TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Rare and common vertebrates span a wide spectrum of population trends

Conservation biologists often assume that rare (or less abundant) species are more likely to be declining under anthropogenic change. Here, the authors synthesise population trend data for ~2000 animal species to show that population trends cover a wide spectrum of change from losses to gains, which are not related to species rarity

Changes in the geographical distribution of plant species and climatic variables on the West Cornwall peninsula (South West UK)

Recent climate change has had a major impact on biodiversity and has altered the geographical distribution of vascular plant species. This trend is visible globally; however, more local and regional scale research is needed to improve understanding of the patterns of change and to develop appropriate conservation strategies that can minimise cultural, health, and economic losses at finer scales. Here we describe a method to manually geo-reference botanical records from a historical herbarium to track changes in the geographical distributions of plant species in West Cornwall (South West England) using both historical (pre-1900) and contemporary (post-1900) distribution records. We also assess the use of Ellenberg and climate indicator values as markers of responses to climate and environmental change. Using these techniques we detect a loss in 19 plant species, with 6 species losing more than 50% of their previous range. Statistical analysis showed that Ellenberg (light, moisture, nitrogen) and climate indicator values (mean January temperature, mean July temperature and mean precipitation) could be used as environmental change indicators. Significantly higher percentages of area lost were detected in species with lower January temperatures, July temperatures, light, and nitrogen values, as well as higher annual precipitation and moisture values. This study highlights the importance of historical records in examining the changes in plant species’ geographical distributions. We present a method for manual geo-referencing of such records, and demonstrate how using Ellenberg and climate indicator values as environmental and climate change indicators can contribute towards directing appropriate conservation strategies

Efficient occupancy model-fitting for extensive citizen-science data

Appropriate large-scale citizen-science data present important new opportunities for biodiversity modelling, due in part to the wide spatial coverage of information. Recently proposed occupancy modelling approaches naturally incorporate random effects in order to account for annual variation in the composition of sites surveyed. In turn this leads to Bayesian analysis and model fitting, which are typically extremely time consuming. Motivated by presence-only records of occurrence from the UK Butterflies for the New Millennium data base, we present an alternative approach, in which site variation is described in a standard way through logistic regression on relevant environmental covariates. This allows efficient occupancy model-fitting using classical inference, which is easily achieved using standard computers. This is especially important when models need to be fitted each year, typically for many different species, as with British butterflies for example. Using both real and simulated data we demonstrate that the two approaches, with and without random effects, can result in similar conclusions regarding trends. There are many advantages to classical model-fitting, including the ability to compare a range of alternative models, identify appropriate covariates and assess model fit, using standard tools of maximum likelihood. In addition, modelling in terms of covariates provides opportunities for understanding the ecological processes that are in operation. We show that there is even greater potential; the classical approach allows us to construct regional indices simply, which indicate how changes in occupancy typically vary over a species’ range. In addition we are also able to construct dynamic occupancy maps, which provide a novel, modern tool for examining temporal changes in species distribution. These new developments may be applied to a wide range of taxa, and are valuable at a time of climate change. They also have the potential to motivate citizen scientists

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Cinétiques rapides dans les liquides sous rayonnement : aspects théoriques

Cet article considère l’applicabilité des méthodes classiques de cinétique de réactions à des systèmes très nonhomogènes, comme les trajectoires de rayonnement. Deux modifications de la théorie sont nécessaires à cause de la proximité des particules dans la trajectoire. Premièrement, la formulation doit être stochastique, afin de prendre en considération le nombre entier de particules dans une grappe. Deuxièmement, la constante de vitesse doit dépendre du temps et décrire correctement la relaxation spatiale de la distribution nonhomogène. Trois façons d’aborder les cinétiques rapides sont décrites. Il est particulièrement important d’essayer les modèles pour s’assurer que les cinétiques théoriques représentent fidèlement la solution exacte à l’équation de diffusion

On the approximation of independent pairs in diffusion kinetics: correlation of distances in a three-body system

This study investigates the problem of diffusion kinetics in a three-body system, motivated by the theory of radiation chemical kinetics. The backward diffusion equation for the joint density of the distances is formulated, and an explicit formula for the infinitesimal covariance of two diffusing distances is derived. The Clifford-Green theorem is used to show how the infinitesimal covariance of two distances is linked to the covariance of the corresponding two squared distances as time evolves. In addition, computer simulations for the problem are presented, which indicate that hitting probabilities are also correlated. While the results indicate that more work is needed before a usable correction to the independence approximation is possible, clear progress has been made

Scavenging and recombination kinetics in radiation chemistry

This work describes stochastic models developed to study the competition between radical scavenging and recombination for simple model systems typical of radiation chemistry, where the reactive particles are tightly clustered and reactions are assumed fully diffusion limited. Three models are developed: a Monte Carlo random flights model with a periodic boundary condition for scavengers, Monte Carlo simulations in which the scavenging rate is calculated from the Smoluchowski theory for diffusion-limited reactions and a modification of the independent reaction times method where the scavengers close to the spur are explicitly included and the scavengers further away are treated as a continuum. The results indicate that the Smoluchowski theory makes a systematic overestimate of the scavenging rate when such competition is present. A correction for the Smoluchowski rate constant is suggested, an analytical justification is presented and it is tested against the simulations, and shown to be a substantial improvement

Scavenging and recombination kinetics in a radiation spur: The successive ordered scavenging events

This study describes stochastic models to investigate the successive ordered scavenging events in a spur of four radicals, a model system based on a radiation spur. Three simulation models have been developed to obtain the probabilities of the ordered scavenging events: (i) a Monte Carlo random flight (RF) model, (ii) hybrid simulations in which the reaction rate coefficient is used to generate scavenging times for the radicals and (iii) the independent reaction times (IRT) method. The results of these simulations are found to be in agreement with one another. In addition, a detailed master equation treatment is also presented, and used to extract simulated rate coefficients of the ordered scavenging reactions from the RF simulations. These rate coefficients are transient, the rate coefficients obtained for subsequent reactions are effectively equal, and in reasonable agreement with the simple correction for competition effects that has recently been proposed