Fast Algorithms for the computation of Fourier Extensions of arbitrary length

Fourier series of smooth, non-periodic functions on $[-1,1]$ are known to exhibit the Gibbs phenomenon, and exhibit overall slow convergence. One way of overcoming these problems is by using a Fourier series on a larger domain, say $[-T,T]$ with $T>1$, a technique called Fourier extension or Fourier continuation. When constructed as the discrete least squares minimizer in equidistant points, the Fourier extension has been shown shown to converge geometrically in the truncation parameter $N$. A fast ${\mathcal O}(N \log^2 N)$ algorithm has been described to compute Fourier extensions for the case where $T=2$, compared to ${\mathcal O}(N^3)$ for solving the dense discrete least squares problem. We present two ${\mathcal O}(N\log^2 N )$ algorithms for the computation of these approximations for the case of general $T$, made possible by exploiting the connection between Fourier extensions and Prolate Spheroidal Wave theory. The first algorithm is based on the explicit computation of so-called periodic discrete prolate spheroidal sequences, while the second algorithm is purely algebraic and only implicitly based on the theory

Simple individual-based models effectively represent Afrotropical forest bird movement in complex landscapes

Reliable estimates of dispersal rates between habitat patches (i.e. functional connectivity) are critical for predicting long-term effects of habitat fragmentation on population persistence. Connectivity measures are frequently derived from least cost path or graph-based approaches, despite the fact that these methods make biologically unrealistic assumptions. Individual-based models (IBMs) have been proposed as an alternative as they allow modelling movement behaviour in response to landscape resistance. However, IBMs typically require excessive data to be useful for management. Here, we test the extent to which an IBM requiring only an uncomplicated set of movement rules [the 'stochastic movement simulator' (SMS)] can predict animal movement behaviour in real-world landscapes. Movement behaviour of two forest birds, the Cabanis's greenbul Phyllastrephus cabanisi (a forest specialist) and the white-starred robin Pogonocichla stellata (a habitat generalist), across an Afrotropical matrix was simulated using SMS. Predictions from SMS were evaluated against a set of detailed movement paths collected by radiotracking homing individuals. SMS was capable of generating credible predictions of bird movement, although simulations were sensitive to the cost values and the movement rules specified. Model performance was generally highest when movement was simulated across low-contrasting cost surfaces and when virtual individuals were assigned low directional persistence and limited perceptual range. SMS better predicted movements of the habitat specialist than the habitat generalist, which highlights its potential to model functional connectivity when species movements are affected by the matrix. Synthesis and applications. Modelling the dispersal process with greater biological realism is likely to be critical for improving our predictive capability regarding functional connectivity and population persistence. For more realistic models to be widely applied, it is vital that their application is not overly complicated or data demanding. Here, we show that given relatively basic understanding of a species' dispersal ecology, the stochastic movement simulator represents a promising tool for estimating connectivity, which can help improve the design of functional ecological networks aimed at successful species conservation

Diet contributes to urban-induced alterations in gut microbiota : experimental evidence from a wild passerine

Urban sprawl increasingly affects the ecology of natural populations, including host-microbiota interactions, with observed differences in the gut microbiota between urban and rural hosts. While different mechanisms could explain this pattern, dietary uptake constitutes a likely candidate. To assess the contribution of diet in explaining urban-rural variation in gut microbiota, we performed an aviary experiment in which urban and rural house sparrows were fed with mimics of urban or rural diets. Before the experiment, rural sparrows hosted more diverse gut communities, with a higher relative abundance of Enterococcaceae and Staphylococcaceae and lower abundance of genes involved in xenobiotic degradation and lipid metabolism than their urban counterparts. The experimental diets significantly altered gut microbiota alpha- and beta-diversity and taxonomic composition, with the strongest shifts occurring in individuals exposed to contrasting diets. Overall, diet-induced shifts resembled initial differences between free-ranging urban and rural hosts. Furthermore, rural diet had a positive impact on urban host body mass but only in hosts with the highest initial gut diversity. Overall, our results indicate that diet constitutes an important factor contributing to differences in gut microbiota along the urbanization gradient and provide new insights on possible fitness consequences of a reduced gut diversity in urban settings

Urbanisation lowers great tit Parus major breeding success at multiple spatial scales

While numerous studies have reported negative effects of urbanisation on birds, few have examined the role of urban scale in influencing breeding success. Furthermore, many studies have relied on qualitative rather than quantitative assessments of urbanisation. This study sought to address these issues by testing the effects of urbanisation, measured at two spatial scales, on the breeding success of great tits Parus major. A nested study design, incorporating over 400 nestboxes, was used in study sites across northern Belgium with a priori quantified degrees of urbanisation at both local and regional scales. All measured breeding parameters were found to vary at one or both spatial scales of urbanisation; in more urbanised areas great tits displayed advanced laying dates but lower breeding success compared to rural areas, with smaller clutch sizes, lower nestling masses and fewer fledglings per egg. Importantly, urbanisation effects were not limited to big cities as birds breeding in gardens or parks in small towns also had comparatively low success. We found that both regional- and local-scale urbanisation had consistent significant effects on laying date, clutch size and nestling mass, while the number of fledglings per egg was negatively influenced by local-scale urbanisation only. Results of this study therefore highlight the importance of utilising multiple spatial scales in analysing urbanisation effects, as well as the potential negative impact of local urbanisation on breeding success. This calls for further investigation into mechanisms driving urbanisation effects and how these may vary at different scales

Cooperative breeding shapes post-fledging survival in an Afrotropical forest bird

For avian group living to be evolutionary stable, multiple fitness benefits are expected. Yet, the difficulty of tracking fledglings, and thus estimating their survival rates, limits our knowledge on how such benefits may manifest postfledging. We radio-tagged breeding females of the Afrotropical cooperatively breeding Placid greenbul (Phyllastrephus placidus) during nesting. Tracking these females after fledging permitted us to locate juvenile birds, their parents, and any helpers present and to build individual fledgling resighting datasets without incurring mortality costs or causing premature fledging due to handling or transmitter effects. A Bayesian framework was used to infer age-specific mortality rates in relation to group size, fledging date, maternal condition, and nestling condition. Postfledging survival was positively related to group size, with fledglings raised in groups with four helpers showing nearly 30% higher survival until independence compared with pair-only offspring, independent of fledging date, maternal condition or nestling condition. Our results demonstrate the importance of studying the early dependency period just after fledging when assessing presumed benefits of cooperative breeding. While studying small, mobile organisms after they leave the nest remains highly challenging, we argue that the telemetric approach proposed here may be a broadly applicable method to obtain unbiased estimates of postfledging survival

A stochastic movement simulator improves estimates of landscape connectivity

Acknowledgments This publication issued from the project TenLamas funded by the French Ministère de l'Energie, de l'Ecologie, du Développement Durable et de la Mer through the EU FP6 BiodivERsA Eranet; by the Agence Nationale de la Recherche (ANR) through the open call INDHET and 6th extinction MOBIGEN to V. M. Stevens, M. Baguette, and A. Coulon, and young researcher GEMS (ANR-13-JSV7-0010-01) to V. M. Stevens and M. Baguette; and by a VLIR-VLADOC scholarship awarded to J. Aben. L. Lens, J. Aben, D. Strubbe, and E. Matthysen are grateful to the Research Foundation Flanders (FWO) for financial support of fieldwork and genetic analysis (grant G.0308.13). V. M. Stevens and M. Baguette are members of the “Laboratoire d'Excellence” (LABEX) entitled TULIP (ANR-10-LABX-41). J. M. J. Travis and S. C. F. Palmer also acknowledge the support of NERC. A. Coulon and J. Aben contributed equally to the work.Peer reviewedPublisher PD

The relationship between readiness to change and work engagement: a case study within an accounting firm undergoing change

Readiness to change is a critical element for the successful implementation of organisational change (Weiner, 2009). Work engagement is an important driver for organisational success (Lockwood, 2007) and it is important that organisations sustain work engagement during organisational changes. Readiness to change and work engagement are both important aspects of a successful organisation. The purpose of this study was to investigate the relationship between readiness to change and work engagement within a mid-tier accounting firm in South Africa. A combined questionnaire, incorporating two measuring instruments was utilised to gather the data for the purpose of this study. These instruments are the Organisational Change Questionnaire – Climate of Change, Process and Readiness (OCQ-C,P,R) as well as Utrecht’s Work Engagement Scale (UWES). The measuring instrument utilised demonstrated adequate reliability. By utilising the OCQ-C,P,R two additional constructs were incorporated into the study namely process of change and trust in leadership. The measuring instrument was sent electronically to all the staff members within the mid-tier accounting firm across South Africa. The researcher obtained a sample of n = 340. A model was constructed based on the measuring instrument to illustrate the hypothesised relationships between the constructs. Results from confirmatory factor analysis suggested that there was a good model fit with the data. Both descriptive and inferential statistics techniques were used for the data analysis. The relationships between the constructs were tested through structure equation modelling and Pearson’s product-moment correlation coefficients. The results of the study indicated that there is a practical and statistically significant relationship between readiness to change and work engagement. The results of the study implied that high levels of work engagement will generate high levels of readiness to change. Engaged employees are better able to cope with job demands during change processes which ultimately will impact whether change implementation is successful. Readiness to change and work engagement also indicated significant correlations with process of change and trust in leadership. Demographic groups had significant differences in the mean scores for work engagement, process of change and trust in leadership

Dispersal: a matter of scale

Population density around the natal site is often invoked as an explanation for variation in dispersal distance, with the expectation that competition for limiting resources, coupled with increased intra‐specific aggression at high densities, should drive changes in dispersal distances. However, tests of the density‐dependent dispersal hypothesis in long‐lived vertebrates have yielded mixed results. Furthermore, conclusions from dispersal studies may depend on the spatial and temporal scales at which density and dispersal patterns are examined, yet multi‐scale studies of dispersal are rare. Here, we present the findings of a long‐term study examining factors influencing natal dispersal distances for the non‐migratory population of Peregrine Falcons (Falco peregrinus) in the British Isles across distinct spatial and temporal scales. Our smallest scale study included Peregrines ringed as nestlings and subsequently recaptured alive in south Scotland–north England, an area that was intensively studied during the time periods 1974–1982 and 2002–2016. Second, we examined dispersal patterns of birds ringed as nestlings in south Scotland–north England, but subsequently recaptured alive or recovered dead anywhere in the British Isles. Finally, we examined the natal dispersal patterns for Peregrines ringed and recaptured or recovered anywhere in the British Isles from 1964 to 2016. Consistent with prior findings, females dispersed farther than males across all scales. However, the patterns of dispersal were strongly scale dependent. Specifically, we found a lack of a discernible relationship between index of density and dispersal distance in the limited study area, but when region‐wide recaptures and recoveries were included in the analyses, a negative relationship was revealed. Our results suggest that conclusions of dispersal studies may be scale dependent, highlighting the importance of spatial and temporal scales in examining and interpreting the relationship between population density and dispersal patterns

Detail of the thermal structure of oceanic fronts in the Southern ocean south of Africa

This investigation addresses the thermal characteristics of the major oceanic frontal systems in the Southern Ocean south of Africa based on data collected to a depth of 500 m on forty-three cruises during a fifteen year period. The width of the Agulhas Front has been shown to vary considerably in both its sea surface and sub-surface thermal manifestation as a result of mesoscale turbulence. Its mean sea surface width of 84 km has a standard deviation of 53 km, and the mean subsurface width of 37 km has a standard deviation of 33 km. The Agulhas Front. has been found to be a separate front north of the Subtropical Convergence in 56 % of the cruises investigated. It has only been observed from 18,2°E to 24,7°E, with a mean sea and subsurface temperature gradient across the Agulhas Front of 0,05 °C/km and 0, 13 °C/km respectively. It has a mean sea surface middle temperature of 17, 8° C and a mean subsurface middle temperature of 12,6° C. The mean sea and sub-surface geographic positions of the thermal expression of the Agulhas Front are 39,3° S; 22,7° E aild 39,1° S; 22,7° E. The Subtropical Convergence at surface has been found to be a single, broad frontal zone across the Central/South East Atlantic Ocean, that does not bifurcate. It has a mean sea surface middle temperature of ·14,3° C and a mean sub-surface middle temperature of 8,4° C. The mean sea and sub-surface temperature gradients across the Subtropical Convergence are O, 03 °C/km and O, 05 °C/km respectively. The mean sea and sub-surface geographic positions of the· thermal expression of the Subtropical Convergence are 41, 8° S; 21, 9° E and 41, 7° S; 22, 0° E. The Subtropical Convergence has a mean sea surface width of 146 km and a mean sub-surface width of 79 km. The Sub-antarctic Front is pressed northward from 45° S to 43° S by the Mid-Ocean Ridge in the South West Indian Ocean sector, after which it converges · with the Subtropical Convergence at approximately 60° E to form a united STC/SAF at subsurface. This united STC/SAF does not however form a "Crozet Front" by joining the Agulhas Front between 52° E and 65° E. It has a mean sea surface middle temperature of 4,4° C and a mean sub-surface middle temperature of 4,0° C. The mean sea and subsurface temperature gradients across the Sub-antarctic Front are 0,02 °C/km. The mean sea and sub-surface geographic positions of the thermal expression of the Sub-antarctic Front are 48,7° S; 18,9° E and 46,8° S; 19,9° E. The Sub-antarctic Front has a mean sea surface width of 73 km and a mean sub-surface width of 77 km. In 30 % of the sections investigated the- Antarctic Polar Front consisted of a primary and secondary front. The Antarctic Polar Front does not join the Sub-antarctic Front east of · 40° E at sub-surface and subsequently no quadruple front is formed. It has a mean sea surface middle temperature of 2, 1 ° C and a mean sub-surface middle temperature of 2,3° C. The mean sea and sub-surface temperature gradients across the Antarctic Polar Front are 0,01 °C/km and 0,02 °C/km respectively. The mean sea and sub-surface geographic position of the thermal expression of the Antarctic Polar Front are 52, 7° S; 14,9° E and 49,2° S; 20,8° E. The Antarctic Polar Front has a mean sea surface width of 66 km and a mean sub-surface width of 74 km