Disturbance alters beta-diversity but not the relative importance of community assembly mechanisms

Ecological disturbances are often hypothesized to alter community assembly processes that influence variation in community composition (β-diversity). Disturbance can cause convergence in community composition (low β-diversity) by increasing niche selection of disturbance-tolerant species. Alternatively, disturbance can cause divergence in community composition (high β-diversity) by increasing habitat filtering across environmental gradients. However, because disturbance may also influence β-diversity through random sampling effects owing to changes in the number of individuals in local communities (community size) or abundances in the regional species pool, observed patterns of β-diversity alone cannot be used to unambiguously discern the relative importance of community assembly mechanisms. We compared β-diversity of woody plants and inferred assembly mechanisms among unburned forests and forests managed with prescribed fires in the Missouri Ozarks, USA. Using a null-model approach, we compared how environmental gradients influenced β-diversity after controlling for differences in local community size and regional species abundances between unburned and burned landscapes. Observed β-diversity was higher in burned landscapes. However, this pattern disappeared or reversed after controlling for smaller community size in burned landscapes. β-diversity was higher than expected by chance in both landscapes, indicating an important role for processes that create clumped species distributions. Moreover, fire appeared to decrease clumping of species at broader spatial scales, suggesting homogenization of community composition through niche selection of disturbance-tolerant species. Environmental variables, however, explained similar amounts of variation in β-diversity in both landscapes, suggesting that disturbance did not alter the relative importance of habitat filtering. Our results indicate that contingent responses of communities to fire reflect a combination of fire-induced changes in local community size and scale-dependent effects of fire on species clumping across landscapes. Synthesis. Although niche-based mechanisms of community assembly are often invoked to explain changes in community composition following disturbance, our results suggest that these changes also arise through random sampling effects owing to the influence of disturbance on community size. Comparative studies of these processes across disturbed ecosystems will provide important insights into the ecological conditions that determine when disturbance alters the interplay of deterministic and stochastic processes in natural and human-modified landscapes

A synthesis of plant invasion effects on biodiversity across spatial scales

PREMISE OF THE STUDY: Invasive plant species are typically thought to pose a large threat to native biodiversity, and local-scale studies typically confirm this view. However, plant invaders rarely cause regional extirpations or global extinctions, causing some to suggest that invasive species\u27 influence on native biodiversity may not be so dire. We aim to synthesize the seemingly conflicting literature in plant invasion biology by evaluating the effects of invasive plant species across spatial scales. METHODS: We first conducted a meta-analysis on the effects of invasive plants on the species richness of invaded communities across a range of spatial extents. We then discuss studies that consider the role of invasive plants on regional spatial scales for which such meta-analyses are not possible. Finally, we develop a conceptual framework to synthesize the influence of invasive species across spatial scales by explicitly recognizing how invasive species alter species-occupancy distributions. KEY RESULTS: We found a negative relationship between the spatial extent of the study and the effect size of invasive plants on species richness. Our simulation models suggest that this result can occur if invaders, either proportionately or disproportionately, reduce the occupancy of common species to a greater degree than rare species. CONCLUSIONS: Future studies should consider the influence of invaders on the abundance and occupancy-level changes in native species to inform how invasive plants will influence native species richness relationships across spatial scales. This approach will allow greater predictive ability for forecasting changes in biodiversity in the face of anthropogenic biological invasions and will inform invasive species management and restoration

Scale-dependent effect sizes of ecological drivers on biodiversity: why standardised sampling is not enough

Abstract There is little consensus about how natural (e.g. productivity, disturbance) and anthropogenic (e.g. invasive species, habitat destruction) ecological drivers influence biodiversity. Here, we show that when sampling is standardised by area (species density) or individuals (rarefied species richness), the measured effect sizes depend critically on the spatial grain and extent of sampling, as well as the size of the species pool. This compromises comparisons of effects sizes within studies using standard statistics, as well as among studies using meta-analysis. To derive an unambiguous effect size, we advocate that comparisons need to be made on a scale-independent metric, such as Hurlbert's Probability of Interspecific Encounter. Analyses of this metric can be used to disentangle the relative influence of changes in the absolute and relative abundances of individuals, as well as their intraspecific aggregations, in driving differences in biodiversity among communities. This and related approaches are necessary to achieve generality in understanding how biodiversity responds to ecological drivers and will necessitate a change in the way many ecologists collect and analyse their data

Revisiting global trends in freshwater insect biodiversity: A reply

Abstract Jähnig et al. make some useful points regarding the conclusions that can be drawn from our meta‐analysis; however, some issues require clarification. First, we never suggested that there was a globally increasing trend of freshwater insect abundances, but only spoke of an average increasing trend in the available data. We also did not suggest that freshwater quality has improved globally, but rather that documented improvements in water quality can explain at least some of the trends we observed. Second, as we acknowledged, our data are not a representative set of freshwater ecosystems around the world, but they are what is currently accessible. Third, there is indeed no doubt that changes in abundance or biomass need not correlate with changes in other aspects of biodiversity, such as species richness or functional composition. Our analysis was specifically focused on trends in community abundance/biomass because it has been the subject of recent study and speculation, and is a widely available metric in long‐term studies. To better understand the recent changes in freshwater insect assemblages, we encourage freshwater ecologists to further open their troves of data from countless long‐term monitoring schemes so that larger and more comprehensive syntheses can be undertaken

All together now : limitations and recommendations for the simultaneous analysis of all eukaryotic soil sequences

The soil environment contains a large, but historically underexplored, reservoir of biodiversity. Sequencing prokaryotic marker genes has become commonplace for the discovery and characterization of soil bacteria and archaea. Increasingly, this approach is also applied to eukaryotic marker genes to characterize the diversity and distribution of soil eukaryotes. However, understanding the properties and limitations of eukaryotic marker sequences is essential for correctly analysing, interpreting, and synthesizing the resulting data. Here, we illustrate several biases from sequencing data that affect measurements of biodiversity that arise from variation in morphology, taxonomy and phylogeny between organisms, as well as from sampling designs. We recommend analytical approaches to overcome these limitations, and outline how the benchmarking and standardization of sequencing protocols may improve the comparability of the data

Effects of site‐selection bias on estimates of biodiversity change

Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site‐selection biases influence estimates of biodiversity change is largely unknown. Site‐selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site‐selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site‐selection bias. We used a simple spatially resolved, individual‐based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site‐selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300–400% compared with randomly selected sites. Based on our simulations, site‐selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of −0.1 to −0.2 on average. Thus, site‐selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site‐selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site‐selection bias, we recommend use of systematic site‐selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site‐selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data

Bayesian High-Redshift Quasar Classification from Optical and Mid-IR Photometry

We identify 885,503 type 1 quasar candidates to i<22 using the combination of optical and mid-IR photometry. Optical photometry is taken from the Sloan Digital Sky Survey-III: Baryon Oscillation Spectroscopic Survey (SDSS-III/BOSS), while mid-IR photometry comes from a combination of data from the Wide-Field Infrared Survey Explorer (WISE) "ALLWISE" data release and several large-area Spitzer Space Telescope fields. Selection is based on a Bayesian kernel density algorithm with a training sample of 157,701 spectroscopically-confirmed type-1 quasars with both optical and mid-IR data. Of the quasar candidates, 733,713 lack spectroscopic confirmation (and 305,623 are objects that we have not previously classified as photometric quasar candidates). These candidates include 7874 objects targeted as high probability potential quasars with 3.5<z<5 (of which 6779 are new photometric candidates). Our algorithm is more complete to z>3.5 than the traditional mid-IR selection "wedges" and to 2.2<z<3.5 quasars than the SDSS-III/BOSS project. Number counts and luminosity function analysis suggests that the resulting catalog is relatively complete to known quasars and is identifying new high-z quasars at z>3. This catalog paves the way for luminosity-dependent clustering investigations of large numbers of faint, high-redshift quasars and for further machine learning quasar selection using Spitzer and WISE data combined with other large-area optical imaging surveys.Comment: 54 pages, 17 figures; accepted by ApJS Data for tables 1 and 2 available at http://www.physics.drexel.edu/~gtr/outgoing/optirqsos/data/master_quasar_catalogs.011414.fits.bz2 and http://www.physics.drexel.edu/~gtr/outgoing/optirqsos/data/optical_ir_quasar_candidates.052015.fits.bz

Mechanistic reconciliation of community and invasion ecology

Community and invasion ecology have mostly grown independently. There is substantial overlap in the processes captured by different models in the two fields, and various frameworks have been developed to reduce this redundancy and synthesize information content. Despite broad recognition that community and invasion ecology are interconnected, a process-based framework synthesizing models across these two fields is lacking. Here we review 65 representative community and invasion models and propose a common framework articulated around six processes (dispersal, drift, abiotic interactions, within-guild interactions, cross-guild interactions, and genetic changes). The framework is designed to synthesize the content of the two fields, provide a general perspective on their development, and enable their comparison. The application of this framework and of a novel method based on network theory reveals some lack of coherence between the two fields, despite some historical similarities. Community ecology models are characterized by combinations of multiple processes, likely reflecting the search for an overarching theory to explain community assembly and structure, drawing predominantly on interaction processes, but also accounting largely for the other processes. In contrast, most models in invasion ecology invoke fewer processes and focus more on interactions between introduced species and their novel biotic and abiotic environment. The historical dominance of interaction processes and their independent developments in the two fields is also reflected in the lower level of coherence for models involving interactions, compared to models involving dispersal, drift, and genetic changes. It appears that community ecology, with a longer history than invasion ecology, has transitioned from the search for single explanations for patterns observed in nature to investigate how processes may interact mechanistically, thereby generating and testing hypotheses. Our framework paves the way for a similar transition in invasion ecology, to better capture the dynamics of multiple alien species introduced in complex communities. Reciprocally, applying insights from invasion to community ecology will help us understand and predict the future of ecological communities in the Anthropocene, in which human activities are weakening species' natural boundaries. Ultimately, the successful integration of the two fields could advance a predictive ecology that is urgently required in a rapidly changing world

Mediterranean marine protected areas have higher biodiversity via increased evenness, not abundance

1. Protected areas are central to biodiversity conservation. For marine fish, marine protected areas (MPAs) often harbour more individuals, especially of species targeted by fisheries. But precise pathways of biodiversity change remain unclear. For example, how local-scale responses combine to affect regional biodiversity, important for managing spatial networks of MPAs, is not well known. Protection potentially influences three components of fish assemblages that determine how species accumulate with sampling effort and spatial scale: the total number of individuals, the relative abundance of species and within-species aggregation. Here, we examined the contributions of each component to species richness changes inside MPAs as a function of spatial scale. 2. Using standardized underwater visual survey data, we measured the abundance and species richness of reef fishes in 43 protected and 41 fished sites in the Mediterranean Sea. 3. At both local and regional scales, increased species evenness caused by added common species in MPAs compared to fished sites was the most important proximate driver of higher diversity. 4. Site-to-site variation in the composition (i.e. β-diversity) of common species was also higher among protected sites, and depended on sensitivity to exploitation. There were more abundant exploited species at regional scales than at local scales, reflecting a tendency for different protected sites to harbour different exploited species. In contrast, fewer abundant unexploited species were found at the regional scale than at the local scale, meaning that relative abundances at the regional scale were less even than at the local scale. 5. Synthesis and applications. Although marine protected areas (MPAs) are known to strongly influence fish community abundance and biomass, we found that changes to the relative abundance of species (i.e. increased evenness) dominated the biodiversity response to protection. MPAs had more relatively common species, which in turn led to higher diversity for a given sampling effort. Moreover, higher β-diversity of common species meant that local-scale responses were magnified at the regional scale due to site-to-site variation inside protected areas for exploited species. Regional conservation efforts can be strengthened by examining how multiple components of biodiversity respond to protection across spatial scales

The recovery of plant community composition following passive restoration across spatial scales

Human impacts have led to dramatic biodiversity change which can be highly scale-dependent across space and time. A primary means to manage these changes is via passive (here, the removal of disturbance) or active (management interventions) ecological restoration. The recovery of biodiversity, following the removal of disturbance, is often incomplete relative to some kind of reference target. The magnitude of recovery of ecological systems following disturbance depends on the landscape matrix and many contingent factors. Inferences about recovery after disturbance and biodiversity change depend on the temporal and spatial scales at which biodiversity is measured. We measured the recovery of biodiversity and species composition over 33 years in 17 temperate grasslands abandoned after agriculture at different points in time, collectively forming a chronosequence since abandonment from 1 to 80 years. We compare these abandoned sites with known agricultural land-use histories to never-disturbed sites as relative benchmarks. We specifically measured aspects of diversity at the local plot-scale (α-scale, 0.5 m2) and site-scale (γ-scale, 10 m2), as well as the within-site heterogeneity (β-diversity) and among-site variation in species composition (turnover and nestedness). At our α-scale, sites recovering after agricultural abandonment only had 70% of the plant species richness (and ~30% of the evenness), compared to never-ploughed sites. Within-site β-diversity recovered following agricultural abandonment to around 90% after 80 years. This effect, however, was not enough to lead to recovery at our γ-scale. Richness in recovering sites was ~65% of that in remnant never-ploughed sites. The presence of species characteristic of the never-disturbed sites increased in the recovering sites through time. Forb and legume cover declines in years since abandonment, relative to graminoid cover across sites. Synthesis. We found that, during the 80 years after agricultural abandonment, old fields did not recover to the level of biodiversity in remnant never-ploughed sites at any scale. β-diversity recovered more than α-scale or γ-scale. Plant species composition recovered, but not completely, over time, and some species groups increased their cover more than others. Patterns of ecological recovery in degraded ecosystems across space and long time-scales can inform targeted active restoration interventions and perhaps, lead to better outcomes