Summary
1. Data on the occurrence of species in grid cells are collected by biological recording schemes, typically with the intention of publishing an atlas. Interpretation of such data is often ...hampered by the lack of information on the effort that went into collecting them. This is the ‘recorder effort problem’.
2. One measure of recorder effort is the proportion of a suite of common species (‘benchmark species’) found at a given location and time. Benchmark species have in the past been taken as a uniform set across a territory. However, if records are available from a neighbourhood surrounding a given location, then a local set benchmark species can be defined by pooling records from the neighbourhood and selecting the commonest species in the pooled set.
3. Neighbourhoods differ in species richness, so that the list of species that ‘ought’ to be found in one location may be longer than that for another. If the richness of a neighbourhood can be estimated, then a suite of benchmark species can be standardized to be the commonest of a fixed proportion of the total expected for the neighbourhood. Recording effort is then defined as the proportion of benchmark species that were found.
4. A method of estimating species richness is proposed here, based on the local frequencies fj of species in neighbouring grid cells. Species discovery is modelled as a Poisson process. It is argued that when a neighbourhood is well sampled, the frequency‐weighted mean frequency /∑fj of species in the neighbourhood will assume a standard value.
5. The method was applied to a data set of 2 000 000 records detailing the occurrence of bryophytes in 3695 out of the total 3854 hectads (10‐km squares) in Great Britain, Ireland, the Isle of Man and the Channel Islands.
6. Three main applications are outlined: estimation of recording effort, scanning data for unexpected presences or absences and measurement of species trends over time. An explicit statistical model was used to estimate trends, modelling the probability of species j being found at location i and time t as the outcome of Poisson process with intensity Qijtxjt, where xjt is a time factor for species j, and Qijt depends on recording effort at location i and time t and on the time‐independent probability of species j being found in hectad i.
The slope and aspect of a vegetated surface strongly affects the amount of solar radiation intercepted by that surface. Solar radiation is the dominant component of the surface energy balance and ...influences ecologically critical factors of microclimate, including near-surface temperatures, evaporative demand and soil moisture content. It also determines the exposure of vegetation to photosynthetically active and ultra-violet wavelengths. Spatial variation in slope and aspect is therefore a key determinant of vegetation pattern, species distribution and ecosystem processes in many environments. Slope and aspect angle may vary considerably over distances of a few metres, and fine-scale species’ distribution patterns frequently follow these topographic patterns. The availability of suitable microclimate at such scales may be critical for the response of species distributions to climatic change at much larger spatial scales. However, quantifying the relevant microclimatic gradients is not straightforward, as the potential variation in solar radiation flux under clear-sky conditions is modified by local and regional variations in cloud cover, and interacts with long-wave radiation exchange, local meteorology and surface characteristics.
We tested simple models of near-surface temperature and potential evapotranspiration driven by meteorological data with the incoming solar radiation flux adjusted for topography against measurements of temperature and soil moisture at two chalk grassland field sites in contrasting regional climates of the United Kingdom. We then estimated the cumulative distribution function of three key ecological variables (monthly temperature sums above 5 and 30
°C, plus potential evapotranspiration) across areas of complex topography at each site using two separate approaches: a spatially explicit and a spatially implicit method. The spatially explicit method uses digital elevation models of the sites to calculate the solar radiation at each grid cell and hence determines the spatial distribution of environmental variables. The second, less computationally intensive, method uses estimated statistical distributions of slope and aspect within the field sites to calculate the proportion of the surface area of each site predicted to exceed a given threshold of temperature sum or potential evapotranspiration. The spatially implicit model reproduces the range of the explicit model reasonably well but is limited by the parameterisation of slope and aspect, underlining the importance of variation in topography in determining the microclimatic conditions of a site.
1 The species composition of fragmented semi-natural grasslands may change over time due to stochastic local extinction and colonization events, successional change and/or as a response to changing ...management or abiotic conditions. The resistance of vegetation to change may be mediated through the effects of topography (slope and aspect) on soils and microclimate. 2 To assess long-term vegetation change in British chalk grasslands, 92 plots first surveyed by F. H. Perring in 1952-53, and distributed across four climatic regions, were re-surveyed during 2001-03. Changes in vegetation since the original survey were assessed by comparing local colonization and extinction rates at the plot scale, and changes in species frequency at the subplot scale. Vegetation change was quantified using indirect ordination (Detrended Correspondence Analysis; DCA) and Ellenberg indicator values. 3 Across all four regions, there was a significant decrease in species number and a marked decline in stress-tolerant species typical of species-rich calcareous grasslands, both in terms of decreased plot occupancy and decreased frequency within occupied plots. More competitive species typical of mesotrophic grasslands had colonized plots they had not previously occupied, but had not increased significantly in frequency within occupied plots. 4 A significant increase in Ellenberg fertility values, which was highly correlated with the first DCA axis, was found across all regions. The magnitude of change of fertility and moisture values was found to decrease with angle of slope and with a topographic solar radiation index derived from slope and aspect. 5 The observed shift from calcareous grassland towards more mesotrophic grassland communities is consistent with the predicted effects of both habitat fragmentation and nutrient enrichment. It is hypothesized that chalk grassland swards on steeply sloping ground are more resistant to invasion by competitive grass species than those on flatter sites due to phosphorus limitation in shallow minerogenic rendzina soils, and that those with a southerly aspect are more resistant due to increased magnitude and frequency of drought events.
Arc is an activity-regulated neuronal protein, but little is known about its interactions, assembly into multiprotein complexes, and role in human disease and cognition. We applied an integrated ...proteomic and genetic strategy by targeting a tandem affinity purification (TAP) tag and Venus fluorescent protein into the endogenous Arc gene in mice. This allowed biochemical and proteomic characterization of native complexes in wild-type and knockout mice. We identified many Arc-interacting proteins, of which PSD95 was the most abundant. PSD95 was essential for Arc assembly into 1.5-MDa complexes and activity-dependent recruitment to excitatory synapses. Integrating human genetic data with proteomic data showed that Arc-PSD95 complexes are enriched in schizophrenia, intellectual disability, autism, and epilepsy mutations and normal variants in intelligence. We propose that Arc-PSD95 postsynaptic complexes potentially affect human cognitive function.
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•TAP tag and purification of endogenous Arc protein complexes from the mouse brain•PSD95 is the major Arc binding protein, and both assemble into 1.5-MDa supercomplexes•PSD95 is essential for recruitment of Arc to synapses•Mutations and genetic variants in Arc-PSD95 are linked to cognition
Fernández et al. use genetics and proteomics to study the Arc protein in the mouse brain. PSD95 recruits Arc to the synapse and assembles it into signaling complexes with neurotransmitter receptors and other proteins. Arc-PSD95 supercomplexes contain genetic variants previously linked to epilepsy, schizophrenia, intellectual disability, and IQ.
Despite the essential role of plasma cells in health and disease, the cellular mechanisms controlling their survival and secretory capacity are still poorly understood. Here, we identified the ...soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) Sec22b as a unique and critical regulator of plasma cell maintenance and function. In the absence of Sec22b, plasma cells were hardly detectable and serum antibody titers were dramatically reduced. Accordingly,
-deficient mice fail to mount a protective immune response. At the mechanistic level, we demonstrated that Sec22b contributes to efficient antibody secretion and is a central regulator of plasma cell maintenance through the regulation of their transcriptional identity and of the morphology of the endoplasmic reticulum and mitochondria. Altogether, our results unveil an essential and nonredundant role for Sec22b as a regulator of plasma cell fitness and of the humoral immune response.
1. Biodiversity is changing at unprecedented rates, and it is increasingly important that these changes are quantified through monitoring programmes. Previous recommendations for developing or ...enhancing these programmes focus either on the end goals, that is the intended use of the data, or on how these goals are achieved, for example through volunteer involvement in citizen science, but not both. These recommendations are rarely prioritized. 2. We used a collaborative approach, involving 52 experts in biodiversity monitoring in the UK, to develop a list of attributes of relevance to any biodiversity monitoring programme and to order these attributes by their priority. We also ranked the attributes according to their importance in monitoring biodiversity in the UK. Experts involved included data users, funders, programme organizers and participants in data collection. They covered expertise in a wide range of taxa. 3. We developed a final list of 25 attributes of biodiversity monitoring schemes, ordered from the most elemental (those essential for monitoring schemes; e.g. articulate the objectives and gain sufficient participants) to the most aspirational (e.g. electronic data capture in the field, reporting change annually). This ordered list is a practical framework which can be used to support the development of monitoring programmes. 4. People's ranking of attributes revealed a difference between those who considered attributes with benefits to end users to be most important (e.g. people from governmental organizations) and those who considered attributes with greatest benefit to participants to be most important (e.g. people involved with volunteer biological recording schemes). This reveals a distinction between focussing on aims and the pragmatism in achieving those aims. 5. Synthesis and applications. The ordered list of attributes developed in this study will assist in prioritizing resources to develop biodiversity monitoring programmes (including citizen science). The potential conflict between end users of data and participants in data collection that we discovered should be addressed by involving the diversity of stakeholders at all stages of programme development. This will maximize the chance of successfully achieving the goals of biodiversity monitoring programmes.
Summary
Clustering multivariate species data can be an effective way of showing groups of species or samples with similar characteristics. Most current techniques classify the samples first and then ...the species. A disadvantage of classifying the samples first is that relatively subtle differences between occurrence profiles of species can be obscured.
The k‐means method of clustering minimizes the sum of squared distances between cluster centres and cluster members. If the entities to be clustered are projected on the unit sphere, then a natural measure of dispersion is the sum of squared chord distances separating the entities from their cluster centres; k‐means clustering with this measure of dispersion is called spherical k‐means (SKM). We also consider a variant in which the sum of squared perpendicular distances to a central ray is minimized.
Unweighted SKM is liable to produce clusters of very rare species. This feature can be avoided if each point on the unit sphere is weighted by the length of the ray that produced it. The standard SKM algorithm converges to very numerous local optima. To avoid this problem, we have developed a computationally intensive algorithm that uses multiple randomizations to select high‐quality seed species.
The species clustering can be used to define simplified attributes for the samples. If the samples are then classified using the same technique, the resulting matrix of clustered species and clustered samples provides a biclustering of the data. The strength of the relationship between clusters can be measured by their mutual information, which is effectively the entropy of the biclustering.
The technique was tested on five ecological and biogeographical datasets ranging in size from 30 species in 20 samples to 1405 species in 3857 samples. Several variants of SKM were compared, together with results from the established program Twinspan. When judged by entropy, SKM always performed adequately and produced the best clustering in all datasets but the smallest.
To identify floristic elements in the European flora by an analysis of the distributions of species and species groups mapped in Atlas Florae Europaeae. Europe, as defined by Flora Europaea. We ...analysed the native distributions of 2762 species and 33 species' aggregates from 79 families, which represent c. 20% of the European flora. The distributional data base, derived from Atlas Florae Europaeae, includes records from 4420 50 x 50-km UTM grid squares. We classified species into floristic elements by a three-stage clustering procedure, which consisted of: (1) constructing a dissimilarity hierarchy by complete linkage clustering, using a distance measure based on Jaccard's coefficient; (2) cutting the hierarchical tree at the 0.95 level to create initial clusters, and forcing small clusters to link with larger ones until the sum of within-group pairwise distances exceeded a threshold value; and (3) checking the allocation of all species to the redefined clusters and reassigning species if appropriate, using the cosine of the angle between the species and cluster centres to measure the similarity of species to clusters. The clustering procedure classified 2793 taxa into 18 floristic elements, which included between 66 and 289 taxa; two species had unique, non-overlapping distributions and could not be classified. The analysis highlights the floristic diversity of the mountains of central and southern Europe, and of the Mediterranean region. The floristic elements of northern latitudes and the temperate lowlands tend to be composed of wide-ranging species and include only a low proportion of European endemics. The montane elements, including those centred on montane areas in the Mediterranean region, are composed predominantly of perennial species and include high or very high proportions of European endemics. Classifications that recognize one 'Alpine' and one 'Mediterranean' biogeographical zone in Europe fail to reflect this floristic diversity.
1. Ellenberg's indicator values scale the flora of a region along gradients reflecting light, temperature, continentality, moisture, soil pH, fertility and salinity. They can be used to monitor ...environmental change. 2. Ellenberg values can be extended from central Europe, for which they were defined, to nearby parts of Europe. Given a database of quadrat samples, they can be repredicted by a simple algorithm consisting of two-way weighted averaging, followed by local regression. 3. A database of British samples was assembled from two large surveys. Ellenberg values were repredicted. 4. Except for the indicator of continentality, the correlation of repredicted and original values was in the range 0.72 (light) to 0.91 (moisture). The continentality indicator could not be adequately repredicted by the algorithm, and is unusable in Britain. 5. Discrepancies between original and repredicted values can be attributed to various causes, including wrong original values, differing ecological requirements in Britain and central Europe, biased sampling of the British range of habitats, and the occurrence of small plants in shaded or basic microhabitats within well illuminated or predominantly acid quadrats. 6. The repredicted values were generally reliable, but a small proportion was clearly wrong. Wrong values were due to either inadequate sampling of species' realized niches in Britain or sampling with quadrats that were too large and included species that were not close associates.
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