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The terrestrial biosphere is a key component of the global carbon cycle and its carbon balance is strongly influenced by climate. Continuing environmental changes are thought to increase global terrestrial carbon uptake. But evidence is mounting that climate extremes such as droughts or storms can lead to a decrease in regional ecosystem carbon stocks and therefore have the potential to negate an expected increase in terrestrial carbon uptake. Here we explore the mechanisms and impacts of climate extremes on the terrestrial carbon cycle, and propose a pathway to improve our understanding of present and future impacts of climate extremes on the terrestrial carbon budget.
Aim Biotic interactions within guilds or across trophic levels have widely been ignored in species distribution models (SDMs). This synthesis outlines the development of species interaction distribution models (SIDMs), which aim to incorporate multispecies interactions at large spatial extents using interaction matrices. Location Local to global. Methods We review recent approaches for extending classical SDMs to incorporate biotic interactions, and identify some methodological and conceptual limitations. To illustrate possible directions for conceptual advancement we explore three principal ways of modelling multispecies interactions using interaction matrices: simple qualitative linkages between species, quantitative interaction coefficients reflecting interaction strengths, and interactions mediated by interaction currencies. We explain methodological advancements for static interaction data and multispecies time series, and outline methods to reduce complexity when modelling multispecies interactions. Results Classical SDMs ignore biotic interactions and recent SDM extensions only include the unidirectional influence of one or a few species. However, novel methods using error matrices in multivariate regression models allow interactions between multiple species to be modelled explicitly with spatial co-occurrence data. If time series are available, multivariate versions of population dynamic models can be applied that account for the effects and relative importance of species interactions and environmental drivers. These methods need to be extended by incorporating the non-stationarity in interaction coefficients across space and time, and are challenged by the limited empirical knowledge on spatio-temporal variation in the existence and strength of species interactions. Model complexity may be reduced by: (1) using prior ecological knowledge to set a subset of interaction coefficients to zero, (2) modelling guilds and functional groups rather than individual species, and (3) modelling interaction currencies and species effect and response traits. Main conclusions There is great potential for developing novel approaches that incorporate multispecies interactions into the projection of species distributions and community structure at large spatial extents. Progress can be made by: (1) developing statistical models with interaction matrices for multispecies co-occurrence datasets across large-scale environmental gradients, (2) testing the potential and limitations of methods for complexity reduction, and (3) sampling and monitoring comprehensive spatio-temporal data on biotic interactions in multispecies communities.
The global expansion of species beyond their ancestral ranges can derive from mechanisms that are trait-based (e.g., post-establishment evolved differences compared to home populations) or circumstantial (e.g., propagule pressure, with no trait-based differences). These mechanisms can be difficult to distinguish following establishment, but each makes unique predictions regarding trait similarity between ancestral ('home') and introduced ('away') populations. Here, we tested for trait-based population differences across four continents for the globally distributed grass Dactylis glomerata, to assess the possible role of trait evolution in its worldwide expansion. We used a common-environment glasshouse experiment to quantify trait differences among home and away populations, and the potential relevance of these differences for competitive interactions. Few significant trait differences were found among continents, suggesting minimal change during global expansion. All populations were polyploids, with similar foliar carbon:nitrogen ratios (a proxy for defense), chlorophyll content, and biomass. Emergence time and growth rate favored home populations, resulting in their competitive superiority over away populations. Small but significant trait differences among away populations suggest different introductory histories or local adaptive responses following establishment. In summary, the worldwide distribution of this species appears to have arisen from its pre-adapted traits promoting growth, and its repeated introduction with cultivation and intense propagule pressure. Global expansion can thus occur without substantial shifts in growth, reproduction, or defense. Rather than focusing strictly on the invader, invasion success may also derive from the traits found (or lacking) in the recipient community and from environmental context including human disturbance.
New N-p-chloro-, N-p-bromo-, and N-p-nitrophenylazobenzylchitosan derivatives, as well as the corresponding azophenyl and azophenyl-p-sulfonic acids, were synthesized by coupling N-benzylvchitosan with aryl diazonium salts. The synthesized molecules were analyzed by UV-Vis, FT-IR, H-1-NMR and N-15-NMR spectroscopy. The capacity of copper chelation by these materials was studied by AAS. Chitosan and the derivatives were subjected to hydrolysis and the products were analyzed by ESI(+)-MS and GC-MS, confirming the formation of N-benzyl chitosan. Furthermore, the MS results indicate that a nucleophilic aromatic substitution (SnAr) reaction occurs under hydrolysis conditions, yielding chloroaniline from N-p-bromo-, and N-p-nitrophenylazo-benzylchitosan as well as bromoaniline from N-p-chloro-, and N-p-nitrophenylazobenzyl-chitosan.