A Refined Methodology for Defining Plant Communities Using Postagricultural Data from the Neotropics

How best to define and quantify plant communities was investigated using long-term plot data sampled from a recovering pasture in Puerto Rico and abandoned sugarcane and banana plantations in Ecuador. Significant positive associations between pairs of old field species were first computed and then clustered together into larger and larger species groups. I found that (1) no pasture or plantation had more than 5% of the possible significant positive associations, (2) clustering metrics showed groups of species participating in similar clusters among the five pasture/plantations over a gradient of decreasing association strength, and (3) there was evidence for repeatable communities—especially after banana cultivation—suggesting that past crops not only persist after abandonment but also form significant associations with invading plants. I then showed how the clustering hierarchy could be used to decide if any two pasture/plantation plots were in the same community, that is, to define old field communities. Finally, I suggested a similar procedure could be used for any plant community where the mechanisms and tolerances of species form the “cohesion” that produces clustering, making plant communities different than random assemblages of species

Effects of Species, Water, and Nitrogen on Competition Among Three Prairie Grasses

We conducted an experiment to investigate effects of species, water (W), and nitrogen (N) on competition among little bluestem (Schizachyrium scoparium), sideoats grama (Bouteloua curtipendula), and indiangrass (Sorghastrum nutans). All biomass parameters and the root:shoot ratio of little bluestem were reduced by the presence off 1 of 2 other species, and its shoot biomass and total biomass were both increased by addition of N. Root and shoot biomass of sideoats grama were reduced by the presence of indiangrass and its total biomass was reduced by the presence of itself, whereas its shoot biomass was increased by addition of W at the highest level. Root biomass and total biomass of indiangrass were increased by N and that response pattern was preserved for root biomass but lost for total biomass when W was added. We conclude that grass seedlings were affected by species more than by levels of W and N, interspecific competition was more important than intraspecific competition, and both N and W effects occurred only in the highest levels of addition with some interaction

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

BOSQUES DE AGUA NEGRO (IGAPÓ) VS. BOSQUES DE AGUAS BLANCAS (VÁRZEA) EN LA AMAZONÍA: FLORÍSTICA Y ESTRUCTURA FÍSICA

Flooded forests occur across the landscape of the Amazon basin and, because they are important to our shared human density, need further investigation. Here I use replicated plots to examine the floristics and physical structure of the two most common kinds of flooded forest-types in the Amazon. I set up four 50 m x 50 m forest plots in black-water forest (igapó) in Peru and also in white-water forest (várzea) in Ecuador. I then sampled all trees in all plots at least 10 cm dbh for species, and then generated a variety of floristic and physical parameters. There was species variation among the plots within both forest-types, but little variation in physical structure. The four igapó plots taken together (now 1 ha) had 16 families, 29 genera and 31 species with Fabaceae, the most common family of which also had the most genera and the most species. The four várzea plots taken together (now 1 ha) had 42 families, 91 genera and 159 species, with Fabaceae again the most common family which also had the most genera and the most species. There were only four species in common. In general the várzea plots had more stems, and more large stems (at least 40 cm dbh) than the igapó plots, but mean stem size was very similar. Structural comparison to terra firme 1 ha plots showed it had more stems, thicker stems and more above-ground biomass compared to either of these pooled 1 ha flooded plots. Finally all study plots conformed to the reverse J stem size distribution pattern for all stems.Los bosques inundados se producen a través del paisaje de la cuenca del Amazonas y, debido a que son importantes para nuestra densidad humana compartida, necesitan una mayor investigación. Aquí utilizo parcelas replicadas para examinar los florística y estructura física de los dos tipos más comunes de los bosques de tipo inundado de la Amazonia. He definido de cuatro parcelas forestales de 50 mx 50 m en los bosques de agua negro (igapó) en Perú y también en los bosques de aguas bravas (várzea) en Ecuador. Entonces probé todos los árboles en todas las parcelas de al menos 10 cm dap para las especies, y luego genero una variedad de parámetros florísticos y físicos. Estos fueron la variación de especies entre las parcelas dentro de los dos tipos de bosque, pero poca variación en la estructura física. Los cuatro parcelas de igapó en conjunto (ahora 1 ha) tenían 16 familias, 29 géneros y 31 especies con Fabaceae la familia más común que también tenía la mayor cantidad de géneros y la mayoría de las especies. Las cuatro parcelas de várzea en su conjunto (ahora 1 ha) tenían 42 familias, 91 géneros y 159 especies de Fabaceae, de nuevo, la familia más común que también tenía la mayor cantidad de géneros y la mayoría de las especies. Sólo había cuatro especies en común. En general las parcelas de várzea tenían más tallos y tallos más grandes (al menos 40 cm dap) que las parcelas de igapó, pero el promedio del tallo tamaño fue muy similar. La comparación estructural a tierra firme 1 ha parcelas mostró que tenía más tallos más gruesos tallos y más biomasa aérea en comparación con cualquiera de estos combinados 1 ha de parcelas inundadas. Finalmente todas las parcelas de estudio se ajustaban al patrón de distribución del tamaño del tallo J inverso para todos los tallos

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

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