The use of acoustic indices to determine avian species richness in audio-recordings of the environment

Interpreting acoustic recordings of the natural environment is an increasingly important technique for ecologists wishing to monitor terrestrial ecosystems. Technological advances make it possible to accumulate many more recordings than can be listened to or interpreted, thereby necessitating automated assistance to identify elements in the soundscape. In this paper we examine the problem of estimating avian species richness by sampling from very long acoustic recordings. We work with data recorded under natural conditions and with all the attendant problems of undefined and unconstrained acoustic content (such as wind, rain, traffic, etc.) which can mask content of interest (in our case, bird calls). We describe 14 acoustic indices calculated at one minute resolution for the duration of a 24 hour recording. An acoustic index is a statistic that summarizes some aspect of the structure and distribution of acoustic energy and information in a recording. Some of the indices we calculate are standard (e.g. signal-to-noise ratio), some have been reported useful for the detection of bioacoustic activity (e.g. temporal and spectral entropies) and some are directed to avian sources (spectral persistence of whistles). We rank the one minute segments of a 24 hour recording in descending order according to an "acoustic richness" score which is derived from a single index or a weighted combination of two or more. We describe combinations of indices which lead to more efficient estimates of species richness than random sampling from the same recording, where efficiency is defined as total species identified for given listening effort. Using random sampling, we achieve a 53% increase in species recognized over traditional field surveys and an increase of 87% using combinations of indices to direct the sampling. We also demonstrate how combinations of the same indices can be used to detect long duration acoustic events (such as heavy rain and cicada chorus) and to construct long duration (24 h) spectrograms.

Computer-assisted sampling of acoustic data for more efficient determination of bird species richness

Bird species richness survey is one of the most intriguing ecological topics for evaluating environmental health. Here, bird species richness denotes the number of unique bird species in a particular area. Factors affecting the investigation of bird species richness include weather, observation bias, and most importantly, the prohibitive costs of conducting surveys at large spatiotemporal scales. Thanks to advances in recording techniques, these problems have been alleviated by deploying sensors for acoustic data collection. Although automated detection techniques have been introduced to identify various bird species, the innate complexity of bird vocalizations, the background noise present in the recording and the escalating volumes of acoustic data pose a challenging task on determination of bird species richness. In this paper we proposed a two-step computer-assisted sampling approach for determining bird species richness in one-day acoustic data. First, a classification model is built based on acoustic indices for filtering out minutes that contain few bird species. Then the classified bird minutes are ordered by an acoustic index and the redundant temporal minutes are removed from the ranked minute sequence. The experimental results show that our method is more efficient in directing experts for determination of bird species compared with the previous methods.

Angling and species richness of aquatic macrophytes in ponds

Ponds are unjustly neglected habitats. This paper aims to raise awareness of the potential interaction between angling and the macrophyte vegetation of ponds. The work described by the author followed on from a study of 57 ponds in East Yorkshire, northeast England, by Linton & Goulder (2000). They found that the species richness of aquatic vascular plants (macrophytes) is greater in ponds that are used for angling and suggest that to some extent there are more species because disturbance by anglers leads to greater habitat diversity. This article describes how the hypothesis was tested by comparing species richness at fished sites with that at non-fished sites around the margins of ponds in two localities in East Yorkshire. The localities were investigated during August-September 1999.

Computer intensive methods for controlling bias in a generalized species diversity index

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

How does the taxonomic status of allopatric populations influence species richness within African cichlid fish assemblages?

Aim  Current estimates of species richness within rapidly evolving species flocks are often highly dependent on the species status of allopatric populations that differ in phenotypic traits. These traits may be unreliable indicators of biological species status and systematists may have inconsistently assigned species among lineages or locations on the basis of these traits, thus hampering comparative studies of regional species richness and speciation rates. Our aim was to develop a method of generating standardized estimates of regional species richness suitable for comparative analysis, and to use these estimates to examine the extent and consistency of species assignment of allopatric populations within rapidly evolving cichlid fish flocks present in three east African lakes. Location  Lakes Malawi, Victoria and Tanganyika. Methods  Using published taxon co-occurrence data, a novel approach was employed to calculate standardized ‘minimum’ estimates of regional species richness for hard substrate associated complexes of cichlids within each of the lakes. Minimum estimates were based on an explicit assumption that if taxa present on equivalent habitats have disjunct distributions, then they are allopatric forms of the same species. These estimates were compared with current observed ‘high-end’ regional species richness estimates for those complexes to determine the consistency of species assignment of allopatric populations between lineages within a lake. A ‘sympatry’ index was developed to enable comparisons of levels of species assignment of allopatric populations between-lakes to be made. Results  Within each lake, the minimum and high-end estimates for species richness were significantly correlated across complexes, indicating that the complexes that contain more recognized species contain the most genuine biological species. However, comparisons of complexes among lakes revealed considerable differences. For equivalent geographical areas, substantially higher proportions of recognized species were totally allopatric within the studied Lake Malawi and Lake Victoria complexes, than those of Lake Tanganyika. Main Conclusions  Among African lakes, levels of assignment to species status of allopatric populations were found to be distinctly different. It is unclear whether the discrepancies are a consequence of differences between the lake faunas in degrees of phenotypic divergence among allopatric populations, or are simply the result of inconsistent taxonomic practices. In either case, these results have considerable wider relevance for they emphasize that quantitative measures of regional and beta diversity are critically dependent on the species status of allopatric populations, an issue usually neglected in comparative studies of species richness. The technique introduced here can be used to standardize measures of regional diversity of lineages for comparative analyses, potentially enabling more accurate identification of processes influencing rates of speciation.

(Table 1) Species richness and diversity of tundra plants in herbivore exclosure and control plots near Barrow, Alaska

To determine the role lemmings play in structuring plant communities and their contribution to the 'greening of the Arctic', we measured plant cover and biomass in 50 + year old lemming exclosures and control plots in the coastal tundra near Barrow, Alaska. The response of plant functional types to herbivore exclusion varied among land cover types. In general, the abundance of lichens and bryophytes increased with the exclusion of lemmings, whereas graminoids decreased, although the magnitude of these responses varied among land cover types. These results suggest that sustained lemming activity promotes a higher biomass of vascular plant functional types than would be expected without their presence and highlights the importance of considering herbivory when interpreting patterns of greening in the Arctic. In light of the rapid environmental change ongoing in the Arctic and the potential regional to global implications of this change, further exploration regarding the long-term influence of arvicoline rodents on ecosystem function (e.g. carbon and energy balance) should be considered a research priority.

On the importance of shrub encroachment by sprouters, climate, species richness and anthropic factors for ecosystem multifunctionality in semi-arid Mediterranean ecosystems

One of the most important changes taking place in drylands worldwide is the increase of the cover and dominance of shrubs in areas formerly devoid of them (shrub encroachment). A large body of research has evaluated the causes and consequences of shrub encroachment for both ecosystem structure and functioning. However, there are virtually no studies evaluating how shrub encroachment affects the ability of ecosystems to maintain multiple functions and services simultaneously (multifunctionality). We aimed to do so by gathering data from ten ecosystem functions linked to the maintenance of primary production and nutrient cycling and storage (organic C, activity of β-glucosidase, pentoses, hexoses, total N, total available N, amino acids, proteins, available inorganic P, and phosphatase activity), and summarizing them in a multifunctionality index (M). We assessed how climate, species richness, anthropic factors (distance to the nearest town, sandy and asphalted road, and human population in the nearest town at several historical periods) and encroachment by sprouting shrubs impacted both the functions in isolation and M along a regional (ca. 350 km) gradient in Mediterranean grasslands and shrublands dominated by a non-sprouting shrub. Values of M were higher in those grasslands and shrublands containing sprouting shrubs (43 and 62%, respectively). A similar response was found when analyzing the different functions in isolation, as encroachment by sprouting shrubs increased functions by 2–80% compared to unencroached areas. Encroachment was the main driver of changes in M along the regional gradient evaluated, followed by anthropic factors and species richness. Climate had little effects on M in comparison to the other factors studied. Similar responses were observed when evaluating the functions in isolation. Overall, our results showed that M was higher at sites with higher sprouting shrub cover, longer distance to roads and higher perennial plant species richness. Our study is the first documenting that ecosystem multifunctionality in shrublands is enhanced by encroaching shrubs differing in size and leaf attributes. Our findings reinforce the idea that encroachment effects on ecosystem functioning cannot be generalized, and that are largely dependent on the traits of the encroaching shrub relative to those of the species being replaced.

Response to comments on "Productivity is a poor predictor of plant species richness"

Pan et al. claim that our results actually support a strong linear positive relationship between productivity and richness, whereas Fridley et al. contend that the data support a strong humped relationship. These responses illustrate how preoccupation with bivariate patterns distracts from a deeper understanding of the multivariate mechanisms that control these important ecosystem properties.

Sampling environmental acoustic recordings to determine species richness : I

Acoustic sensors provide an effective means of monitoring biodiversity at large spatial and temporal scales. They can continuously and passively record large volumes of data over extended periods, however these data must be analysed to detect the presence of vocal species. Automated analysis of acoustic data for large numbers of species is complex and can be subject to high levels of false positive and false negative results. Manual analysis by experienced users can produce accurate results, however the time and effort required to process even small volumes of data can make manual analysis prohibitive. Our research examined the use of sampling methods to reduce the cost of analysing large volumes of acoustic sensor data, while retaining high levels of species detection accuracy. Utilising five days of manually analysed acoustic sensor data from four sites, we examined a range of sampling rates and methods including random, stratified and biologically informed. Our findings indicate that randomly selecting 120, one-minute samples from the three hours immediately following dawn provided the most effective sampling method. This method detected, on average 62% of total species after 120 one-minute samples were analysed, compared to 34% of total species from traditional point counts. Our results demonstrate that targeted sampling methods can provide an effective means for analysing large volumes of acoustic sensor data efficiently and accurately.

Sampling environmental acoustic recordings to determine bird species richness

Acoustic sensors can be used to estimate species richness for vocal species such as birds. They can continuously and passively record large volumes of data over extended periods. These data must subsequently be analyzed to detect the presence of vocal species. Automated analysis of acoustic data for large numbers of species is complex and can be subject to high levels of false positive and false negative results. Manual analysis by experienced surveyors can produce accurate results; however the time and effort required to process even small volumes of data can make manual analysis prohibitive. This study examined the use of sampling methods to reduce the cost of analyzing large volumes of acoustic sensor data, while retaining high levels of species detection accuracy. Utilizing five days of manually analyzed acoustic sensor data from four sites, we examined a range of sampling frequencies and methods including random, stratified, and biologically informed. We found that randomly selecting 120 one-minute samples from the three hours immediately following dawn over five days of recordings, detected the highest number of species. On average, this method detected 62% of total species from 120 one-minute samples, compared to 34% of total species detected from traditional area search methods. Our results demonstrate that targeted sampling methods can provide an effective means for analyzing large volumes of acoustic sensor data efficiently and accurately. Development of automated and semi-automated techniques is required to assist in analyzing large volumes of acoustic sensor data. Read More: http://www.esajournals.org/doi/abs/10.1890/12-2088.1

Productivity is a poor predictor of plant species richness

For more than 30 years, the relationship between net primary productivity and species richness has generated intense debate in ecology about the processes regulating local diversity. The original view, which is still widely accepted, holds that the relationship is hump-shaped, with richness first rising and then declining with increasing productivity. Although recent meta-analyses questioned the generality of hump-shaped patterns, these syntheses have been criticized for failing to account for methodological differences among studies. We addressed such concerns by conducting standardized sampling in 48 herbaceous-dominated plant communities on five continents. We found no clear relationship between productivity and fine-scale (meters−2) richness within sites, within regions, or across the globe. Ecologists should focus on fresh, mechanistic approaches to understanding the multivariate links between productivity and richness.

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.