Range expansion and the possibility of an emerging contact zone between two subspecies of Chiffchaff Phylloscopus collybita ssp.

The Chiffchaff Phylloscopus collybita is represented in Sweden by two different subspecies; the northern well-established abietinus and the southern recently established collybita which has expanded its range northward during the past two decades. At present, an area approximately 500 km wide separates the two subspecies. In order to document differences between the northern and southern populations we compared morphology, vocalisation, habitat choice, and neutral genetic variation in mitochondrial (mt) DNA and at four microsatellite loci of 30 male Chiffchaffs from each subspecies. Our results show significant differences in several morphological traits and in song. Playback experiments revealed a significant difference in aggressive behaviour depending on which population-specific song that was played to the birds. Mitochondrial DNA was geographically structured with similar to 90% of the birds carrying a mt haplotype matching their sample population. No allelic differences at the microsatellite loci were found between populations. Our data demonstrate a substantial differentiation between the northern and southern populations despite gene flow, clearly separating them into the subspecies abietinus and collybita

Balancing Ecology and Economy in Forestry: A Theoretical Investigation

While forests have traditionally been managed for wood production, there are good reasons to account also for other objectives, such as biodiversity conservation and other ecological values. In contrast to clear-cut based .normal. forestry, uneven-aged forest management can preserve a more natural structure and associated ecological values. However, due to the complex interactions among trees in such forests, optimal management modeling quickly becomes analytically intractable, and numerical investigations can prove an insuperable obstacle. A promising recent development to overcome this impasse is the perfect plasticity approximation (PPA, see below), which has opened a new avenue of ecologically realistic and analytically tractable forest models. Here we use a PPA based model to investigate the potential for combining economic and ecological values under uneven-aged forest management

Model-based investigation on the effects of spatial evenness, and size selection in thinning of Picea abies stands

Size and spatial distribution of trees are important for forest stand growth, but the extent to which it matters in thinning operations, in terms of wood production and stand economy, has rarely been documented. Here we investigate how the choice of spatial evenness and tree-size distribution of residual trees impacts wood production and stand economy. A spatially explicit individual-based growth model was used, in conjunction with empirical cost functions for harvesting and forwarding, to calculate net production and net present value for different thinning operations in Norway spruce stands in Northern Sweden. The in silico thinning operations were defined by three variables: (1) spatial evenness after thinning, (2) tree size preference for harvesting, and (3) basal area reduction. We found that thinning that increases spatial evenness increases net production and net present value by around 2.0%, compared to the worst case. When changing the spatial evenness in conjunction with size preference we could observe an improvement of the net production and net present value up to 8.0%. The magnitude of impact differed greatly between the stands (from 1.7% to 8.0%) and was highest in the stand with the lowest stem density

Frequency discrimination in ears with and without contralateral cochlear dead regions

Objective: The purpose of this study was to test the ability to discriminate low-frequency pure-tone stimuli for ears with and without contralateral dead regions, in subjects with bilateral high-frequency hearing loss; we examined associations between hearing loss characteristics and frequency discrimination of low-frequency stimuli in subjects with high-frequency hearing loss. Design: Cochlear dead regions were diagnosed using the TEN-HL test. A frequency discrimination test utilizing an adaptive three-alternative forced choice method provided difference limens for reference frequencies 0.25 kHz and 0.5 kHz. Study sample: Among 105 subjects with bilateral high-frequency hearing loss, unilateral dead regions were found in 15 subjects. These, and an additional 15 matched control subjects without dead regions, were included in the study. Results: Ears with dead regions performed best at the frequency discrimination test. Ears with a contralateral dead region performed significantly better than ears without a contralateral dead region at 0.5 kHz, the reference frequency closest to the mean audiogram cut-off, while the opposite result was obtained at 0.25 kHz. Conclusions: Results may be seen as sign of a contralateral effect of unilateral dead regions on the discrimination of stimuli with frequencies well below the audiogram cut-off in adult subjects with bilateral high-frequency hearing loss

Using natural selection and optimization for smarter vegetation models - challenges and opportunities

Dynamic global vegetation models (DGVMs) are now indispensable for understanding the biosphere and for estimating the capacity of ecosystems to provide services. The models are continuously developed to include an increasing number of processes and to utilize the growing amounts of observed data becoming available. However, while the versatility of the models is increasing as new processes and variables are added, their accuracy suffers from the accumulation of uncertainty, especially in the absence of overarching principles controlling their concerted behaviour. We have initiated a collaborative working group to address this problem based on a ‘missing law’ – adaptation and optimization principles rooted in natural selection. Even though this ‘missing law’ constrains relationships between traits, and therefore can vastly reduce the number of uncertain parameters in ecosystem models, it has rarely been applied to DGVMs. Our recent research have shown that optimization- and trait-based models of gross primary production can be both much simpler and more accurate than current models based on fixed functional types, and that observed plant carbon allocations and distributions of plant functional traits are predictable with eco-evolutionary models. While there are also many other examples of the usefulness of these and other theoretical principles, it is not always straight-forward to make them operational in predictive models. In particular on longer time scales, the representation of functional diversity and the dynamical interactions among individuals and species presents a formidable challenge. Here we will present recent ideas on the use of adaptation and optimization principles in vegetation models, including examples of promising developments, but also limitations of the principles and some key challenges

Partitioning of plant functional trait variation into phenotypic plasticity and neutral components reveals functional differences among neotropical tree species

Background: Tropical plant communities exhibit extraordinary species richness and functional diversity in highly heterogeneous environments. Albeit the fact that such environmental filtering shapes local species composition and associated plant functional traits, it remains elusive to what extend tropical vegetation might be able to acclimate to environmental changes via phenotypic plasticity, which could be a critical determinant affecting the resistance and resilience of tropical vegetation to projected climate change. Methods: Based on a dataset compiled from 345 individuals and comprising 34 tropical tree species we here investigated the role of phenotypic plasticity versus non-plastic variation among key plant functional traits, i.e. wood density, maximum height, leaf thickness, leaf area, specific leaf area, leaf dry mass, nitrogen and phosphorus content. We hypothesized that trait variation due to plasticity is driven by environmental variability independently of spatial effects due to geographic distance between forest stands, whereas non-plastic variation increases with geographic distance due to adaption of the plant community to the local environment. Based on these hypotheses we partitioned total observed trait variation into phenotypic plasticity and neutral components and quantified respective amount of variation related to environmental filtering and neutral community assembly. Results: We found that trait variation was strongly related to spatial factors, thus often masking phenotypic plasticity in response to environmental cues. However, respective environmental factors differed among plant functional traits, such that leaf traits varied in association with light regime and soil nutrient content, whereas wood traits were related to topography and soil water content. Our results further suggest that phenotypic plasticity increased with the range size of congeneric tree species, indicating less plasticity within range restricted endemics compared to their widespread congeners. Conclusions: Differences in phenotypic trait plasticity affect stress tolerance and range size of tropical tree species, therefore endemic species could be especially prone to projected climate change

Inferring community assembly processes from macroscopic patterns using dynamic eco-evolutionary models and Approximate Bayesian Computation (ABC)

Statistical techniques exist for inferring community assembly processes from community patterns. Habitat filtering, competition, and biogeographical effects have, for example, been inferred from signals in phenotypic and phylogenetic data. The usefulness of current inference techniques is, however, debated as a mechanistic and causal link between process and pattern is often lacking, and evolutionary processes and trophic interactions are ignored. Here, we revisit the current knowledge on community assembly across scales and, in line with several reviews that have outlined challenges associated with current inference techniques, we identify a discrepancy between the current paradigm of eco-evolutionary community assembly and current inference techniques that focus mainly on competition and habitat filtering. We argue that trait-based dynamic eco-evolutionary models in combination with recently developed model fitting and model evaluation techniques can provide avenues for more accurate, reliable, and inclusive inference. To exemplify, we implement a trait-based, spatially explicit eco-evolutionary model and discuss steps of model modification, fitting, and evaluation as an iterative approach enabling inference from diverse data sources. Through a case study on inference of prey and predator niche width in an eco-evolutionary context, we demonstrate how inclusive and mechanistic approaches—eco-evolutionary modelling and Approximate Bayesian Computation (ABC)—can enable inference of assembly processes that have been largely neglected by traditional techniques despite the ubiquity of such processes. Much literature points to the limitations of current inference techniques, but concrete solutions to such limitations are few. Many of the challenges associated with novel inference techniques are, however, already to some extent resolved in other fields and thus ready to be put into action in a more formal way for inferring processes of community assembly from signals in various data sources

Functional-structural reorganisation of the neuronal network for auditory perception in subjects with unilateral hearing loss: Review of neuroimaging studies.

This paper aims to provide a review of studies using neuroimaging to measure functional-structural reorganisation of the neuronal network for auditory perception after unilateral hearing loss

The role of phenotypic plasticity for plant functional traits in tropical forests

Tropical tree communities comprise high species richness and functional diversity in highly heterogeneous environments. Phenotypic plasticity is the main mechanism by which trees adjust their functional traits in response to environmental variation and climate change. However, the degree of plasticity is not well known for most plant functional traits. We compiled a dataset based on 345 individuals from 35 tropical tree species investigating the role of phenotypic plasticity versus non-plastic variation among key plant functional traits, (i.e. wood density, total height, SLA, leaf N content). We hypothesized that trait variation due to plastic components are driven by environmental variability independently of geographic distance, whereas the non-plastic component increases with geographic distance due to local adaption of the population to different environments. Based on this hypothesis we partitioned total observed trait variation into phenotypic plasticity and non-plastic components and quantified how functional trait variation is related to environmental heterogeneity and geographic distance among tropical forest stands. We found that overall trait variation was strongly related to spatial factors, thus often masking phenotypic plasticity in response to environmental cues. However, respective environmental controlling factors differed among functional traits, such that leaf traits varied in strong association with edaphic factors, whereas wood traits were more significantly affected by topography and light regime. We further show that the identified pattern of phenotypic plasticity versus non-plastic trait variation increased with the range size of congeneric tree species. Hence, this might indicate less plastic responses of endemic tree species compared to their widespread congeners, which thus could be more vulnerable to environmental changes under future scenarios