Combining ALS and UAV to derive the height of \textit{Araucaria angustifolia

Quantitative data obtained from native forests is costly and time-consuming. Thus, alternative measurement methods need to be developed to provide reliable information, especially in Atlantic Rain Forests. In this study we evaluated the hypothesis that the combination of an Airborne Laser Scanner (ALS) and an Unmanned Aerial Vehicle (UAV) can provide accurate quantitative information on tree height, volume, and aboveground biomass of the Araucaria angustifolia species. The study was carried out in Atlantic Rain forest fragments in southern Brazil. We tested and evaluated 3 digital canopy height model (CHM) scenarios: 1) CHM derived from ALS models; 2) CHM derived from UAV models; and 3) CHM from a combined ALS digital terrain model and UAV digital surface model. The height value at each tree coordinate was extracted from the pixel in the three evaluated scenarios and compared with the field measured values. ALS and UAV+ALS obtained RMSE% of 6.38 and 12.82 for height estimates, while UAV was 49.91%. Volume and aboveground biomass predictions are more accurate by ALS and UAV+ALS, while the UAV produced biased estimates. Since the ALS is currently used, periodic monitoring can be carried out by a combination of active (ALS) and passive (UAV) sensors.

Novel deep learning hybrid models (CNN-GRU and DLDL-RF) for the susceptibility classification of dust sources in the Middle East: a global source

Dust storms have many negative consequences, and affect all kinds of ecosystems, as well as climate and weather conditions. Therefore, classification of dust storm sources into different susceptibility categories can help us mitigate its negative effects. This study aimed to classify the susceptibility of dust sources in the Middle East (ME) by developing two novel deep learning (DL) hybrid models based on the convolutional neural network-gated recurrent unit (CNN-GRU) model, and the dense layer deep learning-random forest (DLDL-RF) model. The Dragonfly algorithm (DA) was used to identify the critical features controlling dust sources. Game theory was used for the interpretability of the DL model's output. Predictive DL models were constructed by dividing datasets randomly into train (70%) and test (30%) groups, six statistical indicators being then applied to assess the DL hybrid model performance for both datasets (train and test). Among 13 potential features (or variables) controlling dust sources, seven variables were selected as important and six as non-important by DA, respectively. Based on the DLDL-RF hybrid model - a model with higher accuracy in comparison with CNN-GRU-23.1, 22.8, and 22.2% of the study area were classified as being of very low, low and moderate susceptibility, whereas 20.2 and 11.7% of the area were classified as representing high and very high susceptibility classes, respectively. Among seven important features selected by DA, clay content, silt content, and precipitation were identified as the three most important by game theory through permutation values. Overall, DL hybrid models were found to be efficient methods for prediction purposes on large spatial scales with no or incomplete datasets from ground-based measurements.

Evaluation of a COVID-19 Vaccine Campaign and SARS-CoV-2 Infection and Mortality Among Adults Aged 60 Years And Older in a Middle-Income Country

IMPORTANCE

Although there are reports of COVID-19 vaccine implementation in real-world populations, these come from high-income countries or from experience with messenger RNA technology vaccines. Data on outcomes of vaccine deployment in low- or middle-income countries are lacking.

OBJECTIVE

To assess whether the pragmatic application of the 3 COVID-19 vaccines available in Argentina, 2 of which have no reports of evaluation in real-world settings to date, were associated with a reduction in morbidity, all-cause mortality, and mortality due to COVID-19.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used individual and ecological data to explore outcomes following vaccination with rAd26-rAd5, ChAdOx1, and BBIBP-CorV. To correct for differences in exposure times, results are shown using incidence density per 100 000 person-days from the start of the vaccination campaign (December 29, 2020) to the occurrence of an event or the end of follow-up (May 15, 2021). Participants included 663 602 people aged at least 60 years residing in the city of Buenos Aires, Argentina. Statistical analysis was performed from June 1 to June 15, 2021.

MAIN OUTCOMES AND MEASURES

Diagnosis of COVID-19 confirmed by reverse transcription-polymerase chain reaction, death from all causes, and death within 30 days of a diagnosis of COVID-19. Poisson regression models were fitted to estimate associations with all 3 outcomes.

RESULTS

Among 663 602 residents of the city of Buenos Aires included in the study, 540 792 (81.4%) were vaccinated with at least 1 dose, with 457 066 receiving 1 dose (mean [SD] age, 74.5 (8.9) years; 61.5% were female [n = 281 284]; 68.0% [n = 310 987] received the rAd26-rAd5 vaccine; 29.5% [n = 135 036] received ChAdOx1; 2.4% [n = 11 043] received BBIBP-CorV) and 83 726 receiving 2 doses (mean [SD] age, 73.4 [6.8] years; 63.5% were female [n = 53 204]). The incidence density of confirmed COVID-19 was 36.25 cases/100 000 person-days (95% CI, 35.80-36.70 cases/100 000 person-days) among those who did not receive a vaccine, 19.13 cases/100 000 person-days (95% CI, 18.63-19.62 cases/100 000 person-days) among those who received 1 dose, and 4.33 cases/100 000 person-days (95% CI, 3.85-4.81 cases/100 000 person-days) among those who received 2 doses. All-cause mortality was 11.74 cases/100 000 person-days (95% CI, 11.51-11.96 cases/100 000 person-days), 4.01 cases/100 000 person-days (95% CI, 3.78-4.24 cases/100 000 person-days) and 0.40 cases/100 000 person-days (95% CI, 0.26-0.55 cases/100 000 person-days). COVID-19-related-death rate was 2.31 cases/100 000 person-days (95% CI, 2.19-2.42 cases/100 000 person-days), 0.59 cases/100 000 person-days (95% CI, 0.50-0.67 cases/100 000 person-days), and 0.04 cases/100 000 person-days (95% CI, 0.0-0.09 cases/100 000 person-days) among the same groups. A 2-dose vaccination schedule was associated with an 88.1% (95% CI, 86.8%-89.2%) reduction in documented infection, 96.6% (95% CI, 95.3%-97.5%) reduction in all-cause death, and 98.3% (95% CI, 95.3%-99.4%) reduction in COVID-19-related death. A single dose was associated with a 47.2% (95% CI, 44.2%-50.1%) reduction in documented infection, 65.8% (95% CI, 61.7%-69.5%) reduction in all-cause death, and 74.5% (95% CI, 66%-80.8%) reduction in COVID-19-related death.

CONCLUSIONS AND RELEVANCE

This study found that within the first 5 months after the start of the vaccination campaign, vaccination was associated with a significant reduction in COVID-19 infection as well as a reduction in mortality.

Fin whale acoustic populations present in New Zealand waters: Description of song types, occurrence and seasonality using passive acoustic monitoring

Southern fin whales (Balaenoptera physalus) are known to migrate from the Antarctic to mid-latitudes during winter for breeding, but the occurrence and distribution of this species is not well known in the waters around New Zealand. The 'doublet' calls are one of the main calls emitted specifically by fin whales and repeated in a regular pattern, which make the acoustic detection of these calls relevant to detect the presence of fin whales. Using a signal processing algorithm to detect 'doublet' calls emitted by fin whales, we studied the occurrence, characteristics and seasonality of these 'doublet' calls in two regions around New Zealand; Cook Strait in 2016/2017 and offshore Gisborne in 2014/2015. The call detection procedure consisted of binarization of the spectrogram and a cross-correlation between the binarized spectrogram and a template of binarized 'doublet' calls spectrogram. A binarization threshold for the data spectrograms and a cross correlation threshold were then determined through multiple trials on a training dataset and a Receiver Operating Characteristics (ROC) curve. Fin whale 'doublet' calls occurred on the east side of New Zealand's Cook Strait during austral winter, specifically in June 2017 and offshore Gisborne in June-August 2014. No 'doublet' calls were detected on the west side of Cook Strait. The 'doublet' calls' Inter-Note Interval (INI) was similar in both datasets. However, there was a difference in alternation of the mean frequency for both HF components of 'doublet' calls in Cook Strait and Gisborne. As the song types were compared with those previously described in the literature, our findings suggest that some fin whales wintering in New Zealand waters may be part of a broader 'acoustic population' whose range extends west to southern Australia and south to Antarctica.

Deep-sea biodiversity at the extremes of the Salas y Gómez and Nazca ridges with implications for conservation

The Salas y Gómez and Nazca ridges are underwater mountain chains that stretch across 2,900 km in the southeastern Pacific and are recognized for their high biodiversity value and unique ecological characteristics. Explorations of deep-water ecosystems have been limited in this region, and elsewhere globally. To characterize community composition of mesophotic and deep-sea demersal fauna at seamounts in the region, we conducted expeditions to Rapa Nui (RN) and Salas y Gómez (SyG) islands in 2011 and Desventuradas Islands in 2013. Remote autonomous baited-cameras were used to conduct stationary video surveys between 150-1,850 m at RN/SyG (N = 20) and 75-2,363 m at Desventuradas (N = 27). Individual organisms were identified to the lowest possible taxonomic level and relative abundance was quantified with the maximum number of individuals per frame. Deployments were attributed with associated environmental variables (temperature, salinity, dissolved oxygen, nitrate, silicate, phosphate, chlorophyll-a, seamount age, and bathymetric position index [BPI]). We identified 55 unique invertebrate taxa and 66 unique fish taxa. Faunal community structure was highly dissimilar between and within subregions both for invertebrate (p < 0.001) and fish taxa (p = 0.022). For fishes, dogfish sharks (Squalidae) accounted for the greatest dissimilarity between subregions (18.27%), with mean abundances of 2.26 ± 2.49 at Desventuradas, an order of magnitude greater than at RN/SyG (0.21 ± 0.54). Depth, seamount age, broad-scale BPI, and nitrate explained most of the variation in both invertebrate (R2 = 0.475) and fish (R2 = 0.419) assemblages. Slightly more than half the deployments at Desventuradas (N = 14) recorded vulnerable marine ecosystem taxa such as corals and sponges. Our study supports mounting evidence that the Salas y Gómez and Nazca ridges are areas of high biodiversity and high conservation value. While Chile and Peru have recently established or proposed marine protected areas in this region, the majority of these ridges lie outside of national jurisdictions and are under threat from overfishing, plastic pollution, climate change, and potential deep-sea mining. Given its intrinsic value, this region should be comprehensively protected using the best available conservation measures to ensure that the Salas y Gómez and Nazca ridges remain a globally unique biodiversity hotspot.

Maximizing regional biodiversity requires a mosaic of protection levels

Protected areas are the flagship management tools to secure biodiversity from anthropogenic impacts. However, the extent to which adjacent areas with distinct protection levels host different species numbers and compositions remains uncertain. Here, using reef fishes, European alpine plants, and North American birds, we show that the composition of species in adjacent Strictly Protected, Restricted, and Non-Protected areas is highly dissimilar, whereas the number of species is similar, after controlling for environmental conditions, sample size, and rarity. We find that between 12% and 15% of species are only recorded in Non-Protected areas, suggesting that a non-negligible part of regional biodiversity occurs where human activities are less regulated. For imperiled species, the proportion only recorded in Strictly Protected areas reaches 58% for fishes, 11% for birds, and 7% for plants, highlighting the fundamental and unique role of protected areas and their environmental conditions in biodiversity conservation.

This study shows that the dissimilarity in species composition between sites with different levels of protection is consistently high, suggesting that adjacent and connected areas with different protection levels host very dissimilar species assemblages.

Recognizing and counting Dendrocephalus brasiliensis (Crustacea: Anostraca) cysts using deep learning

The Dendrocephalus brasiliensis, a native species from South America, is a freshwater crustacean well explored in conservational and productive activities. Its main characteristics are its rusticity and resistance cysts production, in which the hatching requires a period of dehydration. Independent of the species utilization nature, it is essential to manipulate its cysts, such as the counting using microscopes. Manually counting is a difficult task, prone to errors, and that also very time-consuming. In this paper, we propose an automatized approach for the detection and counting of Dendrocephalus brasiliensis cysts from images captured by a digital microscope. For this purpose, we built the DBrasiliensis dataset, a repository with 246 images containing 5141 cysts of Dendrocephalus brasiliensis. Then, we trained two state-of-the-art object detection methods, YOLOv3 (You Only Look Once) and Faster R-CNN (Region-based Convolutional Neural Networks), on DBrasiliensis dataset in order to compare them under both cyst detection and counting tasks. Experiments showed evidence that YOLOv3 is superior to Faster R-CNN, achieving an accuracy rate of 83,74%, R² of 0.88, RMSE (Root Mean Square Error) of 3.49, and MAE (Mean Absolute Error) of 2.24 on cyst detection and counting. Moreover, we showed that is possible to infer the number of cysts of a substrate, with known weight, by performing the automated counting of some of its samples. In conclusion, the proposed approach using YOLOv3 is adequate to detect and count Dendrocephalus brasiliensis cysts. The DBrasiliensis dataset can be accessed at: https://doi.org/10.6084/m9.figshare.13073240.

Long-term monitoring of margays (Leopardus wiedii): Implications for understanding low detection rates

Population assessments of wide-ranging, cryptic, terrestrial mammals rely on camera trap surveys. While camera trapping is a powerful method of detecting presence, it is difficult distinguishing rarity from low detection rate. The margay (Leopardus wiedii) is an example of a species considered rare based on its low detection rates across its range. Although margays have a wide distribution, detection rates with camera traps are universally low; consequently, the species is listed as Near Threatened. Our 12-year camera trap study of margays in protected broadleaf forest in Belize suggests that while margays have low detection rate, they do not seem to be rare, rather that they are difficult to detect with camera traps. We detected a maximum of 187 individuals, all with few or no recaptures over the years (mean = 2.0 captures/individual ± SD 2.1), with two-thirds of individuals detected only once. The few individuals that were recaptured across years exhibited long tenures up to 9 years and were at least 10 years old at their final detection. We detected multiple individuals of both sexes at the same locations during the same survey, suggesting overlapping ranges with non-exclusive territories, providing further evidence of a high-density population. By studying the sparse annual datasets across multiple years, we found evidence of an abundant margay population in the forest of the Cockscomb Basin, which might have been deemed low density and rare, if studied in the short term. We encourage more long-term camera trap studies to assess population status of semi-arboreal carnivore species that have hitherto been considered rare based on low detection rates.

eDNA metabarcoding as a biomonitoring tool for marine protected areas

Monitoring of marine protected areas (MPAs) is critical for marine ecosystem management, yet current protocols rely on SCUBA-based visual surveys that are costly and time consuming, limiting their scope and effectiveness. Environmental DNA (eDNA) metabarcoding is a promising alternative for marine ecosystem monitoring, but more direct comparisons to visual surveys are needed to understand the strengths and limitations of each approach. This study compares fish communities inside and outside the Scorpion State Marine Reserve off Santa Cruz Island, CA using eDNA metabarcoding and underwater visual census surveys. Results from eDNA captured 76% (19/25) of fish species and 95% (19/20) of fish genera observed during pairwise underwater visual census. Species missed by eDNA were due to the inability of MiFish 12S barcodes to differentiate species of rockfishes (Sebastes, n = 4) or low site occupancy rates of crevice-dwelling Lythrypnus gobies. However, eDNA detected an additional 23 fish species not recorded in paired visual surveys, but previously reported from prior visual surveys, highlighting the sensitivity of eDNA. Significant variation in eDNA signatures by location (50 m) and site (~1000 m) demonstrates the sensitivity of eDNA to address key questions such as community composition inside and outside MPAs. Results demonstrate the utility of eDNA metabarcoding for monitoring marine ecosystems, providing an important complementary tool to visual methods.

Ecosystem engineers drive differing microbial community composition in intertidal estuarine sediments

Intertidal systems are complex and dynamic environments with many interacting factors influencing biochemical characteristics and microbial communities. One key factor are the actions of resident fauna, many of which are regarded as ecosystem engineers because of their bioturbation, bioirrigation and sediment stabilising activities. The purpose of this investigation was to elucidate the evolutionary implications of the ecosystem engineering process by identifying, if any, aspects that act as selection pressures upon microbial communities. A mesocosm study was performed using the well characterised intertidal ecosystem engineers Corophium volutator, Hediste diversicolor, and microphytobenthos, in addition to manual turbation of sediments to compare effects of bioturbation, bioirrigation and stabilisation. A range of sediment functions and biogeochemical gradients were measured in conjunction with 16S rRNA sequencing and diatom taxonomy, with downstream bacterial metagenome function prediction, to identify selection pressures that incited change to microbial community composition and function. Bacterial communities were predominantly Proteobacteria, with the relative abundance of Bacteroidetes, Alphaproteobacteria and Verrucomicrobia being partially displaced by Deltaproteobacteria, Acidobacteria and Chloroflexi as dissolved oxygen concentration and redox potential decreased. Bacterial community composition was driven strongly by biogeochemistry; surface communities were affected by a combination of sediment functions and overlying water turbidity, and subsurface communities by biogeochemical gradients driven by sediment reworking. Diatom communities were dominated by Nitzschia laevis and Achnanthes sp., and assemblage composition was influenced by overlying water turbidity (manual or biogenic) rather than direct infaunal influences such as grazing.

Long-term changes in kelp forests in an inner basin of the Salish Sea

Kelp forests form an important biogenic habitat that responds to natural and human drivers. Global concerns exist about threats to kelp forests, yet long-term information is limited and research suggests that trends are geographically distinct. We examined distribution of the bull kelp Nereocystis luetkeana over 145 years in South Puget Sound (SPS), a semi-protected inner basin in a fjord estuary complex in the northeast Pacific Ocean. We synthesized 48 historical and modern Nereocystis surveys and examined presence/absence within 1-km segments along 452 km of shoreline. Compared to the earliest baseline in 1878, Nereocystis extent in 2017 decreased 63%, with individual sub-basins showing up to 96% loss. Losses have persisted for decades, across a range of climate conditions. In recent decades, Nereocystis predominantly occurred along shorelines with intense currents and mixing, where temperature and nutrient concentrations did not reach thresholds for impacts to Nereocystis performance, and high current speeds likely excluded grazers. Losses predominated in areas with elevated temperature, lower nutrient concentrations, and relatively low current velocities. The pattern of long-term losses in SPS contrasts with stability in floating kelp abundance during the last century in an area of the Salish Sea with greater wave exposure and proximity to oceanic conditions. These findings support the hypothesis that kelp beds along wave-sheltered shorelines exhibit greater sensitivity to environmental stressors. Additionally, shorelines with strong currents and deep-water mixing may provide refugia within sheltered systems.

Seasonal influence of snow conditions on Dall's sheep productivity in Wrangell-St Elias National Park and Preserve

Dall's sheep (Ovis dalli dalli) are endemic to alpine areas of sub-Arctic and Arctic northwest America and are an ungulate species of high economic and cultural importance. Populations have historically experienced large fluctuations in size, and studies have linked population declines to decreased productivity as a consequence of late-spring snow cover. However, it is not known how the seasonality of snow accumulation and characteristics such as depth and density may affect Dall's sheep productivity. We examined relationships between snow and climate conditions and summer lamb production in Wrangell-St Elias National Park and Preserve, Alaska over a 37-year study period. To produce covariates pertaining to the quality of the snowpack, a spatially-explicit snow evolution model was forced with meteorological data from a gridded climate re-analysis from 1980 to 2017 and calibrated with ground-based snow surveys and validated by snow depth data from remote cameras. The best calibrated model produced an RMSE of 0.08 m (bias 0.06 m) for snow depth compared to the remote camera data. Observed lamb-to-ewe ratios from 19 summers of survey data were regressed against seasonally aggregated modelled snow and climate properties from the preceding snow season. We found that a multiple regression model of fall snow depth and fall air temperature explained 41% of the variance in lamb-to-ewe ratios (R2 = .41, F(2,38) = 14.89, p<0.001), with decreased lamb production following deep snow conditions and colder fall temperatures. Our results suggest the early establishment and persistence of challenging snow conditions is more important than snow conditions immediately prior to and during lambing. These findings may help wildlife managers to better anticipate Dall's sheep recruitment dynamics.

Integrative assessment of the ecological risk of heavy metals in a South American estuary under human pressures

Biomonitoring of heavy metal pollution through the use of biomarkers could be a difficult task since the organisms' physiological changes could shift regarding natural factors (i.e., the season of the year) and due to the anthropogenic pressures of the environment. In the Southwest Atlantic Ocean, where most industrial and developing countries are settled, it is essential to address these concerns to generate information for the stakeholders and monitoring programs that aim to use biochemical biomarkers as early warning signals to detect heavy metal pollution. The present study intended to determinate the heavy metal concentrations in sediments and the hepatopancreas of the crab species Neohelice granulata as well as the ecological risk through the use of biomarkers and geochemical indices in sites with different anthropogenic pressures of the Bahía Blanca estuary (SW Atlantic Ocean) during the warm and cold season. The results showed low to moderate heavy metal pollution in the sediments by Cu with possible effects on the biota in a site with sewage waters' discharges. Except for GST that was explained by Cd, the biomarkers employed were not useful to assess spatial heavy metal pollution, and they might be ruled out by physiological seasonal variations rather than anthropogenic constraints, or another type of pollutants in the area.

Incorporating Biological Traits into Conservation Strategies

Implementation of marine conservation strategies, such as increasing the numbers, extent, and effectiveness of protected areas (PAs), can help achieve conservation and restoration of ocean health and associated goods and services. Despite increasing recognition of the importance of including aspects of ecological functioning in PA design, the physical characteristics of habitats and simple measures of species diversity inform most PA designations. Marine and terrestrial ecologists have recently been using biological traits to assess community dynamics, functioning, and vulnerability to anthropogenic impacts. Here, we explore potential trait-based marine applications to advance PA design. We recommend strategies to integrate biological traits into (a) conservation objectives (e.g., by assessing and predicting impacts and vulnerability), (b) PA spatial planning (e.g., mapping ecosystem functions and functional diversity hot spots), and (c) time series monitoring protocols (e.g., using functional traits to detect recoveries). We conclude by emphasizing the need for pragmatic tools to improve the efficacy of spatial planning and monitoring efforts.

Assessment of fishery resources using environmental DNA: Small yellow croaker (Larimichthys polyactis) in East China Sea

Species distribution monitoring and biomass assessment are crucial for fishery management and resource conservation. However, traditional methods such as motor trawling are costly and less effective than the novel environmental DNA (eDNA) approach. This study employs eDNA approach to investigate horizontal and vertical distributions of small yellow croaker (Larimichthys polyactis), an economically important species, in the East China Sea. The analysis of 171 eDNA samples collected from 44 stations using the species-specific primers and Taqman probe suggests a presence of small yellow croaker at 28 sampling layers in 44 stations. Significant differences in croaker eDNA concentrations were revealed among sampling stations and layers, consistent with previous findings through motor-trawl capture offshore and nearshore ichthyoplakton surveys, indicating small yellow croaker exhibits strong regional distribution and layer preference. In addition, we found a high eDNA concentration of small yellow croaker in the surface waters beyond the motor-trawl prohibition line, which confirms spawning grounds have been expanded from nearshore to offshore areas. Such expansion of spawning grounds could be a response by small yellow croaker to stressors such as overfishing, climate change, and nearshore environment contamination. To identify environmental variables potentially associated with small yellow croaker presence and absence, we conducted a correlation analysis between eDNA concentration and environmental variables, and the results provide a guideline for further investigation of fishery resources in the future. In conclusion, this study demonstrates the power of the eDNA approach in monitoring small yellow croaker at extensive geographic scales. The developed protocols and the findings are expected to assist in long-term monitoring and protection programs and benefit sustainable fishery in small yellow croaker.

Habitat suitability maps for juvenile tri-spine horseshoe crabs in Japanese intertidal zones: A model approach using unmanned aerial vehicles and the Structure from Motion technique

The tri-spine horseshoe crab, Tachypleus tridentatus, is a threatened species that inhabits coastal areas from South to East Asia. A Conservation management system is urgently required for managing its nursery habitats, i.e., intertidal flats, especially in Japan. Habitat suitability maps are useful in drafting conservation plans; however, they have rarely been prepared for juvenile T. tridentatus. In this study, we examined the possibility of constructing robust habitat suitability models (HSMs) for juveniles based on topographical data acquired using unmanned aerial vehicles and the Structure from Motion (UAV-SfM) technique. The distribution data of the juveniles in the Tsuyazaki and Imazu intertidal flats from 2017 to 2019 were determined. The data were divided into a training dataset for HSM construction and three test datasets for model evaluation. High accuracy digital surface models were built for each region using the UAV-SfM technique. Normalized elevation was assessed by converting the topographical models that consider the tidal range in each region, and the slope was calculated based on these models. Using the training data, HSMs of the juveniles were constructed with normalized elevation and slope as the predictor variables. The HSMs were evaluated using the test data. The results showed that HSMs exhibited acceptable discrimination performance for each region. Habitat suitability maps were built for the juveniles in each region, and the suitable areas were estimated to be approximately 6.1 ha of the total 19.5 ha in Tuyazaki, and 3.7 ha of the total 7.9 ha area in Imazu. In conclusion, our findings support the usefulness of the UAV-SfM technique in constructing HSMs for juvenile T. tridentatus. The monitoring of suitable habitat areas for the juveniles using the UAV-SfM technique is expected to reduce survey costs, as it can be conducted with fewer investigators over vast intertidal zones within a short period of time.

Substrate stabilisation and small structures in coral restoration: State of knowledge, and considerations for management and implementation

Coral reef ecosystems are under increasing pressure from local and regional stressors and a changing climate. Current management focuses on reducing stressors to allow for natural recovery, but in many areas where coral reefs are damaged, natural recovery can be restricted, delayed or interrupted because of unstable, unconsolidated coral fragments, or rubble. Rubble fields are a natural component of coral reefs, but repeated or high-magnitude disturbances can prevent natural cementation and consolidation processes, so that coral recruits fail to survive. A suite of interventions have been used to target this issue globally, such as using mesh to stabilise rubble, removing the rubble to reveal hard substrate and deploying rocks or other hard substrates over the rubble to facilitate recruit survival. Small, modular structures can be used at multiple scales, with or without attached coral fragments, to create structural complexity and settlement surfaces. However, these can introduce foreign materials to the reef, and a limited understanding of natural recovery processes exists for the potential of this type of active intervention to successfully restore local coral reef structure. This review synthesises available knowledge about the ecological role of coral rubble, natural coral recolonisation and recovery rates and the potential benefits and risks associated with active interventions in this rapidly evolving field. Fundamental knowledge gaps include baseline levels of rubble, the structural complexity of reef habitats in space and time, natural rubble consolidation processes and the risks associated with each intervention method. Any restoration intervention needs to be underpinned by risk assessment, and the decision to repair rubble fields must arise from an understanding of when and where unconsolidated substrate and lack of structure impair natural reef recovery and ecological function. Monitoring is necessary to ascertain the success or failure of the intervention and impacts of potential risks, but there is a strong need to specify desired outcomes, the spatial and temporal context and indicators to be measured. With a focus on the Great Barrier Reef, we synthesise the techniques, successes and failures associated with rubble stabilisation and the use of small structures, review monitoring methods and indicators, and provide recommendations to ensure that we learn from past projects.

A simulation study of the use of temporal occupancy for identifying core and transient species

Transient species, which do not maintain self-sustaining populations in a system where they are observed, are ubiquitous in nature and their presence often impacts the interpretation of ecological patterns and processes. Identifying transient species from temporal occupancy, the proportion of time a species is observed at a given site over a time series, is subject to classification errors as a result of imperfect detection and source-sink dynamics. We use a simulation-based approach to assess how often errors in detection or classification occur in order to validate the use of temporal occupancy as a metric for inferring whether a species is a core or transient member of a community. We found that low detection increases error in the classification of core species, while high habitat heterogeneity and high detection increase error in classification of transient species. These findings confirm that temporal occupancy is a valid metric for inferring whether a species can maintain a self-sustaining population, but imperfect detection, low abundance, and highly heterogeneous landscapes may yield high misclassification rates.

New 3D measurements of large redwood trees for biomass and structure

Large trees are disproportionately important in terms of their above ground biomass (AGB) and carbon storage, as well as their wider impact on ecosystem structure. They are also very hard to measure and so tend to be underrepresented in measurements and models of AGB. We show the first detailed 3D terrestrial laser scanning (TLS) estimates of the volume and AGB of large coastal redwood Sequoia sempervirens trees from three sites in Northern California, representing some of the highest biomass ecosystems on Earth. Our TLS estimates agree to within 2% AGB with a species-specific model based on detailed manual crown mapping of 3D tree structure. However TLS-derived AGB was more than 30% higher compared to widely-used general (non species-specific) allometries. We derive an allometry from TLS that spans a much greater range of tree size than previous models and so is potentially better-suited for use with new Earth Observation data for these exceptionally high biomass areas. We suggest that where possible, TLS and crown mapping should be used to provide complementary, independent 3D structure measurements of these very large trees.

Investigating effects of soil chemicals on density of small mammal bioindicators using spatial capture-recapture models

Monitoring the ecological impacts of environmental pollution and the effectiveness of remediation efforts requires identifying relationships between contaminants and the disruption of biological processes in populations, communities, or ecosystems. Wildlife are useful bioindicators, but traditional comparative experimental approaches rely on a staunch and typically unverifiable assumption that, in the absence of contaminants, reference and contaminated sites would support the same densities of bioindicators, thereby inferring direct causation from indirect data. We demonstrate the utility of spatial capture-recapture (SCR) models for overcoming these issues, testing if community density of common small mammal bioindicators was directly influenced by soil chemical concentrations. By modeling density as an inhomogeneous Poisson point process, we found evidence for an inverse spatial relationship between Peromyscus density and soil mercury concentrations, but not other chemicals, such as polychlorinated biphenyls, at a site formerly occupied by a nuclear reactor. Although the coefficient point estimate supported Peromyscus density being lower where mercury concentrations were higher (β = –0.44), the 95% confidence interval overlapped zero, suggesting no effect was also compatible with our data. Estimated density from the most parsimonious model (2.88 mice/ha; 95% CI = 1.63–5.08), which did not support a density-chemical relationship, was within the range of reported densities for Peromyscus that did not inhabit contaminated sites elsewhere. Environmental pollution remains a global threat to biodiversity and ecosystem and human health, and our study provides an illustrative example of the utility of SCR models for investigating the effects that chemicals may have on wildlife bioindicator populations and communities.

A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis

Visual analysis of complex fish habitats is an important step towards sustainable fisheries for human consumption and environmental protection. Deep Learning methods have shown great promise for scene analysis when trained on large-scale datasets. However, current datasets for fish analysis tend to focus on the classification task within constrained, plain environments which do not capture the complexity of underwater fish habitats. To address this limitation, we present DeepFish as a benchmark suite with a large-scale dataset to train and test methods for several computer vision tasks. The dataset consists of approximately 40 thousand images collected underwater from 20 habitats in the marine-environments of tropical Australia. The dataset originally contained only classification labels. Thus, we collected point-level and segmentation labels to have a more comprehensive fish analysis benchmark. These labels enable models to learn to automatically monitor fish count, identify their locations, and estimate their sizes. Our experiments provide an in-depth analysis of the dataset characteristics, and the performance evaluation of several state-of-the-art approaches based on our benchmark. Although models pre-trained on ImageNet have successfully performed on this benchmark, there is still room for improvement. Therefore, this benchmark serves as a testbed to motivate further development in this challenging domain of underwater computer vision.

Performance of spatial capture-recapture models with repurposed data: Assessing estimator robustness for retrospective applications

Advancements in statistical ecology offer the opportunity to gain further inferences from existing data with minimal financial cost. Spatial capture-recapture (SCR) models extend traditional capture-recapture models to incorporate spatial position of capture and enable direct estimation of animal densities across a region of interest. The additional inferences provided are both ecologically interesting and valuable for decision making, which has resulted in traditional capture-recapture data being repurposed using SCR. Yet, many capture-recapture studies were not designed for SCR and the limitations of repurposing data from such studies are rarely assessed in practice. We used simulation to evaluate the robustness of SCR for retrospectively estimating large mammal densities over a variety of scenarios using repurposed capture-recapture data collected by an asymmetrical sampling grid and covering a broad spatial extent in a heterogenous landscape. We found performance of SCR models fit using repurposed data simulated from the existing grid was not robust, but instead bias and precision of density estimates varied considerably among simulations scenarios. For example, while the smallest relatives bias of density estimates was 3%, it ranged by 14 orders of magnitude among scenarios and was most strongly influenced by detection parameters. Our results caution against the casual repurposing of non-spatial capture-recapture data using SCR and demonstrate the importance of using simulation to assessing model performance during retrospective applications.

Undirected singing rate as a non-invasive tool for welfare monitoring in isolated male zebra finches

Research on the songbird zebra finch (Taeniopygia guttata) has advanced our behavioral, hormonal, neuronal, and genetic understanding of vocal learning. However, little is known about the impact of typical experimental manipulations on the welfare of these birds. Here we explore whether the undirected singing rate can be used as an indicator of welfare. We tested this idea by performing a post hoc analysis of singing behavior in isolated male zebra finches subjected to interactive white noise, to surgery, or to tethering. We find that the latter two experimental manipulations transiently but reliably decreased singing rates. By contraposition, we infer that a high-sustained singing rate is suggestive of successful coping or improved welfare in these experiments. Our analysis across more than 300 days of song data suggests that a singing rate above a threshold of several hundred song motifs per day implies an absence of an acute stressor or a successful coping with stress. Because singing rate can be measured in a completely automatic fashion, its observation can help to reduce experimenter bias in welfare monitoring. Because singing rate measurements are non-invasive, we expect this study to contribute to the refinement of the current welfare monitoring tools in zebra finches.

Microbial communities can predict the ecological condition of headwater streams

Humanity’s reliance on clean water and the ecosystem services provided makes identifying efficient and effective ways to assess the ecological condition of streams ever more important. We used high throughput sequencing of the 16S rRNA region to explore relationships between stream microbial communities, environmental attributes, and assessments of stream ecological condition. Bacteria and archaea in microbial community samples collected from the water column and from stream sediments during spring and summer were used to replicate standard assessments of ecological condition performed with benthic macroinvertebrate collections via the Benthic Index of Biotic Integrity (BIBI). Microbe-based condition assessments were generated at different levels of taxonomic resolution from phylum to OTU (Operational Taxonomic Units) in order to understand appropriate levels of taxonomic aggregation. Stream sediment microbial communities from both spring and summer were much better than the water column at replicating BIBI condition assessment results. Accuracies were as high as 100% on training data used to build the models and up to 80% on validation data used to assess predictions. Assessments using all OTUs usually had the highest accuracy on training data, but were lower on validation data due to overfitting. In contrast, assessments at the order-level had similar performance accuracy for validation data, and a reduced subset of orders also performed well, suggesting the method could be generalized to other watersheds. Subsets of the important orders responded similarly to environmental gradients compared to the entire community, where strong shifts in community structure occurred for known aquatic stressors such as pH, dissolved organic carbon, and nitrate nitrogen. The results suggest the stream microbes may be useful for assessing the ecological condition of streams and especially useful for stream restorations where many eukaryotic taxa have been eliminated due to prior degradation and are unable to recolonize.

Adapting reintroduction tactics in successive trials increases the likelihood of establishment for an endangered carnivore in a fenced sanctuary

Threatened species recovery programs are increasingly turning to reintroductions to reverse biodiversity loss. Here we present a real-world example where tactics (techniques which influence post-release performance and persistence) and an adaptive management framework (which incorporates feedback between monitoring and future actions) improved reintroduction success. Across three successive trials we investigated the influence of tactics on the effective survival and post-release dispersal of endangered eastern quolls (Dasyurus viverrinus) reintroduced into Mulligans Flat Woodland Sanctuary, Australian Capital Territory. Founders were monitored for 42 days post-release, and probability of survival and post-release dispersal were tested against trial, origin, sex, den sharing and presence of pouch young. We adopted an adaptive management framework, using monitoring to facilitate rapid learning and to implement interventions that improved reintroduction success. Founders released in the first trial were less likely to survive (28.6%, n = 14) than those founders released the second (76.9%, n = 13) and third trials (87.5%, n = 8). We adapted several tactics in the second and third trials, including the selection of female-only founders to avoid elevated male mortality, and post-mating releases to reduce stress. Founders that moved dens between consecutive nights were less likely to survive, suggesting that minimising post-release dispersal can increase the probability of survival. The probability of moving dens was lower in the second and third trials, for females, and when den sharing with another founder. This study demonstrates that, through iterative trials of tactics involving monitoring and learning, adaptive management can be used to significantly improve the success of reintroduction programs.

Leveraging risk maps of malaria vector abundance to guide control efforts reduces malaria incidence in Eastern Province, Zambia

Although transmission of malaria and other mosquito-borne diseases is geographically heterogeneous, in sub-Saharan Africa risk maps are rarely used to determine which communities receive vector control interventions. We compared outcomes in areas receiving different indoor residual spray (IRS) strategies in Eastern Province, Zambia: (1) concentrating IRS interventions within a geographical area, (2) prioritizing communities to receive IRS based on predicted probabilities of Anopheles funestus, and (3) prioritizing communities to receive IRS based on observed malaria incidence at nearby health centers. Here we show that the use of predicted probabilities of An. funestus to guide IRS implementation saw the largest decrease in malaria incidence at health centers, a 13% reduction (95% confidence interval = 5-21%) compared to concentrating IRS geographically and a 37% reduction (95% confidence interval = 30-44%) compared to targeting IRS based on health facility incidence. These results suggest that vector control programs could produce better outcomes by prioritizing IRS according to malaria-vector risk maps.

Comparative migration ecology of striped bass and Atlantic sturgeon in the US Southern mid-Atlantic bight flyway

Seasonal migrations are key to the production and persistence of marine fish populations but movements within shelf migration corridors or, “flyways”, are poorly known. Atlantic sturgeon and striped bass, two critical anadromous species, are known for their extensive migrations along the US Mid-Atlantic Bight. Seasonal patterns of habitat selection have been described within spawning rivers, estuaries,and shelf foraging habitats, but information on the location and timing of key coastal migrations is limited. Using a gradient-based array of acoustic telemetry receivers, we compared the seasonal incidence and movement behavior of these species in the near-shelf region of Maryland, USA. Atlantic sturgeon incidence was highest in the spring and fall and tended to be biased toward shallow regions, while striped bass had increased presence during spring and winter months and selected deeper waters. Incidence was transient (mean = ~2 d) for both species with a pattern of increased residency (>2 d) during autumn and winter, particularly for striped bass, with many individuals exhibiting prolonged presence on the outer shelf during winter. Flyways also differed spatially between northern and southern migrations for both species and were related to temperature: striped bass were more likely to occur in cool conditions while Atlantic sturgeon preferred warmer temperatures. Observed timing and spatial distribution within the Mid-Atlantic flyway were dynamic between years and sensitive to climate variables. As shelf ecosystems come under increasing maritime development, gridded telemetry designs represent a feasible approach to provide impact responses within key marine flyways like those that occur within the US Mid-Atlantic Bight.

Remote assessment of the fate of phytoplankton in the Southern Ocean sea-ice zone

In the Southern Ocean, large-scale phytoplankton blooms occur in open water and the sea-ice zone (SIZ). These blooms have a range of fates including physical advection, downward carbon export, or grazing. Here, we determine the magnitude, timing and spatial trends of the biogeochemical (export) and ecological (foodwebs) fates of phytoplankton, based on seven BGC-Argo floats spanning three years across the SIZ. We calculate loss terms using the production of chlorophyll-based on nitrate depletion-compared with measured chlorophyll. Export losses are estimated using conspicuous chlorophyll pulses at depth. By subtracting export losses, we calculate grazing-mediated losses. Herbivory accounts for ~90% of the annually-averaged losses (169 mg C m-2 d-1), and phytodetritus POC export comprises ~10%. Furthermore, export and grazing losses each exhibit distinctive seasonality captured by all floats spanning 60°S to 69°S. These similar trends reveal widespread patterns in phytoplankton fate throughout the Southern Ocean SIZ.

Abundance, density, and social structure of African forest elephants (Loxodonta cyclotis) in a human-modified landscape in southwestern Gabon

Population monitoring is critical to effective conservation, but forest living taxa can be difficult to directly observe. This has been true of African forest elephants (Loxodonta cyclotis), for which we have limited information regarding population size and social behavior despite their threatened conservation status. In this study, we estimated demographic parameters using genetic capture-recapture of forest elephants in the southern Industrial Corridor of the Gamba Complex of Protected Areas in southwestern Gabon, which is considered a global stronghold for forest elephants. Additionally, we examined social networks, predicting that we would find matrilineal structure seen in both savanna and forest elephants. Given 95% confidence intervals, we estimate population size in the sampled area to be between 754 and 1,502 individuals and our best density estimate ranges from 0.47 to 0.80 elephants per km². When extrapolated across the entire Industrial Corridor, this estimate suggests an elephant population size of 3,033 to 6,043 based on abundance or 1,684 to 2,832 based on density, approximately 40–80% smaller than previously suggested. Our social network analysis revealed approximately half of network components included females with different mitochondrial haplotypes suggesting a wider range of variation in forest elephant sociality than previously thought. This study emphasizes the threatened status of forest elephants and demonstrates the need to further refine baseline estimates of population size and knowledge on social behavior in this taxon, both of which will aid in determining how population dynamics in this keystone species may be changing through time in relation to increasing conservation threats.

The MacKinnon Lists Technique: An efficient new method for rapidly assessing biodiversity and species abundance ranks in the marine environment

Widespread and ever-increasing anthropogenic impacts in the marine environment are driving a need to develop more efficient survey methods for monitoring changes in marine biodiversity. There is a particular urgent need for survey methods that could more rapidly and effectively detect change in species richness, abundance and community composition. Here, test the suitability of the Mackinnon Lists Technique for use in the marine environment by testing its effectiveness for rapid assessment of fish communities. The MacKinnon Lists Technique is a time-efficient and cost-effective sampling method developed for studying avian tropical biodiversity, in which several list samples of species can be collected from a single survey. Using the well-established MaxN approach on data from deployments of a Baited Remote Underwater Video Systems for comparison, we tested the suitability of the MacKinnon Lists Technique for use in marine environments by analysing tropical reef fish communities. Using both methods for each data set, differences in community composition between depths and levels of protection were assessed. Both methods were comparable for diversity and evenness indices with similar ranks for species. Multivariate analysis showed that the MacKinnon Lists Technique and MaxN detected similar differences in community composition at different depths and protection status. However, the MacKinnon Lists Technique detected significant differences between factors when fewer videos (representing reduced survey effort) were used. We conclude that the MacKinnon Lists Technique is at least as effective as the widely used MaxN method for detecting differences between communities in the marine environment and suggest can do so with lower survey effort. The MacKinnon Lists Technique has the potential to be widely used as an effective new tool for rapid conservation monitoring in marine ecosystems.

A comparison of cost and quality of three methods for estimating density for wild pig (Sus scrofa)

A critical element in effective wildlife management is monitoring the status of wildlife populations; however, resources to monitor wildlife populations are typically limited. We compared cost effectiveness of three common population estimation methods (i.e. non-invasive DNA sampling, camera sampling, and sampling from trapping) by applying them to wild pigs (Sus scrofa) across three habitats in South Carolina, U.S.A where they are invasive. We used mark-recapture analyses for fecal DNA sampling data, spatially-explicit capture-recapture analyses for camera sampling data, and a removal analysis for removal sampling from trap data. Density estimates were similar across methods. Camera sampling was the least expensive, but had large variances. Fecal DNA sampling was the most expensive, although this technique generally performed well. We examined how reductions in effort by method related to increases in relative bias or imprecision. For removal sampling, the largest cost savings while maintaining unbiased density estimates was from reducing the number of traps. For fecal DNA sampling, a reduction in effort only minimally reduced costs due to the need for increased lab replicates while maintaining high quality estimates. For camera sampling, effort could only be marginally reduced before inducing bias. We provide a decision tree for researchers to help make monitoring decisions.

Projected distribution and climate refugia of endangered Kashmir musk deer Moschus cupreus in greater Himalaya, South Asia

Kashmir musk deer Moschus cupreus (KMD) are the least studied species of musk deer. We compiled genetically validated occurrence records of KMD to construct species distribution models using Maximum Entropy. We show that the distribution of KMD is limited between central Nepal on the east and north-east Afghanistan on the west and is primarily determined by precipitation of driest quarter, annual mean temperature, water vapor, and precipitation during the coldest quarter. Precipitation being the most influential determinant of distribution suggests the importance of pre-monsoon moisture for growth of the dominant vegetation, Himalayan birch Betula utilis and Himalayan fir Abies spectabilis, in KMD's preferred forests. All four Representative Concentration Pathway Scenarios result an expansion of suitable habitat in Uttarakhand, India, west Nepal and their associated areas in China in 2050s and 2070s but a dramatic loss of suitable habitat elsewhere (Kashmir region and Pakistan-Afghanistan border). About 1/4th of the current habitat will remain as climate refugia in future. Since the existing network of protected areas will only include a tiny fraction (4%) of the climatic refugia of KMD, the fate of the species will be determined by the interplay of more urgent short-term forces of poaching and habitat degradation and long-term forces of climate change.

Wind energy development and wildlife conservation in Lithuania: A mapping tool for conflict assessment

The paper presents a mapping tool aiming to identify and minimise potential conflicts between onshore wind energy development and wildlife conservation in Lithuania. It merges current information on the distribution, conservation status and sensitivity of birds and bats to wind power with an integrated evaluation of wind resources (modelled wind speed), special planning status and technical perspectives of wind energy development. The paper includes assessment of the selected wildlife species which were described as sensitive to wind power (69 breeding and 43 migratory bird species and 17 bat species bats in the country). Used species level information allowed the precise identification of sensitive territories and might be used to mitigate negative wind farm effects using special measures based on species behavior. Finally, we delivered overlaps as possible conflicts among the most promising wind farm areas and the areas with high sensitivity in relation to bird and bat distribution. These overlaps point to the required attention and relevant decisions that are needed to ensure sustainable development of wind energy throughout the country. We suggest this tool for initial determination of appropriate areas for wind energy development in the country and as supplement to Environmental Impact Assessment.

Isotope analysis reveals proportional change and site-selection variation of river- and lake-produced eggs of a landlocked migratory fish

Changes in the proportions of river- and lake-produced eggs of a landlocked amphidromous fish, ayu (Plecoglossus altivelis altivelis) in the Lake Biwa water system, Japan, were monitored by stable isotope analysis, based on different δ¹⁵ N and δ¹³ C values of prey organisms between the lake and its tributaries. During the 3 month reproduction season, the δ¹⁵ N values of spawned eggs decreased with time. This result implies that there was a shift from lake-produced eggs to river-produced eggs within a reproductive season, based on the observation that adult fish in the lake had previously been shown to have eggs with distinctly higher δ¹⁵ N values in their ovaries than those in the tributaries. This explanation was also supported by the change in δ¹³ C values of the spawned eggs. Furthermore, eggs with lower δ¹⁵ N and higher δ¹³ C values tended to be spawned at less variable depths, suggesting that females spawning river-produced eggs selected the spawning sites from a narrower range. We conclude that stable isotope ratios of spawned eggs can be indicators of the relative contributions of different food chains and can enable comparisons of reproductive characteristics between types of egg.

Validation of a novel time-to-event nest density estimator on passerines: An example using Brewer's sparrows (Spizella breweri)

Human impacts on natural resources increasingly necessitate understanding of the demographic rates driving wildlife population trends. Breeding productivity in many avian species is the demographic parameter that primarily influences population fluctuations. Nest density is a vital component of breeding productivity despite the fact that it is most often inferred exclusively from nest success. Unfortunately, locating every nest in a given area to determine nest density is often not feasible and can be biased by measurement error. The availability of a nest to be detected and the probability it will be detected during nest searching are two prominent sources of measurement error. A time-to-event nest density estimator has been developed that, unlike standard distance sampling methods, accounts for availability and can use nest data from outside structured surveys routinely collected to assess nest success. Its application is currently limited to Anseriformes, so we evaluated the general applicability of the time-to-event estimator in the order Passeriformes. To do this, we compared estimates of nest detection rate and nest density from the time-to-event estimator to distance sampling methods for 42 Brewer’s sparrow (Spizella breweri) nests monitored in 2015. The time-to-event estimator produced similar but more precise nest detection and density estimates than distance sampling methods.

Guanidinocalix[5]arene for sensitive fluorescence detection and magnetic removal of perfluorinated pollutants

Perfluorinated alkyl substances, such as perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are toxic materials that are known to globally contaminate water, air, and soil resources. Strategies for the simultaneous detection and removal of these compounds are desired to address this emerging health and environmental issue. Herein, we develop a type of guanidinocalix[5]arene that can selectively and strongly bind to PFOS and PFOA, which we use to demonstrate the sensitive and quantitative detection of these compounds in contaminated water through a fluorescent indicator displacement assay. Moreover, by co-assembling iron oxide nanoparticle with the amphiphilic guanidinocalix[5]arene, we are able to use simple magnetic absorption and filtration to efficiently remove PFOS and PFOA from contaminated water. This supramolecular approach that uses both molecular recognition and self-assembly of macrocyclic amphiphiles is promising for the detection and remediation of water pollution.

Increased performance of DNA metabarcoding of macroinvertebrates by taxonomic sorting

DNA-based identification through the use of metabarcoding has been proposed as the next step in the monitoring of biological communities, such as those assessed under the Water Framework Directive (WFD). Advances have been made in the field of metabarcoding, but challenges remain when using complex samples. Uneven biomass distributions, preferential amplification and reference database deficiencies can all lead to discrepancies between morphological and DNA-based taxa lists. The effects of different taxonomic groups on these issues remain understudied. By metabarcoding WFD monitoring samples, we analyzed six different taxonomic groups of freshwater organisms, both separately and combined. Identifications based on metabarcoding data were compared directly to morphological assessments performed under the WFD. The diversity of taxa for both morphological and DNA-based assessments was similar, although large differences were observed in some samples. The overlap between the two taxon lists was 56.8% on average across all taxa, and was highest for Crustacea, Heteroptera, and Coleoptera, and lowest for Annelida and Mollusca. Taxonomic sorting in six basic groups before DNA extraction and amplification improved taxon recovery by 46.5%. The impact on ecological quality ratio (EQR) scoring was considerable when replacing morphology with DNA-based identifications, but there was a high correlation when only replacing a single taxonomic group with molecular data. Different taxonomic groups provide their own challenges and benefits. Some groups might benefit from a more consistent and robust method of identification. Others present difficulties in molecular processing, due to uneven biomass distributions, large genetic diversity or shortcomings of the reference database. Sorting samples into basic taxonomic groups that require little taxonomic knowledge greatly improves the recovery of taxa with metabarcoding. Current standards for EQR monitoring may not be easily replaced completely with molecular strategies, but the effectiveness of molecular methods opens up the way for a paradigm shift in biomonitoring.

Rapid wound healing in a reef manta ray masks the extent of vessel strike

Increasing vessel traffic in the marine environment due to commercial and recreational activities has amplified the number of conflicts with marine animals. However, there are limited multi-year observations of the healing rate of marine animals following vessel strike. Here we document the healing rate of a reef manta ray Mobula alfredi, following lacerations caused by a propeller along the pectoral fin. We demonstrate a high healing capacity, with wound length following a negative exponential curve over time. Lacerations healed to 5% of the initial wound length (i.e. 95% closure) within 295 days. The wounds appeared to stabilise at this point as observed more than three years following the incident and resulted in a distinctive scarring pattern. Examination of an extensive photo-identification catalogue of manta rays from the Ningaloo Coast World Heritage Area showed that the scarring pattern occurs more frequently than previously recognised, as the wounds had been previously attributed to failed predation attempts. This study provides baseline information for wound healing from vessel strike in reef manta rays and indirect evidence for increased vessel strikes on manta rays within the Ningaloo Coast World Heritage Area. We discuss the implication for spatial and behavioural management of vessels around manta rays.

Target Strength and swimbladder morphology of Mueller's pearlside (Maurolicus muelleri)

In the last few years, there has been increasing interest in the commercial exploitation of mesopelagic fish and a trawl-acoustic methodology has been recommended to make estimates of abundance of these resources. This study provides relevant information on the scattering properties of a key mesopelagic fish species in the Bay of Biscay, Mueller's pearlside (Maurolicus muelleri), necessary to convert the acoustic density into numerical abundance. The target strength (TS) of pearlside was estimated for the first time at five frequencies commonly used in acoustic surveys. A high-density filter was applied to reduce the bias derived from overlapping echoes erroneously assigned to single targets. Its relationship with fish length (b20) was also determined (-65.9 ± 2, -69.2 ± 3, -69.2 ± 2, -69.5 ± 2.5 and -71.5 ± 2.5 dB at 18, 38, 70, 120 and 200 kHz, respectively). Biomass estimates of pearlside in the Bay of Biscay during the four years of study (2014-2017) are given using the 38 kHz frequency. Morphological measurements of the swimbladder were obtained from soft X-ray images and used in the backscattering simulation of a gas-filled ellipsoid. Pearlside is a physoclist species, which means that they can compensate the swimbadder volume against pressure changes. However, the best fit between the model and the experimental data showed that they lose that capacity during the trawling process, when the swimbladder volume is affected by Boyle's law.

Depicting changes in land surface cover at Al-Hassa oasis of Saudi Arabia using remote sensing and GIS techniques

This study assessed the spatial and temporal variations of land cover in the agricultural areas of the Al-Hassa oasis, Kingdom of Saudi Arabia (KSA). Change detection technique was applied in order to classify variations among different surface cover aspects, during three successive stages between 1985 and 2017 (i.e., 1985 to 1999 (14 years), 1999 to 2013 (14 years), and 2013 to 2017 (4 years)), using two scenarios. During the first stage, significant urban sprawl (i.e., 3,200 ha) occurred on bare lands within the old oasis, while only 590 ha of the oasis’s vegetation area was occupied by urban cover. However, the final stage revealed rapid urban development (1,270 ha by 2017) within the oasis’s vegetation region, while no urban sprawl occurred on bare lands (area of 1,900 ha, same as that in 1999–2013). Vegetation cover of around 1,000 ha changed to the bare soil class, in addition to the areas that were occupied by the urban class (1,700 ha in total). The study provides quantitative information on the influence of urban development on the spatial changes in vegetation cover of the oasis, especially during recent decades.

Effects of forest management and roe deer impact on a mountain forest development in the Italian Apennines: A modelling approach using LANDIS-II

Forest development is a complex phenomenon which, for the number of actors involved and the response time expressed by forests, is difficult to understand and explore. Forests in Italy, as in several areas of Europe, are experiencing intensive management and recently, an increasing impact by ungulates. The effects on forest development of these two disturbances combined are difficult to predict, and consequently to be properly managed. We used a forest landscape change model, LANDIS-II, to simulate forest development as driven by forestry practices and roe deer impact for 200 years in a mountain forest of the Italian Apennines. We found that each disturbance alters forest tree species richness, forest type abundance and distribution, and forest structure. When considered combined, the two disturbances show additive behavior, enhancing or moderating each other’s effects. Forest management has a negative effect on tree species richness. We expected roe deer to have a negative effect on harvest yields, but this result was significant only for two of seven harvesting treatments. On the other hand, roe deer presence had a positive effect on tree species richness. All the simulation scenarios returned some extent of forest loss. The amount of the forest loss is lowest in the scenario without disturbances, and greatest when both disturbances are considered. However, the two disturbances combined, with the magnitude modelled in our simulations, have relatively low effects on the forest dynamics we analyzed in our study area. LANDIS-II was an effective approach for simulating combined management and ungulate driven trends of forest development, and to help understand the dynamics that lay behind it.

Resilience assessment of Puerto Rico's coral reefs to inform reef management

Globally increasing sea surface temperatures threaten coral reefs, both directly and through interactions with local stressors. More resilient reefs have a higher likelihood of returning to a coral-dominated state following a disturbance, such as a mass bleaching event. To advance practical approaches to reef resilience assessments and aid resilience-based management of coral reefs, we conducted a resilience assessment for Puerto Rico's coral reefs, modified from methods used in other U.S. jurisdictions. We calculated relative resilience scores for 103 sites from an existing commonwealth-wide survey using eight resilience indicators-such as coral diversity, macroalgae percent cover, and herbivorous fish biomass-and assessed which indicators most drove resilience. We found that sites of very different relative resilience were generally highly spatially intermixed, underscoring the importance and necessity of decision making and management at fine scales. In combination with information on levels of two localized stressors (fishing pressure and pollution exposure), we used the resilience indicators to assess which of seven potential management actions could be used at each site to maintain or improve resilience. Fishery management was the management action that applied to the most sites. Furthermore, we combined sites' resilience scores with projected ocean warming to assign sites to vulnerability categories. Island-wide or community-level managers can use the actions and vulnerability information as a starting point for resilience-based management of their reefs. This assessment differs from many previous ones because we tested how much information could be yielded by a "desktop" assessment using freely-available, existing data rather than from a customized, resilience-focused field survey. The available data still permitted analyses comparable to previous assessments, demonstrating that desktop resilience assessments can substitute for assessments with field components under some circumstances.

Genetic Biomonitoring and Biodiversity Assessment Using Portable Sequencing Technologies: Current Uses and Future Directions

We live in an era of unprecedented biodiversity loss, affecting the taxonomic composition of ecosystems worldwide. The immense task of quantifying human imprints on global ecosystems has been greatly simplified by developments in high-throughput DNA sequencing technology (HTS). Approaches like DNA metabarcoding enable the study of biological communities at unparalleled detail. However, current protocols for HTS-based biodiversity exploration have several drawbacks. They are usually based on short sequences, with limited taxonomic and phylogenetic information content. Access to expensive HTS technology is often restricted in developing countries. Ecosystems of particular conservation priority are often remote and hard to access, requiring extensive time from field collection to laboratory processing of specimens. The advent of inexpensive mobile laboratory and DNA sequencing technologies show great promise to facilitate monitoring projects in biodiversity hot-spots around the world. Recent attention has been given to portable DNA sequencing studies related to infectious organisms, such as bacteria and viruses, yet relatively few studies have focused on applying these tools to Eukaryotes, such as plants and animals. Here, we outline the current state of genetic biodiversity monitoring of higher Eukaryotes using Oxford Nanopore Technology's MinION portable sequencing platform, as well as summarize areas of recent development.

Global areas of low human impact ('Low Impact Areas') and fragmentation of the natural world

Habitat loss and fragmentation due to human activities is the leading cause of the loss of biodiversity and ecosystem services. Protected areas are the primary response to this challenge and are the cornerstone of biodiversity conservation efforts. Roughly 15% of land is currently protected although there is momentum to dramatically raise protected area targets towards 50%. But, how much land remains in a natural state? We answer this critical question by using open-access, frequently updated data sets on terrestrial human impacts to create a new categorical map of global human influence ('Low Impact Areas') at a 1 km2 resolution. We found that 56% of the terrestrial surface, minus permanent ice and snow, currently has low human impact. This suggests that increased protected area targets could be met in areas minimally impacted by people, although there is substantial variation across ecoregions and biomes. While habitat loss is well documented, habitat fragmentation and differences in fragmentation rates between biomes has received little attention. Low Impact Areas uniquely enabled us to calculate global fragmentation rates across biomes, and we compared these to an idealized globe with no human-caused fragmentation. The land in Low Impact Areas is heavily fragmented, compromised by reduced patch size and core area, and exposed to edge effects. Tropical dry forests and temperate grasslands are the world's most impacted biomes. We demonstrate that when habitat fragmentation is considered in addition to habitat loss, the world's species, ecosystems and associated services are in worse condition than previously reported.

EFForTS-LGraf: A landscape generator for creating smallholder-driven land-use mosaics

Spatially-explicit simulation models are commonly used to study complex ecological and socio-economic research questions. Often these models depend on detailed input data, such as initial land-cover maps to set up model simulations. Here we present the landscape generator EFFortS-LGraf that provides artificially-generated land-use maps of agricultural landscapes shaped by small-scale farms. EFForTS-LGraf is a process-based landscape generator that explicitly incorporates the human dimension of land-use change. The model generates roads and villages that consist of smallholder farming households. These smallholders use different establishment strategies to create fields in their close vicinity. Crop types are distributed to these fields based on crop fractions and specialization levels. EFForTS-LGraf model parameters such as household area or field size frequency distributions can be derived from household surveys or geospatial data. This can be an advantage over the abstract parameters of neutral landscape generators. We tested the model using oil palm and rubber farming in Indonesia as a case study and validated the artificially-generated maps against classified satellite images. Our results show that EFForTS-LGraf is able to generate realistic land-cover maps with properties that lie within the boundaries of landscapes from classified satellite images. An applied simulation experiment on landscape-level effects of increasing household area and crop specialization revealed that larger households with higher specialization levels led to spatially more homogeneous and less scattered crop type distributions and reduced edge area proportion. Thus, EFForTS-LGraf can be applied both to generate maps as inputs for simulation modelling and as a stand-alone tool for specific landscape-scale analyses in the context of ecological-economic studies of smallholder farming systems.

Global distribution modelling, invasion risk assessment and niche dynamics of Leucanthemum vulgare (Ox-eye Daisy) under climate change

In an era of climate change, biological invasions by alien species represent one of the main anthropogenic drivers of global environmental change. The present study, using an ensemble modelling approach, has mapped current and future global distribution of the invasive Leucanthemum vulgare (Ox-eye Daisy) and predicted the invasion hotspots under climate change. The current potential distribution of Ox-eye Daisy coincides well with the actual distribution records, thereby indicating robustness of our model. The model predicted a global increase in the suitable habitat for the potential invasion of this species under climate change. Oceania was shown to be the high-risk region to the potential invasion of this species under both current and future climate change scenarios. The results revealed niche conservatism for Australia and Northern America, but contrastingly a niche shift for Africa, Asia, Oceania and Southern America. The global distribution modelling and risk assessment of Ox-eye Daisy has immediate implications in mitigating its invasion impacts under climate change, as well as predicting the global invasion hotspots and developing region-specific invasion management strategies. Interestingly, the contrasting patterns of niche dynamics shown by this invasive plant species provide novel insights towards disentangling the different operative mechanisms underlying the process of biological invasions at the global scale.

Enhanced convolutional neural network for plankton identification and enumeration

Despite the rapid increase in the number and applications of plankton imaging systems in marine science, processing large numbers of images remains a major challenge due to large variations in image content and quality in different marine environments. We constructed an automatic plankton image recognition and enumeration system using an enhanced Convolutional Neural Network (CNN) and examined the performance of different network structures on automatic plankton image classification. The procedure started with an adaptive thresholding approach to extract Region of Interest (ROIs) from in situ plankton images, followed by a procedure to suppress the background noise and enhance target features for each extracted ROI. The enhanced ROIs were classified into seven categories by a pre-trained classifier which was a combination of a CNN and a Support Vector Machine (SVM). The CNN was selected to improve feature description and the SVM was utilized to improve classification accuracy. A series of comparison experiments were then conducted to test the effectiveness of the pre-trained classifier including the combination of CNN and SVM versus CNN alone, and the performance of different CNN models. Compared to CNN model alone, the combination of CNN and SVM increased classification accuracy and recall rate by 7.13% and 6.41%, respectively. Among the selected CNN models, the ResNet50 performed the best with accuracy and recall at 94.52% and 94.13% respectively. The present study demonstrates that deep learning technique can improve plankton image recognition and that the results can provide useful information on the selection of different CNN models for plankton recognition. The proposed algorithm could be generally applied to images acquired from different imaging systems.

Have the cake and eat it: Optimizing nondestructive DNA metabarcoding of macroinvertebrate samples for freshwater biomonitoring

DNA metabarcoding can contribute to improving cost-effectiveness and accuracy of biological assessments of aquatic ecosystems, but significant optimization and standardization efforts are still required to mainstream its application into biomonitoring programmes. In assessments based on freshwater macroinvertebrates, a key challenge is that DNA is often extracted from cleaned, sorted and homogenized bulk samples, which is time-consuming and may be incompatible with sample preservation requirements of regulatory agencies. Here, we optimize and evaluate metabarcoding procedures based on DNA recovered from 96% ethanol used to preserve field samples and thus including potential PCR inhibitors and nontarget organisms. We sampled macroinvertebrates at five sites and subsampled the preservative ethanol at 1 to 14 days thereafter. DNA was extracted using column-based enzymatic (TISSUE) or mechanic (SOIL) protocols, or with a new magnetic-based enzymatic protocol (BEAD), and a 313-bp COI fragment was amplified. Metabarcoding detected at least 200 macroinvertebrate taxa, including most taxa detected through morphology and for which there was a reference barcode. Better results were obtained with BEAD than SOIL or TISSUE, and with subsamples taken 7-14 than 1-7 days after sampling, in terms of DNA concentration and integrity, taxa diversity and matching between metabarcoding and morphology. Most variation in community composition was explained by differences among sites, with small but significant contributions of subsampling day and extraction method, and negligible contributions of extraction and PCR replication. Our methods enhance reliability of preservative ethanol as a potential source of DNA for macroinvertebrate metabarcoding, with a strong potential application in freshwater biomonitoring.

Release of eDNA by different life history stages and during spawning activities of laboratory-reared Japanese eels for interpretation of oceanic survey data

To assist in detection of offshore spawning activities of the Japanese eel Anguilla japonica and facilitate interpretation of results of environmental DNA (eDNA) analysis in their spawning area, we examined the eDNA concentration released by each life history stage of artificially reared Japanese eels in the laboratory using quantitative real-time PCR (qPCR). We also compared eDNA concentrations between before and after artificially induced spawning activities. eDNA was not detected from three 30 L seawater tanks containing each single fertilized egg, but eDNA was found from other tanks each containing single individuals of larval stages (preleptocephalus and leptocephalus), juvenile stages (glass eel, elver and yellow eel) or adult stage (silver eel). The eDNA concentrations increased in the life history stages, showed a significant difference among all stages, and were positively correlated with the total length and wet weight. Moreover, the eDNA concentration after spawning was 10-200 times higher than that before spawning, which indicated that the spawning events in the ocean would produce relatively high eDNA concentration. These results in the laboratory suggested that eDNA analysis appears to be an effective method for assisting oceanic surveys to estimate the presence and spawning events of the Japanese eel in the spawning area.