Is the weighted z‐test the best method for combining probabilities from independent tests?

Through simulation, Whitlock showed that when all the alternatives have the same effect size, the weighted z-test is superior to both unweighted z-test and Fisher's method when combining P-values from independent studies. In this paper, we show that under the same situation, the generalized Fisher method due to Lancaster outperforms the weighted z-test.     

Which function describes the species–area relationship best? A review and empirical evaluation

Aim The aims of this study are to resolve terminological confusion around different types of species–area relationships (SARs) and their delimitation from species sampling relationships (SSRs), to provide a comprehensive overview of models and analytical methods for SARs, to evaluate these theoretically and empirically, and to suggest a more consistent approach for the treatment of species–area data. Location Curonian Spit in north‐west Russia and archipelagos world‐wide. Methods First, I review various typologies for SARs and SSRs as well as mathematical models, fitting procedures and goodness‐of‐fit measures applied to SARs. This results in a list of 23 function types, which are applicable both for untransformed (S) and for log‐transformed (log S) species richness. Then, example data sets for nested plots in continuous vegetation (n = 14) and islands (n = 6) are fitted to a selection of 12 function types (linear, power, logarithmic, saturation, sigmoid) both for S and for log S. The suitability of these models is assessed with Akaike’s information criterion for S and log S, and with a newly proposed metric that addresses extrapolation capability. Results SARs, which provide species numbers for different areas and have no upper asymptote, must be distinguished from SSRs, which approach the species richness of one single area asymptotically. Among SARs, nested plots in continuous ecosystems, non‐nested plots in continuous ecosystems, and isolates can be distinguished. For the SARs of the empirical data sets, the normal and quadratic power functions as well as two of the sigmoid functions (Lomolino, cumulative beta‐P) generally performed well. The normal power function (fitted for S) was particularly suitable for predicting richness values over ten‐fold increases in area. Linear, logarithmic, convex saturation and logistic functions generally were inappropriate. However, the two sigmoid models produced unstable results with arbitrary parameter estimates, and the quadratic power function resulted in decreasing richness values for large areas. Main conclusions Based on theoretical considerations and empirical results, I suggest that the power law should be used to describe and compare any type of SAR while at the same time testing whether the exponent z changes with spatial scale. In addition, one should be aware that power‐law parameters are significantly influenced by methodology.     

IPBES-6: the best plenary yet?

The Intergovernmental Science-Policy Platform for Biodiversity and Ecosystem Services (IPBES) held its 6th plenary session in Medellin (Colombia) during March 2018. Several assessments were due for acceptance by the plenary. We here give news from the plenary and the platform, sketch out important key messages from the regional assessments as well as of the global thematic assessment on land degradation and restoration. We further give an outlook on the work ahead and potential for contributions from the scientific community to the important work of IPBES.     

The best of all worlds or the best possible world? Developmental constraint in the evolution of β-tubulin and the sperm tail axoneme

Through evolutionary history, some features of the phenotype show little variation. Stabilizing selection could produce this result, but the possibility also exists that a feature is conserved because it is developmentally constrained--only one or a few developmental mechanisms can produce that feature. We present experimental data documenting developmental constraint in the assembly of the motile sperm tail axoneme. The 9+2 microtubule architecture of the eukaryotic axoneme has been deeply conserved. We argue that the quality of motility supported by axonemes with this morphology explains their long conservation, rather than a developmental necessity for the 9+2 architecture. However, our functional tests in Drosophila spermatogenesis reveal considerable constraint in the coevolution of testis-specific beta-tubulin and the sperm tail axoneme. The evolution of testis beta-tubulins used in insect sperm tail axonemes is highly punctuated, indicating some pressure acting on their evolution. We provide a mechanistic explanation for their punctuated evolution by testing structure-function relationships between testis beta-tubulin and the motile axoneme in D. melanogaster. We discovered that a highly conserved sequence feature of beta-tubulins used in motile axonemes is needed to specify central pair formation. Second, our data suggest that cooperativity in the function of internal beta-tubulin amino acids is needed to support the long axonemes characteristic of Drosophila sperm tails. Thus, central pair formation constrains the evolution of the axoneme motif, and intramolecular cooperativity makes the evolution of the internal residues path dependent, which slows their evolution. Our results explain why a highly specialized beta-tubulin is needed to construct the Drosophila sperm tail axoneme. We conclude that these constraints have fixed testis-specific beta-tubulin identity in Drosophila.     

Taking the brakes off-are IC foundries in the industry's best interest?

Following up last issue's editorial topic, GaAs evangelism, another prime driving factor for the IC industry is the need for more design freedom. Before any new technology can be taken up, there must be enough engineers out there versed in the methodology. This obvious statement begs the question: where does this knowledge come from? Most noticeably from the IC foundries who are, for the most part, keen to restrict the spread of this knowledge outside their “club” of users. Is this in the best interest of progress in the GaAs industry as a whole?     

How can the functional reponse best be determined?

Summary We evaluated three methods for the analysis of functional response data by asking whether a given method could discriminate among functional responses and whether it could accurately identify regions of positive density-dependent predation. We evaluated comparative curve fitting with foraging models, linear least-squares analysis using the angular transformation, and logit analysis. Using data from nature and simulations, we found that the analyses of predation rates with the angular transformation and logit analysis were best at consistently determining the true functional response, i.e. the model used to generate simulated data. These methods also produced the most accurate estimates of the true regions of density dependence. Of these two methods, functional response data best fulfill the assumptions of logit analysis. Angularly transformed predation rates only approximate the assumptions of linear leastsquares analysis for predation rates between 0.1 and 0.9. Lack-of-fit statistics can reveal inadequate fit of a model to a data set where simple regression statistics might erroneously suggest a good match.     

Micro‐ or macroscale? Which one best predicts the establishment of an endemic Atlantic Forest palm?

Historically, macroecology and microecology have diverged with regard to the niche concept. A better understanding of functioning ecological systems, however, depends on an integrative approach to this concept at different spatial scales. A mixed approach, merging macro‐ and microscale by validating ecological niche modeling (ENM) with the results of in situ experiments and environmental data collection was used to understand if areas identified by ENM as highly suitable for adult palms are also adequate for seedling establishment. Syagrus weddelliana's (Arecaceae) distribution range falls within the Atlantic Rain Forest, and more specifically Serra dos Órgãos region (Rio de Janeiro state), southeastern Brazil. The following steps were performed: (a) ENM to delimit the area of occurrence of S. weddelliana and locate experimental areas; (b) a seed sowing experiment in areas with presence or absence of the species in areas of high or low environmental suitability at 36 experimental stations; and (c) characterization of each microhabitat which was related back to the macroscale results of ENM. Evidence of biotic and abiotic limitations was found for S. weddelliana distribution. Areas of higher suitability had lower seed predation rates and, consequently, higher seed germination rates. On the other hand, areas with low environmental suitability at the macroscale were divided into two types: areas with microhabitat similar to that of areas with high environmental suitability that had some germination despite high predation and areas with different environmental conditions that had no germination and high predation rates. Seedlings and adults had different abiotic requirements. Microhabitat conditions were more important for the initial establishment of S. weddelliana than macroclimatic variables. This finding demonstrates that macro‐ and microecological information works in a complementary way to a better understanding of the distribution of S. weddelliana.     

Translational biomaterials — the journey from the bench to the market — think ‘product’

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Is vegetation composition or soil chemistry the best predictor of the soil microbial community?

With the species composition and/or functioning of many ecosystems currently changing due to anthropogenic drivers it is important to understand and, ideally, predict how changes in one part of the ecosystem will affect another. Here we assess if vegetation composition or soil chemistry best predicts the soil microbial community. The above and below-ground communities and soil chemical properties along a successional gradient from dwarf shrubland (moorland) to deciduous woodland (Betula dominated) were studied. The vegetation and soil chemistry were recorded and the soil microbial community (SMC) assessed using Phospholipid Fatty Acid Extraction (PLFA) and Multiplex Terminal Restriction Fragment Length Polymorphism (M-TRFLP). Vegetation composition and soil chemistry were used to predict the SMC using Co-Correspondence analysis and Canonical Correspondence Analysis and the predictive power of the two analyses compared. The vegetation composition predicted the soil microbial community at least as well as the soil chemical data. Removing rare plant species from the data set did not improve the predictive power of the vegetation data. The predictive power of the soil chemistry improved when only selected soil variables were used, but which soil variables gave the best prediction varied between the different soil microbial communities being studied (PLFA or bacterial/fungal/archaeal TRFLP). Vegetation composition may represent a more stable ‘summary’ of the effects of multiple drivers over time and may thus be a better predictor of the soil microbial community than one-off measurements of soil properties.     

Human adult olfactory bulb neurogenesis? Novelty is the best policy

There is ongoing controversy as to whether the understanding of adult mammalian neurogenesis gained from rodent studies is applicable to humans. In this issue of Neuron, Bergmann et al. (2012) propose that adult human olfactory bulb neurogenesis with long-term neuronal survival is extremely limited.