Diego Nieto-Lugilde

Detection of airborne allergen (Ole e 1) in relation to Olea europaea pollen in S Spain

Background In recent years, it has been demonstrated that the air carries not only airborne pollen but also plant particles of smaller size that have allergenic activity, and, being within the respirable range, these particles can trigger rapid attacks in the lower respiratory tract. The study of particles according to size (0.7–40 μm) could provide valuable information on the real allergenic activity in the atmosphere.

A matter of scale: apparent niche differentiation of diploid and tetraploid plants may depend on extent and grain of analysis

Abstract Aim Emerging polyploids may depend on environmental niche shifts for successful establishment. Using the alpine plant Ranunculus kuepferi as a model system, we explore the niche shift hypothesis at different spatial resolutions and in contrasting parts of the species range. Location European Alps. Methods We sampled 12 individuals from each of 102 populations of R. kuepferi across the Alps, determined their ploidy levels, derived coarse‐grain (100 × 100 m) environmental descriptors for all sampling sites by downscaling WorldClim maps, and calculated fine‐scale environmental descriptors (2 × 2 m) from indicator values of the vegetation accompanying the sampled individuals. Both coarse and fine‐scale variables were further computed for 8239 vegetation plots from across the Alps. Subsequently, we compared niche optima and breadths of diploid and tetraploid cytotypes by combining principal components analysis and kernel smoothing procedures. Comparisons were done separately for coarse and fine‐grain data sets and for sympatric, allopatric and the total set of populations. Results All comparisons indicate that the niches of the two cytotypes differ in optima and/or breadths, but results vary in important details. The whole‐range analysis suggests differentiation along the temperature gradient to be most important. However, sympatric comparisons indicate that this climatic shift was not a direct response to competition with diploid ancestors. Moreover, fine‐grained analyses demonstrate niche contraction of tetraploids, especially in the sympatric range, that goes undetected with coarse‐grained data. Main conclusions Although the niche optima of the two cytotypes differ, separation along ecological gradients was probably less decisive for polyploid establishment than a shift towards facultative apomixis, a particularly effective strategy to avoid minority cytotype exclusion. In addition, our results suggest that coarse‐grained analyses overestimate niche breadths of widely distributed taxa. Niche comparison analyses should hence be conducted at environmental data resolutions appropriate for the organism and question under study.

Controlled comparison of species- and community-level models across novel climates and communities.

Species distribution models (SDMs) assume species exist in isolation and do not influence one anothers distributions, thus potentially limiting their ability to predict biodiversity patterns. Community-level models (CLMs) capitalize on species co-occurrences to fit shared environmental responses of species and communities, and therefore may result in more robust and transferable models. Here, we conduct a controlled comparison of five paired SDMs and CLMs across changing climates, using palaeoclimatic simulations and fossil-pollen records of eastern North America for the past 21 000 years. Both SDMs and CLMs performed poorly when projected to time periods that are temporally distant and climatically dissimilar from those in which they were fit; however, CLMs generally outperformed SDMs in these instances, especially when models were fit with sparse calibration datasets. Additionally, CLMs did not over-fit training data, unlike SDMs. The expected emergence of novel climates presents a major forecasting challenge for all models, but CLMs may better rise to this challenge by borrowing information from co-occurring taxa.

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD.

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950–2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850–2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity.

Multiresponse algorithms for community‐level modelling: Review of theory, applications, and comparison to species distribution models

1.Community-level models (CLMs) consider multiple, co-occurring species in model fitting and are lesser known alternatives to species distribution models (SDMs) for analyzing and predicting biodiversity patterns. CLMs simultaneously model multiple species, including rare species, while reducing overfitting and implicitly considering drivers of co-occurrence. Many CLMs are direct extensions of well-known SDMs and therefore should be familiar to ecologists. However, CLMs remain underutilized, and there have been few tests of their potential benefits and no systematic reviews of their assumptions and implementations. Here we review this emerging field and provide examples in R to fit common CLMs. Our goal is to introduce CLMs to a broader audience, and discuss their attributes, benefits, and limitations relative to SDMs. 2.We review i) statistical implementations and applications of CLMs, ii) their advantages and limitations, and iii) comparative analyses of CLMs and SDMs. We also suggest directions for future research. 3.We identify seven CLM algorithms with similar data structures and predictive outputs as SDMs that should be most accessible to ecologists familiar with species-level modeling, including five methods that predict assemblage composition and individual species distributions and two methods that model compositional turnover along environmental gradients. CLMs have been applied to numerous taxa, regions, and spatial scales, and a variety of topics (e.g., studying drivers of community structure or assessing relationships between community composition and functional traits). Studies suggest that the relative benefits of CLMs and SDMs may be case specific, especially in terms of predicting species distributions and community composition. However, CLMs may offer advantages in terms of computational efficiency, modeling rare species, and projecting to no-analog climates. A major shortcoming of CLMs is their reliance on presence-absence community composition data. 4.Studies are needed to assess the relative merits of SDMs and CLMs, and different CLM algorithms, with a focus on three key areas: i) under which circumstances CLMs improve predictions for rare species, ii) how CLMs perform under different community compositions (e.g. relative abundance of rare vs. common species), including the extent to which co-occurrence patterns are structured by biotic interactions, and iii) ability to project across time/space. This article is protected by copyright. All rights reserved.

Correction to 'Controlled comparison of species- and community-level models across novel climates and communities'.

[ Proc. R. Soc. B 283 , 20152817. (16 March 2016; Published online 9 March 2016) ([doi:10.1098/rspb.2015.2817][2])][2] One of the six climate variables used to fit the models was listed incorrectly in the Environmental variables section under Material and methods [[1][2]]. Mean yearly

Reconstructing geographical parthenogenesis: effects of niche differentiation and reproductive mode on Holocene range expansion of an alpine plant

Abstract Asexual taxa often have larger ranges than their sexual progenitors, particularly in areas affected by Pleistocene glaciations. The reasons given for this ‘geographical parthenogenesis’ are contentious, with expansion of the ecological niche or colonisation advantages of uniparental reproduction assumed most important in case of plants. Here, we parameterized a spread model for the alpine buttercup Ranunculus kuepferi and reconstructed the joint Holocene range expansion of its sexual and apomictic cytotype across the European Alps under different simulation settings. We found that, rather than niche broadening or a higher migration rate, a shift of the apomicts niche towards colder conditions per se was crucial as it facilitated overcoming of topographical barriers, a factor likely relevant for many alpine apomicts. More generally, our simulations suggest potentially strong interacting effects of niche differentiation and reproductive modes on range formation of related sexual and asexual taxa arising from their differential sensitivity to minority cytotype disadvantage.

Estudiando los determinantes de la composición de comunidades y sus dinámicas en el pasado incorporando información filogenética y funcional al registro fósil

Delgado L.A. 2018. Landscape Heterogeneity and tree species diversity in a tropical forest. Development and validation of a methodological proposal. Ecosistemas 27(1): 105-115. Doi.: 10.7818/ECOS.1475 Many landscapes exist as unstable spatial-temporal mosaics where changes in patterns of biodiversity are affected by nature processes and the dynamic interaction between social and ecological factors. It is a consequence of the natural dynamics of socio-economic systems that regulate man-made tropical forests. However, a significant proportion of studies have made generalizations about the relative values of biodiversity, without taking into account the high levels of internal heterogeneity in the biophysical properties and land uses of each site. The purpose of this study is to propose and validate a methodology to delimit the heterogeneity of the landscape based on criteria that integrate the coupling of human-ecological systems such as: space-time dynamics of deforestation and fragmentation; complexity of the landscape structure; current and historical land use and biophysical variability. For this, the use of satellite images, landscape metrics, field work, documentary review and multivariate analysis were combined. The proposed methodology is intended to help guide the empirical delimitation of landscape heterogeneity as a prerequisite for the selection of similar landscapes and forest patches in studies of the diversity of tree species, in order to provide an opportunity to control the possible difficulties caused by variability in the proportion of forests, landscape configuration and successional states, in estimating its effects on forest richness and floristic composition.

Studies applying Community Level Models

Summary table of empirical studies applying Community Level Models (CLMs). The studies have been grouped by CLM algorithm.