• Energy Research

15 páginas, 1 tabla, 2 figuras Digging and hand-sorting of soil blocks is a very widespread method in the study of earthworm communities. One disadvantage of this method is that it is very time consuming and often many earthworms are incomplete because they were cut by the digging tools. When authors report earthworm biomass, no mention is made of the assessment of any relationship between the mass of those cut earthworms and their overall weight. In such cases, biomass is generally underestimated. In this paper, our objective was to propose a new method to estimate the weight of incomplete earthworms on the basis of preclitellar diameter and its usefulness for studying the dynamics of earthworm populations. Complete earthworms were collected from samplings performed in native savannahs and man-made pastures of the eastern plains of Colombia and from a poplar grove (Populus sp.) in Central Spain. A strong correlation between the preserved fresh weight and the maximum preclitellar diameter was found for all the species studied. Three types of models have provided a convenient method to estimate earthworm biomass: (i) linear for almost all the species; (ii) exponential for a large Neotropical anecic species, Martiodrilus carimaguensis (Glossoscolecidae); and (iii) second degree polynomic equation. This study was included within the STD-3 European Macrofauna Project (No. ts3*ct920128) and the Tropical Lowlands Program at the International Center for Tropical Agriculture, CIAT (Cali, Colombia). This study was supported partly by a research grant obtained by the first author within the Macrofauna programme. E. Mamolar received a one-year scholarship from ‘Fundación CajaMadrid’ (Spain). The first author deeply thanks Thibaud Decaëns, from the ‘Université de Rouen’ (France) for his criticism in a first version of the manuscript and two anonymous referees for their helpful comments. Peer reviewed

AbstractCurrent analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long‐term average thermal conditions at coarse spatial resolutions only. Hence, many climate‐forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold‐air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free‐air temperatures, microclimatic ground and near‐surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near‐surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.

AbstractResearch 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‐km2resolution 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‐km2pixels (summarized from 8519 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.