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The marine biological carbon pump (BCP) stores carbon in the ocean interior, isolating it from exchange with the atmosphere and thereby coregulating atmospheric carbon dioxide (CO2). As the BCP commonly is equated with the flux of organic material to the ocean interior, termed "export flux," a change in export flux is perceived to directly impact atmospheric CO2, and thus climate. Here, we recap how this perception contrasts with current understanding of the BCP, emphasizing the lack of a direct relationship between global export flux and atmospheric CO2. We argue for the use of the storage of carbon of biological origin in the ocean interior as a diagnostic that directly relates to atmospheric CO2, as a way forward to quantify the changes in the BCP in a changing climate. The diagnostic is conveniently applicable to both climate model data and increasingly available observational data. It can explain a seemingly paradoxical response under anthropogenic climate change: Despite a decrease in export flux, the BCP intensifies due to a longer reemergence time of biogenically stored carbon back to the ocean surface and thereby provides a negative feedback to increasing atmospheric CO2. This feedback is notably small compared with anthropogenic CO2 emissions and other carbon‐climate feedbacks. In this Opinion paper, we advocate for a comprehensive view of the BCP's impact on atmospheric CO2, providing a prerequisite for assessing the effectiveness of marine CO2 removal approaches that target marine biology. [ABSTRACT FROM AUTHOR]

Our understanding of how increasing atmospheric CO2 and climate change influences the marine CO2 system and in turn ecosystems has increasingly focused on perturbations to carbonate chemistry variability. This variability can affect ocean-climate feedbacks and has been shown to influence marine ecosystems. The seasonal variability of the ocean CO2 system has already changed, with enhanced seasonal variations in the surface ocean pCO2 over recent decades and further amplification projected by models over the 21st century. Mesocosm studies and CO2 vent sites indicate that diurnal variability of the CO2 system, the amplitude of which in extreme events can exceed that of mean seasonal variability, is also likely to be altered by climate change. Here, we modified a global ocean biogeochemical model to resolve physically and biologically driven diurnal variability of the ocean CO2 system. Forcing the model with 3-h atmospheric outputs derived from an Earth system model, we explore how surface ocean diurnal variability responds to historical changes and project how it changes under two contrasting 21st-century emission scenarios. Compared to preindustrial values, the global mean diurnal amplitude of pCO2 increases by 4.8 μatm (+226%) in the high-emission scenario but only 1.2 μatm (+55%) in the high-mitigation scenario. The probability of extreme diurnal amplitudes of pCO2 and [H+] is also affected, with 30-to 60-fold increases relative to the preindustrial under high 21st-century emissions. The main driver of heightened pCO2 diurnal variability is the enhanced sensitivity of pCO2 to changes in temperature as the ocean absorbs atmospheric CO2. Our projections suggest that organisms in the future ocean will be exposed to enhanced diurnal variability in pCO2 and [H+], with likely increases in the associated metabolic cost that such variability imposes. [ABSTRACT FROM AUTHOR]

Climate change influences the ocean's physical and biogeochemical conditions, causing additional pressures on marine environments and ecosystems, now and in the future. Such changes occur in environments that already today suffer under pressures from, for example, eutrophication, pollution, shipping, and more. We demonstrate how to implement climate change into regional marine spatial planning by introducing data of future temperature, salinity, and sea ice cover from regional ocean climate model projections to an existing cumulative impact model. This makes it possible to assess climate change impact in relation to pre‐existing cumulative impact from current human activities. Results indicate that end‐of‐century projected climate change alone is a threat of the same magnitude as the combination of all current pressures to the marine environment. These findings give marine planners and policymakers forewarning on how future climate change may impact marine ecosystems, across space, emission scenarios, and in relation to other pressures. [ABSTRACT FROM AUTHOR]

Tropical coral reefs are among the most sensitive ecosystems to climate change and will benefit from the more ambitious aims of the United Nations Framework Convention on Climate Change's Paris Agreement, which proposed to limit global warming to 1.5° rather than 2°C above pre‐industrial levels. Only in the latest Intergovernmental Panel on Climate Change focussed assessment, the Coupled Model Intercomparison Project phase 6 (CMIP6), have climate models been used to investigate the 1.5° warming scenario directly. Here, we combine the most recent model updates from CMIP6 with a semi‐dynamic downscaling to evaluate the difference between the 1.5 and 2°C global warming targets on coral thermal stress metrics for the Great Barrier Reef (GBR). By ~2080, severe bleaching events are expected to occur annually under intensifying emissions (shared socioeconomic pathway SSP5‐8.5). Adherence to 2° warming (SSP1‐2.6) halves this frequency but the main benefit of confining warming to 1.5° (SSP1‐1.9) is that bleaching events are reduced further to 3 events per decade. Attaining low emissions of 1.5° is also paramount to prevent the mean magnitude of thermal stress from stabilizing close to a critical thermal threshold (8 Degree Heating Weeks). Thermal stress under the more pessimistic pathways SSP3‐7.0 and SSP5‐8.5 is three to fourfold higher than the present day, with grave implications for future reef ecosystem health. As global warming continues, our projections also indicate more regional warming in the central and southern GBR than the far north and northern GBR. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

There is a major concern for the fate of Amazonia over the coming century in the face of anthropogenic climate change. A key area of uncertainty is the scale of rainforest dieback to be expected under a future, drier climate. In this study, we use the middle Holocene (ca. 6000 years before present) as an approximate analogue for a drier future, given that palaeoclimate data show much of Amazonia was significantly drier than present at this time. Here, we use an ensemble of climate and vegetation models to explore the sensitivity of Amazonian biomes to mid‐Holocene climate change. For this, we employ three dynamic vegetation models (JULES, IBIS, and SDGVM) forced by the bias‐corrected mid‐Holocene climate simulations from seven models that participated in the Palaeoclimate Modelling Intercomparison Project 3 (PMIP3). These model outputs are compared with a multi‐proxy palaeoecological dataset to gain a better understanding of where in Amazonia we have most confidence in the mid‐Holocene vegetation simulations. A robust feature of all simulations and palaeodata is that the central Amazonian rainforest biome is unaffected by mid‐Holocene drought. Greater divergence in mid‐Holocene simulations exists in ecotonal eastern and southern Amazonia. Vegetation models driven with climate models that simulate a drier mid‐Holocene (100–150 mm per year decrease) better capture the observed (palaeodata) tropical forest dieback in these areas. Based on the relationship between simulated rainfall decrease and vegetation change, we find indications that in southern Amazonia the rate of tropical forest dieback was ~125,000 km2 per 100 mm rainfall decrease in the mid‐Holocene. This provides a baseline sensitivity of tropical forests to drought for this region (without human‐driven changes to greenhouse gases, fire, and deforestation). We highlight the need for more palaeoecological and palaeoclimate data across lowland Amazonia to constrain model responses. [ABSTRACT FROM AUTHOR]

Bumblebees are ubiquitous, cold‐adapted eusocial bees found worldwide from subarctic to tropical regions of the world. They are key pollinators in most temperate and boreal ecosystems, and both wild and managed populations are significant contributors to agricultural pollination services. Despite their broad ecological niche at the genus level, bumblebee species are threatened by climate change, particularly by rising average temperatures, intensifying seasonality and the increasing frequency of extreme weather events. While some temperature extremes may be offset at the individual or colony level through temperature regulation, most bumblebees are expected to exhibit specific plastic responses, selection in various key traits, and/or range contractions under even the mildest climate change. In this review, we provide an in‐depth and up‐to‐date review on the various ways by which bumblebees overcome the threats associated with current and future global change. We use examples relevant to the fields of bumblebee physiology, morphology, behaviour, phenology, and dispersal to illustrate and discuss the contours of this new theoretical framework. Furthermore, we speculate on the extent to which adaptive responses to climate change may be influenced by bumblebees' capacity to disperse and track suitable climate conditions. Closing the knowledge gap and improving our understanding of bumblebees' adaptability or avoidance behaviour to different climatic circumstances will be necessary to improve current species climate response models. These models are essential to make correct predictions of species vulnerability in the face of future climate change and human‐induced environmental changes to unfold appropriate future conservation strategies. [ABSTRACT FROM AUTHOR]

Climate change affects global agricultural production and threatens food security. Faster phenological development of crops due to climate warming is one of the main drivers for potential future yield reductions. To counter the effect of faster maturity, adapted varieties would require more heat units to regain the previous growing period length. In this study, we investigate the effects of variety adaptation on global caloric production under four different future climate change scenarios for maize, rice, soybean, and wheat. Thereby, we empirically identify areas that could require new varieties and areas where variety adaptation could be achieved by shifting existing varieties into new regions. The study uses an ensemble of seven global gridded crop models and five CMIP6 climate models. We found that 39% (SSP5‐8.5) of global cropland could require new crop varieties to avoid yield loss from climate change by the end of the century. At low levels of warming (SSP1‐2.6), 85% of currently cultivated land can draw from existing varieties to shift within an agro‐ecological zone for adaptation. The assumptions on available varieties for adaptation have major impacts on the effectiveness of variety adaptation, which could more than half in SSP5‐8.5. The results highlight that region‐specific breeding efforts are required to allow for a successful adaptation to climate change. [ABSTRACT FROM AUTHOR]

Spatiotemporal redistribution of incident rainfall in vegetated ecosystems results from the partitioning by plants into intercepted, stemflow, and throughfall fractions. However, variation in patterns and drivers of rainfall partitioning across global biomes remains poorly understood, which limited the ability of climate models to improve the predictions of biome hydrological cycle under global climate change scenario. Here, we synthesized and analyzed the partitioning of incident rainfall into interception, stemflow, and throughfall by trees and shrubs at the global scale using 2430 observations from 236 independent publications. We found that (1) globally, median levels of relative interception, stemflow, and throughfall accounted for 21.8%, 3.2%, and 73.0% of total incident rainfall, respectively; (2) rainfall partitioning varied among different biomes, due to variation in plant composition, canopy structure, and macroclimate; (3) relative stemflow tended to be driven by plant traits, such as crown height:width ratio, basal area, and height, while relative interception and throughfall tended to be driven by plant traits as well as meteorological variables. Our global assessment of patterns and drivers of rainfall partitioning underpins the role of meteorological factors and plant traits in biome‐specific ecohydrological cycles. We suggest to include these factors in climate models to improve the predictions of local hydrological cycles and associated biodiversity and function responses to changing climate conditions. [ABSTRACT FROM AUTHOR]

Novel climates - emerging conditions with no analog in the observational record - are an open problem in ecological modeling. Detecting extrapolation into novel conditions is a critical step in evaluating bioclimatic projections of how species and ecosystems will respond to climate change. However, biologically informed novelty detection methods remain elusive for many modeling algorithms. To assist with bioclimatic model design and evaluation, we present a first-approximation assessment of general novelty based on a simple and consistent characterization of climate. We build on the seminal global analysis of Williams et al. (2007 PNAS, 104, 5738) by assessing of end-of-21st-century novelty for North America at high spatial resolution and by refining their standardized Euclidean distance into an intuitive Mahalanobian metric called sigma dissimilarity. Like this previous study, we found extensive novelty in end-of-21st-century projections for the warm southern margin of the continent as well as the western Arctic. In addition, we detected localized novelty in lower topographic positions at all latitudes: By the end of the 21st century, novel climates are projected to emerge at low elevations in 80% and 99% of ecoregions in the RCP4.5 and RCP8.5 emissions scenarios, respectively. Novel climates are limited to 7% of the continent's area in RCP4.5, but are much more extensive in RCP8.5 (40% of area). These three risk factors for novel climates - regional susceptibility, topographic position, and the magnitude of projected climate change - represent a priori evaluation criteria for the credibility of bioclimatic projections. Our findings indicate that novel climates can emerge in any landscape. Interpreting climatic novelty in the context of nonlinear biological responses to climate is an important challenge for future research. [ABSTRACT FROM AUTHOR]

Current climate models project changes in both temperature and precipitation patterns across the globe in the coming years. Migratory species, which move to take advantage of seasonal climate patterns, are likely to be affected by these changes, and indeed, a number of studies have shown a relationship between changing climate and the migration timing of various species. However, these studies have almost exclusively focused on the effects of temperature change on species that inhabit temperate zones. Here, we explore the relationship between rainfall and migration timing in a tropical species, Gecarcoidea natalis (Christmas Island red crab). We find that the timing of the annual crab breeding migration is closely related to the amount of rain that falls during a 'migration window' period prior to potential egg release dates, which is in turn related to the Southern Oscillation Index, an atmospheric El Niño- Southern Oscillation Index. As reproduction in this species is conditional on successful migration, major changes in migration patterns could have detrimental consequences for the survival of the species. This study serves to broaden our understanding of the effects of climate change on migratory species and will hopefully inspire future work on rainfall and tropical migrations. [ABSTRACT FROM AUTHOR]

Concern over rapid global changes and the potential for interactions among multiple threats are prompting scientists to combine multiple modelling approaches to understand impacts on biodiversity. A relatively recent development is the combination of species distribution models, land-use change predictions, and dynamic population models to predict the relative and combined impacts of climate change, land-use change, and altered disturbance regimes on species' extinction risk. Each modelling component introduces its own source of uncertainty through different parameters and assumptions, which, when combined, can result in compounded uncertainty that can have major implications for management. Although some uncertainty analyses have been conducted separately on various model components - such as climate predictions, species distribution models, land-use change predictions, and population models - a unified sensitivity analysis comparing various sources of uncertainty in combined modelling approaches is needed to identify the most influential and problematic assumptions. We estimated the sensitivities of long-run population predictions to different ecological assumptions and parameter settings for a rare and endangered annual plant species ( Acanthomintha ilicifolia, or San Diego thornmint). Uncertainty about habitat suitability predictions, due to the choice of species distribution model, contributed most to variation in predictions about long-run populations. [ABSTRACT FROM AUTHOR]