Global economic impacts of climate variability and change during the 20th century

Estimates of the global economic impacts of observed climate change during the 20th century obtained by applying five impact functions of different integrated assessment models (IAMs) are separated into their main natural and anthropogenic components. The estimates of the costs that can be attributed to natural variability factors and to the anthropogenic intervention with the climate system in general tend to show that: 1) during the first half of the century, the amplitude of the impacts associated with natural variability is considerably larger than that produced by anthropogenic factors and the effects of natural variability fluctuated between being negative and positive. These non-monotonic impacts are mostly determined by the low-frequency variability and the persistence of the climate system; 2) IAMs do not agree on the sign (nor on the magnitude) of the impacts of anthropogenic forcing but indicate that they steadily grew over the first part of the century, rapidly accelerated since the mid 1970's, and decelerated during the first decade of the 21st century. This deceleration is accentuated by the existence of interaction effects between natural variability and natural and anthropogenic forcing. The economic impacts of anthropogenic forcing range in the tenths of percentage of the world GDP by the end of the 20th century; 3) the impacts of natural forcing are about one order of magnitude lower than those associated with anthropogenic forcing and are dominated by the solar forcing; 4) the interaction effects between natural and anthropogenic factors can importantly modulate how impacts actually occur, at least for moderate increases in external forcing. Human activities became dominant drivers of the estimated economic impacts at the end of the 20th century, producing larger impacts than those of low-frequency natural variability. Some of the uses and limitations of IAMs are discussed

Ecological networks: Pursuing the shortest path, however narrow and crooked

International audienceRepresenting data as networks cuts across all sub-disciplines in ecology and evolutionary biology. Besides providing a compact representation of the interconnections between agents, network analysis allows the identification of especially important nodes, according to various metrics that often rely on the calculation of the shortest paths connecting any two nodes. While the interpretation of a shortest paths is straightforward in binary, unweighted networks, whenever weights are reported, the calculation could yield unexpected results. We analyzed 129 studies of ecological networks published in the last decade that use shortest paths, and discovered a methodological inaccuracy related to the edge weights used to calculate shortest paths (and related centrality measures), particularly in interaction networks. Specifically, 49% of the studies do not report sufficient information on the calculation to allow their replication, and 61% of the studies on weighted networks may contain errors in how shortest paths are calculated. Using toy models and empirical ecological data, we show how to transform the data prior to calculation and illustrate the pitfalls that need to be avoided. We conclude by proposing a five-point checklist to foster best-practices in the calculation and reporting of centrality measures in ecology and evolution studies. The last two decades have witnessed an exponential increase in the use of graph analysis in ecological and conservation studies (see refs. 1,2 for recent introductions to network theory in ecology and evolution). Networks (graphs) represent agents as nodes linked by edges representing pairwise relationships. For instance, a food web can be represented as a network of species (nodes) and their feeding relationships (edges) 3. Similarly, the spatial dynamics of a metapopulation can be analyzed by connecting the patches of suitable habitat (nodes) with edges measuring dispersal between patches 4. Data might either simply report the presence/absence of an edge (binary, unweighted networks), or provide a strength for each edge (weighted networks). In turn, these weights can represent a variety of ecologically-relevant quantities, depending on the system being described. For instance, edge weights can quantify interaction frequency (e.g., visitation networks 5), interaction strength (e.g., per-capita effect of one species on the growth rate of another 3), carbon-flow between trophic levels 6 , genetic similarity 7 , niche overlap (e.g., number of shared resources between two species 8), affinity 9 , dispersal probabilities (e.g., the rate at which individuals of a population move between patches 10), cost of dispersal between patches (e.g., resistance 11), etc. Despite such large variety of ecological network representations, a common task is the identification of nodes of high importance, such as keystone species in a food web, patches acting as stepping stones in a dispersal network , or genes with pleiotropic effects. The identification of important nodes is typically accomplished through centrality measures 5,12. Many centrality measures has been proposed, each probing complementary aspects of node-to-node relationships 13. For instance, Closeness centrality 14,15 highlights nodes that are "near" to all othe

Biological invasion of European tomato crops by Tuta absoluta: ecology, geographic expansion and prospects for biological control

The tomato leafminer Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) is a devastating pest of tomato originating from South America. After its initial detection in eastern Spain in 2006, it rapidly invaded various other European countries and spread throughout the Mediterranean basin. If no control measures are taken, then the pest can cause up to 80-100% yield losses in tomato crops in recently invaded areas and may pose a threat to both greenhouse and open-field tomato production. The exceptional speed and extent of T. absoluta invasion have called for studies documenting its biology and ecology, while indicating an urgent need for efficient and sustainable management methods. The development of approaches to manage T. absoluta would be facilitated through a detailed revision of information on this pest in its area of origin. This review combines information on the invasion by T. absoluta, its ecology, and potential management strategies, including data that may help the implementation of efficient biological control programs. These programs, together with a variety of other management tactics, may allow efficient integrated pest management of T. absoluta in Europe and Mediterranean Basin countries. © 2010 Springer-Verlag

Propensity of the Tomato Leafminer, Tuta absoluta (Lepidoptera: Gelechiidae), to Develop on Four Potato Plant Varieties

The tomato leafminer, Tuta absoluta (Lepidoptera: Gelechiidae), is now considered to be one of the most damaging invasive pests of tomatoes in the world. Tomato is regarded as the main host of T. absoluta, but the pest can also feed, develop and reproduce on other cultivated Solanaceae, such as potato (Solanum tuberosum L). In the present study, we examined the ability of T. absoluta to develop on four commonly cultivated varieties of potato, under laboratory conditions. The survival rate of T. absoluta did not differ between the five tested host plants (tomato: Solanum lycopersicum cv. Moneymaker; and potato: Solanum tuberosum cv. Spunta, Charlotte, Nicola, and Bintje), but its development time (egg to pupation) was significantly affected. Compared to tomato, development times were longer on Bintje and shorter on Nicola, Charlotte, and Spunta. These results show the high capacity of T. absoluta to develop on potato crops

Sea Ice Modelling

Peer reviewe

Measurement of event-shape observables in Z -> l(+)l(-) events in pp collisions at root s=7 TeV with the ATLAS detector at the LHC

Event-shape observables measured using charged particles in inclusive Z-boson events are presented, using the electron and muon decay modes of the Z bosons. The measurements are based on an integrated luminosity of 1.1 fb(-1) of proton-proton collisions recorded by the ATLAS detector at the LHC at a centre-of-mass energy root s = 7 TeV. Charged-particle distributions, excluding the lepton-antilepton pair from the Z-boson decay, are measured in different ranges of transverse momentum of the Z boson. Distributions include multiplicity, scalar sum of transverse momenta, beam thrust, transverse thrust, spherocity, and F-parameter, which are in particular sensitive to properties of the underlying event at small values of the Z-boson transverse momentum. The measured observables are compared with predictions from PYTHIA 8, Sherpa, and HERWIG 7. Typically, all three Monte Carlo generators provide predictions that are in better agreement with the data at high Z-boson transverse momenta than at low Z-boson transverse momenta, and for the observables that are less sensitive to the number of charged particles in the event