THE MARINE RADIOCARBON BOMB PULSE ACROSS THE TEMPERATE NORTH ATLANTIC: A COMPILATION OF Delta C-14 TIME HISTORIES FROM ARCTICA ISLANDICA GROWTH INCREMENTS

Marine radiocarbon bomb-pulse time histories of annually resolved archives from temperate regions have been underexploited. We present here series of Delta C-14 excess from known-age annual increments of the long-lived bivalve mollusk Arctica islandica from 4 sites across the coastal North Atlantic (German Bight, North Sea; Tromso, north Norway; Siglufjordur, north Icelandic shelf; Grimsey, north Icelandic shelf) combined with published series from Georges Bank and Sable Bank (NW Atlantic) and the Oyster Ground (North Sea). The atmospheric bomb pulse is shown to be a step-function whose response in the marine environment is immediate but of smaller amplitude and which has a longer decay time as a result of the much larger marine carbon reservoir. Attenuation is determined by the regional hydrographic setting of the sites, vertical mixing, processes controlling the isotopic exchange of C-14 at the air-sea boundary, C-14 content of the freshwater flux, primary productivity, and the residence time of organic matter in the sediment mixed layer. The inventories form a sequence from high magnitude-early peak (German Bight) to low magnitude-late peak (Grimsey). All series show a rapid response to the increase in atmospheric Delta C-14 excess but a slow response to the subsequent decline resulting from the succession of rapid isotopic air-sea exchange followed by the more gradual isotopic equilibration in the mixed layer due to the variable marine carbon reservoir and incorporation of organic carbon from the sediment mixed layer. The data constitute calibration series for the use of the bomb pulse as a high-resolution dating tool in the marine environment and as a tracer of coastal ocean water masses.

Functional Complexity: The source of value in biodiversity.

Biodiversity may be seen as a scientific measure of the complexity of a biological system, implying an information basis. Complexity cannot be directly valued, so economists have tried to define the services it provides, though often just valuing the services of 'key' species. Here we provide a new definition of biodiversity as a measure of functional information, arguing that complexity embodies meaningful information as Gregory Bateson defined it. We argue that functional information content (FIC) is the potentially valuable component of total (algorithmic) information content (AIC), as it alone determines biological fitness and supports ecosystem services. Inspired by recent extensions to the Noah's Ark problem, we show how FIC/AIC can be calculated to measure the degree of substitutability within an ecological community. Establishing substitutability is an essential foundation for valuation. From it, we derive a way to rank whole communities by Indirect Use Value, through quantifying the relation between system complexity and the production rate of ecosystem services. Understanding biodiversity as information evidently serves as a practical interface between economics and ecological science. © 2012 Elsevier B.V.

Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data

The relationships among organisms and their surroundings can be of immense complexity. To describe and understand an ecosystem as a tangled bank, multiple ways of interaction and their effects have to be considered, such as predation, competition, mutualism and facilitation. Understanding the resulting interaction networks is a challenge in changing environments, e.g. to predict knock-on effects of invasive species and to understand how climate change impacts biodiversity. The elucidation of complex ecological systems with their interactions will benefit enormously from the development of new machine learning tools that aim to infer the structure of interaction networks from field data. In the present study, we propose a novel Bayesian regression and multiple changepoint model (BRAM) for reconstructing species interaction networks from observed species distributions. The model has been devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity. We have evaluated the model on simulated data that combines a trophic niche model with a stochastic population model on a 2-dimensional lattice, and we have compared the performance of our model with L1-penalized sparse regression (LASSO) and non-linear Bayesian networks with the BDe scoring scheme. In addition, we have applied our method to plant ground coverage data from the western shore of the Outer Hebrides with the objective to infer the ecological interactions. (C) 2012 Elsevier B.V. All rights reserved.

Trait assembly in plant assemblages and its modulation by productivity and disturbance

Understanding how communities assemble is a key challenge in ecology. Conflicting hypotheses suggest that plant traits within communities should show divergence to reflect strategies to reduce competition or convergence to reflect strong selection for the environmental conditions operating. Further hypotheses suggest that plant traits related to productivity show convergence within communities, but those related to disturbance show divergence. Data on functional diversity (FD ) of 12 traits from 30 communities ranging from arable fields, mown and grazed grasslands to moorland and woodland were employed to test this using randomisations tests and correlation and regression analysis. No traits showed consistent significant convergence or divergence in functional diversity. When correlated to measures of the environment, the most common pattern was for functional diversity to decline (7 out of 12 traits) and the degree of convergence (7 out of 12 traits) to increase as the levels of productivity (measured as primary productivity, soil nitrogen release and vegetation C:N) and disturbance increased. Convergence or a relationship between functional diversity and the environment was not seen for a number of important traits, such as LDMC and SLA, which are considered as key predictors of ecosystem function. The analysis indicates that taking into account functional diversity within a system may be a necessary part of predicting the relationship between plant traits and ecosystem function, and that this may be of particular importance within less productive and less disturbed systems. © 2011 Springer-Verlag.

Regression analysis of spatial data

Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative analysis involves using methods including generalized least squares, spatial filters, wavelet revised models, conditional autoregressive models and generalized additive mixed models to estimate regression coefficients from synthetic but realistic data sets, including some which violate standard regression assumptions. We assess the performance of each method using two measures and using statistical error rates for model selection. Methods that performed well included generalized least squares family of models and a Bayesian implementation of the conditional auto-regressive model. Ordinary least squares also performed adequately in the absence of model selection, but had poorly controlled Type I error rates and so did not show the improvements in performance under model selection when using the above methods. Removing large-scale spatial trends in the response led to poor performance. These are empirical results; hence extrapolation of these findings to other situations should be performed cautiously. Nevertheless, our simulation-based approach provides much stronger evidence for comparative analysis than assessments based on single or small numbers of data sets, and should be considered a necessary foundation for statements of this type in future.

Are richness patterns of common and rare species equally well explained by environmental variables?

We investigated relationships between richness patterns of rare and common grassland species and environmental factors, focussing on comparing the degree to which the richness patterns of rare and common species are determined by simple environmental variables. Using data collected in the Machair grassland of the Outer Hebrides of Scotland, we fitted spatial regression models using a suite of grazing, soil physicochemical and microtopographic covariates, to nested sub-assemblages of vascular and non-vascular species ranked according to rarity. As expected, we found that common species drive richness patterns, but rare vascular species had significantly stronger affinity for high richness areas. After correcting for the prevalence of individual species distributions, we found differences between common and rare species in 1) the amount of variation explained: richness patterns of common species were better summarised by simple environmental variables, 2) the associations of environmental variables with richness showed systematic trends between common and rare species with coefficient sign reversal for several factors, and 3) richness associations with rare environments: richness patterns of rare vascular species significantly matched rare environments but those of non-vascular species did not. Richness patterns of rare species, at least in this system, may be intrinsically less predictable than those of common species.

New susceptibility Loci associated with kidney disease in type 1 diabetes

Diabetic kidney disease, or diabetic nephropathy (DN), is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD) that requires dialysis treatment or kidney transplantation. In addition to the decrease in the quality of life, DN accounts for a large proportion of the excess mortality associated with type 1 diabetes (T1D). Whereas the degree of glycemia plays a pivotal role in DN, a subset of individuals with poorly controlled T1D do not develop DN. Furthermore, strong familial aggregation supports genetic susceptibility to DN. However, the genes and the molecular mechanisms behind the disease remain poorly understood, and current therapeutic strategies rarely result in reversal of DN. In the GEnetics of Nephropathy: an International Effort (GENIE) consortium, we have undertaken a meta-analysis of genome-wide association studies (GWAS) of T1D DN comprising ~2.4 million single nucleotide polymorphisms (SNPs) imputed in 6,691 individuals. After additional genotyping of 41 top ranked SNPs representing 24 independent signals in 5,873 individuals, combined meta-analysis revealed association of two SNPs with ESRD: rs7583877 in the AFF3 gene (P?=?1.2×10(-8)) and an intergenic SNP on chromosome 15q26 between the genes RGMA and MCTP2, rs12437854 (P?=?2.0×10(-9)). Functional data suggest that AFF3 influences renal tubule fibrosis via the transforming growth factor-beta (TGF-ß1) pathway. The strongest association with DN as a primary phenotype was seen for an intronic SNP in the ERBB4 gene (rs7588550, P?=?2.1×10(-7)), a gene with type 2 diabetes DN differential expression and in the same intron as a variant with cis-eQTL expression of ERBB4. All these detected associations represent new signals in the pathogenesis of DN.

Determining trophic niche width: An experimental test of the stable isotope approach

Determining the trophic niche width of an animal population and the relative degree to which a generalist population consists of dietary specialists are long-standing problems of ecology. It has been proposed that the variance of stable isotope values in consumer tissues could be used to quantify trophic niche width of consumer populations. However, this promising idea has not yet been rigorously tested. By conducting controlled laboratory experiments using model consumer populations (Daphnia sp., Crustacea) with controlled diets, we investigated the effect of individual- and population-level specialisation and generalism on consumer d C mean and variance values. While our experimental data follow general expectations, we extend current qualitative models to quantitative predictions of the dependence of isotopic variance on dietary correlation time, a measure for the typical time over which a consumer changes its diet. This quantitative approach allows us to pinpoint possible procedural pitfalls and critical sources of measurement uncertainty. Our results show that the stable isotope approach represents a powerful method for estimating trophic niche widths, especially when taking the quantitative concept of dietary correlation time into account. © 2012 The Authors.

Demersal fish biodiversity: species-level indicators and trends-based targets for the Marine Strategy Framework Directive

The maintenance of biodiversity is a fundamental theme of the Marine Strategy Framework Directive. Appropriate indicators to monitor change in biodiversity, along with associated targets representing "good environmental status" (GES), are required to be in place by July 2012. A method for selecting species-specific metrics to fulfil various specified indicator roles is proposed for demersal fish communities. Available data frequently do not extend far enough back in time to allow GES to be defined empirically. In such situations, trends-based targets offer a pragmatic solution. A method is proposed for setting indicator-level targets for the number of species-specific metrics required to meet their trends-based metric-level targets. This is based on demonstrating significant departures from the binomial distribution. The procedure is trialled using North Sea demersal fish survey data. Although fisheries management in the North Sea has improved in recent decades, management goals to stop further decline in biodiversity, and to initiate recovery, are yet to be met.

A complete analytic theory for structure and dynamics of populations and communities spanning wide ranges in body size

The prediction and management of ecosystem responses to global environmental change would profit from a clearer understanding of the mechanisms determining the structure and dynamics of ecological communities. The analytic theory presented here develops a causally closed picture for the mechanisms controlling community and population size structure, in particular community size spectra, and their dynamic responses to perturbations, with emphasis on marine ecosystems. Important implications are summarised in non-technical form. These include the identification of three different responses of community size spectra to size-specific pressures (of which one is the classical trophic cascade), an explanation for the observed slow recovery of fish communities from exploitation, and clarification of the mechanism controlling predation mortality rates. The theory builds on a community model that describes trophic interactions among size-structured populations and explicitly represents the full life cycles of species. An approximate time-dependent analytic solution of the model is obtained by coarse graining over maturation body sizes to obtain a simple description of the model steady state, linearising near the steady state, and then eliminating intraspecific size structure by means of the quasi-neutral approximation. The result is a convolution equation for trophic interactions among species of different maturation body sizes, which is solved analytically using a novel technique based on a multiscale expansion.

Predicting the impacts of climate change on the distribution of threatened forest-restricted birds in Madagascar

The greatest common threat to birds in Madagascar has historically been from anthropogenic deforestation. During recent decades, global climate change is now also regarded as a significant threat to biodiversity. This study uses Maximum Entropy species distribution modeling to explore how potential climate change could affect the distribution of 17 threatened forest endemic bird species, using a range of climate variables from the Hadley Center's HadCM3 climate change model, for IPCC scenario B2a, for 2050. We explore the importance of forest cover as a modeling variable and we test the use of pseudo-presences drawn from extent of occurrence distributions. Inclusion of the forest cover variable improves the models and models derived from real-presence data with forest layer are better predictors than those from pseudo-presence data. Using real-presence data, we analyzed the impacts of climate change on the distribution of nine species. We could not predict the impact of climate change on eight species because of low numbers of occurrences. All nine species were predicted to experience reductions in their total range areas, and their maximum modeled probabilities of occurrence. In general, species range and altitudinal contractions follow the reductive trend of the Maximum presence probability. Only two species (Tyto soumagnei and Newtonia fanovanae) are expected to expand their altitude range. These results indicate that future availability of suitable habitat at different elevations is likely to be critical for species persistence through climate change. Five species (Eutriorchis astur, Neodrepanis hypoxantha, Mesitornis unicolor, Euryceros prevostii, and Oriola bernieri) are probably the most vulnerable to climate change. Four of them (E. astur, M. unicolor, E. prevostii, and O. bernieri) were found vulnerable to the forest fragmentation during previous research. Combination of these two threats in the future could negatively affect these species in a drastic way. Climate change is expected to act differently on each species and it is important to incorporate complex ecological variables into species distribution models.

Postglacial dispersal, rather than in situ glacial survival, best explains the disjunct distribution of the Lusitanian plant species Daboecia cantabrica (Ericaceae)

Aim:

The distribution of the Lusitanian flora and fauna, species which are found only in southern and western Ireland and in northern Spain and Portugal but which are absent from intervening countries, represents one of the classic conundrums of biogeography. The aim of the present study was to determine whether the distribution of the Lusitanian plant species Daboecia cantabrica was due to persistence in separate Irish and Iberian refugia, or has resulted from post-glacial recolonization followed by subsequent extinction of intervening populations.

Location:

Northern Spain and Co. Galway, western Ireland.

Methods:

Palaeodistribution modelling using Maxent was employed to identify putative refugial areas for D. cantabrica at the Last Glacial Maximum (LGM). Phylogeographical analysis of samples from 64 locations in Ireland and Spain were carried out using a chloroplast marker (atpB–rbcL), the nuclear ITS region, and an anonymous nuclear single-copy locus.

Results:

The palaeodistribution model indicated areas with a high probability of survival for D. cantabrica at the LGM off the western coast of Galicia in Spain, and in the Bay of Biscay. Spanish populations exhibited substantially higher genetic diversity than Irish populations at all three loci, as well as geographical structuring of haplotypes within Spain consistent with divergence in separate refugia. Spanish populations also exhibited far more endemic haplotypes. Divergence time between Irish and Spanish populations associated with the putative Biscay refugium was estimated as 3.333–32 ka.

Main conclusions:

Our data indicate persistence by D. cantabrica throughout the LGM in two separate southern refugia: one in western Galicia and one in the area off the coast of western France which now lies in the Bay of Biscay. Spain was recolonized from both refugia, whilst Ireland was most likely recolonized from the Biscay refugium. On the balance of evidence across the three marker types and the palaeodistribution modelling, our findings do not support the idea of in situ survival of D. cantabrica in Ireland, contrary to earlier suggestions. The fact that we cannot conclusively rule out the existence of a small, more northerly refugium, however, highlights the need for further analysis of Lusitanian plant species.

Levels and patterns of population genetic diversity in the red seaweed Chondrus crispus (Florideophyceae): a direct comparison of single nucleotide polymorphisms and microsatellites

Single nucleotide polymorphisms (SNPs) are predicted to supersede microsatellites as the marker of choice for population genetic studies in the near future. To date, however, very few studies have directly compared both marker systems in natural populations, particularly in non-model organisms. In the present study, we compared the utility of SNPs and microsatellites for population genetic analysis of the red seaweed Chondrus crispus (Florideophyceae). Six SNP loci yielded very different patterns of intrapopulation genetic diversity compared to those obtained using seven moderately (mean 5.2 alleles) polymorphic microsatellite loci, although Bayesian clustering analysis gave largely congruent results between the two marker classes. A weak but significant pattern of isolation-by-distance was observed across scales from a few hundred metres to approximately 200?km using the combined SNP and microsatellite data set of 13 loci. Over larger scales, however, there was little correlation between genetic divergence and geographical distance. Our findings suggest that even a moderate number of SNPs is sufficient to determine patterns of genetic diversity across natural populations, and also highlight the fact that patterns of genetic variation in seaweeds arise through a complex interplay of short- and long-term natural processes, as well as anthropogenic influence.

Foraging trip time-activity budgets and reproductive success in the black-legged kittiwake

Seabirds are central place foragers during the breeding season and, as marine food resources are often patchily distributed, flexibility in foraging behaviour may be important in maintaining prey delivery rates to chicks. We developed a methodological approach using a combination of GPS data loggers and temperature-depth recorders that allowed us to describe the behaviour of surface-feeding seabirds. Specifically, we tested whether differences in foraging behaviour of black-legged kittiwakes Rissa tridactyla could be linked with reproductive success by comparing 2 consecutive years at 2 sites. At Rathlin Island (Northern Ireland) during 2010, foraging differed markedly from that during 2009 and from that at Lambay Island (Republic of Ireland) during both years. Birds exhibited foraging trips of greater duration, travelled a greater total distance, spent more time in transit and spent longer recuperating on the surface of the water. This notable shift was associated with a decline in breeding success, with greater loss of eggs to predation and lower prey delivery rates, resulting in the starvation of 15 % of chicks. We suggest that food resources were reduced or geographically less accessible during 2010, with suitable foraging areas located further from the colony. Birds did not invest greater amounts of time attempting to catch prey. Thus, our results indicate that kittiwakes at Rathlin modulated their foraging behaviour not by increasing foraging effort through feeding more intensively within prey patches but by extending their range to increase the probability of encountering more profitable prey patches. © Inter-Research 2012.