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Appalachian LCC PI and Clemson scientists unveil software that revolutionizes wildlife habitat connectivity modeling
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A trio of Clemson University scientists has unveiled a groundbreaking computational software called “GFlow” that makes wildlife habitat connectivity modeling vastly faster, more efficient and superior in quality and scope.
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Palaeodata-informed modelling of large carbon losses from recent burning of boreal forests
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Wildfires play a key role in the boreal forest carbon cycle(1,2), and models suggest that accelerated burning will increase boreal C emissions in the coming century (3). However, these predictions may be compromised because brief observational records provide limited constraints to model initial conditions (4). We confronted this limitation by using palaeoenvironmental data to drive simulations of long-term C dynamics in the Alaskan bo- real forest. Results show that fire was the dominant control on C cycling over the past millennium, with changes in fire frequency accounting for 84% of C stock variability. A recent rise in fire frequency inferred from the palaeorecord5 led to simulated C losses of 1.4 kg C m?2(12% of ecosystem C stocks) from 1950 to 2006. In stark contrast, a small net C sink of 0.3 kg C m?2 occurred if the past fire regime was assumed to be similar to the modern regime, as is common in models of C dynamics. Although boreal fire regimes are heterogeneous, recent trends6 and future projections (7) point to increasing fire activity in response to climate warming throughout the biome. Thus, predictions (8) that terrestrial C sinks of northern high latitudes will mitigate rising atmospheric CO2 may be over-optimistic.
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Global non-linear effect of temperature on economic production
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Growing evidence demonstrates that climatic conditions can have a profound impact on the functioning of modern human societies (1,2), but effects on economic activity appear inconsistent. Fundamental productive elements of modern economies, such as workers and crops, exhibit highly non-linear responses to local temperature even in wealthy countries (3,4). In contrast, aggregate macroeconomic productivity of entire wealthy countries is reported not to respond to temperature (5), while poor countries respond only linearly (5,6). Resolving this conflict between micro and macro observations is critical to understanding the role of wealth in coupled human–natural systems (7,8) and to anticipating the global impact of climate change (9,10). Here we unify these seemingly contradictory results by accounting for non-linearity at the macro scale. We show that overall economic productivity is non- linear in temperature for all countries, with productivity peaking at an annual average temperature of 13 6C and declining strongly at higher temperatures. The relationship is globally generalizable, unchanged since 1960, and apparent for agricultural and non-agricultural activity in both rich and poor countries. These results provide the first evidence that economic activity in all regions is coupled to the global climate and establish a new empirical foundation for modelling economic loss in response to climate change (11,12), with important implications. If future adaptation mimics past adaptation, unmitigated warming is expected to reshape the global economy by reducing average global incomes roughly 23% by 2100 and widening global income inequality, relative to scenarios without climate change. In contrast to prior estimates, expected global losses are approximately linear in global mean temperature, with median losses many times larger than leading models indicate.
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Novel climates, no-analog communities, and ecological surprises
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No-analog communities (communities that are compositionally unlike any found today) occurred frequently in the past and will develop in the greenhouse world of the future. The well documented no-analog plant communities of late-glacial North America are closely linked to “novel” climates also lacking modern analogs, characterized by high seasonality of temperature. In climate simulations for the Intergovernmental Panel on Climate Change A2 and B1 emission scenarios, novel climates arise by 2100 AD, primarily in tropical and subtropical regions. These future novel climates are warmer than any present climates globally, with spatially variable shifts in precipitation, and increase the risk of species reshuffling into future no-analog communities and other ecological surprises. Most ecological models are at least partially parameterized from modern observations and so may fail to accurately predict ecological responses to these novel climates. There is an urgent need to test the robustness of ecological models to climate conditions outside modern experience.
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Uncertainty in the response of transpiration to CO2 and implications for climate change
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While terrestrial precipitation is a societally highly relevant climate variable, there is little consensus among climate models about its projected 21st century changes. An important source of precipitable water over land is plant transpiration. Plants control transpiration by opening and closing their stomata. The sensitivity of this process to increasing CO2 concentrations is uncertain. To assess the impact of this uncertainty on future climate, we perform experiments with an intermediate complexity Earth System Climate Model (UVic ESCM) for a range of model-imposed transpiration- sensitivities to CO2. Changing the sensitivity of transpiration to CO2 causes simulated terrestrial precipitation to change by −10% to +27% by 2100 under a high emission scenario. This study emphasises the importance of an improved assessment of the dynamics of environmental impact on vegetation to better predict future changes of the terrestrial hydrological and carbon cycles.
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Duality in climate science
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Delivery of palatable 2 °C mitigation scenarios depends on speculative negative emissions or changing the past. Scientists must make their assumptions transparent and defensible, however politically uncomfortable the conclusions.
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THE COST OF INACTION: RECOGNISING THE VALUE AT RISK FROM CLIMATE CHANGE
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The asset management industry—and thus the wider community of investors of all sizes— is facing the prospect of significant losses from the effects of climate change. Assets can be directly damaged by floods, droughts and severe storms, but portfolios can also be harmed indirectly, through weaker growth and lower asset returns. Climate change is a long-term, probably irreversible problem beset by substantial uncertainty. Crucially, however, climate change is a problem of extreme risk: this means that the average losses to be expected are not the only source of concern; on the contrary, the outliers, the particularly extreme scenarios, may matter most of all.
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Predicting a change in the order of spring phenology in temperate forests
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The rise in spring temperatures over the past half-century has led to advances in the phenology of many nontropical plants and animals. As species and populations differ in their phenological responses to temperature, an increase in temperatures has the potential to alter timing-dependent species interactions. One species-interaction that may be affected is the competition for light in deciduous forests, where early vernal species have a narrow window of opportunity for growth before late spring species cast shade. Here we consider the Marsham phenology time series of first leafing dates of thirteen tree species and flowering dates of one ground flora species, which spans two centuries. The exceptional length of this time series permits a rare comparison of the statistical support for parameter-rich regression and mechanistic thermal sensitivity phenology models. While mechanistic models perform best in the majority of cases, both they and the regression models provide remarkably consistent insights into the relative sensitivity of each species to forcing and chilling effects. All species are sensitive to spring forcing, but we also find that vernal and
northern European species are responsive to cold temperatures in the previous autumn. Whether this sensitivity reflects a chilling requirement or a delaying of dormancy remains to be tested. We then apply the models to projected future temperature data under a fossil fuel intensive emissions scenario and predict that while some species will advance substantially others will advance by less and may even be delayed due to a rise in autumn and winter temperatures. Considering the projected responses of all fourteen species, we anticipate a change in the order of spring events, which may lead to changes in competitive advantage for light with potential implications for the composition of temperate forests.
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The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2013
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The WMO Global Atmosphere Watch (GAW) coordinates observations of the most important contributors to climate change: long-lived greenhouse gases(LLGHG). In the figure, their radiative forcing (RF) is plotted along with a simple illustration of the impacts on future RF of different emission reduction scenarios. Analysis of GAW observations shows that a reduction in RF from its current level (2.92 W·m–2 in
2013)[1] requires significant reductions in anthropogenic emissions of all major greenhouse gases (GHGs).
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Temporal dynamics of a commensal network of cavity-nesting vertebrates: increased diversity during an insect outbreak
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Network analysis offers insight into the structure and function of ecological
communities, but little is known about how empirical networks change over time during
perturbations. ‘‘Nest webs’’ are commensal networks that link secondary cavity-nesting
vertebrates (e.g., bluebirds, ducks, and squirrels, which depend on tree cavities for nesting)
with the excavators (e.g., woodpeckers) that produce cavities. In central British Columbia,
Canada, Northern Flicker (Colaptes auratus) is considered a keystone excavator, providing
most cavities for secondary cavity-nesters. However, roles of species in the network, and
overall network architecture, are expected to vary with population fluctuations. Many
excavator species increased in abundance in association with a pulse of food (adult and larval
beetles) during an outbreak of mountain pine beetle (Dendroctonus ponderosae), which peaked
in 2003–2004. We studied nest-web dynamics from 1998 to 2011 to determine how network
architecture changed during this resource pulse.Cavity availability increased at the onset of the beetle outbreak and peaked in 2005. During and after the outbreak, secondary cavity-nesters increased their use of cavities made by five species of beetle-eating excavators, and decreased their use of flicker cavities. We found low link turnover, with 74% of links conserved from year to year. Nevertheless, the network
increased in evenness and diversity of interactions, and declined slightly in nestedness and
niche overlap. These patterns remained evident seven years after the beetle outbreak,
suggesting a legacy effect. In contrast to previous snapshot studies of nest webs, our dynamic approach reveals how the role of each cavity producer, and thus quantitative network architecture, can vary over
time. The increase in interaction diversity with the beetle outbreak adds to growing evidence
that insect outbreaks can increase components of biodiversity in forest ecosystems at various
temporal scales. The observed changes in (quantitative) network architecture contrast with the
relatively stable (qualitative) architecture of empirical mutualistic networks that have been
studied to date. However, they are consistent with recent theory on the importance of
population fluctuations in driving network architecture. Our results support the view that
models should allow for the possibility of rewiring (species switching partners) to avoid
overestimation of secondary extinction risk.
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