Algal epiphytes of Zostera marina: Variation in assemblage structure from individual leaves to regional scale

Data from a hierarchical study of four Zostera marina beds in Wales were used to identify the spatial scales of variation in epiphyte assemblages. There were significant within and among bed differences in assemblage structure. The differences in assemblage structure with spatial scale generally persisted when species identifications were aggregated into functional groups. There was also significant within and among bed variability in Zostera density and average length. Local variations in Zostera canopy variables at the quadrat scale (total leaf length, average leaf length and leaf density per quadrat) were not related to epiphyte species richness nor to the structure of the assemblage. In contrast, individual leaf length was significantly related to species richness in two of the beds and the structure of epiphyte assemblages was always related to individual leaf lengths. The absence of links between quadrat scale measurements of canopy variables and assemblage structure may reflect the high turnover of individual Zostera leaves. Experimental work is required to discriminate further between the potential causes of epiphyte assemblage variation within and between beds. No bed represented a refuge where a rare species was abundant. If a species was uncommon at the bed scale, it was also uncommon in beds where it occurred. The heterogeneous assemblages found in this study suggest that a precautionary approach to conservation is advisable.

The geographical structure of British bird distributions:diversity, spatial turnover and scale

1. Using data on the spatial distribution of the British avifauna, we address three basic questions about the spatial structure of assemblages: (i) Is there a relationship between species richness (alpha diversity) and spatial turnover of species (beta diversity)? (ii) Do high richness locations have fewer species in common with neighbouring areas than low richness locations?, and (iii) Are any such relationships contingent on spatial scale (resolution or quadrat area), and do they reflect the operation of a particular kind of species-area relationship (SAR)?

2. For all measures of spatial turnover, we found a negative relationship with species richness. This held across all scales, with the exception of turnover measured as beta (sim).

3. Higher richness areas were found to have more species in common with neighbouring areas.

4. The logarithmic SAR fitted better than the power SAR overall, and fitted significantly better in areas with low richness and high turnover.

5. Spatial patterns of both turnover and richness vary with scale. The finest scale richness pattern (10 km) and the coarse scale richness pattern (90 km) are statistically unrelated. The same is true of the turnover patterns.

6. With coarsening scale, locations of the most species-rich quadrats move north. This observed sensitivity of richness 'hotspot' location to spatial scale has implications for conservation biology, e.g. the location of a reserve selected on the basis of maximum richness may change considerably with reserve size or scale of analysis.

7. Average turnover measured using indices declined with coarsening scale, but the average number of species gained or lost between neighbouring quadrats was essentially scale invariant at 10-13 species, despite mean richness rising from 80 to 146 species (across an 81-fold area increase). We show that this kind of scale invariance is consistent with the logarithmic SAR.

Predicting critical source areas of sediment in headwater catchments

Mitigation of diffuse nutrient and sediment delivery to streams requires successful identification andmanagement of critical source areas within catchments. Approaches to predicting high risk areas forsediment loss have typically relied on structural drivers of connectivity and risk, with little considera-tion given to process driven water quality responses. To assess the applicability of structural metrics topredict critical source areas, geochemical tracing of land use sources was conducted in three headwateragricultural catchments in Co. Down and Co. Louth, Ireland, within a Monte Carlo framework. Outputswere applied to the inverse optimisation of a connectivity model, based on LiDAR DEM data, to assess theefficacy of land use risk weightings to predict sediment source contributions over the 18 month studyperiod in the Louth Upper, Louth Lower and Down catchments. Results of the study indicated sedimentproportions over the study period varied from 6 to 10%, 84 to 87%, 4%, and 2 to 3% for the Down Catch-ment, 79 to 85%, 9 to 17%, 1 to 3% and 2 to 3% in the Louth Upper and 2 to 3%, 79 to 85%, 10 to 17%and 2 to 3% in the Louth Lower for arable, channel bank, grassland, and woodland sources, respectively.Optimised land use risk weightings for each sampling period showed that at the larger catchment scale,no variation in median land use weightings were required to predict land use contributions. However,for the two smaller study catchments, variation in median risk weightings was considerable, which mayindicate the importance of functional connectivity processes at this spatial scale. In all instances, arableland consistently generated the highest risk of sediment loss across all catchments and sampling times.This study documents some of the first data on sediment provenance in Ireland and indicates the needfor cautious consideration of land use as a tool to predict critical source areas at the headwater scale

Plant community assembly at small scales: spatial versus environmental factors in a central European grassland

Dispersal limitation and environmental conditions are crucial drivers of plant species distribution and establishment. As these factors operate at different spatial scales, we asked: Do the environmental factors known to determine community assembly at broad scales operate at fine scales (few meters)? How much do these factors account for community variation at fine scales? In which way do biotic and abiotic interactions drive changes in species composition? We surveyed the plant community within a dry grassland along a very steep gradient of soil characteristics like pH and nutrients. We used a spatially explicit sampling design, based on three replicated macroplots of 15x15, 12x12 and 12x12 meters in extent. Soil samples were taken to quantify several soil properties (carbon, nitrogen, plant available phosphorus, pH, water content and dehydrogenase activity as a proxy for overall microbial activity). We performed variance partitioning to assess the effect of these variables on plant composition and statistically controlled for spatial autocorrelation via eigenvector mapping. We also applied null model analysis to test for non-random patterns in species co-occurrence using randomization schemes that account for patterns expected under species interactions. At a fine spatial scale, environmental factors explained 18% of variation when controlling for spatial autocorrelation in the distribution of plant species, whereas purely spatial processes accounted for 14% variation. Null model analysis showed that species spatially segregated in a non-random way and these spatial patterns could be due to a combination of environmental filtering and biotic interactions. Our grassland study suggests that environmental factors found to be directly relevant in broad scale studies are present also at small scales, but are supplemented by spatial processes and more direct interactions like competition.

Are Northern Ireland’s communities dividing? Evidence from geographically consistent Census of Population data, 1971–2001

There is an extensive literature on various aspects of segregation in Northern Ireland (NI). However, there are no census-based analyses of population change and residential segregation that cover the entire 1971 – 2001 period using consistent geographical units through time for all NI. This shortcoming is addressed in this paper by an analysis of changes in (ihs1) the spatial distribution of population and (iihs1) residential segregation between 1971 and 2001 using the NI Grid-Square Product comprising data for a set of 1 rm km2 cells that cover all populated areas in NI. The substantive issue of whether NI has become more segregated through time is addressed as are questions about measuring change through time using the census and the importance of spatial scale. One important conclusion is that NI indeed became more residentially segregated between 1971 and 2001, but that residential segregation in 2001 remained approximately at its 1991 level according to most indicators.

Observational tests of interstellar methanol formation

Context. It has been established that the classical gas-phase production of interstellar methanol (CH3OH) cannot explain observed abundances. Instead it is now generally thought that the main formation path has to be by successive hydrogenation of solid CO on interstellar grain surfaces. Aims. While theoretical models and laboratory experiments show that methanol is efficiently formed from CO on cold grains, our aim is to test this scenario by astronomical observations of gas associated with young stellar objects (YSOs). Methods. We have observed the rotational transition quartets J = 2K – 1K of 12CH3OH and 13CH3OH at 96.7 and 94.4 GHz, respectively, towards a sample of massive YSOs in different stages of evolution. In addition, the J = 1-0 transitions of 12C18O and 13C18O were observed towards some of these sources. We use the 12C/13C ratio to discriminate between gas-phase and grain surface origin: If methanol is formed from CO on grains, the ratios should be similar in CH3OH and CO. If not, the ratio should be higher in CH3OH due to 13C fractionation in cold CO gas. We also estimate the abundance ratios between the nuclear spin types of methanol (E and A). If methanol is formed on grains, this ratio is likely to have been thermalized at the low physical temperature of the grain, and therefore show a relative over-abundance of A-methanol. Results. We show that the 12C/13C isotopic ratio is very similar in gas-phase CH3OH and C18O, on the spatial scale of about 40 arcsec, towards four YSOs. For two of our sources we find an overabundance of A-methanol as compared to E-methanol, corresponding to nuclear spin temperatures of 10 and 16 K. For the remaining five sources, the methanol E/A ratio is less than unity. Conclusions. While the 12C/13C ratio test is consistent with methanol formation from hydrogenation of CO on grain surfaces, the result of the E/A ratio test is inconclusive.

Monitoring and population estimation of the European badger (Meles meles) in Northern Ireland

The estimation of animal abundance has a central role in wildlife management and research, including the role of badgers Meles meles in bovine tuberculosis transmission to cattle. This is the first study to examine temporal change in the badger population of Northern Ireland over amedium- to long-term time frame of 14-18 years by repeating a national survey first conducted during 1990-1993. A total of 212 1-km2 squares were surveyed during 2007-2008 and the number, type and activity of setts therein recorded. Badgers were widespread with 75% of squares containing at least one sett. The mean density of activemain setts,which was equivalent to badger social group density, was 0.56 (95%CI: 0.46-0.67) active main setts per km2 during 2007-2008. Social group density varied significantly among landclass groups and counties. The total number of social groups was estimated at 7,600 (95%CI: 6,200-9,000) and, not withstanding probable sources of error in estimating social group size, the total abundance of badgers was estimated to be 34,100 (95% CI: 26,200-42,000). There was no significant change in the badger population from that recorded during 1990-1993. A resource selection model provided a relative probability of sett construction at a spatial scale of 25m. Sett locations were negatively associated with elevation and positively associated with slope, aspect, soil sand content, the presence of cover, and the area of improved grassland and arable agriculture within 300 m.

Agricultural intensification and biodiversity partitioning in European landscapes comparing plants, carabids, and birds

Effects of agricultural intensification (AI) on biodiversity are often assessed on the plot scale, although processes determining diversity also operate on larger spatial scales. Here, we analyzed the diversity of vascular plants, carabid beetles, and birds in agricultural landscapes in cereal crop fields at the field (n = 1350), farm (n = 270), and European-region (n = 9) scale. We partitioned diversity into its additive components alpha, beta, and gamma, and assessed the relative contribution of beta diversity to total species richness at each spatial scale. AI was determined using pesticide and fertilizer inputs, as well as tillage operations and categorized into low, medium, and high levels. As AI was not significantly related to landscape complexity, we could disentangle potential AI effects on local vs. landscape community homogenization. AI negatively affected the species richness of plants and birds, but not carabid beetles, at all spatial scales. Hence, local AI was closely correlated to beta diversity on larger scales up to the farm and region level, and thereby was an indicator of farm-and region-wide biodiversity losses. At the scale of farms (12.83-20.52%) and regions (68.34-80.18%), beta diversity accounted for the major part of the total species richness for all three taxa, indicating great dissimilarity in environmental conditions on larger spatial scales. For plants, relative importance of alpha diversity decreased with AI, while relative importance of beta diversity on the farm scale increased with AI for carabids and birds. Hence, and in contrast to our expectations, AI does not necessarily homogenize local communities, presumably due to the heterogeneity of farming practices. In conclusion, a more detailed understanding of AI effects on diversity patterns of various taxa and at multiple spatial scales would contribute to more efficient agri-environmental schemes in agroecosystems.

How do grazers achieve their distribution? A continuum of models from random diffusion to the ideal free distribution using biased random walks

A conceptual model is described for generating distributions of grazing animals, according to their searching behavior, to investigate the mechanisms animals may use to achieve their distributions. The model simulates behaviors ranging from random diffusion, through taxis and cognitively aided navigation (i.e., using memory), to the optimization extreme of the Ideal Free Distribution. These behaviors are generated from simulation of biased diffusion that operates at multiple scales simultaneously, formalizing ideas of multiple-scale foraging behavior. It uses probabilistic bias to represent decisions, allowing multiple search goals to be combined (e.g., foraging and social goals) and the representation of suboptimal behavior. By allowing bias to arise at multiple scales within the environment, each weighted relative to the others, the model can represent different scales of simultaneous decision-making and scale-dependent behavior. The model also allows different constraints to be applied to the animal's ability (e.g., applying food-patch accessibility and information limits). Simulations show that foraging-decision randomness and spatial scale of decision bias have potentially profound effects on both animal intake rate and the distribution of resources in the environment. Spatial variograms show that foraging strategies can differentially change the spatial pattern of resource abundance in the environment to one characteristic of the foraging strategy.</

Signal and variability within a Holocene peat bog - Chronological uncertainties of pollen, macrofossil and fungal proxies

A single raised bog from the eastern Netherlands has been repeatedly analysed and ¹⁴C dated over the past few decades. Here we assess the within-site variability of fossil proxy data through comparing the regional
pollen, macrofossils and non-pollen palynomorphs of four of these profiles. High-resolution chronologies were obtained using ¹⁴C dating and Bayesian age-depth modelling. Where chronologies of profiles overlap, proxy curves are compared between the profiles using greyscale graphs that visualise chronological uncertainties. Even at this small spatial scale, there is considerable variability of the fossil proxy curves. Implications regarding signal (climate) and noise (internal dynamics) of the different types of fossil proxies are discussed. Single cores are of limited value for reconstructing centennial-scale climate change, and only by combining multiple cores and proxies can we obtain a reliable understanding of past environmental change and possible forcing factors (e.g., solar variability).

Determinants of root-associated fungal communities within Asteraceae in a semi-arid grassland

Summary

1.While plant–fungal interactions are important determinants of plant community assembly and ecosystem functioning, the processes underlying fungal community composition are poorly understood.
2.Here, we studied for the first time the root-associated eumycotan communities in a set of co-occurring plant species of varying relatedness in a species-rich, semi-arid grassland in Germany. The study system provides an opportunity to evaluate the importance of host plants and gradients in soil type and landscape structure as drivers of fungal community structure on a relevant spatial scale. We used 454 pyrosequencing of the fungal internal transcribed spacer region to analyse root-associated eumycotan communities of 25 species within the Asteraceae, which were sampled at different locations within a soil type gradient. We partitioned the variance accounted for by three predictors (host plant phylogeny, spatial distribution and soil type) to quantify their relative roles in determining fungal community composition and used null model analyses to determine whether community composition was influenced by biotic interactions among the fungi.
3.We found a high fungal diversity (156 816 sequences clustered in 1100 operational taxonomic units (OTUs)). Most OTUs belonged to the phylum Ascomycota (35.8%); the most abundant phylotype best-matched Phialophora mustea. Basidiomycota were represented by 18.3%, with Sebacina as most abundant genus. The three predictors explained 30% of variation in the community structure of root-associated fungi, with host plant phylogeny being the most important variance component. Null model analysis suggested that many fungal taxa co-occurred less often than expected by chance, which demonstrates spatial segregation and indicates that negative interactions may prevail in the assembly of fungal communities.
4.Synthesis. The results show that the phylogenetic relationship of host plants is the most important predictor of root-associated fungal community assembly, indicating that fungal colonization of host plants might be facilitated by certain plant traits that may be shared among closely related plant species.

Validation of non‑stationary precipitation series for site‑specific impact assessment: comparison of two statistical downscaling techniques

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.

The imprint of the geographical, evolutionary and ecological context on species-area relationships

Species-area relationships (SAR) are fundamental in the understanding of biodiversity patterns and of critical importance for predicting species extinction risk worldwide. Despite the enormous attention given to SAR in the form of many individual analyses, little attempt has been made to synthesize these studies. We conducted a quantitative meta-analysis of 794 SAR, comprising a wide span of organisms, habitats and locations. We identified factors reflecting both pattern-based and dynamic approaches to SAR and tested whether these factors leave significant imprints on the slope and strength of SAR. Our analysis revealed that SAR are significantly affected by variables characterizing the sampling scheme, the spatial scale, and the types of organisms or habitats involved. We found that steeper SAR are generated at lower latitudes and by larger organisms. SAR varied significantly between nested and independent sampling schemes and between major ecosystem types, but not generally between the terrestrial and the aquatic realm. Both the fit and the slope of the SAR were scale-dependent. We conclude that factors dynamically regulating species richness at different spatial scales strongly affect the shape of SAR. We highlight important consequences of this systematic variation in SAR for ecological theory, conservation management and extinction risk predictions.

Coherence and discontinuity in the scaling of species' distribution patterns

The spatial distribution of a species can be characterized at many different spatial scales, from fine-scale measures of local population density to coarse-scale geographical-range structure. Previous studies have shown a degree of correlation in species' distribution patterns across narrow ranges of scales, making it possible to predict fine-scale properties from coarser-scale distributions. To test the limits of such extrapolation, we have compiled distributional information on 16 species of British plants, at scales ranging across six orders of magnitude in linear resolution (1 in to 100 km). As expected, the correlation between patterns at different spatial scales tends to degrade as the scales become more widely separated. There is, however, an abrupt breakdown in cross-scale correlations across intermediate (ca. 0.5 km) scales, suggesting that local and regional patterns are influenced by essentially non-overlapping sets of processes. The scaling discontinuity may also reflect characteristic scales of human land use in Britain, suggesting a novel method for analysing the 'footprint' of humanity on a landscape.