声景生态学研究进展和展望

声景生态学以景观中的声音为研究对象, 探讨其在不同时空维度上的分布和变化模式, 从而揭示自然环境、野生动物和人类活动的相互作用关系。本文通过系统检索声景生态学研究的相关文献, 回顾了该学科的研究框架和研究方法, 总结了目前常用的声学指标, 重点归纳了声景生态学的研究内容, 包括声景组成和各组分间的相互作用, 声景的时空格局, 以及声景生态学在生物多样性监测中的应用。目前, 声景监测中存在的问题主要包括监测的生态系统类型和物种类群有限、声学指标效力有待提高等。建议未来着重推进建立系统性的声景监测网络和数据管理平台, 开发和完善音频数据采集、分析方法和评估指标, 并重视声景数据的采集, 将声景视作一种资源进行研究和保护。     

Connecting soundscape to landscape: Which acoustic index best describes landscape configuration?

Soundscape assessment has been proposed as a remote ecological monitoring tool for measuring biodiversity, but few studies have examined how soundscape patterns vary with landscape configuration and condition. The goal of our study was to examine a suite of published acoustic indices to determine whether they provide comparable results relative to varying levels of landscape fragmentation and ecological condition in nineteen forest sites in eastern Australia. Our comparison of six acoustic indices according to time of day revealed that two indices, the acoustic complexity and the bioacoustic index, presented a similar pattern that was linked to avian song intensity, but was not related to landscape and biodiversity attributes. The diversity indices, acoustic entropy and acoustic diversity, and the normalized difference soundscape index revealed high nighttime sound, as well as a dawn and dusk chorus. These indices appear to be sensitive to nocturnal biodiversity which is abundant at night in warm, subtropical environments. We argue that there is need to better understand temporal partitioning of the soundscape by specific taxonomic groups, and this should involve integrated research on amphibians, insects and birds during a 24 h cycle. The three indices that best connected the soundscape with landscape characteristics, ecological condition and bird species richness were acoustic entropy, acoustic evenness and the normalized difference soundscape index. This study has demonstrated that remote soundscape assessment can be implemented as an ecological monitoring tool in fragmented Australian forest landscapes. However, further investigation should be dedicated to refining and/or combining existing acoustic indices and also to determine if these indices are appropriate in other landscapes and for other survey purposes.     

Do soundscape indices predict landscape‐scale restoration outcomes? A comparative study of restored seabird island soundscapes

Measuring restoration outcomes is essential, but challenging and expensive, particularly on remote islands. Acoustic recording increases the scale of monitoring inexpensively; however, extracting biological information from large volumes of recordings remains challenging. Soundscape approaches, characterizing communities using acoustic indices, rapidly analyze large acoustic datasets and can be used to compare restoration sites against reference conditions. We tested this approach to measure nocturnal seabird recovery following invasive predator removal in the Aleutian Islands. We used recordings of nocturnal seabird soundscapes from six islands with varied histories of predators, from never invaded (one island) to 9–34 years post‐predator removal (four islands) and currently invaded (one island). We calculated 10 indices of acoustic intensity and complexity, and two pairwise indices of acoustic differences. Three indices reflected patterns of seabird recovery. Acoustic richness (measuring temporal entropy and amplitude) increased with time since predator removal and presence of historical predator refugia (r² = 0.44). These factors and moonlight accounted for 30% of variation in cumulative spectral difference from the reference island. Over 10% of acoustic richness and temporal entropy was explained by Leach's Storm‐petrel (Oceanodroma leucorhoa) calls. However, indices characterized the soundscape of rat‐invaded Kiska Island like a never invaded island, likely due to high abiotic noise and few seabird calls. Soundscape indices have potential to monitor outcomes of seabird restoration quickly and cheaply, if confounding factors are considered and controlled in experimental design. We suggest soundscape indices become part of the expanding acoustic monitoring toolbox to cost‐effectively measure restoration outcomes at scale and in remote areas.     

Soundscape analysis and acoustic monitoring document impacts of natural gas exploration on biodiversity in a tropical forest

Natural resource extraction is increasing rapidly in tropical forests, but we lag behind in understanding the impacts of these disturbances on biodiversity. In high diversity tropical habitats, acoustic monitoring is an efficient tool for sampling a large proportion of the fauna across varied spatial and temporal scales. We used passive acoustic monitoring in a pre-montane forest in Peru to investigate how soundscape composition and richness of acoustic frequencies varied with distance from a natural gas exploratory well and with operational phase (construction and drilling). We also evaluated how anuran and avian species richness and vocal activity varied with distance and between phases. Soundscape analyses showed that acoustic frequency similarity was greatest among sites closer to (≤250 m) and farther from (≥500 m) the platform. Soundscapes revealed more frequencies were used during construction and showed a weak trend of increasing frequency richness with increasing distance from the disturbance. Avian species richness and detections increased with distance from the platform, but anuran richness and detections declined with distance. Operational phase did not play a significant role in overall richness or activity patterns of either group. Among birds, insectivore detections increased with distance from the platform, and nectarivores were detected more frequently during the drilling phase. Results demonstrate that acoustic monitoring and soundscape analyses are useful tools for evaluating the impact of development activity on the vocalizing community, and should be implemented as a best practice in monitoring biodiversity and for guiding specific mitigation strategies.     

基于语谱图特征信息分割提取的声景观中鸟类生物多样性分析

声学手段是监测和研究生态系统生物活动规律、评价生态系统健康状况的一种新方法,声景观生态学也是景观生态学的一个新兴研究领域。声景指数是描述复杂的音频数据生态学特征的有效方法,但是,单一的声景指数并不能有效的指示物种的真实丰度。在充分挖掘音频文件时频结构特征的基础上,将遥感领域常用的面向对象图像分割技术引入语谱图分割,并提出了适合于自然界鸟类生物多样性提取的知识规则和斑块统计分析方法。研究实验在杭州植物园的不同区域布点采集音频数据,研究结果表明:鸟类的多样性与地物景观类型和人类活动影响程度密切相关,鸟类叫声的中心频率集中分布在2.5—4.5k Hz之间,最低频率分布在0.67—2.1k Hz之间,最高频率分布在7.6—8.9k Hz之间,人类活动较多的区域,鸟类活动较少且叫声更短促。此外,该方法提取的斑块面积周长比参数,可以定量的反映鸟类叫声的婉转程度。     

Acoustic monitoring reveals diversity and surprising dynamics in tropical freshwater soundscapes

1. Freshwater systems are globally threatened and in need of enhanced monitoring and assessment. We applied soundscape recording and analysis—which presents an opportunity for long-term, high-resolution animal community monitoring and assessment—to a freshwater context to better understand the acoustic diversity and dynamics of these systems.
2. We recorded the aquatic soundscape of a Neotropical freshwater swamp in Costa Rica for 23 days in January and February 2015 during the dry season. We classified biological sound types in these recordings and developed measurements of richness and occupancy based on this classification. We also calculated six complementary acoustic indices to assess soundscape diversity and daily and longer-term soundscape dynamics, and we examined correlations between these acoustic indices and sound type metrics.
3. We found rich soundscapes in which biological sounds were almost always present, and we classified 18 sound types that we attribute to aquatic insects. These sound types showed distinct daily patterns and exhibited temporal and spectral acoustic niche partitioning. Sound type richness was most correlated with the number of peaks index (correlation = .36; p < .001), while sound type occupancy was most correlated with the Bioacoustic Index (correlation = .92; p < .001). In contrast to generally high levels of acoustic activity, there were brief (approximately 1 hr), unexpected quiet periods around dawn and dusk.
4. This study represents an early attempt to comprehensively describe tropical freshwater soundscapes in a systematic and quantitative manner. We demonstrate that sound type classification and the quantification of acoustic occupancy capture aspects of soundscape diversity and dynamics that are complementary to those assessed by acoustic indices. Our analyses reveal that the soundscapes of this tropical wetland were diverse and exhibited daily dynamics that differed from those found in other ecosystems.

     

Visualization of temporal change in soundscape power of a Michigan lake habitat over a 4-year period

Soundscape Ecology is an emerging area of science that does not focus on the identification of species in the soundscape but attempts to characterize sounds by organizing them into those produced by biological organisms such as birds, amphibians, insects or mammals; physical environmental factors such as thunder, rainfall or wind; and sounds produced by human entities such as airplanes, automobiles or air conditioners. The soundscape changes throughout the day and throughout the seasons. The soundscape components that create the sound occur at different frequencies. A set of metrics termed soundscape power was computed and visualized to examine the patterns of daily and seasonal change in the soundscape.Automated recorders were used to record soundscape samples every half hour for one minute duration from six sites on an uninhabited island in Twin Lakes located near Cheboygan in Michigan's northern Lower Peninsula. Each recording was divided into 1 kHz frequency intervals and visualization tools were used to examine the soundscape power in each interval during 48 half-hour time segments from April–October for four consecutive years. Daily patterns of soundscape power change were also examined during the seven month sample period. To synthesize the data set, three dimensional contour plots were used to visualize day of the year (x), time of day (y) and soundscape power (z) for several frequency intervals. A further synthesis was developed to visualize soundscape change using a Normalized Difference Soundscape Index (NDSI) which is a ratio of low to high frequencies.The visualization of the soundscape revealed discrete patterns in the soundscape including striking changes in the time of the occurrence of dawn and dusk choruses. The patterns in the soundscape were remarkably similar over the four-year investigation. Soundscape power in the lower frequency examined (1–2 kHz) was a dominant feature of the soundscape at Twin Lakes and the low frequency soundscape power was negatively correlated with higher frequency sounds.The soundscape power metrics and the visualizations of the soundscape produced in this study should provide a means of rapidly synthesizing large numbers of recordings into meaningful patterns to examine soundscape change. This is especially useful because of the need to develop indices of ecological metrics based on soundscape attributes to assist resource managers in making decisions about ecosystem integrity. Visualization can also be of immense benefit to examine patterns in large soundscape time series data sets that can be produced by automated recording devices.     

城市公园春季声景观与植被结构的关系

城市公园是城市生态系统的重要组成部分和城市生物多样性热点地区,具有丰富的声景观资源。由于声景观及声学方法具有信息量大,成本低,低侵入的特点,因此其研究和应用对生态系统健康及监测具有较高价值。声景观研究通过总结生物声的活动或多样性来衡量生物多样性。记录了北京20个城市公园的春季声景观,使用定量方法描述了声景观特征与变化;测试三种了已被证明与生物多样性相关并被广泛使用的声学指数（BIO、ADI、NDSI）与植被群落关系,完成了城市环境中声景观与环境关系的初步探究。研究结果表明：（1）声学指数能够有效表征城市公园声景观信息,具有显著的时间动态特性,能准确反映鸟类黎明合唱等重要生物生态活动;（2）声学强度指数也具有显著的时间动态变化和沿频率梯度的变化,不同的频率区间反映了不同声学群落的活动信息;（3）植被结构尤其是垂直结构对声景观起着重要作用,垂直异质性越大,声学多样性越高。发现支持声景观作为公园植被状况的度量,强调了其作为生物多样性和生态系统健康状况监测方法,用于城市管理和可持续发展的巨大潜力。     

Acoustic detection and acoustic habitat characterisation of the critically endangered white-bellied heron (Ardea insignis) in Bhutan

1. Growing developmental activities, such as hydropower construction, farm roads, and other human activities, are affecting the critically endangered white-bellied heron (WBH). Out of a known global population of 60, 28 individuals inhabit the river basin area and freshwater lakes and ponds of Bhutan. Several constraints impede continuous monitoring of endangered species, such as the isolated and cryptic nature of the species and the remoteness of its habitat; to date, there are no long-term reference data or techniques implemented for continuous monitoring of this species.
2. In this study, we designed acoustic detection and habitat characterisation methods using long-duration recordings from three habitat areas in Bhutan. Acoustic indices were extracted and used to implement a species-specific call detector and to generate habitat soundscape representations. Using WBH calls annotated in month-long recordings from a known site, a novel indices-based detector was implemented and tested. A total of 960 hr of continuous audio recordings from three habitats in Bhutan were analysed.
3. We found that a species call detector implemented using a combination of acoustic indices (that includes measures of spectral and temporal entropy and different angles of spectral ridges) has a correct detection rate of 81%. Additionally, visual inspection of the species’ acoustic habitat using long-duration false-colour spectrograms enabled qualitative assessment of acoustic habitat structure and other dominant acoustic events.
4. This study proposes a combined approach of species acoustic detection and habitat soundscape analysis for holistic acoustic monitoring of endangered species. As a direct outcome of this work, we documented acoustic reference data on the critically endangered WBH from multiple habitat areas and have analysed its temporal vocalisation patterns across sites.

     

Sensing ecosystem dynamics via audio source separation: A case study of marine soundscapes off northeastern Taiwan

Remote acquisition of information on ecosystem dynamics is essential for conservation management, especially for the deep ocean. Soundscape offers unique opportunities to study the behavior of soniferous marine animals and their interactions with various noise-generating activities at a fine temporal resolution. However, the retrieval of soundscape information remains challenging owing to limitations in audio analysis techniques that are effective in the face of highly variable interfering sources. This study investigated the application of a seafloor acoustic observatory as a long-term platform for observing marine ecosystem dynamics through audio source separation. A source separation model based on the assumption of source-specific periodicity was used to factorize time-frequency representations of long-duration underwater recordings. With minimal supervision, the model learned to discriminate source-specific spectral features and prove to be effective in the separation of sounds made by cetaceans, soniferous fish, and abiotic sources from the deep-water soundscapes off northeastern Taiwan. Results revealed phenological differences among the sound sources and identified diurnal and seasonal interactions between cetaceans and soniferous fish. The application of clustering to source separation results generated a database featuring the diversity of soundscapes and revealed a compositional shift in clusters of cetacean vocalizations and fish choruses during diurnal and seasonal cycles. The source separation model enables the transformation of single-channel audio into multiple channels encoding the dynamics of biophony, geophony, and anthropophony, which are essential for characterizing the community of soniferous animals, quality of acoustic habitat, and their interactions. Our results demonstrated the application of source separation could facilitate acoustic diversity assessment, which is a crucial task in soundscape-based ecosystem monitoring. Future implementation of soundscape information retrieval in long-term marine observation networks will lead to the use of soundscapes as a new tool for conservation management in an increasingly noisy ocean.     

Alpha声学指数效应的meta分析

通过声学指数量化声音的特征反映生物的组成和生境信息,是一种高效率、低干扰的监测方式。该研究领域在近十多年来得到了快速的发展,不断有新的声学指数被提出,同时也有大量的实证研究。声学指数可分为反映录音内信息的alpha声学指数和比较不同录音之间差异的beta声学指数,其中alpha声学指数的实证研究较多。本文在汇总已有研究数据的基础上进行meta分析,关注alpha声学指数与动物多样性、生境质量、动物活跃性之间关联的方向和程度。基于文献调研,本文对8个常用的声学指数进行了总结分析:声学复杂度指数(acoustic complexity index,ACI)、声学熵指数(acoustic entropy index,H)、生物声学指数(bioacoustic index,BI)、标准化声景差异指数(normalized difference soundscape index,NDSI)、声学多样性指数(acoustic diversity index,ADI)、声学均匀度指数(acoustic evenness index,AEI)、声学丰富度指数(acoustic richness ind...     

Measuring community responses to large-scale disturbance in conservation biogeography

Aim   Which community metrics should be used to reflect community response to large-scale habitat alterations is unclear. Here, we assess what and how community changes should be measured to accurately track community responses to large-scale disturbance in space and/or time.
Location   France.
Method   We first developed a simulation model to examine temporal changes in the species composition of large-scale metacommunities. Using this model, we assessed how species richness, Shannon index, trends of particular subset of species or community indices of habitat specialization were influenced by different disturbance scenarios, and whether these indices were biased by imperfect detectability. We further used more than 1000 empirical bird communities from the French Breeding Bird Survey recently exposed to disturbances of various intensities as a case study.
Results   Our simulation and empirical results both demonstrate that species richness and diversity measures can show confusing trends and even provide misleading messages of communities' fate. In contrast, reflecting the composition of the community in terms of habitat specialist and generalist species was more robust and powerful to reflect disturbance effects.
Main conclusions   We highlight the weakness of using community metrics that fail to incorporate ecological difference among species when summarizing community-level trends in disturbed landscapes.     

Acoustic patterns at the Samford Ecological Research Facility in South East Queensland,Australia: The Peri-Urban SuperSite of the Terrestrial Ecosystem Research Network

Acoustic signals that emanate from ecosystems are an important ecological variable which can provide evidence of current ecological condition as well as ecological change over time. The Terrestrial Ecosystem Research Network (TERN) established protocols to record sounds in ten SuperSites distributed throughout Australia with the objective of characterizing the soundscape in a representative landscape in different regions of Australia. This acoustic monitoring system enables a comparison of the soundscapes within and between Australian regions to determine similarities and differences in these landscapes and regions.This research quantifies the soundscape patterns in one of these SuperSites, Samford Ecological Research Facility (TERN-SERF), which is part of the South-East Queensland Peri-Urban SuperSite. An analysis and visualization of patterns in the soundscape was conducted using a continuous acoustic recording collected at TERN-SERF. The recording was made using a Song Meter (SM2) in a representative wooded habitat at TERN-SERF from 1 August to 30 September 2013. The recording was made in 16-bit stereo at 44 kHz and stored in wav file format. The recording was split into 1-minute-long recordings comprising 86,196 records and then sub-sampled at a 30-minute interval, providing 2878 one-minute-long recordings every 1/2 h. Soundscape metrics were computed for each of the two recording intervals. Soundscape power values were computed for each of ten frequency intervals (1–11 kHz) for both the 1-minute and the 30-minute interval recordings. In addition, six acoustic indices were computed from each recording.The acoustics metrics derived from the two sets of recordings (1-minute and 30-minute recording intervals) were examined to determine if they revealed different patterns. Several soundscape metrics were calculated for each recording including ten soundscape power values at 1 kHz frequency intervals and six acoustics indices. The soundscape shows a dynamic but consistent pattern over time of day during the monitoring period, depending on the metric examined. The metrics revealed different soundscape patterns. All soundscape power values at 1 kHz frequency intervals defined the dawn and dusk chorus, some more distinctly than others. Three of six acoustic indices also changed abruptly at the dawn chorus. No significant difference was found when soundscape metrics were compared between the 1-minute (high resolution) and 30-minute (lower resolution) recording intervals. A t-test was used to compare the mean values of ten soundscape power frequency intervals (p = 0.44) and the mean values of six acoustics indices (p = 0.41).Sounds were identified in 180 recordings made at 0530 h, 0600 h and 0630 h in the 1-minute long 30-minute interval recordings each day during the recording period (August and September). Sixty-seven species of birds were identified. Soundscape metrics were correlated with avian species counts and calls by all species using a correlation threshold of r > 0.7. This analysis revealed that soundscape power at the frequency interval 3–4 kHz was correlated with both the number of species (r = − 0.927) and total calls (r = − 0.996) over the three time periods. Three indices, the ADI (r = 0.953, r = 0.709), the AEI (r = 0.978, r = 0.774) and (H) (r = 0.795, r = 0.985) were similarly correlated as was an index derived soundscape power, the Shannon-Weaver Index (r = − 0.997, r = − 0.849). Other indices were correlated (r > 0.7) with only the number of avian species or only the number of calls.This methodology establishes an analysis protocol for analyzing large acoustic data sets, and demonstrates the effectiveness of using acoustic metrics for summarizing and interpreting long-term recordings.     

Contributions of MIR to Soundscape Ecology. Part 2: Spectral timbral analysis for discriminating soundscape components

Soundscape ecology evaluates biodiversity and environmental disturbances by investigating the interaction among soundscape components (biological, geophysical, and human-produced sounds) using data collected with autonomous recording units. Current analyses consider the acoustic properties of frequency and amplitude resulting in varied metrics, but rarely focus on the discrimination of soundscape components. Computational musicologists analyze similar data but consider a third acoustic property, timbre.Here, we investigated the effectiveness of spectral timbral analysis to distinguish among dominant soundscape components. This process included manually labeling and extracting spectral timbral features for each recording. Then, we tested classification accuracy with linear and quadratic discriminant analyses on combinations of spectral timbral features.Different spectral timbral feature groups distinguished between biological, geophysical, and manmade sounds in a single field recording. Furthermore, as we tested different combinations of spectral timbral features that resulted in both high and very low accuracy results, we found that they could be ordered to “sift” out field recordings by individual dominant soundscape component.By using timbre as a new acoustic property in soundscape analyses, we could classify dominant soundscape components effectively. We propose further investigation into a sifting scheme that may allow researchers to focus on more specific research questions such as understanding changes in biodiversity, discriminating by taxonomic class, or to inspect weather-related events.     

Partitioning the diversity of riverine fish: the roles of habitat types and non-native species

1. Quantifying how biological diversity is distributed in the landscape is one of the central themes of conservation ecology. For this purpose, landscape classifications are being intensively used in conservation planning and biodiversity management, although there is still little information about their efficacy. 2. I used data from 158 running water sites in Hungary to examine the contribution of six a priori established habitat types to regional level diversity of fish assemblages. Three community measures [species richness, diversity (Shannon, Simpson indices), assemblage composition] were examined at two assemblage levels (entire assemblage, the native assemblage). The relative role of non‐native species was quantified to examine their contribution to patterns in diversity in this strongly human influenced landscape. 3. Additive diversity partitioning revealed the primary importance of beta diversity (i.e. among‐site factors) to patterns in species richness. Landscape‐scale patterns in species richness were best explained by between‐habitat type (beta₂: 41.2%), followed by within‐habitat type (beta₁: 37.7%) and finally within‐site (alpha: 21.1%) diversity. Diversity indices showed patterns different from species richness, indicating the importance of relative abundance distributions on the results. Exclusion of non‐natives from the analysis gave similar results to the entire‐assemblage level analysis. 4. Canonical analysis of principal coordinates, complemented with indicator species analysis justified the separation of fish assemblages among the habitat types, although classification error was high. Multivariate dispersion, a measure of compositional beta diversity, showed significant differences among the habitat types. Contrary to species diversity (i.e. richness, diversity indices), patterns in compositional diversity were strongly influenced by the exclusion of non‐natives from the analyses. 5. This study is the first to quantify how running water habitat types contribute to fish diversity at the landscape scale and how non‐native species influence this pattern. These results on riverine fish assemblages support the hypothesis that environmental variability (i.e. the diversity of habitat types) is an indication of biodiversity and can be used in large‐scale conservation designs. The study emphasises the joint application of additive diversity partitioning and multivariate statistics when exploring the contribution of landscape components to the overall biodiversity of the landscape mosaic.     

Assessing the value of acoustic indices to distinguish species and quantify activity: A case study using frogs

1. Soundscapes can provide information about a wide range of habitats and species through the recording of vocalisations over long temporal scales. Because of the large volumes of data collected, computational approaches, such as the application of acoustic indices, are required to extract useful information from long-duration recordings.
2. Acoustic indices summarise various soundscape features into frequency ranges over defined time intervals and can aid in the visual exploration, detection, and analysis of species vocalisation patterns. Here, we examine the performance of combinations of three acoustic indices commonly used in visual exploration, the acoustic complexity index, the temporal entropy spectrum index, and the event spectrum index, and assess their ability to distinguish species and describe acoustic features commonly used to detect species and analyse activity. Our case study focuses on three frog species with distinct call structures from Bickerton Island, Northern Territory, Australia. Call structure was categorised based on the number of pulses and harmonics.
3. We summarised acoustic activity by calculating acoustic indices in 256 equal-sized bins over the entire the frequency spectrum, for 30-s intervals, and found that acoustic index values could be used to distinguish species and describe acoustic features. The acoustic complexity index was the most effective index for distinguishing species. To describe acoustic features, we examined correlations between acoustic index values and summarised acoustic features, including call rate, total duration, loudness and signal-to-noise ratio. In single-pulsed species with no harmonics, we found spectral index values were significantly and sometimes strongly correlated with acoustic features. In comparison, species with harmonics were found to be weakly and less frequently correlated with acoustic features even if sampled calls were loud and have high signal-to-noise ratio. We suggest that acoustic indices have the potential to describe acoustic features in single-pulsed species but are limited in those with harmonics.
4. We conclude that acoustic indices can be a useful tool to distinguish some anuran species and to broadly understand specific acoustic features used to analyse calling activity over long periods of time.
5. Further research is required to better understand the relationships between acoustic indices and acoustic features to determine the general utility of indices to detect and distinguish audible species and to identify other acoustic features of various taxa.

     

Twenty‐five years of plant community dynamics and invasion in New Zealand tussock grasslands

Understanding how plant communities respond to plant invasions is important both for understanding community structure and for predicting future ecosystem change. In a system undergoing intense plant invasion for 25 years, we investigated patterns of community change at a regional scale. Specifically, we sought to quantify how tussock grassland plant community structure had changed and whether changes were related to increases in plant invasion. Frequency data for all vascular plants were recorded on 124, permanent transects in tussock grasslands across the lower eastern South Island of New Zealand measured three times over a period of 25 years. Multivariate analyses of species richness were used to describe spatial and temporal patterns in the vegetation. Linear mixed‐effects models were used to relate temporal changes in community structure to the level and rate of invasion of three dominant invasive species in the genus Hieracium while accounting for relationships with other biotic and abiotic variables. There was a strong compositional gradient from exotic‐ to native‐dominated plant communities that correlated with increasing elevation. Over the 25 years, small‐scale species richness significantly decreased and then increased again; however, these changes differed in different plant communities. Exotic species frequency consistently increased on some transects and consistently declined on others. Species richness changes were correlated with the level of Hieracium invasion and abiotic factors, although the relationship with Hieracium changed from negative to positive over time. Compositional changes were not related to measured predictors. Our results suggest that observed broad‐scale fluctuations in species richness and community composition dynamics were not driven by Hieracium invasion. Given the relatively minor changes in community composition over time, we conclude that there is no evidence for widespread degradation of these grasslands over the last 25 years. However, because of continuing weed invasion, particularly at lower elevations, impacts may emerge in the longer term.     

Spatio‐temporal scaling of biodiversity and the species–time relationship in a stream fish assemblage

1. The increase of species richness with the area of the habitat sampled, that is the species–area relationship, and its temporal analogue, the species–time relationship (STR), are among the few general laws in ecology with strong conservation implications. However, these two scale‐dependent phenomena have rarely been considered together in biodiversity assessment, especially in freshwater systems. 2. We examined how the spatial scale of sampling influences STRs for a Central‐European stream fish assemblage (second‐order Bernecei stream, Hungary) using field survey data in two simulation‐based experiments. 3. In experiment one, we examined how increasing the number of channel units, such as riffles and pools (13 altogether), and the number of field surveys involved in the analyses (12 sampling occasions during 3 years), influence species richness. Complete nested curves were constructed to quantify how many species one observes in the community on average for a given number of sampling occasions at a given spatial scale. 4. In experiment two, we examined STRs for the Bernecei fish assemblage from a landscape perspective. Here, we evaluated a 10‐year reach level data set (2000–09) for the Bernecei stream and its recipient watercourse (third‐order Kemence stream) to complement results on experiment one and to explore the mechanisms behind the observed patterns in more detail. 5. Experiment one indicated the strong influence of the spatial scale of sampling on the accumulation of species richness, although time clearly had an additional effect. The simulation methodology advocated here helped to estimate the number of species in a diverse combination of spatial and temporal scale and, therefore, to determine how different scale combinations influence sampling sufficiency. 6. Experiment two revealed differences in STRs between the upstream (Bernecei) and downstream (Kemence) sites, with steeper curves for the downstream site. Equations of STR curves were within the range observed in other studies, predominantly from terrestrial systems. Assemblage composition data suggested that extinction–colonisation dynamics of rare, non‐resident (i.e. satellite) species influenced patterns in STRs. 7. Our results highlight that the determination of species richness can benefit from the joint consideration of spatial and temporal scales in biodiversity inventory surveys. Additionally, we reveal how our randomisation‐based methodology may help to quantify the scale dependency of diversity components (α, β, γ) in both space and time, which have critical importance in the applied context.