Characterization of food web structure of the upper continental slope of the Celtic Sea highlighting the trophic ecology of five deep‐sea fishes

In marine ecosystems, the study of trophic relationships has extensively benefited from the development of stable isotope analyses (SIA) as dietary tracers. SIA are particularly useful in elucidating the structure of deep sea food webs given the constraints involved in obtaining gut‐content data from deep trawling. We used carbon and nitrogen stable isotope analyses and Stable Isotope Bayesian Ellipses in R (SIBER) and Stable Isotope Analysis in R (SIAR) routines, to determine the trophic ecology of five deep‐sea fishes from the upper continental slope of the Celtic Sea. SIA made it possible to deduce some general tendencies in food‐web structure and species trophic interactions and confirmed diet determined by gut‐content analysis for the same species, in other ecoregions. More specifically, mixing models revealed that the deep sea species considered are omnivorous and are able to feed on all the sampled taxa. Based on isotopic ratio, no clear differences in fish diet could be detected from one species to another except for rabbit fish, which has benthic affinities. Three species, blackbelly rosefish, greater forkbeard and softhead grenadier showed overlapping isotopic niches. This study is the first attempt to describe the trophic ecology of deep sea species on the Celtic Sea upper continental slope. In the context of the development of ecosystem integrated modeling approaches for managing fisheries in the Celtic sea, and considering the vulnerability of deep‐water species, improving the knowledge on the trophic ecology of these local species is of importance in order to allow their sustainable exploitation.     

The Tyrosine Phosphatase STEP Is Involved in Age-Related Memory Decline

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The severity of psychiatric disorders

The issue of the severity of psychiatric disorders has great clinical importance. For example, severity influences decisions about level of care, and affects decisions to seek government assistance due to psychiatric disability. Controversy exists as to the efficacy of antidepressants across the spectrum of depression severity, and whether patients with severe depression should be preferentially treated with medication rather than psychotherapy. Measures of severity are used to evaluate outcome in treatment studies and may be used as meaningful endpoints in clinical practice. But, what does it mean to say that someone has a severe illness? Does severity refer to the number of symptoms a patient is experiencing? To the intensity of the symptoms? To symptom frequency or persistence? To the impact of symptoms on functioning or on quality of life? To the likelihood of the illness resulting in permanent disability or death? Putting aside the issue of how severity should be operationalized, another consideration is whether severity should be conceptualized similarly for all illnesses or be disorder specific. In this paper, we examine how severity is characterized in research and contemporary psychiatric diagnostic systems, with a special focus on depression and personality disorders. Our review shows that the DSM‐5 has defined the severity of various disorders in different ways, and that researchers have adopted a myriad of ways of defining severity for both depression and personality disorders, although the severity of the former was predominantly defined according to scores on symptom rating scales, whereas the severity of the latter was often linked with impairments in functioning. Because the functional impact of symptom‐defined disorders depends on factors extrinsic to those disorders, such as self‐efficacy, resilience, coping ability, social support, cultural and social expectations, as well as the responsibilities related to one's primary role function and the availability of others to assume those responsibilities, we argue that the severity of such disorders should be defined independently from functional impairment.     

Estimating individual fitness in the wild using capture–recapture data

The concept of Darwinian fitness is central in evolutionary ecology, and its estimation has motivated the development of several approaches. However, measuring individual fitness remains challenging in empirical case studies in the wild. Measuring fitness requires a continuous monitoring of individuals from birth to death, which is very difficult to get in part because individuals may or may not be controlled at each reproductive event and recovered at death. Imperfect detection hampers keeping track of mortality and reproductive events over the whole lifetime of individuals. We propose a new statistical approach to estimate individual fitness while accounting for imperfect detection. Based on hidden process modelling of longitudinal data on marked animals, we show that standard metrics to quantify fitness, namely lifetime reproductive success, individual growth rate and lifetime individual contribution to population growth, can be extended to cope with imperfect detection inherent to most monitoring programs in the wild. We illustrate our approach using data collected on individual roe deer in an intensively monitored population.     

Genetics of dispersal

Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal‐related phenotypes or evidence for the micro‐evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment‐dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non‐additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non‐equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context‐dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits.     

Land use and life history limit migration capacity of eastern tree species

Aim

Temperate tree species overwhelmingly responded to past climate change by migrating rather than adapting. However, past climate change did not have the modern human‐driven patterns of land use and fragmentation, raising questions of whether tree migration will still be able to keep pace with climate. Previous studies using coarse‐grained or randomized landscapes suggest that dispersal may be delayed but have not identified outright barriers to migration. Here, we use real‐world fragmented landscapes at the scale of forest stands to assess the migration capacity of eastern tree species.

Location

Eastern U.S.A.

Time period

Present day to 2100.

Major taxa studied

Eastern U.S. trees.

Methods

We simulated dispersal over 100 years for 15 species common to the mid‐Atlantic region and that are predicted to gain suitable habitat in the northeast. In contrast to previous studies, we incorporated greater realism with species‐specific life histories and real‐world spatial configurations of anthropogenic land use. We used simulation results to calculate dispersal rates for each species and related these to predicted rates of species habitat shift.

Results

Our simulations suggest that land use in the human‐dominated east‐coast corridor slows species dispersal rates by 12–40% and may prevent keeping pace with climate. Species most impacted by anthropogenic land use were often those with the highest predicted species habitat shifts. We identified two major dispersal barriers, the Washington DC metropolitan area and central NY, that severely impeded tree migration.

Main conclusions

Patterns of anthropogenic land use not only slowed migration but also resulted in effective barriers to dispersal. These impacts were exacerbated by tree life histories, such as long ages to maturity and narrow dispersal kernels. Without intervention, the migration lags predicted here may lead to loss in biodiversity and ecosystem functions as current forest species decline, and may contribute to formation of novel communities.     

Creating individual accessible area hypotheses improves stacked species distribution model performance

Aim

Stacked species distribution models (SDMs) are an important step towards estimating species richness, but frequently overpredict this metric and therefore erroneously predict which species comprise a given community. We test the idea that developing hypotheses about accessible area a priori can greatly improve model performance. By integrating dispersal ability via accessible area into SDM creation, we address an often‐overlooked facet of ecological niche modelling.

Innovation

By limiting the training and transference areas to theoretically accessible areas, we are creating more accurate SDMs on the basis of a taxon's explorable environments. This limitation of space and environment is a more accurate reflection of a taxon's true dispersal properties and more accurately reflects the geographical and environmental space to which a taxon is exposed. Here, we compare the predictive performance of stacked SDMs derived from spatially constrained and unconstrained training areas.

Main conclusions

Restricting a species’ training and transference areas to a theoretically accessible area greatly improves model performance. Stacked SDMs drawn from spatially restricted training areas predicted species richness and community composition more accurately than non‐restricted stacked SDMs. These accessible area‐based restrictions mimic true dispersal barriers to species and limit training areas to the suite of environments to those which a species is exposed to in nature. Furthermore, these restrictions serve to ‘clip’ predictions in geographical space, thus removing overpredictions in adjacent geographical regions where the species is known to be absent.     

Homogeneous vs. patient specific breast models for Monte Carlo evaluation of mean glandular dose in mammography

PurposeTo compare, via Monte Carlo simulations, homogeneous and non-homogenous breast models adopted for mean glandular dose (MGD) estimates in mammography vs. patient specific digital breast phantoms.MethodsWe developed a GEANT4 Monte Carlo code simulating four homogenous cylindrical breast models featured as follows: (1) semi-cylindrical section enveloped in a 5-mm adipose layer; (2) semi-elliptical section with a 4-mm thick skin; (3) semi-cylindrical section with a 1.45-mm skin layer; (4) semi-cylindrical section in a 1.45-mm skin layer and 2-mm subcutaneous adipose layer. Twenty patient specific digital breast phantoms produced from a dedicated CT scanner were assumed as reference in the comparison. We simulated two spectra produced from two anode/filter combinations. An additional digital breast phantom was produced via BreastSimulator software.ResultsWith reference to the results for patient-specific breast phantoms and for W/Al spectra, models #1 and #3 showed higher MGD values by about 1% (ranges [–33%; +28%] and [−31%; +30%], respectively), while for model #4 it was 2% lower (range [−34%; +26%]) and for model #2 –11% (range [−39%; +14%]), on average. On the other hand, for W/Rh spectra, models #1 and #4 showed lower MGD values by 2% and 1%, while for model #2 and #3 it was 14% and 8% lower, respectively (ranges [−43%; +13%] and [−41%; +21%]). The simulation with the digital breast phantom produced with BreastSimulator showed a MGD overestimation of +33%.ConclusionsThe homogeneous breast models led to maximum MGD underestimation and overestimation of 43% and 28%, respectively, when compared to patient specific breast phantoms derived from clinical CT scans.     

Matching effort to threat: Strategies to increase the scale and effectiveness of revegetation in southern Australia

The past 30 years of restoration activities in Australia has been mere cautious fiddling in the face of continental‐wide native habitat loss, fragmentation and degradation. A fundamental principle of conservation is to address threats at the scale of the threatening processes. This is still not happening for two reasons: we do not know how to effectively restore at scale, and if we did, there is no demand because it does not pay. The first problem of developing the technologies needed for large‐scale revegetation will largely be solved if we collectively demand revegetation at scale. Such a scale of demand by Australian governments (taxpayers) is only likely if a permanent Natural Heritage Trust is created for long‐term funding complemented by a price on carbon pollution. That will take a lot of political will. The other big opportunity is to create demand for large‐scale revegetation cofunded by farmers to improve their farm's long‐term productivity, resilience and economic viability. This requires sustained R&D supported by novel partnerships with the massive Australian agricultural market. Native vegetation must move from the margins to the mainstream if scale is to be achieved.