Predicting species' tolerance to salinity and alkalinity using distribution data and geochemical modelling: a case study using Australian grasses

BACKGROUND AND AIMS: Salt tolerance has evolved many times independently in different plant groups. One possible explanation for this pattern is that it builds upon a general suite of stress-tolerance traits. If this is the case, then we might expect a correlation between salt tolerance and other tolerances to different environmental stresses. This association has been hypothesized for salt and alkalinity tolerance. However, a major limitation in investigating large-scale patterns of these tolerances is that lists of known tolerant species are incomplete. This study explores whether species' salt and alkalinity tolerance can be predicted using geochemical modelling for Australian grasses. The correlation between taxa found in conditions of high predicted salinity and alkalinity is then assessed. METHODS: Extensive occurrence data for Australian grasses is used together with geochemical modelling to predict values of pH and electrical conductivity to which species are exposed in their natural distributions. Using parametric and phylogeny-corrected tests, the geochemical predictions are evaluated using a list of known halophytes as a control, and it is determined whether taxa that occur in conditions of high predicted salinity are also found in conditions of high predicted alkalinity. KEY RESULTS: It is shown that genera containing known halophytes have higher predicted salinity conditions than those not containing known halophytes. Additionally, taxa occurring in high predicted salinity tend to also occur in high predicted alkalinity. CONCLUSIONS: Geochemical modelling using species' occurrence data is a potentially useful approach to predict species' relative natural tolerance to challenging environmental conditions. The findings also demonstrate a correlation between salinity tolerance and alkalinity tolerance. Further investigations can consider the phylogenetic distribution of specific traits involved in these ecophysiological strategies, ideally by incorporating more complete, finer-scale geochemical information, as well as laboratory experiments.This work was supported by the Australian Research Council

Location equivalence in a parametric setting

AbstractLocation equivalence has been presented in [5] as a bisimulation-based equivalence able to take into account the spatial distribution of processes.In this work, the parametric approach of [12] is applied to location equivalence. An observation domain for localities is identified and the associated equivalence is shown to coincide with the equivalence introducted in [6,16]. The observation of a computation is a forest (defined up to isomorphism) whose nodes are the events (labeled by observable actions) and where the arcs describe the sublocation relation.We show in the paper that our approach is really parametric. By performing minor changes in the definitions, many equivalences are captured: partial and mixed ordering causal semantics, interleaving, and a variation of location equivalence where the generation ordering is not evidenced. It seems difficult to modify the definitions of [6,16] to obtain the last observation. The equivalence induced by this observation corresponds to the very intuitive assumption that different locations cannot share a common clock, and hence the ordering between events occurring in different places cannot be determined.Thanks to the general results proved in [12] for the parametric approach, all the observation equivalences described in this paper come equipped with sound and complete axiomatizations

A new measure of conservation value combining rarity and ecological diversity: a case study with light trap collected caddisflies (Insecta: Trichoptera)

The objective of the present study was to analyse the conservation importance of streams, rivers and lakes for maintaining caddistly assemblages of Hungarian localities. Light traps ensured comparable catches of caddisflies from different aquatic habitats. A total of 245,363 individuals belonging to 152 species collected from 23 localities over the flight period were included in the analysis. Conservation value of caddistly assemblages was evaluated on the basis of a newly developed Rarity and Ecological Diversity (RED)-index expressing ecological diversity and the average rarity of caddistlies in Hungarian localities. The results showed that streams were the most suitable habitats for maintaining rare caddisfly species in diverse assemblages, while rivers had the lowest conservation importance

How good a map ? Putting small area estimation to the test

The authors examine the performance of small area welfare estimation. The method combines census and survey data to produce spatially disaggregated poverty and inequality estimates. To test the method, they compare predicted welfare indicators for a set of target populations with their true values. They construct target populations using actual data from a census of households in a set of rural Mexican communities. They examine estimates along three criteria: accuracy of confidence intervals, bias, and correlation with true values. The authors find that while point estimates are very stable, the precision of the estimates varies with alternative simulation methods. While the original approach of numerical gradient estimation yields standard errors that seem appropriate, some computationally less-intensive simulation procedures yield confidence intervals that are slightly too narrow. The precision of estimates is shown to diminish markedly if unobserved location effects at the village level are not well captured in underlying consumption models. With well specified models there is only slight evidence of bias, but the authors show that bias increases if underlying models fail to capture latent location effects. Correlations between estimated and true welfare at the local level are highest for mean expenditure and poverty measures and lower for inequality measures.Small Area Estimation Poverty Mapping,Rural Poverty Reduction,Science Education,Scientific Research&Science Parks,Population Policies

The Effect of Income on Demand for Micronutrients in Poor Rural Mexico

We estimate income elasticities for a variety of macro- and micro-nutrients using a sample of poor rural households in Mexico. The nutrient-income elasticity is estimated using a linear regression model controlling both for the clustered nature of our data and for the bias due to measurement error in nutrient consumption at the household level. Our preferred estimates (instrumental variable-fixed effect specification for the sample of all households) show a sizeable positive elasticity for some nutrients (especially vitamin A 0.8, vitamin C 0.69 and calcium 0.45). For other nutrients the effect of income on the consumption is still significant but very small (elasticity for fiber is only 0.09 and for iron 0.08). We also test for the robustness of our estimates using a semi-parametric estimator (partially linear model) and whether the presence of zero consumption for specific micronutrients in our sample, such as cholesterol and heme iron, can be a source of bias for our estimates.vitamin A , vitamin C; folate; iron; zinc; calcium; calories; protein; fat; carbohydrates; Income elasticity; partially linear model.

Price-concentration analysis in merger cases with differentiated products

This paper considers the empirical assessment of the relationship between prices and number of firms in local markets in geographic or, more generally, characteristic space and its use as evidence in merger cases. It outlines a structural, semi-nonparametric econometric model of competition in such markets, examines its testable implications in terms of price-concentration relationships, and demonstrates that the model is non-parametrically identified. This general approach to price-concentration analysis in differentiated product markets is illustrated in a small-scale application to cinemas in the UK. The application highlights the main decision points faced by an authority when assessing the weight that can be attached to this type of analysis as evidence

Can Social Programs be Reliably Evaluated with NonExperimental Methods? Evidence on the Performance of Regression Discontinuity Design using PROGRESA data

In 1997 a social program called PROGRESA was introduced in Mexico using a design for a randomized experiment. We exploit a build in, but neglected, discontinuity in the eligibility rule and use the quasi-experimental Regression-Discontinuity design in order to estimate marginal average treatment effects. Our findings show substantial regional variation. Moreover, given that the RDD approach allows us to use only data from the treated sample, we are able to investigate the extend to which the introduction of the program had an effect on ineligible children in the localities it was introduced and compare its performance to the experimental outcomes.treatment effects, regression discontinuity design, PROGRESA

Can Social Protection Reduce Environmental Damages?

Why do damages from changes in environmental quality differ across and within countries? Causal investigation of this question has been challenging because differences may stem from heterogeneity in cumulative exposure or differences in socioeconomic factors such as income. We revisit the temperature-violence relationship and show that cash transfers attenuate one-half to two-thirds of the effects of higher same-day temperatures on homicides. Our results not only demonstrate causally that income can explain much of the heterogeneity in the marginal effects of higher temperatures, but also imply that social protection programs can help the poor adapt to rising temperatures