Understanding of Coupled Terrestrial Carbon, Nitrogen and Water Dynamics—An Overview

Coupled terrestrial carbon (C), nitrogen (N) and hydrological processes play a crucial role in the climate system, providing both positive and negative feedbacks to climate change. In this review we summarize published research results to gain an increased understanding of the dynamics between vegetation and atmosphere processes. A variety of methods, including monitoring (e.g., eddy covariance flux tower, remote sensing, etc.) and modeling (i.e., ecosystem, hydrology and atmospheric inversion modeling) the terrestrial carbon and water budgeting, are evaluated and compared. We highlight two major research areas where additional research could be focused: (i) Conceptually, the hydrological and biogeochemical processes are closely linked, however, the coupling processes between terrestrial C, N and hydrological processes are far from well understood; and (ii) there are significant uncertainties in estimates of the components of the C balance, especially at landscape and regional scales. To address these two questions, a synthetic research framework is needed which includes both bottom-up and top-down approaches integrating scalable (footprint and ecosystem) models and a spatially nested hierarchy of observations which include multispectral remote sensing, inventories, existing regional clusters of eddy-covariance flux towers and CO2 mixing ratio towers and chambers

BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series

Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL