Ab initio calculation of H + He+^+ charge transfer cross sections for plasma physics

The charge transfer in low energy (0.25 to 150 eV/amu) H($nl$) + He$^+(1s)$ collisions is investigated using a quasi-molecular approach for the $n=2,3$ as well as the first two $n=4$ singlet states. The diabatic potential energy curves of the HeH$^+$ molecular ion are obtained from the adiabatic potential energy curves and the non-adiabatic radial coupling matrix elements using a two-by-two diabatization method, and a time-dependent wave-packet approach is used to calculate the state-to-state cross sections. We find a strong dependence of the charge transfer cross section in the principal and orbital quantum numbers $n$ and $l$ of the initial or final state. We estimate the effect of the non-adiabatic rotational couplings, which is found to be important even at energies below 1 eV/amu. However, the effect is small on the total cross sections at energies below 10 eV/amu. We observe that to calculate charge transfer cross sections in a $n$ manifold, it is only necessary to include states with $n^{\prime}\leq n$, and we discuss the limitations of our approach as the number of states increases.Comment: 14 pages, 10 figure

Relationships between Biodiversity and Production in Grasslands at Local and Regional Scales

Key points 1. Experimental manipulations of plant species diversity in unfertilised prairies and meadows has revealed that increasing diversity often leads to increased productivity (range of observed relationships varies from flat to log-linearly positive); driven by a combination of facilitation, niche-partitioning and sampling/selection effects. 2. The longer-term effects of diversity on ecosystem stability are not as clear and in need of further work. 3. Recent applied work, and a new review of the grassland literature, both show the potential for biodiversity to increase productivity under realistic field conditions. 4. The longer-term feedback of grazers on biodiversity gradients is unknown, and grassland biodiversity experiments that incorporate grazers will be needed to test whether patterns differ from those seen in ungrazed prairies and meadows. 5. The relationship between diversity and productivity seen in local experiments is often different from regional-scale correlations, and the scaling-up of experimental results remains a research priority

Can the Evolution of Plant Defense Lead to Plant-Herbivore Mutualism?

Moderate rates of herbivory can enhance primary production. This hypothesis has led to a controversy as to whether such positive effects can result in mutualistic interactions between plants and herbivores. We present a model for the ecology and evolution of plant-herbivore systems to address this question. In this model, herbivores have a positive indirect effect on plants through recycling of a limiting nutrient. Plants can evolve but are constrained by a trade-off between growth and antiherbivore defense. Although evolution generally does not lead to optimal plant performance, our evolutionary analysis shows that, under certain conditions, the plant-herbivore interaction can be considered mutualistic. This requires in particular that herbivores efficiently recycle nutrients and that plant reproduction be positively correlated with primary production. We emphasize that two different definitions of mutualism need to be distinguished. A first ecological definition of mutualism is based on the short-term response of plants to herbivore removal, whereas a second evolutionary definition rests on the long-term response of plants to herbivore removal, allowing plants to adapt to the absence of herbivores. The conditions for an evolutionary mutualism are more stringent than those for an ecological mutualism. A particularly counterintuitive result is that higher herbivore recycling efficiency results both in increased plant benefits and in the evolution of increased plant defense. Thus, antagonistic evolution occurs within a mutualistic interaction

Emergence and maintenance of biodiversity in an evolutionary food-web model

Ecological communities emerge as a consequence of gradual evolution, speciation, and immigration. In this study, we explore how these processes and the structure of the evolved food webs are affected by species-level properties. Using a model of biodiversity formation that is based on body size as the evolving trait and incorporates gradual evolution and adaptive radiation, we investigate how conditions for initial diversification relate to the eventual diversity of a food web. We also study how trophic interactions, interference competition, and energy availability affect a food web's maximum trophic level and contrast this with conditions for high diversity. We find that there is not always a positive relationship between conditions that promote initial diversification and eventual diversity, and that the most diverse food webs often do not have the highest trophic levels

Cold collisions of C2−_{2}^{-} anions with Li and Rb atoms in hybrid traps

We present a theoretical investigation of reactive and non-reactive collisions of Li and Rb atoms with C$_{2}^{-}$ molecular anions at low temperatures in the context of sympathetic cooling in hybrid trap experiments. Based on recently reported accurate potential energy surfaces for the singlet and triplet states of the Li-C$_{2}^{-}$ and Rb-C$_{2}^{-}$ systems, we show that the associative electronic detachment reaction is slow if the colliding partners are in their ground state, but fast if they are excited. The results are expected to be representative of the alkali-metal series. We also investigate rotationally inelastic collisions in order to explore the cooling of the translational and rotational degrees of freedom of C$_2^-$ in hybrid ion-atom traps. The effect of micromotion is taken into account by considering Tsallis distributions of collision energies. We show that the translational cooling occurs much more rapidly than rotational cooling and that the presence of excited atoms leads to losses of anions on a timescale comparable to that of rotational cooling.Comment: ICPEAC 2019 conferenc

Biodiversity, productivity, and the spatial insurance hypothesis revisited

Accelerating rates of biodiversity loss have led ecologists to explore the effects of species richness on ecosystem functioning and the flow of ecosystem services. One explanation of the relationship between biodiversity and ecosystem functioning lies in the spatial insurance hypothesis, which centers on the idea that productivity and stability increase with biodiversity in a temporally varying, spatially heterogeneous environment. However, there has been little work on the impact of dispersal where environmental risk are more or less spatially correlated, or where dispersal rates are variable. In this paper, we extend the original Loreau model to consider stochastic temporal variation in resource availability, which we refer to as "environmental risk", and heterogeneity in species dispersal rates. We find that asynchronies across communities and species provide community-level stabilizing effects on productivity, despite varying levels of species richness. Although intermediate dispersal rates play a role in mitigating risk, they are less effective in insuring productivity against global (metacommunity-level) than local (individual community-level) risks. These results are particularly interesting given the emergence of global sources of risk such as climate change or the closer integration of world markets. Our results offer deeper insights into the Loreau model and new perspectives on the effectiveness of spatial insurance in the face of environmental risks

Global relationship between phytoplankton diversity and productivity in the ocean

The shape of the productivity–diversity relationship (PDR) for marine phytoplankton has been suggested to be unimodal, that is, diversity peaking at intermediate levels of productivity. However, there are few observations and there has been little attempt to understand the mechanisms that would lead to such a shape for planktonic organisms. Here we use a marine ecosystem model together with the community assembly theory to explain the shape of the unimodal PDR we obtain at the global scale. The positive slope from low to intermediate productivity is due to grazer control with selective feeding, which leads to the predator-mediated coexistence of prey. The negative slope at high productivity is due to seasonal blooms of opportunist species that occur before they are regulated by grazers. The negative side is only unveiled when the temporal scale of the observation captures the transient dynamics, which are especially relevant at highly seasonal latitudes. Thus selective predation explains the positive side while transient competitive exclusion explains the negative side of the unimodal PDR curve. The phytoplankton community composition of the positive and negative sides is mostly dominated by slow-growing nutrient specialists and fast-growing nutrient opportunist species, respectively.Marie Curie International Outgoing Fellowship (FP7)Gordon and Betty Moore FoundationSpain. Ministerio de Economía y Competitividad (Ramon y Cajal Contracts

Mapping the species richness and composition of tropical forests from remotely sensed data with neural networks

The understanding and management of biodiversity is often limited by a lack of data. Remote sensing has considerable potential as a source of data on biodiversity at spatial and temporal scales appropriate for biodiversity management. To-date, most remote sensing studies have focused on only one aspect of biodiversity, species richness, and have generally used conventional image analysis techniques that may not fully exploit the data's information content. Here, we report on a study that aimed to estimate biodiversity more fully from remotely sensed data with the aid of neural networks. Two neural network models, feedforward networks to estimate basic indices of biodiversity and Kohonen networks to provide information on species composition, were used. Biodiversity indices of species richness and evenness derived from the remotely sensed data were strongly correlated with those derived from field survey. For example, the predicted tree species richness was significantly correlated with that observed in the field (r=0.69, significant at the 95% level of confidence). In addition, there was a high degree of correspondence (?83%) between the partitioning of the outputs from Kohonen networks applied to tree species and remotely sensed data sets that indicated the potential to map species composition. Combining the outputs of the two sets of neural network based analyses enabled a map of biodiversity to be produce