Detection Rate of Bird Species and What It Depends on: Tips for Field Surveys

Bird counting inevitably suffers from imperfect detection, which varies across species, habitats, period of the day, and seasons. Although various modeling techniques have recently been developed to account for this phenomenon, the biological basis of natural variation in detection remains insufficiently known. This study examined the bird species’ detection rate throughout the day, considering their body mass and diet type, concerning the environment and weather characteristics. Species detection rates were significantly affected by the number of individuals of that species but were unrelated to body mass. Overall, species with the highest detection rate were Corn bunting, Blackbird, European robin, House sparrow and Common chiffchaff. Granivores-insectivores and insectivores showed significant differences in detection rates throughout the day among habitats, with higher detection rates in grasslands during the afternoon. Insectivores showed higher detection rates in farmland during midday (warmest time of the day). Granivores, omnivores and scavengers did not show changes in detection rates in different day periods. Such patterns in daily detection rates were significant even when considering abundance and total species richness in each community. Finally, cloudiness was unrelated to the overall detection rate of birds, while temperature and wind affected detection rates in some guilds. Our findings provide some advice for choosing a suitable ornithological sampling method by considering the avian communities composition in combination with the type of environment, the diet of bird species, and the period of the day.

Comparing species detection success between molecular markers in DNA metabarcoding of coastal macroinvertebrates

DNA metabarcoding has great potential to improve marine biomonitoring programs by providing a rapid and accurate assessment of species composition in zoobenthic communities. However, some methodological improvements are still required, especially regarding failed detections, primers efficiency and incompleteness of databases. Here we assessed the efficiency of two different marker loci (COI and 18S) and three primer pairs in marine species detection through DNA metabarcoding of the macrozoobenthic communities colonizing three types of artificial substrates (slate, PVC and granite), sampled between 3 and 15 months of deployment. To accurately compare detection success between markers, we also compared the representativeness of the detected species in public databases and revised the reliability of the taxonomic assignments. Globally, we recorded extensive complementarity in the species detected by each marker, with 69% of the species exclusively detected by either 18S or COI. Individually, each of the three primer pairs recovered, at most, 52% of all species detected on the samples, showing also different abilities to amplify specific taxonomic groups. Most of the detected species have reliable reference sequences in their respective databases (82% for COI and 72% for 18S), meaning that when a species was detected by one marker and not by the other, it was most likely due to faulty amplification, and not by lack of matching sequences in the database. Overall, results showed the impact of marker and primer applied on species detection ability and indicated that, currently, if only a single marker or primer pair is employed in marine zoobenthos metabarcoding, a fair portion of the diversity may be overlooked.

Towards harmonization of DNA metabarcoding for monitoring marine macrobenthos: the effect of technical replicates and pooled DNA extractions on species detection

DNA-based monitoring methods are potentially faster and cheaper compared to traditional morphological benthic identification. DNA metabarcoding involves various methodological choices which can introduce bias leading to a different outcome in biodiversity patterns. Therefore, it is important to harmonize DNA metabarcoding protocols to allow comparison across studies and this requires a good understanding of the effect of methodological choices on diversity estimates. This study investigated the impact of DNA and PCR replicates on the detection of macrobenthos species in locations with high, medium and low diversity. Our results show that two to three DNA replicates were needed in locations with a high and medium diversity to detect at least 80% of the species found in the six DNA replicates, while three to four replicates were needed in the location with low diversity. In contrast to general belief, larger body size or higher abundance of the species in a sample did not increase its detection prevalence among DNA replicates. However, rare species were less consistently detected across all DNA replicates of the location with high diversity compared to locations with less diversity. Our results further show that pooling of DNA replicates did not significantly alter diversity patterns, although a small number of rare species was lost. Finally, our results confirm high variation in species detection between PCR replicates, especially for the detection of rare species. These results contribute to create reliable, time and cost efficient metabarcoding protocols for the characterization of macrobenthos.

Reinforcement of Environmental DNA Based Methods (Sensu stricto) in Biodiversity Monitoring and Conservation: A Review

Recently developed non-invasive environmental DNA-based (eDNA) techniques have enlightened modern conservation biology, propelling the monitoring/management of natural populations to a more effective and efficient approach, compared to traditional surveys. However, due to rapid-expansion of eDNA, confusion in terminology and collection/analytical pipelines can potentially jeopardize research progression, methodological standardization, and practitioner adoption in several ways. Present investigation reflects the developmental progress of eDNA (sensu stricto) including highlighting the successful case studies in conservation management. The eDNA technique is successfully relevant in several areas of conservation research (invasive/conserve species detection) with a high accuracy and authentication, which gradually upgrading modern conservation approaches. The eDNA technique related bioinformatics (e.g., taxon-specific-primers MiFish, MiBird, etc.), sample-dependent methodology, and advancement of sequencing technology (e.g., oxford-nanopore-sequencing) are helping in research progress. The investigation shows that the eDNA technique is applicable largely in (i) early detection of invasive species, (ii) species detection for conservation, (iii) community level biodiversity monitoring, (iv) ecosystem health monitoring, (v) study on trophic interactions, etc. Thus, the eDNA technique with a high accuracy and authentication can be applicable alone or coupled with traditional surveys in conservation biology. However, a comprehensive eDNA-based monitoring program (ecosystem modeling and function) is essential on a global scale for future management decisions.

Variable detectability and El-Niño associations with riparian snakes in Sabah, Malaysian Borneo

Although snake populations are suffering numerous local declines, determining the scale of these declines is problematic due to the elusive nature of snakes. Determining the factors associated with species detection is therefore essential for quantifying disturbance effects on populations. From 2017 to 2019, we assessed the detectability associations of five river-associated snake species and all snake detections in general within two logging concessions in Sabah, Malaysian Borneo. Data collected from both stream transects and visual encounter surveys at 47 stream sites were incorporated into an occupancy-modelling framework to determine the climatological, temporal and survey distance associations with species detection probability. Detection probability of riparian snake species was significantly associated with humidity, month (2 spp. each), survey distance and total rainfall over 60 days (1 spp. each). Pooled snake species detectability was significantly positively associated with transect distance and the 2019 El-Niño year, whilst yearly pooled snake species detections in stream transects spiked during El-Niño (2017 = 2.05, 2018 = 2.47, 2019 = 4.5 snakes per km). This study provides new insights into the detectability of riparian rainforest snakes and suggests that future studies should account for short-term (climatological and temporal) and long-term (El-Niño) factors associated with detection probability when surveying and assessing snake populations.

A Performance Comparison and Enhancement of Animal Species Detection in Images with Various R-CNN Models

Object detection is one of the vital and challenging tasks of computer vision. It supports a wide range of applications in real life, such as surveillance, shipping, and medical diagnostics. Object detection techniques aim to detect objects of certain target classes in a given image and assign each object to a corresponding class label. These techniques proceed differently in network architecture, training strategy and optimization function. In this paper, we focus on animal species detection as an initial step to mitigate the negative impacts of wildlife–human and wildlife–vehicle encounters in remote wilderness regions and on highways. Our goal is to provide a summary of object detection techniques based on R-CNN models, and to enhance the performance of detecting animal species in accuracy and speed, by using four different R-CNN models and a deformable convolutional neural network. Each model is applied on three wildlife datasets, results are compared and analyzed by using four evaluation metrics. Based on the evaluation, an animal species detection system is proposed.