Three new papers from the lab have been accepted during the last weeks. They will be published online early during the next weeks/months, but here go the abstracts:
Ulrich, W., S. Soliveres, W. Kryszewski, F. T. Maestre & N. J. Gotelli. Matrix models for quantifying competitive intransitivity from species abundance data. Oikos
In a network of competing species, a competitive intransitivity occurs when the ranking of competitive abilities does not follow a linear hierarchy (A>B>C but C>A). A variety of mathematical models suggests that intransitive networks can prevent or slow down competitive exclusion and maintain biodiversity by enhancing species coexistence. However, it has been difficult to assess empirically the relative importance of intransitive competition because a large number of pairwise species competition experiments are needed to construct a competition matrix that is used to parameterize existing models. Here we introduce a statistical framework for evaluating the contribution of intransitivity to community structure using species abundance matrices that are commonly generated from replicated sampling of species assemblages. We provide metrics and analytical methods for using abundance matrices to estimate species competition and patch transition matrices by using reverse-engineering and a colonization-competition model. These matrices provide complementary metrics to estimate the degree of intransitivity in the competition network of the sampled communities. Benchmark tests reveal that the proposed methods could successfully detect intransitive competition networks, even in the absence of direct measures of pairwise competitive strength. To illustrate the approach, we analyzed patterns of abundance and biomass of five species of necrophagous Diptera and eight species of their hymenopteran parasitoids that co-occur in beech forests in Germany. We found evidence for a strong competitive hierarchy within communities of flies and parasitoids. However, for parasitoids, there was a tendency towards increasing intransitivity in higher weight classes, which represented larger resource patches. These tests provide novel methods for empirically estimating the degree of intransitivity in competitive networks from observational datasets. They can be applied to experimental measures of pairwise species interactions, as well as to spatio-temporal samples of assemblages in homogenous environments or environmental gradients.
Escudero, A., S. Palacio, F. T. Maestre & A. Luzuriaga. 2014. Plant life on gypsum: a review of its multiple facets. Biological Reviews
The adaptation of plants to particular soil types has long intrigued biologists. Gypsum soils occupy large areas in many regions of the world and host a striking biological diversity, but their vegetation has been much less studied than that developing over serpentine or saline soils. Herein, we review all aspects of plant life on gypsum ecosystems, discuss the main processes driving their structure and functioning, and highlight the main conservation threats that they face. Plant communities in gypsum habitats typically show distinctive bands at very small spatial scales, which are mainly determined by topography. Plants living on gypsum soils can be classified into three categories: (i) wide gypsophiles are specialists that can penetrate the physical soil crust during early life stages and have physiological adjustments to cope with the chemical limitations imposed by gypsum soils; (ii) narrow gypsophiles are refugee plants which successfully deal with the physical soil crust and can tolerate these chemical limitations but do not show specific adaptations for this type of soils; and (iii) gypsovags are non-specialist gypsum plants that can only thrive in gypsum soils when the physical crust is absent or reduced. Their ability to survive in gypsum soils may also be mediated by below-ground interactions with soil microorganisms. Gypsophiles and gypsovags show efficient germination at low temperatures, seed and fruit heteromorphism within and among populations, and variation in seed dormancy among plants and populations. In gypsum ecosystems, spatio-temporal changes in the composition and structure of aboveground vegetation are closely related to those of the soil seed bank. Biological soil crusts (BSCs) dominated by cyanobacteria, lichens and mosses are conspicuous in gypsum environments worldwide, and are important drivers of ecosystem processes such as carbon and nitrogen cycling, water infiltration and run-off and soil stability. These organisms are also important determinants of the structure of annual plant communities living on gypsum soils. The short-distance seed dispersal of gypsophiles is responsible for the high number of very narrow endemisms typically found in gypsum outcrops, and suggests that these species are evolutionarily old taxa due to the time they need to colonize isolated gypsum outcrops by chance. Climate change and habitat fragmentation negatively affect both plants and BSCs in gypsum habitats, and are among the major threats to these ecosystems. Gypsum habitats and specialists offer the chance to advance our knowledge on restrictive soils, and are ideal models not only to test important evolutionary questions such as tolerance to low Ca/Mg proportions in soils, but also to improve the theoretical framework of community ecology and ecosystem functioning.
Guerrero, C., B. Stenberg, J. Wetterlind, R. A. Viscarra Rossel, A. M. Mouazen, R. Zornoza, F. T. Maestre, J. D. Ruiz-Sinoga & B. Kuang. 2014. Assessment of soil organic carbon at local scale with spiked NIR calibrations: effects of selection and extra-weight of the spiking subset. European Journal of Soil Science
Spiking is an interesting approach to improve the accuracy of regional or national spectroscopic calibrations when they are used to predict at local. For doing this, a small subset of local samples (spiking subset; SS) is added to recalibrate the regional or national calibration. If the SS is small in comparison with the size of the initial calibration (IC) set, then the information added with this SS could have a little noticeable effect, and the improvement in the calibration model is also small. For these reasons, we hypothesised that the accuracy of the spiked calibrations can be improved when the statistical relevance of the SS is extra-weighted (EW). Moreover, we also hypothesised that the selection of the SS, and also the size of the IC set are relevant and can affect the accuracy of the recalibrated models. With the aim to test these hypotheses, we have evaluated thirteen different strategies, without and with EW, to select the best SS to spike three ICs of different sizes. These calibrations were used to predict the soil organic carbon (SOC) in samples from four independent target sites. The results confirmed that spiking improves the prediction accuracy of the ICs. The accuracy was significantly improved when the SS was EW. This result is very interesting because EW is a simple, fast and inexpensive task. As expected, we observed differences in accuracy depending on the SS used. The best results were obtained with the SS containing local samples evenly distributed in the spectral space, regardless the characteristics of the ICs. The best results were obtained using the small- and medium-sized ICs, suggesting that incipient spectral libraries could be useful if the SS is properly selected and EW. Overall, our results indicate that the efforts needed for the use NIR spectroscopy for SOC assessment at local scale can be minimized by using EW, which is highly recommended when calibrations are spiked.