Belowground DNA-based techniques: untangling the network of plant root interactions

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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

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

Biodiversity loss and its impact on humanity

The most unique feature of Earth is the existence of life, and the most extraordinary feature of life is its diversity. Approximately 9 million types of plants, animals, protists and fungi inhabit the earth. So, too, do 7 billion people. Two decades ago, at the first Earth Summit, the vast majority of the world's nations declared that human actions were dismantling Earth's ecosystems, eliminating genes, 30 species, and biological traits at an alarming rate. This observation led to a daunting question: How will loss of biological diversity alter the functioning of ecosystems and their ability to provide society with the goods and services needed to prosper

Analysis of the forest fires in the Antalya region of Turkey using the Keetch-Byram drought index

We investigated the correlation of large fires (> 300 ha) from 1992 to 2013 within the borders of the Antalya Regional Directorate of Forestry using the Keetch-Byram drought index (KBDI). Daily KBDI values were calculated for each year, and values for the period before the year 2000 differed significantly from those after 2000. After 2000 (large fires occurred in 2004, 2006, 2007, 2008, 2010, and 2013), when KBDI values increased, the KBDI, but not the number of fires, was inversely correlated with the natural log of the burned area (NLBA). While there were both high and low KBDI values when the NLBA was small, only high KBDI values were associated with high NLBA values. Particularly for logarithmic values of 4 and higher, KBDI values increased in parallel with increases in NLBA values. On the basis of a Mann-Whitney U test done in addition to a Pearson correlation test, we found that when the burned areas were grouped according to small and large areas, the KBDI could be used to distinguish the two groups. Using a conditional probability analysis, we found that 4th, 5th and 6th class KBDI values may lead to large fires at the 60 \% possibility. Similarly, the possibility of large fires greater than the median burned area in any given 6 years was found to be 48 \%. In addition, while the mean value of KBDI is 390.51 for the period from May to September for these 6 years, it is 359.93 for the other years. Consequently, the area burned also increased as the KBDI classes (Class 0: 0-99, Class 1: 100-199, Class 2: 200-299, Class 3: 300-399, Class 4: 400-499, Class 5: 500-599, Class 6: 600-699, and Class 7: 700-800) increase

Flammability of Some Ornamental Species in Wildland–Urban Interfaces in Southeastern France: Laboratory Assessment at Particle Level

Assessment of the flammability of ornamental vegetation (particularly hedges) planted around houses is necessary in light of the increasing urbanization of the wildland-urban interfaces (WUIs) and the high fire occurrence in such areas. The structure and flammability of seven of the species most frequently planted as hedges in Provence (South-eastern France) were studied at particle level. Spatial repartition of the different types of fuel particles within plants was assessed by means of the Cube Method. The leaf flammability was assessed using an epiradiator as a burning device and measurements of foliar physical characteristics and gross heat of combustion (GHC) helped to explain the results of burning experiments. Co-inertia analysis revealed that species with thin leaves were quick to ignite (Pyracantha coccinea, Phyllostachys sp.) and species with high leaf GHC burned the longest (Pittosporum tobira, Nerium oleander). Species presenting high ignitability (Photinia fraseri, Phyllostachys sp. and Pyracantha coccinea) were characterised by high foliar surface area-to-volume ratio, and species presenting lower ignitability were characterised by high GHC (Pittosporum tobira, Nerium oleander, Cupressus sempervirens). Hierarchical cluster analysis of the flammability variables (ignition frequency, time-to-ignition and flaming duration) categorized the relative flammability of the seven species (including dead Cupressus sempervirens) in five clusters of species from poorly flammable (Pittosporum tobira) to extremely flammable (dead Cupressus sempervirens). This study provides useful information for reducing fire risk in WUIs in the study area