probable records using species distribution models (SDMs), and this is particularly useful for generally undersampled and rarely encountered groups. Here, we use existing distribution records for species and genera of Mantophasmatodea (Insecta: Notoptera) to generate SDMs and discuss their utility for future sampling efforts. We used two different algorithms (Envelope Score and MaxEnt) to generate potential distributions and indicate areas for future field surveys for some of the genera and species of Mantophasmatodea with at least 10 unique occurrence records. The models showed good predictive capability (true skill statistics >0.9), with different taxa exhibiting variables, endemic ranges largely in southern and southwestern Africa, areas under considerable risk from climate change. South and Southwest Africa are the best places to focus sampling efforts for empirical data on current occurrences and any possible future shifts, as well as the potential for discovery of previously unknown species. These results also highlight the need to study the smaller and lesser known lineages of invertebrates that may not represent charismatic target taxa but nonetheless harbor unique life histories with unknown ecological roles.

Phylogeography and systematics ofPyramidula(Pulmonata: Pyramidulidae) in the eastern Alps: still a taxonomic challenge

The rock-dwelling land snail Pyramidula pusilla was analysed genetically and morphologically with an emphasis on its eastern Alpine distributional area. Genetic variation and phylogeographic patterns were inferred by mitochondrial cytochrome c oxidase subunit 1 gene sequences (650 bp), while shell variability was investigated by shell measurements and landmark analyses. The phylogenetic analyses revealed two clades in Austria (clades 3 and 4), of which one also contained individuals from Turkey. Other samples originating from the Balkan region (Albania, Greece) and Turkey were well separated in the tree, forming two distinct sister clades (clades 1 and 2). Concerning clades 3 and 4 there is no clear geographical pattern and both clades cooccur at several (11) sites; the same is true for clades 1 and 2. There are also morphological differences between clades: clades 1 and 2 differ from the other clades in size as well as shape, whereas clade 3 differs from clade 4 only in size. Considering all results combined, they imply that the samples analysed might actually represent more than one species and that, contrary to former assumptions, two species of Pyramidula may occur within the eastern Alps. However, comprehensive taxonomic conclusions cannot yet be drawn, for reasons connected with insufficiently justified species assignment: (1) high morphological variation within clades, (2) lack of clear diagnostic information in original descriptions, causing a lack of reliable distributional data and (3) lack of data over the whole distributional range of the genus. Analyses of ncDNA (e.g. microsatellites) to quantify the extent of gene flow, as well as breeding experiments between different clades, could help to clarify the delimitation of species. Despite these taxonomic uncertainties, the results provide insights on Pyramidula within the eastern Alpine region, suggesting that it survived the Pleistocene oscillations without dramatic bottlenecks and is capable of fast expansion to (re)populate formerly glaciated areas.

Latitudinal species diversity gradient of mushroom corals off eastern Australia: a baseline from the 1970s

Based on a study of mushroom coral species of eastern Australia, a decrease in species richness can be discerned from north to south. Eastern Australia, including the Great Barrier Reef (GBR), is one of only few coral reef areas suitable for studies on large-scale latitudinal biodiversity patterns. Such patterns may help to recognize biogeographic boundaries and factors regulating biodiversity. Owing to the eastern Australian long coastline, such studies are a logistic challenge unless reliable distribution data are already available, as in museum collections. A large coral collection predominantly sampled from this area in the 1970s is present in the Museum of Tropical Queensland (MTQ). The scleractinian family Fungiidae (mushroom corals), representing about 10% of Indo-Pacific reef coral species, was selected as proxy. It was represented by 1289 specimens belonging to 34 species with latitudinal ranges between 09°09′S and 31°28′S. The fauna of the northernmost reefs in the Gulf of Papua and the Torres Strait, and north of the Great Barrier Reef Marine Park (GBRMP), was represented by a maximum of 30 fungiids. From here a southward decline in species number was observed, down to Lord Howe Island with only one species. Together with previous records, the mushroom coral fauna of eastern Australia consists of 37 species, which is more diverse than hitherto known and similar to numbers found in the Coral Triangle. Future field surveys in the GBR should specifically target rarely known species, which are mainly small and found at depths >25 m. In the light of global climate change, they may also show whether previously recorded species are still present and whether their latitudinal ranges have shifted, using the 1970s records as a baseline.

Monitoring the near-extinct European weather loach in Denmark based on environmental DNA from water samples

The European weather loach (Misgurnus fossilis) represents one of many European freshwater fishes in decline. Efficient monitoring is essential if conservation efforts are to be successful, but due to the species’ cryptic biology, traditional monitoring methods currently in use are inefficient, time consuming and likely prone to non-detection error. Here, we investigate the usefulness of environmental DNA (eDNA) monitoring as an alternative or supplementary method for surveying the Danish weather loach population, which is presumed to consist primarily of a single group of no more than 50 individuals. In 2008, the majority of historical Danish localities were surveyed, using traditional fishing techniques. We then applied eDNA methods to a number of these, as well as other potential localities. We successfully detected the weather loach at multiple sites in the single known remaining locality; a result that was later confirmed when local managers caught eight live specimens. Furthermore, the eDNA method indicated presence of the weather loach in another historical locality, where the species has not been observed since 1995. At the remaining localities, weather loach eDNA was not detected, providing further evidence for its absence. Importantly, the eDNA survey required less effort in person-hours and lower costs than the traditional fishing survey. This study confirms that eDNA monitoring is a valid supplement to traditional monitoring methods currently applied to monitor rare freshwater fishes. We propose that by providing reliable distribution data at lower cost and limited effort, the eDNA method can allow for increased management efficiency of endangered freshwater species such as the European weather loach.

Distributed Agent-Based Computing in Material-Embedded Sensor Network Systems With the Agent-on-Chip Architecture

Distributed material-embedded systems like sensor networks integrated in sensorial materials require new data processing and communication architectures. Reliability and robustness of the entire heterogeneous environment in the presence of node, sensor, link, data processing, and communication failures must be offered, especially concerning limited service of material-embedded systems after manufacturing. In this paper, multiagent systems with state-based mobile agents are used for computing in unreliable mesh-like networks of nodes, usually consisting of a single microchip, introducing a novel design approach for reliable distributed and parallel data processing on embedded systems with static resources. An advanced high-level synthesis approach is used to map the agent behavior to multiagent systems implementable entirely on microchip-level supporting agent-on-chip (AoC) processing architectures. The agent behavior, interaction, and mobility are fully integrated on the microchip using a reconfigurable pipelined communicating process architecture implemented with finite-state machines and register-transfer logic. The agent processing architecture is related to Petri Net token processing. A reconfiguration mechanism of the agent processing system achieves some degree of agent adaptation and algorithmic selection. The agent behavior, interaction, and mobility features are modeled and specified with an activity-based agent behavior programming language. Agent interaction and communication is provided by a simple tuple-space database implemented on node level and signals providing remote inter-node level communication and interaction.

Optimized secure and reliable distributed data storage scheme and performance evaluation in unattended WSNs

Unattended Wireless Sensor Networks (UWSNs), characterized by the absence of real-time communication between sensors and sinks, impose sensors to retain data till the next visit of a mobile sink to off-load their data. In such networks, if a sensor is compromised, data accumulated in the sensor are exposed to attackers. In addition, by holding the secret key of the compromised sensor, attackers can also learn post-compromise data accumulated by the sensor. Furthermore, once sensors stop working due to, for instance, node crash or battery depletion, all the accumulated data will be lost. In this paper, we propose a secure and reliable data distribution scheme that addresses these challenges. Detailed analysis shows that our scheme can provide forward secrecy, probabilistic backward secrecy and data reliability. To further improve probabilistic backward secrecy and data reliability, a constrained optimization data distribution scheme is also proposed. Detailed analysis and simulation results show the superiority of the proposed scheme in comparison with several existing schemes developed for UWSNs.

Calumma vohibola, a new chameleon species (Squamata: Chamaeleonidae) from the littoral forests of eastern Madagascar

We describe Calumma vohibola sp. nov., a morphologically distinct chameleon species of the Calumma nasutum species group from littoral forest fragments of the north-central east coast of Madagascar. Males and females of this species differ from all other species of the Calumma nasutum group by an almost absent rostral appendage, by a characteristic stress colouration in the female consisting of a dark reddish ground colouration with many irregular light blue spots, and by significant sequence divergence in the mitochondrial ND2 gene (10.5–19.4% pairwise distance) and no haplotype sharing in the nuclear C-mos gene compared with other members of the C. nasutum group. A molecular survey of C. nasutum populations occurring near the type locality of the new species reveals an extraordinarily high genetic diversity within this morphologically conservative chameleon group. We suspect that C. vohibola might be restricted to a rather small and fragmented distribution range within the last littoral forest fragments along the coast. Owing to the unsolved taxonomic situation of the C. nasutum group, no reliable distribution data of any member of this group are available at present, and hence we cannot ascertain whether the extent of occurrence of C. vohibola is indeed as restricted as suspected. Intensive surveys and field studies are necessary to clarify the distribution limits of this new species and to assess its conservation status reliably.