Convergence in phosphorus constraints to photosynthesis in forests around the world

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability: The photosynthesis and leaf nutrient data reported in the paper are available at https://doi.org/10.6084/m9.figshare.20010485.v1, and the model results are available on the European open-access repository Zenodo at https://doi.org/10.5281/zenodo.6619615. All other data reported in the paper are presented in the supplementary materials.Code availability: The R code used for analyses is at https://github.com/ellswor2/photo_p_repo2.git. The source code for ORCHIDEE is at https://doi.org/10.14768/20200407002.1.Tropical forests take up more carbon (C) from the atmosphere per annum by photosynthesis than any other type of vegetation. Phosphorus (P) limitations to C uptake are paramount for tropical and subtropical forests around the globe. Yet the generality of photosynthesis-P relationships underlying these limitations are in question, and hence are not represented well in terrestrial biosphere models. Here we demonstrate the dependence of photosynthesis and underlying processes on both leaf N and P concentrations. The regulation of photosynthetic capacity by P was similar across four continents. Implementing P constraints in the ORCHIDEE-CNP model, gross photosynthesis was reduced by 36% across the tropics and subtropics relative to traditional N constraints and unlimiting leaf P. Our results provide a quantitative relationship for the P dependence for photosynthesis for the front-end of global terrestrial C models that is consistent with canopy leaf measurements

A reporting format for leaf-level gas exchange data and metadata

Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy's ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system

Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease

We sought to identify new susceptibility loci for Alzheimer's disease through a staged association study (GERAD+) and by testing suggestive loci reported by the Alzheimer's Disease Genetic Consortium (ADGC) in a companion paper. We undertook a combined analysis of four genome-wide association datasets (stage 1) and identified ten newly associated variants with P ≤ 1 × 10−5. We tested these variants for association in an independent sample (stage 2). Three SNPs at two loci replicated and showed evidence for association in a further sample (stage 3). Meta-analyses of all data provided compelling evidence that ABCA7 (rs3764650, meta P = 4.5 × 10−17; including ADGC data, meta P = 5.0 × 10−21) and the MS4A gene cluster (rs610932, meta P = 1.8 × 10−14; including ADGC data, meta P = 1.2 × 10−16) are new Alzheimer's disease susceptibility loci. We also found independent evidence for association for three loci reported by the ADGC, which, when combined, showed genome-wide significance: CD2AP (GERAD+, P = 8.0 × 10−4; including ADGC data, meta P = 8.6 × 10−9), CD33 (GERAD+, P = 2.2 × 10−4; including ADGC data, meta P = 1.6 × 10−9) and EPHA1 (GERAD+, P = 3.4 × 10−4; including ADGC data, meta P = 6.0 × 10−10)

Enhanced future changes in wet and dry extremes over Africa at convection-permitting scale

African society is particularly vulnerable to climate change. The representation of convection in climate models has so far restricted our ability to accurately simulate African weather extremes, limiting climate change predictions. Here we show results from climate change experiments with a convection-permitting (4.5 km grid-spacing) model, for the first time over an Africa-wide domain (CP4A). The model realistically captures hourly rainfall characteristics, unlike coarser resolution models. CP4A shows greater future increases in extreme 3-hourly precipitation compared to a convection-parameterised 25 km model (R25). CP4A also shows future increases in dry spell length during the wet season over western and central Africa, weaker or not apparent in R25. These differences relate to the more realistic representation of convection in CP4A, and its response to increasing atmospheric moisture and stability. We conclude that, with the more accurate representation of convection, projected changes in both wet and dry extremes over Africa may be more severe

Lower land-use emissions responsible for increased net land carbon sink during the slow warming period

The terrestrial carbon sink accelerated during 1998–2012, concurrently with the slow warming period, but the mechanisms behind this acceleration are unclear. Here we analyse recent changes in the net land carbon sink (NLS) and its driving factors, using atmospheric inversions and terrestrial carbon models. We show that the linear trend of NLS during 1998–2012 is about 0.17 ± 0.05 Pg C yr−2 , which is three times larger than during 1980–1998 (0.05 ± 0.05 Pg C yr−2). According to terrestrial carbon model simulations, the intensification of the NLS cannot be explained by CO2 fertilization or climate change alone. We therefore use a bookkeeping model to explore the contribution of changes in land-use emissions and find that decreasing land-use emissions are the dominant cause of the intensification of the NLS during the slow warming period. This reduction of land-use emissions is due to both decreased tropical forest area loss and increased afforestation in northern temperate regions. The estimate based on atmospheric inversions shows consistently reduced land-use emissions, whereas another bookkeeping model did not reproduce such changes, probably owing to missing the signal of reduced tropical deforestation. These results highlight the importance of better constraining emissions from land-use change to understand recent trends in land carbon sinks

Anthropogenic climate change has driven over 5 million km² of drylands towards desertification

Drylands cover 41% of the earth’s land surface and include 45% of the world’s agricultural land. These regions are among the most vulnerable ecosystems to anthropogenic climate and land use change and are under threat of desertification. Understanding the roles of anthropogenic climate change, which includes the CO2 fertilization effect, and land use in driving desertification is essential for effective policy responses but remains poorly quantified with methodological differences resulting in large variations in attribution. Here, we perform the first observation-based attribution study of desertification that accounts for climate change, climate variability, CO2 fertilization as well as both the gradual and rapid ecosystem changes caused by land use. We found that, between 1982 and 2015, 6% of the world’s drylands underwent desertification driven by unsustainable land use practices compounded by anthropogenic climate change. Despite an average global greening, anthropogenic climate change has degraded 12.6% (5.43 million km2) of drylands, contributing to desertification and affecting 213 million people, 93% of who live in developing economies

Evaluating the Contribution of Land-Atmosphere Coupling to Heat Extremes in CMIP5 Models

Land-atmosphere coupling can amplify heat extremes under declining soil moisture. Here we evaluate this coupling in 25 Coupled Model Intercomparison Project Phase 5 models using flux tower observations over Europe and North America. We compared heat extremes (2.5% of the hottest days of the year) and the evaporative fraction (EF; a measure of land surface dryness) on the day the heat extremes occurred. We found a negative relationship between the magnitude of heat extremes and EF in both models and observations in transitional regions, with the hottest temperatures occurring during the driest days, with a similar but less certain relationship in dry regions. Surprisingly, many models also showed an amplification of heat extremes by low EF in wet regions, a finding not supported by observations. Many models may therefore overamplify heat extremes over wet regions by overestimating the strength of land-atmosphere coupling, with consequences for future projections of heat extremes

Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe

Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSM and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account