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Scientists are increasingly using volunteer efforts of citizen scientists to classify images captured by motion‐activated trail cameras. The rising popularity of citizen science reflects its potential to engage the public in conservation science and accelerate processing of the large volume of images generated by trail cameras. While image classification accuracy by citizen scientists can vary across species, the influence of other factors on accuracy is poorly understood. Inaccuracy diminishes the value of citizen science derived data and prompts the need for specific best‐practice protocols to decrease error. We compare the accuracy between three programs that use crowdsourced citizen scientists to process images online: Snapshot Serengeti, Wildwatch Kenya, and AmazonCam Tambopata. We hypothesized that habitat type and camera settings would influence accuracy. To evaluate these factors, each photograph was circulated to multiple volunteers. All volunteer classifications were aggregated to a single best answer for each photograph using a plurality algorithm. Subsequently, a subset of these images underwent expert review and were compared to the citizen scientist results. Classification errors were categorized by the nature of the error (e.g., false species or false empty), and reason for the false classification (e.g., misidentification). Our results show that Snapshot Serengeti had the highest accuracy (97.9%), followed by AmazonCam Tambopata (93.5%), then Wildwatch Kenya (83.4%). Error type was influenced by habitat, with false empty images more prevalent in open‐grassy habitat (27%) compared to woodlands (10%). For medium to large animal surveys across all habitat types, our results suggest that to significantly improve accuracy in crowdsourced projects, researchers should use a trail camera set up protocol with a burst of three consecutive photographs, a short field of view, and determine camera sensitivity settings based on in situ testing. Accuracy level comparisons such as this study can improve reliability of future citizen science projects, and subsequently encourage the increased use of such data. We show that the accuracy levels of trail‐camera image classification by citizen scientists are affected by habitat type and trail‐camera set up. By comparing the accuracy results from three camera trap citizen science projects, we found that setting trail cameras to capture 3 images per burst, testing the appropriate camera sensitivity, and a shorter field of view resulting from dense vegetation may significantly improve citizen scientist image classification accuracy when compared to classifications by experts.

Background In the speciation continuum, the strength of reproductive isolation varies, and species boundaries are blurred by gene flow. Interbreeding among giraffe ( Giraffa spp.) in captivity is known, and anecdotal reports of natural hybrids exist. In Kenya, Nubian ( G. camelopardalis camelopardalis ), reticulated ( G. reticulata ), and Masai giraffe sensu stricto ( G. tippelskirchi tippelskirchi ) are parapatric, and thus, the country might be a melting pot for these taxa. We analyzed 128 genomes of wild giraffe, 113 newly sequenced, representing these three taxa. Results We found varying levels of Nubian ancestry in 13 reticulated giraffe sampled across the Laikipia Plateau most likely reflecting historical gene flow between these two lineages. Although comparatively weaker signs of ancestral gene flow and potential mitochondrial introgression from reticulated into Masai giraffe were also detected, estimated admixture levels between these two lineages are minimal. Importantly, contemporary gene flow between East African giraffe lineages was not statistically significant. Effective population sizes have declined since the Late Pleistocene, more severely for Nubian and reticulated giraffe. Conclusions Despite historically hybridizing, these three giraffe lineages have maintained their overall genomic integrity suggesting effective reproductive isolation, consistent with the previous classification of giraffe into four species.

ContextReduced connectivity across grassland ecosystems can impair their functional heterogeneity and negatively impact large herbivore populations. Maintaining landscape connectivity across human-dominated rangelands is therefore a key conservation priority.ObjectiveIntegrate data on large herbivore occurrence and species richness with analyses of functional landscape connectivity to identify important areas for maintaining or restoring connectivity for large herbivores.MethodsThe study was conducted on a landscape with a mosaic of multiple land uses in Laikipia County, Kenya. We used occupancy estimates for four herbivore species [African elephant (Loxodonta africana), reticulated giraffe (Giraffa reticulata), plains zebra (Equus quagga), and Grevy’s zebra (Equus grevyi)] and species richness estimates derived from aerial surveys to create resistance surfaces to movement for single species and a multi-species assemblage, respectively. We validated single-species resistance surfaces using telemetry data. We used circuit theory and least cost-path analyses to model linkage zones across the landscape and prioritize areas for connectivity restoration.ResultsResistance layers approximated the movements of our focal species. Results for single-species and multi-species connectivity models were highly correlated (rp > 0.9), indicating similar spatial patterns of functional connectivity between individual species and the larger herbivore assemblage. We identified critical linkage zones that may improve permeability to large-herbivore movements.ConclusionOur analysis highlights the utility of aerial surveys in modeling landscape connectivity and informing conservation management when animal movement data are scarce. Our results can guide management decisions, providing valuable information to evaluate the trade-offs between improving landscape connectivity and safeguarding livelihoods with electrified fences across rangelands.

In the speciation continuum the strength of reproductive isolation varies, and species boundaries are blurred by gene flow. Interbreeding among giraffe (Giraffa spp.) in captivity is known and anecdotal reports of natural hybrids exist. In Kenya, Nubian (G. camelopardalis camelopardalis), reticulated (G. reticulata), and Masai giraffe sensu stricto (G. tippelskirchi tippelskirchi) are parapatric, and thus the country might be a melting pot for these taxa. We analyzed 128 genomes of wild giraffe, 113 newly sequenced, representing these three taxa. We found varying levels of Nubian ancestry in 13 reticulated giraffe sampled across the Laikipia Plateau most likely reflecting historical gene flow between these two lineages. Although comparatively weaker signs of ancestral gene flow and potential mitochondrial introgression from reticulated into Masai giraffe were also detected, estimated admixture levels between these two lineages are minimal. Importantly, contemporary gene flow between East African giraffe lineages was not statistically significant. Effective population sizes have declined since the Late Pleistocene, more severely for Nubian and reticulated giraffe. Despite historically hybridizing, these three giraffe lineages have maintained their overall genomic integrity suggesting effective reproductive isolation, consistent with the previous classification of giraffe into four species.

Animals moving through landscapes need to strike a balance between finding sufficient resources to grow and reproduce while minimizing encounters with predators. Because encounter rates are determined by the average distance over which directed motion persists, this trade-off should be apparent in individuals' movement. Using GPS data from 1,396 individuals across 62 species of terrestrial mammals, we show how predators maintained directed motion ~7 times longer than for similarly-sized prey, revealing how prey species must trade off search efficiency against predator encounter rates. Individual search strategies were also modulated by resource abundance, with prey species forced to risk higher predator encounter rates when resources were scarce. These findings highlight the interplay between encounter rates and resource availability in shaping broad patterns mammalian movement strategies.Competing Interest StatementThe authors have declared no competing interest.Footnotes* https://github.com/NoonanM/BallisticMotion