Spatio‐temporal scaling of biodiversity in acoustic tropical bird communities

Automated analysis of acoustic communities is a rapidly emerging approach for the characterization and monitoring of biodiversity. To evaluate its utility, we should verify that such ‘bioacoustics’ can accurately detect ecological signal in spatiotemporal acoustic data. Targeting the ‘Biological Dynamics of Forest Fragments Project’ sites in Brazil, we ask: What is the relative contribution of the spatial, temporal and habitat dimension to variation in bird acoustic communities in a previously fragmented tropical rainforest? Does the functional diversity of bird communities scale similarly to space and time as does species diversity, when both are recorded by bioacoustics means? Overall, is the imprint of landscape fragmentation 30 years ago still audible in the present‐day soundscape? We sampled forty‐four sites in secondary forest and 107 sites in old‐growth forest, resulting in 11 000 h of audio recordings. We detected 60 bird species with satisfactory precision and recovered a linear log–log relation between sampling time and species diversity. Sites in primary forest host more species than sites in secondary forest, but the difference decreased with sampling time, as the slope was slightly higher in secondary than primary forests. Functional diversity, as exposed by vocalizing birds, accumulates faster than does species diversity. The similarity among local communities decreases with distance in both time and space, but stability in time is remarkably high: two acoustic samples from the same site one year (or more) apart prove more similar than two samples taken at the same time but from sites situated just a few hundred meters apart. These findings suggest that habitat modification can be heard as a long‐lasting imprint on the soundscape of regenerating habitats and identify soundscape–area and soundscape–time relations as a promising tool for biodiversity research, applied biomonitoring and restoration ecology.     

The theory of the nested species–area relationship: geometric foundations of biodiversity scaling

The relationship between sampled area and the number of species within that area, the species–area relationship (SAR), is a major biodiversity pattern and one of a few law‐like regularities in ecology. While the SAR for isolated units (islands or continents) is assumed to result from the dynamics of species colonization, speciation and extinction, the SAR for contiguous areas in which smaller plots are nested within larger sample areas can be attributed to spatial patterns in the distribution of individuals. The nested SAR is typically triphasic in logarithmic space, so that it increases steeply at smaller scales, decelerates at intermediate scales and increases steeply again at continental scales. I will review current theory for this pattern, showing that all three phases of the SAR can be derived from simple geometric considerations. The increase of species richness with area in logarithmic space is generally determined by overall species rarity, so that the rarer the species are on average, the higher is the local slope z. Rarity is scale‐dependent: species occupy only a minor proportion of area at broad spatial scales, leading to upward accelerating shape of the SAR at continental scales. Similarly, species are represented by only a few individuals at fine spatial scales, leading to high SAR slope also at small areas. Geometric considerations reveal links of the SAR to other macroecological patterns, namely patterns of β‐diversity, the species–abundance distribution, and the relationship between energy availability (or productivity) and species richness. Knowledge of the regularities concerning nested SARs may be used for standardizing unequal areas, upscaling species richness and estimating species loss due to area loss, but all these applications have their limits, which also follow from the geometric considerations.     

Density‐dependent effects of non‐native brown trout Salmo trutta on the species–area relationship in stream fish assemblages

The spatial scale and density‐dependent effects of non‐native brown trout Salmo trutta on species richness of fish assemblages were examined at 48 study sites in Mamachi Stream, a tributary of Chitose River, Hokkaido, Japan. The density of age ≥1 year S. trutta was high in the upstream side of the main stem of Mamachi Stream. Fish species richness increased with increasing area of study sites (habitat size), but the increasing magnitude of the species richness with area decreased with increasing age of ≥1 year S. trutta density. The relationships between age ≥1 year S. trutta, however, and presence–absence of each species seemed to be different among species. Species richness was also determined by location and physical environmental variables, i.e. it was high on the downstream side and in structurally complex environments.     

Plants on small islands revisited: the effects of spatial scale and habitat quality on the species–area relationship

Understanding how species diversity is related to sampling area and spatial scale is central to ecology and biogeography. Small islands and small sampling units support fewer species than larger ones. However, the factors influencing species richness may not be consistent across scales. Richness at local scales is primarily affected by small‐scale environmental factors, stochasticity and the richness at the island scale. Richness at whole‐island scale, however, is usually strongly related to island area, isolation and habitat diversity. Despite these contrasting drivers at local and island scales, island species–area relationships (SARs) are often constructed based on richness sampled at the local scale. Whether local scale samples adequately predict richness at the island scale and how local scale samples influence the island SAR remains poorly understood. We investigated the effects of different sampling scales on the SAR of trees on 60 small islands in the Raja Ampat archipelago (Indonesia) using standardised transects and a hierarchically nested sampling design. We compared species richness at different grain sizes ranging from single (sub)transects to whole islands and tested whether the shape of the SAR changed with sampling scale. We then determined the importance of island area, isolation, shape and habitat quality at each scale on species richness. We found strong support for scale dependency of the SAR. The SAR changed from exponential shape at local sampling scales to sigmoidal shape at the island scale indicating variation of species richness independent of area for small islands and hence the presence of a small‐island effect. Island area was the most important variable explaining species richness at all scales, but habitat quality was also important at local scales. We conclude that the SAR and drivers of species richness are influenced by sampling scale, and that the sampling design for assessing the island SARs therefore requires careful consideration.     

sars: an R package for fitting,evaluating and comparing species–area relationship models

The species–area relationship (SAR) constitutes one of the most general ecological patterns globally. A number of different SAR models have been proposed. Recent work has shown that no single model universally provides the best fit to empirical SAR datasets: multiple models may be of practical and theoretical interest. However, there are no software packages available that a) allow users to fit the full range of published SAR models, or b) provide functions to undertake a range of additional SAR‐related analyses. To address these needs, we have developed the R package ‘sars’ that provides a wide variety of SAR‐related functionality. The package provides functions to: a) fit 20 SAR models using non‐linear and linear regression, b) calculate multi‐model averaged curves using various information criteria, and c) generate confidence intervals using bootstrapping. Plotting functions allow users to depict and scrutinize the fits of individual models and multi‐model averaged curves. The package also provides additional SAR functionality, including functions to fit, plot and evaluate the random placement model using a species–sites abundance matrix, and to fit the general dynamic model of oceanic island biogeography. The ‘sars’ R package will aid future SAR research by providing a comprehensive set of simple to use tools that enable in‐depth exploration of SARs and SAR‐related patterns. The package has been designed to allow other researchers to add new functions and models in the future and thus the package represents a resource for future SAR work that can be built on and expanded by workers in the field.     

Functional redundancy modifies species–area relationship for freshwater phytoplankton

Although species–area relationship (SAR ) is among the most extensively studied patterns in ecology, studies on aquatic and/or microbial systems are seriously underrepresented in the literature. We tested the algal SAR in lakes, pools and ponds of various sizes (10^?2–10⁸ m²) and similar hydromorphological and trophic characteristics using species‐specific data and functional groups. Besides the expectation that species richness increases monotonously with area, we found a right‐skewed hump‐shaped relationship between the area and phytoplankton species richness. Functional richness however did not show such distortion. Differences between the area dependence of species and functional richness indicate that functional redundancy is responsible for the unusual hump‐backed SAR . We demonstrated that the Small Island Effect, which is a characteristic for macroscopic SAR s can also be observed for the phytoplankton. Our results imply a so‐called large lake effect, which means that in case of large lakes, wind‐induced mixing acts strongly against the habitat diversity and development of phytoplankton patchiness and finally results in lower phytoplankton species richness in the pelagial. High functional redundancy of the groups that prefer small‐scale heterogeneity of the habitats is responsible for the unusual humpback relationship. The results lead us to conclude that although the mechanisms that regulate the richness of both microbial communities and communities of macroscopic organisms are similar, their importance can be different in micro‐ and macroscales.     

Niches and neutral processes contribute to the resource–diversity relationships of stream detritivores

1. Explaining resource–diversity relationships is a long‐standing goal in ecology, and there is currently little consensus as to the relative contributions of neutral versus a variety of proposed niche‐related mechanisms. 2. The resource–diversity relationship of insect detritivores was examined in a survey of 25 small, parallel streams flowing into the Bay of Fundy in eastern Canada, with the objective of determining whether neutral processes (sampling effects) could account for the observed patterns. 3. Detritivore taxonomic richness showed a positive, but decelerating relationship with quantity of detritus. Richness also increased with catchment area and with stream permanence. 4. Species distribution patterns were significantly nested, and low resource streams (little detritus) tended to have species with large ranges (i.e. found in many or most streams). 5. Sampling effects could explain only part of the positive relationship between richness and detrital resources, but accounted for the species richness–area relationship. 6. Two mechanisms that could potentially increase niche space as resource abundance increased were rejected: there was no evidence that riparian forest diversity or beta diversity increased with detrital resources. 7. Two niche‐related mechanisms were consistent with existing data, but will require further testing. First, flood disturbance may decrease species richness by eliminating species that require benign habitat, and lowering detritus retention, producing a positive correlation between detritivore richness and resources. Second, large wood in streams located in older riparian forest may increase habitat heterogeneity (number of niches) and the retention of organic matter, again leading to a positive relationship between detritivore diversity and detrital resources. 8. It was concluded that the positive ‘productivity–diversity’ relationship for stream detritivores was most likely produced in part by sampling effects, but also by ecological processes (disturbance and succession) that simultaneously influence resource level and niche availability.     

Island biogeography is not a single‐variable discipline: the small island effect debate

In some island systems, an ‘anomalous’ feature of species richness on smaller islands, in comparison with larger ones, has been observed. This has been described as the small island effect (SIE). The precise meaning of the term remains unresolved, as does the explanation for the phenomenon and even whether it exists. Dengler (2010 ; Diversity Distrib, 16 , 256–266.) addresses a number of conceptual and methodological issues concerning the nature and the detection of the SIE but fails to settle conclusively most of the issues he raises. We contend that his approach is theoretically flawed, especially in its treatment of habitat diversity. We offer a few suggestions of what is needed to advance understanding of the SIE.