Comparing and contrasting flooded and unflooded forests in western Amazonia: seed predation, seed pathogens, germination

Because of the importance of the Amazon to our shared human future and because we need to understand how its forests regenerate, I set out seeds for a week in igapó, palm, terra firme, várzea and white sand forests and then collected them, scoring seed losses to predators, seed losses to pathogens and seeds that germinated. I found (1) terra firme forest, white sand forest, várzea forest and igapó forest under water 1 month every year, were significantly different for seed mechanisms and tolerances, terra firme forest, palm forest, várzea forest and igapó forest under water 1 month per year, were significantly different among species, and the interaction term was significant for all forests except for the two most flooded igapó forests, (2) in terra firme forest seed predators took most seeds regardless of species, (3) in palm forest species were different regardless of seed mechanism and tolerance, (4) in white sand forest seed predators took most seeds regardless of species, (5) in várzea forest seed predators took most seeds but with some species differences and (6) in igapó forest under water 1 month per year, there were differences in predation, pathogens and germination, and in species variation. I conclude that seed predation losses strength as forests become more stressed either by loss of soil fertility or by flooding with nutrient-poor water. Conversely seed pathogens become more important with water-logged soils and with flooding. Seed loss variation among species within forests was always a secondary factor

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

Related herbivore species show similar temporal dynamics

1.Within natural communities, different taxa display different dynamics in time. Why this is the case we do not fully know. This thwarts our ability to predict changes in community structure, which is important for both the conservation of rare species in natural communities and for the prediction of pest outbreaks in agriculture. 2.Species sharing phylogeny, natural enemies and/or life‐history traits have been hypothesized to share similar temporal dynamics. We operationalized these concepts into testing whether feeding guild, voltinism, similarity in parasitoid community and/or phylogenetic relatedness explained similarities in temporal dynamics among herbivorous community members. 3.Focusing on two similar datasets from different geographical regions (Finland and Japan), we used asymmetric eigenvector maps as temporal variables to characterize species‐ and community‐level dynamics of specialist insect herbivores on oak (Quercus). We then assessed whether feeding guild, voltinism, similarity in parasitoid community and/or phylogenetic relatedness explained similarities in temporal dynamics among taxa. 4.Species‐specific temporal dynamics varied widely, ranging from directional decline or increase to more complex patterns. Phylogeny was a clear predictor of similarity in temporal dynamics at the Finnish site, whereas for the Japanese site, the data were uninformative regarding a phylogenetic imprint. Voltinism, feeding guild and parasitoid overlap explained little variation at either location. Despite the rapid temporal dynamics observed at the level of individual species, these changes did not translate into any consistent temporal changes at the community level in either Finland or Japan. 5.Overall, our findings offer no direct support for the notion that species sharing natural enemies and/or life‐history traits would be characterized by similar temporal dynamics, but reveal a strong imprint of phylogenetic relatedness. As this phylogenetic signal cannot be attributed to guild, voltinism or parasitoids, it will likely derive from shared microhabitat, microclimate, anatomy, physiology or behaviour. This has important implications for predicting insect outbreaks and for informing insect conservation. We hope that future studies will assess the generality of our findings across plant‐feeding insect communities and beyond, and establish the more precise mechanism(s) underlying the phylogenetic imprint

Dcas Supports Cell Polarization and Cell-Cell Adhesion Complexes in Development

Mammalian Cas proteins regulate cell migration, division and survival, and are often deregulated in cancer. However, the presence of four paralogous Cas family members in mammals (BCAR1/p130Cas, EFS/Sin1, NEDD9/HEF1/Cas-L, and CASS4/HEPL) has limited their analysis in development. We deleted the single Drosophila Cas gene, Dcas, to probe the developmental function of Dcas. Loss of Dcas had limited effect on embryonal development. However, we found that Dcas is an important modulator of the severity of the developmental phenotypes of mutations affecting integrins (If and mew) and their downstream effectors Fak56D or Src42A. Strikingly, embryonic lethal Fak56D-Dcas double mutant embryos had extensive cell polarity defects, including mislocalization and reduced expression of E-cadherin. Further genetic analysis established that loss of Dcas modified the embryonal lethal phenotypes of embryos with mutations in E-cadherin (Shg) or its signaling partners p120- and β-catenin (Arm). These results support an important role for Cas proteins in cell-cell adhesion signaling in development

Conceptual Frameworks and Methods for Advancing Invasion Ecology

Invasion ecology has much advanced since its early beginnings. Nevertheless, explanation, prediction, and management of biological invasions remain difficult. We argue that progress in invasion research can be accelerated by, first, pointing out difficulties this field is currently facing and, second, looking for measures to overcome them. We see basic and applied research in invasion ecology confronted with difficulties arising from (A) societal issues, e.g., disparate perceptions of invasive species; (B) the peculiarity of the invasion process, e.g., its complexity and context dependency; and (C) the scientific methodology, e.g., imprecise hypotheses. To overcome these difficulties, we propose three key measures: (1) a checklist for definitions to encourage explicit definitions; (2) implementation of a hierarchy of hypotheses (HoH), where general hypotheses branch into specific and precisely testable hypotheses; and (3) platforms for improved communication. These measures may significantly increase conceptual clarity and enhance communication, thus advancing invasion ecology

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant 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.Peer reviewe

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

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