Climate change research and action must look beyond 2100.

Anthropogenic activity is changing Earth's climate and ecosystems in ways that are potentially dangerous and disruptive to humans. Greenhouse gas concentrations in the atmosphere continue to rise, ensuring that these changes will be felt for centuries beyond 2100, the current benchmark for projection. Estimating the effects of past, current, and potential future emissions to only 2100 is therefore short-sighted. Critical problems for food production and climate-forced human migration are projected to arise well before 2100, raising questions regarding the habitability of some regions of the Earth after the turn of the century. To highlight the need for more distant horizon scanning, we model climate change to 2500 under a suite of emission scenarios and quantify associated projections of crop viability and heat stress. Together, our projections show global climate impacts increase significantly after 2100 without rapid mitigation. As a result, we argue that projections of climate and its effects on human well-being and associated governance and policy must be framed beyond 2100.

The latitudinal diversity gradient of tetrapods across the Permo-Triassic mass extinction and recovery interval.

The decline in species richness from the equator to the poles is referred to as the latitudinal diversity gradient (LDG). Higher equatorial diversity has been recognized for over 200 years, but the consistency of this pattern in deep time remains uncertain. Examination of spatial biodiversity patterns in the past across different global climate regimes and continental configurations can reveal how LDGs have varied over Earth history and potentially differentiate between suggested causal mechanisms. The Late Permian-Middle Triassic represents an ideal time interval for study, because it is characterized by large-scale volcanic episodes, extreme greenhouse temperatures and the most severe mass extinction event in Earth history. We examined terrestrial and marine tetrapod spatial biodiversity patterns using a database of global tetrapod occurrences. Terrestrial tetrapods exhibit a bimodal richness distribution throughout the Late Permian-Middle Triassic, with peaks in the northern low latitudes and southern mid-latitudes around 20-40° N and 60° S, respectively. Marine reptile fossils are known almost exclusively from the Northern Hemisphere in the Early and Middle Triassic, with highest diversity around 20° N. Reconstructed terrestrial LDGs contrast strongly with the generally unimodal gradients of today, potentially reflecting high global temperatures and prevailing Pangaean super-monsoonal climate system during the Permo-Triassic.

Projected future climatic forcing on the global distribution of vegetation types.

Most emissions scenarios suggest temperature and precipitation regimes will change dramatically across the globe over the next 500 years. These changes will have large impacts on the biosphere, with species forced to migrate to follow their preferred environmental conditions, therefore moving and fragmenting ecosystems. However, most projections of the impacts of climate change only reach 2100, limiting our understanding of the temporal scope of climate impacts, and potentially impeding suitable adaptive action. To address this data gap, we model future climate change every 20 years from 2000 to 2500 CE, under different CO2 emissions scenarios, using a general circulation model. We then apply a biome model to these modelled climate futures, to investigate shifts in climatic forcing on vegetation worldwide, the feasibility of the migration required to enact these modelled vegetation changes, and potential overlap with human land use based on modern-day anthromes. Under a business-as-usual scenario, up to 40% of terrestrial area is expected to be suited to a different biome by 2500. Cold-adapted biomes, particularly boreal forest and dry tundra, are predicted to experience the greatest losses of suitable area. Without mitigation, these changes could have severe consequences both for global biodiversity and the provision of ecosystem services. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

How predictable are mass extinction events?

Many modern extinction drivers are shared with past mass extinction events, such as rapid climate warming, habitat loss, pollution and invasive species. This commonality presents a key question: can the extinction risk of species during past mass extinction events inform our predictions for a modern biodiversity crisis? To investigate if it is possible to establish which species were more likely to go extinct during mass extinctions, we applied a functional trait-based model of extinction risk using a machine learning algorithm to datasets of marine fossils for the end-Permian, end-Triassic and end-Cretaceous mass extinctions. Extinction selectivity was inferred across each individual mass extinction event, before testing whether the selectivity patterns obtained could be used to 'predict' the extinction selectivity exhibited during the other mass extinctions. Our analyses show that, despite some similarities in extinction selectivity patterns between ancient crises, the selectivity of mass extinction events is inconsistent, which leads to a poor predictive performance. This lack of predictability is attributed to evolution in marine ecosystems, particularly during the Mesozoic Marine Revolution, associated with shifts in community structure alongside coincident Earth system changes. Our results suggest that past extinctions are unlikely to be informative for predicting extinction risk during a projected mass extinction.

PTHrP(12-48) Modulates the Bone Marrow Microenvironment and Suppresses Human Osteoclast Differentiation and Lifespan.

Bone is a common site for metastasis in breast cancer patients and is associated with a series of complications that significantly compromise patient survival, partially due to the advanced stage of disease at the time of detection. Currently, no clinically-approved biomarkers can identify or predict the development of bone metastasis. We recently identified a unique peptide fragment of parathyroid hormone-related protein (PTHrP), PTHrP(12-48), as a validated serum biomarker in breast cancer patients that correlates with and predicts the presence of bone metastases. In this study, the biological activity and mode of action of PTHrP(12-48) was investigated. Sequence-based and structure-based bioinformatics techniques predicted that the PTHrP(12-48) fragment formed an alpha helical core followed by an unstructured region after residue 40 or 42. Thereafter, detailed structure alignment and molecular docking simulations predicted a lack of interaction between PTHrP(12-48) and the cognate PTH1 receptor (PTHR1). The in silico prediction was confirmed by the lack of PTHrP(12-48)-stimulated cAMP accumulation in PTHR1-expressing human SaOS2 cells. Using a specific human PTHrP(12-48) antibody that we developed, PTHrP(12-48) was immunolocalized in primary and bone metastatic human breast cancer cells, as well as within human osteoclasts (OCLs) in bone metastasis biopsies, with little or no localization in other resident bone or bone marrow cells. In vitro, PTHrP(12-48) was internalized into cultured primary human OCLs and their precursors within 60 min. Interestingly, PTHrP(12-48) treatment dose-dependently suppressed osteoclastogenesis, via the induction of apoptosis in both OCL precursors as well as in mature OCLs, as measured by the activation of cleaved caspase 3. Collectively, these data suggest that PTHrP(12-48) is a bioactive breast cancer-derived peptide that locally regulates the differentiation of hematopoietic cells and the activity of osteoclasts within the tumor-bone marrow microenvironment, perhaps to facilitate tumor control of bone. © 2017 American Society for Bone and Mineral Research.