Clustering acoustic events in environmental recordings for species richness surveys

Environmental acoustic recordings can be used to perform avian species richness surveys, whereby a trained ornithologist can observe the species present by listening to the recording. This could be made more efficient by using computational methods for iteratively selecting the richest parts of a long recording for the human observer to listen to, a process known as “smart sampling”. This allows scaling up to much larger ecological datasets. In this paper we explore computational approaches based on information and diversity of selected samples. We propose to use an event detection algorithm to estimate the amount of information present in each sample. We further propose to cluster the detected events for a better estimate of this amount of information. Additionally, we present a time dispersal approach to estimating diversity between iteratively selected samples. Combinations of approaches were evaluated on seven 24-hour recordings that have been manually labeled by bird watchers. The results show that on average all the methods we have explored would allow annotators to observe more new species in fewer minutes compared to a baseline of random sampling at dawn.

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Assistive classification for improving the efficiency of avian species richness surveys

Avian species richness surveys, which measure the total number of unique avian species, can be conducted via remote acoustic sensors. An immense quantity of data can be collected, which, although rich in useful information, places a great workload on the scientists who manually inspect the audio. To deal with this big data problem, we calculated acoustic indices from audio data at a one-minute resolution and used them to classify one-minute recordings into five classes. By filtering out the non-avian minutes, we can reduce the amount of data by about 50% and improve the efficiency of determining avian species richness. The experimental results show that, given 60 one-minute samples, our approach enables to direct ecologists to find about 10% more avian species.

Frequency and precision of aerial surveys for kangaroo management

The appropriate frequency and precision for surveys of wildlife populations represent a trade-off between survey cost and the risk of making suboptimal management decisions because of poor survey data. The commercial harvest of kangaroos is primarily regulated through annual quotas set as proportions of absolute estimates of population size. Stochastic models were used to explore the effects of varying precision, survey frequency and harvest rate on the risk of quasiextinction for an arid-zone and a more mesic-zone kangaroo population. Quasiextinction probability increases in a sigmoidal fashion as survey frequency is reduced. The risk is greater in more arid regions and is highly sensitive to harvest rate. An appropriate management regime involves regular surveys in the major harvest areas where harvest rate can be set close to the maximum sustained yield. Outside these areas, survey frequency can be reduced in relatively mesic areas and reduced in arid regions when combined with lowered harvest rates. Relative to other factors, quasiextinction risk is only affected by survey precision (standard error/mean × 100) when it is >50%, partly reflecting the safety of the strategy of harvesting a proportion of a population estimate.

The influence of animal mobility on the assumption of uniform distances in aerial line-transect surveys

Line-transect distance sampling is a widely used method for estimating animal density from aerial surveys. Analysis of line-transect distance data usually relies on a requirement that the statistical distribution of distances of animal groups from the transect line is uniform. We show that this requirement is satisfied by the survey design if all other assumptions of distance sampling hold, but it can be violated by consistent survey problems such as responsive movement of the animals towards or away from the observer. We hypothesise that problems with the uniform requirement are unlikely to be encountered for immobile taxa, but might become substantial for species of high mobility. We test evidence for non-uniformity using double-observer distance data from two aerial surveys of five species with a spectrum of mobility capabilities and tendencies. No clear evidence against uniformity was found for crabeater seals or emperor penguins on the pack-ice in East Antarctica, while minor non-uniformity consistent with responsive movement up to 30 m was found for Adelie penguins. Strong evidence of either non-uniformity or a failure of the capture-recapture validating method was found for eastern grey kangaroos and red kangaroos in Queensland.

A comparison of mark-recapture distance-sampling methods applied to aerial surveys of eastern grey kangaroos

Aerial surveys of kangaroos (Macropus spp.) in Queensland are used to make economically important judgements on the levels of viable commercial harvest. Previous analysis methods for aerial kangaroo surveys have used both mark-recapture methodologies and conventional distance-sampling analyses. Conventional distance sampling has the disadvantage that detection is assumed to be perfect on the transect line, while mark-recapture methods are notoriously sensitive to problems with unmodelled heterogeneity in capture probabilities. We introduce three methodologies for combining together mark-recapture and distance-sampling data, aimed at exploiting the strengths of both methodologies and overcoming the weaknesses. Of these methods, two are based on the assumption of full independence between observers in the mark-recapture component, and this appears to introduce more bias in density estimation than it resolves through allowing uncertain trackline detection. Both of these methods give lower density estimates than conventional distance sampling, indicating a clear failure of the independence assumption. The third method, termed point independence, appears to perform very well, giving credible density estimates and good properties in terms of goodness-of-fit and percentage coefficient of variation. Estimated densities of eastern grey kangaroos range from 21 to 36 individuals km-2, with estimated coefficients of variation between 11% and 14% and estimated trackline detection probabilities primarily between 0.7 and 0.9.

The impact of a streamlined funding application process on application time: Two cross-sectional surveys of Australian researchers

Objective: To examine if streamlining a medical research funding application process saved time for applicants. Design: Cross-sectional surveys before and after the streamlining. Setting: The National Health and Medical Research Council (NHMRC) of Australia. Participants: Researchers who submitted one or more NHMRC Project Grant applications in 2012 or 2014. Main outcome measures: Average researcher time spent preparing an application and the total time for all applications in working days. Results: The average time per application increased from 34 working days before streamlining (95% CI 33 to 35) to 38 working days after streamlining (95% CI 37 to 39; mean difference 4 days, bootstrap p value <0.001). The estimated total time spent by all researchers on applications after streamlining was 614 working years, a 67-year increase from before streamlining. Conclusions: Streamlined applications were shorter but took longer to prepare on average. Researchers may be allocating a fixed amount of time to preparing funding applications based on their expected return, or may be increasing their time in response to increased competition. Many potentially productive years of researcher time are still being lost to preparing failed applications.

Large scale surveys suggest limited mercury availability in tropical north Queensland (Australia)

Little is known about the threat of mercury (Hg) to consumers in food webs of Australia's wet-dry tropics. This is despite high concentrations in similar biomes elsewhere and a recent history of gold mining that could lead to a high degree of exposure for biota. We analysed Hg in water, sediments, invertebrates and fishes in rivers and estuaries of north Queensland, Australia to determine its availability and biomagnification in food webs. Concentrations in water and sediments were low relative to other regions of Hg concern, with only four of 138 water samples and five of 60 sediment samples above detection limits of 0.1 mu g L-1 and 01 mu g g(-1), respectively. Concentrations of Hg in fishes and invertebrates from riverine and wetland food webs were well below international consumption guidelines, including those in piscivorous fishes, likely due to low baseline concentrations and limited rates of biomagnification (average slope of log Hg vs. delta N-15 = 0.08). A large fish species of recreational, commercial, and cultural importance (the barramundi, Lates calcarifer), had low concentrations that were below consumption guidelines. Observed variation in Hg concentrations in this species was primarily explained by age and foraging location (floodplain vs. coastal), with floodplain feeders having higher Hg concentrations than those foraging at sea. These analyses suggest that there is a limited threat of Hg exposure for fish-eating consumers in this region. (C) 2011 Published by Elsevier B.V.

Contribution of geophysical surveys to groundwater modelling of a porous aquifer in semiarid Niger: An overview

Subsurface geophysical surveys were carried out using a large range of methods in an unconfined sandstone aquifer in semiarid south-western Niger for improving both the conceptual model of water flow through the unsaturated zone and the parameterization of numerical a groundwater model of the aquifer. Methods included: electromagnetic mapping, electrical resistivity tomography (ERT), resistivity logging, time domain electromagnetic sounding (TDEM), and magnetic resonance sounding (MRS). Analyses of electrical conductivities, complemented by geochemical measurements, allowed us to identify preferential pathways for infiltration and drainage beneath gullies and alluvial fans. The mean water content estimated by MRS (13%) was used for computing the regional groundwater recharge from long-term change in the water table. The ranges in permeability and water content obtained with MRS allowed a reduction of the degree of freedom of aquifer parameters used in groundwater modelling.

Using multi-label classification for acoustic pattern detection and assisting bird species surveys

Acoustics is a rich source of environmental information that can reflect the ecological dynamics. To deal with the escalating acoustic data, a variety of automated classification techniques have been used for acoustic patterns or scene recognition, including urban soundscapes such as streets and restaurants; and natural soundscapes such as raining and thundering. It is common to classify acoustic patterns under the assumption that a single type of soundscapes present in an audio clip. This assumption is reasonable for some carefully selected audios. However, only few experiments have been focused on classifying simultaneous acoustic patterns in long-duration recordings. This paper proposes a binary relevance based multi-label classification approach to recognise simultaneous acoustic patterns in one-minute audio clips. By utilising acoustic indices as global features and multilayer perceptron as a base classifier, we achieve good classification performance on in-the-field data. Compared with single-label classification, multi-label classification approach provides more detailed information about the distributions of various acoustic patterns in long-duration recordings. These results will merit further biodiversity investigations, such as bird species surveys.

Phylogeography unplugged: comparative surveys in the genomic era

In March 2012, the authors met at the National Evolutionary Synthesis Center (NESCent) in Durham, North Carolina, USA, to discuss approaches and cooperative ventures in Indo-Pacific phylogeography. The group emerged with a series of findings: (1) Marine population structure is complex, but single locus mtDNA studies continue to provide powerful first assessment of phylogeographic patterns. (2) These patterns gain greater significance/power when resolved in a diversity of taxa. New analytical tools are emerging to address these analyses with multi-taxon approaches. (3) Genome-wide analyses are warranted if selection is indicated by surveys of standard markers. Such indicators can include discordance between genetic loci, or between genetic loci and morphology. Phylogeographic information provides a valuable context for studies of selection and adaptation. (4) Phylogeographic inferences are greatly enhanced by an understanding of the biology and ecology of study organisms. (5) Thorough, range-wide sampling of taxa is the foundation for robust phylogeographic inference. (6) Congruent geographic and taxonomic sampling by the Indo-Pacific community of scientists would facilitate better comparative analyses. The group concluded that at this stage of technology and software development, judicious rather than wholesale application of genomics appears to be the most robust course for marine phylogeographic studies. Therefore, our group intends to affirm the value of traditional (''unplugged'') approaches, such as those based on mtDNA sequencing and microsatellites, along with essential field studies, in an era with increasing emphasis on genomic approaches.

Beach surveys of South Carlsbad State Beach onshore of Carlsbad artificial reef

(Document pdf contains 9 pages)

Biological surveys of five southern artificial reefs: Oceanside #1, Oceanside #2, Carlsbad, Pacific Beach, and Mission Bay

(Document pdf contains 19 pages)

Analysis of Sample Frames and Subsampling Methods for Reef Fish Surveys

Introduction: The National Oceanic and Atmospheric Administration’s Biogeography Branch has conducted surveys of reef fish in the Caribbean since 1999. Surveys were initially undertaken to identify essential fish habitat, but later were used to characterize and monitor reef fish populations and benthic communities over time. The Branch’s goals are to develop knowledge and products on the distribution and ecology of living marine resources and provide resource managers, scientists and the public with an improved ecosystem basis for making decisions. The Biogeography Branch monitors reef fishes and benthic communities in three study areas: (1) St. John, USVI, (2) Buck Island, St. Croix, USVI, and (3) La Parguera, Puerto Rico. In addition, the Branch has characterized the reef fish and benthic communities in the Flower Garden Banks National Marine Sanctuary, Gray’s Reef National Marine Sanctuary and around the island of Vieques, Puerto Rico. Reef fish data are collected using a stratified random sampling design and stringent measurement protocols. Over time, the sampling design has changed in order to meet different management objectives (i.e. identification of essential fish habitat vs. monitoring), but the designs have always remained: • Probabilistic – to allow inferences to a larger targeted population, • Objective – to satisfy management objectives, and • Stratified – to reduce sampling costs and obtain population estimates for strata. There are two aspects of the sampling design which are now under consideration and are the focus of this report: first, the application of a sample frame, identified as a set of points or grid elements from which a sample is selected; and second, the application of subsampling in a two-stage sampling design. To evaluate these considerations, the pros and cons of implementing a sampling frame and subsampling are discussed. Particular attention is paid to the impacts of each design on accuracy (bias), feasibility and sampling cost (precision). Further, this report presents an analysis of data to determine the optimal number of subsamples to collect if subsampling were used. (PDF contains 19 pages)