Towards the integration of animal‐borne instruments into global ocean observing systems

Marine animals are increasingly instrumented with environmental sensors that provide large volumes of oceanographic data. Here, we conduct an innovative and comprehensive global analysis to determine the potential contribution of animal‐borne instruments (ABI) into ocean observing systems (OOSs) and provide a foundation to establish future integrated ocean monitoring programmes. We analyse the current gaps of the long‐term Argo observing system (>1.5 million profiles) and assess its spatial overlap with the distribution of marine animals across eight major species groups (tuna and billfishes, sharks and rays, marine turtles, pinnipeds, cetaceans, sirenians, flying seabirds and penguins). We combine distribution ranges of 183 species and satellite tracking observations from >3,000 animals. Our analyses identify potential areas where ABI could complement OOS. Specifically, ABI have the potential to fill gaps in marginal seas, upwelling areas, the upper 10 m of the water column, shelf regions and polewards of 60° latitude. Our approach provides the global baseline required to plan the integration of ABI into global and regional OOS while integrating conservation and ocean monitoring priorities.     

Reforestation and surface cooling in temperate zones: Mechanisms and implications

Land‐use/cover change (LUCC) is an important driver of environmental change, occurring at the same time as, and often interacting with, global climate change. Reforestation and deforestation have been critical aspects of LUCC over the past two centuries and are widely studied for their potential to perturb the global carbon cycle. More recently, there has been keen interest in understanding the extent to which reforestation affects terrestrial energy cycling and thus surface temperature directly by altering surface physical properties (e.g., albedo and emissivity) and land–atmosphere energy exchange. The impacts of reforestation on land surface temperature and their mechanisms are relatively well understood in tropical and boreal climates, but the effects of reforestation on warming and/or cooling in temperate zones are less certain. This study is designed to elucidate the biophysical mechanisms that link land cover and surface temperature in temperate ecosystems. To achieve this goal, we used data from six paired eddy‐covariance towers over co‐located forests and grasslands in the temperate eastern United States, where radiation components, latent and sensible heat fluxes, and meteorological conditions were measured. The results show that, at the annual time scale, the surface of the forests is 1–2°C cooler than grasslands, indicating a substantial cooling effect of reforestation. The enhanced latent and sensible heat fluxes of forests have an average cooling effect of ?2.5°C, which offsets the net warming effect (+1.5°C) of albedo warming (+2.3°C) and emissivity cooling effect (?0.8°C) associated with surface properties. Additional daytime cooling over forests is driven by local feedbacks to incoming radiation. We further show that the forest cooling effect is most pronounced when land surface temperature is higher, often exceeding ?5°C. Our results contribute important observational evidence that reforestation in the temperate zone offers opportunities for local climate mitigation and adaptation.     

Evidence of non‐stationary relationships between climate and forest responses: Increased sensitivity to climate change in Iberian forests

Climate and forest structure are considered major drivers of forest demography and productivity. However, recent evidence suggests that the relationships between climate and tree growth are generally non‐stationary (i.e. non‐time stable), and it remains uncertain whether the relationships between climate, forest structure, demography and productivity are stationary or are being altered by recent climatic and structural changes. Here we analysed three surveys from the Spanish Forest Inventory covering c. 30 years of information and we applied mixed and structural equation models to assess temporal trends in forest structure (stand density, basal area, tree size and tree size inequality), forest demography (ingrowth, growth and mortality) and above‐ground forest productivity. We also quantified whether the interactive effects of climate and forest structure on forest demography and above‐ground forest productivity were stationary over two consecutive time periods. Since the 1980s, density, basal area and tree size increased in Iberian forests, and tree size inequality decreased. In addition, we observed reductions in ingrowth and growth, and increases in mortality. Initial forest structure and water availability mainly modulated the temporal trends in forest structure and demography. The magnitude and direction of the interactive effects of climate and forest structure on forest demography changed over the two time periods analysed indicating non‐stationary relationships between climate, forest structure and demography. Above‐ground forest productivity increased due to a positive balance between ingrowth, growth and mortality. Despite increasing productivity over time, we observed an aggravation of the negative effects of climate change and increased competition on forest demography, reducing ingrowth and growth, and increasing mortality. Interestingly, our results suggest that the negative effects of climate change on forest demography could be ameliorated through forest management, which has profound implications for forest adaptation to climate change.     

Heterogeneity–diversity relationships in sessile organisms: a unified framework

The hypothesis that environmental heterogeneity promotes species richness by increasing opportunities for niche partitioning is a fundamental paradigm in ecology. However, recent studies suggest that heterogeneity–diversity relationships (HDR) are more complex than expected from this niche‐based perspective, and often show a decrease in richness at high levels of heterogeneity. These findings have motivated ecologists to propose new mechanisms that may explain such deviations. Here we provide an overview of currently recognised mechanisms affecting the shape of HDRs and present a conceptual model that integrates all previously proposed mechanisms within a unified framework. We also translate the proposed framework into an explicit community dynamic model and use the model as a tool for generating testable predictions concerning how landscape properties interact with species traits in determining the shape of HDRs. Our main finding is that, despite the enormous complexity of such interactions, the predicted HDRs are rather simple, ranging from positive to unimodal patterns in a highly consistent and predictable manner.     

A chemically triggered transition from conflict to cooperation in burying beetles

Although interspecific competition has long been recognised as a major driver of trait divergence and adaptive evolution, relatively little effort has focused on how it influences the evolution of intraspecific cooperation. Here we identify the mechanism by which the perceived pressure of interspecific competition influences the transition from intraspecific conflict to cooperation in a facultative cooperatively breeding species, the Asian burying beetle Nicrophorus nepalensis. We not only found that beetles are more cooperative at carcasses when blowfly maggots have begun to digest the tissue, but that this social cooperation appears to be triggered by a single chemical cue – dimethyl disulfide (DMDS) – emitted from carcasses consumed by blowflies, but not from control carcasses lacking blowflies. Our results provide experimental evidence that interspecific competition promotes the transition from intraspecific conflict to cooperation in N. nepalensis via a surprisingly simple social chemical cue that is a reliable indicator of resource competition between species.     

Thinner bark increases sensitivity of wetter Amazonian tropical forests to fire

Understory fires represent an accelerating threat to Amazonian tropical forests and can, during drought, affect larger areas than deforestation itself. These fires kill trees at rates varying from < 10 to c. 90% depending on fire intensity, forest disturbance history and tree functional traits. Here, we examine variation in bark thickness across the Amazon. Bark can protect trees from fires, but it is often assumed to be consistently thin across tropical forests. Here, we show that investment in bark varies, with thicker bark in dry forests and thinner in wetter forests. We also show that thinner bark translated into higher fire‐driven tree mortality in wetter forests, with between 0.67 and 5.86 gigatonnes CO₂ lost in Amazon understory fires between 2001 and 2010. Trait‐enabled global vegetation models that explicitly include variation in bark thickness are likely to improve the predictions of fire effects on carbon cycling in tropical forests.     

Shortlisting SARS‐CoV‐2 Peptides for Targeted Studies from Experimental Data‐Dependent Acquisition Tandem Mass Spectrometry Data

Detection of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is a crucial tool for fighting the COVID‐19 pandemic. This dataset brief presents the exploration of a shotgun proteomics dataset acquired on SARS‐CoV‐2 infected Vero cells. Proteins from inactivated virus samples were extracted, digested with trypsin, and the resulting peptides were identified by data‐dependent acquisition tandem mass spectrometry. The 101 peptides reporting for six viral proteins were specifically analyzed in terms of their analytical characteristics, species specificity and conservation, and their proneness to structural modifications. Based on these results, a shortlist of 14 peptides from the N, S, and M main structural proteins that could be used for targeted mass‐spectrometry method development and diagnostic of the new SARS‐CoV‐2 is proposed and the best candidates are commented.     

New Approaches for Absolute Quantification of Stable‐Isotope‐Labeled Peptide Standards for Targeted Proteomics Based on a UV Active Tag

Targeted proteomics depends on the availability of stable isotope labeled (SIL) peptide standards, which for absolute protein quantification need to be absolutely quantified. In the present study, three new approaches for absolute quantification of SIL peptides are developed. All approaches rely on a quantification tag (Qtag) with a specific UV absorption. The Qtag is attached to the peptide during synthesis and is removed by tryptic digestion under standard proteomics workflow conditions. While one quantification method (method A) is designed to allow the fast and economic production of absolutely quantified SIL peptides, two other methods (methods B and C) are developed to enable the straightforward re‐quantification of SIL peptides after reconstitution to control and monitor known problems related to peptide solubility, precipitation, and adhesion to vials. All methods yield consistent results when compared to each other and when compared to quantification by amino acid analysis. The precise quantitation methods are used to characterize the in vivo specificity of the H3 specific histone methyltransferase EZH2.