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Sound-mapping a coniferous forest-Perspectives for biodiversity monitoring and noise mitigation.

ABSTRACT: Acoustic diversity indices have been proposed as low-cost biodiversity monitoring tools. The acoustic diversity of a soundscape can be indicative of the richness of an acoustic community and the structural/vegetation characteristics of a habitat. There is a need to apply these methods to landscapes that are ecologically and/or economically important. We investigate the relationship between the acoustic properties of a coniferous forest with stand-age and structure. We sampled a 73 point grid in part of the UK's largest man-made lowland coniferous plantation forest, covering a 320ha mosaic of different aged stands. Forest stands ranged from 0-85 years old providing an age-gradient. Short soundscape recordings were collected from each grid point on multiple mornings (between 6am-11am) to capture the dawn chorus. We repeated the study during July/August in 2014 and again in 2015. Five acoustic indices were calculated for a total of 889 two minute samples. Moderate relationships between acoustic diversity with forest stand-age and vegetation characteristics (canopy height; canopy cover) were observed. Ordinations suggest that as structural complexity and forest age increases, the higher frequency bands (4-10KHz) become more represented in the soundscape. A strong linear relationship was observed between distance to the nearest road and the ratio of anthropogenic noise to biological sounds within the soundscape. Similar acoustic patterns were observed in both years, though acoustic diversity was generally lower in 2014, which was likely due to differences in wind conditions between years. Our results suggest that developing these relatively low-cost acoustic monitoring methods to inform adaptive management of production landscapes, may lead to improved biodiversity monitoring. The methods may also prove useful for modelling road noise, landscape planning and noise mitigation.

SUBMITTER: Turner A

PROVIDER: S-EPMC5761852 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Sound-mapping a coniferous forest-Perspectives for biodiversity monitoring and noise mitigation.

Turner Anthony A Fischer Michael M Tzanopoulos Joseph J

PloS one 20180110 1

Acoustic diversity indices have been proposed as low-cost biodiversity monitoring tools. The acoustic diversity of a soundscape can be indicative of the richness of an acoustic community and the structural/vegetation characteristics of a habitat. There is a need to apply these methods to landscapes that are ecologically and/or economically important. We investigate the relationship between the acoustic properties of a coniferous forest with stand-age and structure. We sampled a 73 point grid in ...[more]

PMID: 29320514

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Project description:Artificial drainage (ditching) is widely used to increase timber yield in northern forests. When the drainage systems are maintained, their environmental impacts are likely to accumulate over time and along accompanying management, notably after logging when new forest develops on decayed peat. Our study provides the first comprehensive documentation of long-term ditching impacts on terrestrial and arboreal biodiversity by comparing natural alder swamps and second-generation drained forests that have evolved from such swamps in Estonia. We explored species composition of four potentially drainage-sensitive taxonomic groups (vascular plants, bryophytes, lichens, and snails), abundance of species of conservation concern, and their relationships with stand structure in two-ha plots representing four management types (ranging from old growth to clearcut). We found that drainage affected plot-scale species richness only weakly but it profoundly changed assemblage composition. Bryophytes and lichens were the taxonomic groups that were most sensitive both to drainage and timber-harvesting; in closed stands they responded to changed microhabitat structure, notably impoverished tree diversity and dead-wood supply. As a result, natural old-growth plots were the most species-rich and hosted several specific species of conservation concern. Because the most influential structural changes are slow, drainage impacts may be long hidden. The results also indicated that even very old drained stands do not provide quality habitats for old-growth species of drier forest types. However, drained forests hosted many threatened species that were less site type specific, including early-successional vascular plants and snails on clearcuts and retention cuts, and bryophytes and lichens of successional and old forests. We conclude that three types of specific science-based management tools are needed to mitigate ditching effects on forest biodiversity: (i) silvicultural techniques to maintain stand structural complexity; (ii) context-dependent spatial analysis and planning of drained landscapes; and (iii) lists of focal species to monitor and guide ditching practices.

Project description:Effective monitoring programs for biodiversity are needed to assess trends in biodiversity and evaluate the consequences of management. This is particularly true for birds and faunas that occupy interior forest and other areas of low human population density, as these are frequently under-sampled compared to other habitats. For birds, Autonomous Recording Units (ARUs) have been proposed as a supplement or alternative to point counts made by human observers to enhance monitoring efforts. We employed two strategies (i.e., simultaneous-collection and same-season) to compare point count and ARU methods for quantifying species richness and composition of birds in temperate interior forests. The simultaneous-collection strategy compares surveys by ARUs and point counts, with methods matched in time, location, and survey duration such that the person and machine simultaneously collect data. The same-season strategy compares surveys from ARUs and point counts conducted at the same locations throughout the breeding season, but methods differ in the number, duration, and frequency of surveys. This second strategy more closely follows the ways in which monitoring programs are likely to be implemented. Site-specific estimates of richness (but not species composition) differed between methods; however, the nature of the relationship was dependent on the assessment strategy. Estimates of richness from point counts were greater than estimates from ARUs in the simultaneous-collection strategy. Woodpeckers in particular, were less frequently identified from ARUs than point counts with this strategy. Conversely, estimates of richness were lower from point counts than ARUs in the same-season strategy. Moreover, in the same-season strategy, ARUs detected the occurrence of passerines at a higher frequency than did point counts. Differences between ARU and point count methods were only detected in site-level comparisons. Importantly, both methods provide similar estimates of species richness and composition for the region. Consequently, if single visits to sites or short-term monitoring are the goal, point counts will likely perform better than ARUs, especially if species are rare or vocalize infrequently. However, if seasonal or annual monitoring of sites is the goal, ARUs offer a viable alternative to standard point-count methods, especially in the context of large-scale or long-term monitoring of temperate forest birds.

Project description:IntroductionOne major challenge in PET radiomics is its sensitivity to noise. Low signal-to-noise ratio (SNR) affects not only the precision but also the accuracy of quantitative metrics extracted from the images resulting in noise-induced bias. This phantom study aims to identify the radiomic features that are robust to noise in terms of precision and accuracy and to explore some methods that might help to correct noise-induced bias.MethodsA phantom containing three 18F-FDG filled 3D printed inserts, reflecting heterogeneous tracer uptake and realistic tumor shapes, was used in the study. The three different phantom inserts were filled and scanned with three different tumor-to-background ratios, simulating a total of nine different tumors. From the 40-minute list-mode data, ten frames each for 5 s, 10 s, 30 s, and 120 s frame duration were reconstructed to generate images with different noise levels. Under these noise conditions, the precision and accuracy of the radiomic features were analyzed using intraclass correlation coefficient (ICC) and similarity distance metric (SDM) respectively. Based on the ICC and SDM values, the radiomic features were categorized into four groups: poor, moderate, good, and excellent precision and accuracy. A "difference image" created by subtracting two statistically equivalent replicate images was used to develop a model to correct the noise-induced bias. Several regression methods (e.g., linear, exponential, sigmoid, and power-law) were tested. The best fitting model was chosen based on Akaike information criteria.ResultsSeveral radiomic features derived from low SNR images have high repeatability, with 68% of radiomic features having ICC ≥ 0.9 for images with a frame duration of 5 s. However, most features show a systematic bias that correlates with the increase in noise level. Out of 143 features with noise-induced bias, the SDM values were improved based on a regression model (53 features to excellent and 67 to good) indicating that the noise-induced bias of these features can be, at least partially, corrected.ConclusionTo have a predictive value, radiomic features should reflect tumor characteristics and be minimally affected by noise. The present study has shown that it is possible to correct for noise-induced bias, at least in a subset of the features, using a regression model based on the local image noise estimates.

Dataset Information

Sound-mapping a coniferous forest-Perspectives for biodiversity monitoring and noise mitigation.

Publications

Sound-mapping a coniferous forest-Perspectives for biodiversity monitoring and noise mitigation.

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