Toward a theory for diversity gradients: the abundance–adaptation hypothesis

The abundance–adaptation hypothesis argues that taxa with more individuals and faster generation times will have more evolutionary ‘experiments’ allowing expansion into, and diversification within, novel habitats. Thus, as older taxa have produced more individuals over time, and smaller taxa have higher population sizes and faster generation times, the Latitudinal Diversity Gradients (LDGs) of these clades should show shallower slopes. We describe the LDGs for archaea, bacteria, fungi, invertebrates and trees from six North American forests. For three focal groups – bacteria, ants, and trees – older taxa had shallower LDG slopes than the more recent, terminal taxa. Across 12 orders of magnitude of body mass, LDG slopes were steeper in larger taxa. The slopes of LDGs vary systematically with body size and clade age, underscoring the non-canonical nature of LDGs. The steepest LDG slopes were found for the largest organisms while the smallest, from bacteria to small litter-soil invertebrates, have shallower- to zero-slope LDGs. If tropical niche conservatism is the failure of clades to adapt to, and diversify in temperate habitats, then the steep LDGs of chordates and plants likely arise from the decreased ability of clades with large individuals to adapt to the multiple challenges of extra-tropical life

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

Open Science principles for accelerating trait-based science across the Tree of Life

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges

Plant trait and vegetation data along a 1314 m elevation gradient with fire history in Puna grasslands, Per\ufa

\ua9 2024. The Author(s). Alpine grassland vegetation supports globally important biodiversity and ecosystems that are increasingly threatened by climate warming and other environmental changes. Trait-based approaches can support understanding of vegetation responses to global change drivers and consequences for ecosystem functioning. In six sites along a 1314 m elevational gradient in Puna grasslands in the Peruvian Andes, we collected datasets on vascular plant composition, plant functional traits, biomass, ecosystem fluxes, and climate data over three years. The data were collected in the wet and dry season and from plots with different fire histories. We selected traits associated with plant resource use, growth, and life history strategies (leaf area, leaf dry/wet mass, leaf thickness, specific leaf area, leaf dry matter content, leaf C, N, P content, C and N isotopes). The trait dataset contains 3,665 plant records from 145 taxa, 54,036 trait measurements (increasing the trait data coverage of the regional flora by 420%) covering 14 traits and 121 plant taxa (ca. 40% of which have no previous publicly available trait data) across 33 families

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

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

A global analysis of terrestrial plant litter dynamics in non-perennial waterways

Perennial rivers and streams make a disproportionate contribution to global carbon (C) cycling. However, the contribution of intermittent rivers and ephemeral streams (IRES), which sometimes cease to flow and can dry completely, is largely ignored although they represent over half the global river network. Substantial amounts of terrestrial plant litter (TPL) accumulate in dry riverbeds and, upon rewetting, this material can undergo rapid microbial processing. We present the results of a global research collaboration that collected and analysed TPL from 212 dry riverbeds across major environmental gradients and climate zones. We assessed litter decomposability by quantifying the litter carbon-to-nitrogen ratio and oxygen (O2) consumption in standardized assays and estimated the potential short-term CO2 emissions during rewetting events. Aridity, cover of riparian vegetation, channel width and dry-phase duration explained most variability in the quantity and decomposability of plant litter in IRES. Our estimates indicate that a single pulse of CO2 emission upon litter rewetting contributes up to 10% of the daily CO2 emission from perennial rivers and stream, particularly in temperate climates. This indicates that the contributions of IRES should be included in global C-cycling assessments

A model for leaf temperature decoupling from air temperature

Leaf temperature (Tleaf) influences rates of respiration, photosynthesis, and transpiration. The local slope of the relationship between Tleaf and Tair, β describes leaf thermal responses. A range of values have been observed, with β <1 indicating limited homeothermy where Tleaf increases at a lower rate than Tair, β = 1 indicating poikilothermy where Tleaf tracks Tair, and β >1 indicating megathermy where Tleaf increasingly exceeds Tair. However, theory for variation in β has not been developed. Here we derive an equation for β that predicts how it varies with multiple trait and microenvironment variables. The approach also predicts how maintenance of Tleaf away from lethally high values may help explain regulation of stomatal conductance (gS). The work delineates contexts in which each class of leaf thermal response is expected and develops concepts for predicting leaf responses to thermally extreme environments

A model for leaf temperature decoupling from air temperature

Leaf temperature (Tleaf) influences rates of respiration, photosynthesis, and transpiration. The local slope of the relationship between Tleaf and Tair, β describes leaf thermal responses. A range of values have been observed, with β 1 indicating megathermy where Tleaf increasingly exceeds Tair. However, theory for variation in β has not been developed. Here we derive an equation for β that predicts how it varies with multiple trait and microenvironment variables. The approach also predicts how maintenance of Tleaf away from lethally high values may help explain regulation of stomatal conductance (gS). The work delineates contexts in which each class of leaf thermal response is expected and develops concepts for predicting leaf responses to thermally extreme environments

Predicting climate change effects on wildfires requires linking processes across scales

Accurate process-based prediction of climate change effects on wildfires requires coupling processes across orders of magnitude of time and space scales, because climate dynamic processes operate at relatively large scales (e.g., hemispherical and centennial), but fire behavior processes operate at relatively small scales (e.g., molecules and microseconds). In this review, we outline some of the current understanding of the processes by which climate/meteorology controls wildfire behavior by focusing on four critical stages of wildfire development: (1) fuel drying, (2) ignition, (3) spread, and (4) extinction. We identify some key mechanisms that are required for predicting climate change effects on fires, as well as gaps in our understanding of the processes linking climate and fires. It is currently not possible to make accurate predictions of climate change effects on wildfires due to the limited understanding of the linkage between general circulation model outputs and the local-scale meteorology to which fire behavior processes respond. © 2010 John Wiley and Sons, Ltd