Geolocated fish spawning habitats.

Fish spawning locations are a crucial input into fisheries management and conservation plans, and many stocks are especially sensitive to the environmental conditions within these localized zones. Globally collated data on spawning locations across many species has been unavailable, hindering global stock assessments and analyses of sustainable development and global environmental change. To address this, we created a geocoded fish spawning dataset using qualitative spawning information from FishBase and Science and Conservation of Fish Aggregations (SCRFA). We cleaned and geocoded the spawning locations of 1,045 marine fish species into 2,931 regions. Each spawning region is defined by one or more polygons, and most spawning regions are associated with spawning months. The resulting dataset covers oceans globally. This dataset will be useful to scientists studying marine fish population dynamics and their interactions with the physical environment on regional to large scales.

The costs of "costless" climate mitigation.

The IPCC and leading economic models have different ideas about emissions reduction costs.

Interbasin water transfers in the United States and Canada.

Interbasin water transfers (IBTs) can have a significant impact on the environment, water availability, and economies within the basins importing and exporting water, as well as basins downstream of these water transfers. The lack of comprehensive data identifying and describing IBTs inhibits understanding of the role IBTs play in supplying water for society, as well as their collective hydrologic impact. We develop three connected datasets inventorying IBTs in the United States and Canada, including their features, geospatial details, and water transfer volumes. We surveyed the academic and gray literature, as well as local, state, and federal water agencies, to collect, process, and verify IBTs in Canada and the United States. Our comprehensive IBT datasets represent all known transfers of untreated water that cross subregion (US) or subdrainage area (CA) boundaries, characterizing a total of 641 IBT projects. The infrastructure-level data made available by these data products can be used to close water budgets, connect water supplies to water use, and better represent human impacts within hydrologic and ecosystem models.

The missing risks of climate change.

The risks of climate change are enormous, threatening the lives and livelihoods of millions to billions of people. The economic consequences of many of the complex risks associated with climate change cannot, however, currently be quantified. Here we argue that these unquantified, poorly understood and often deeply uncertain risks can and should be included in economic evaluations and decision-making processes. We present an overview of these unquantified risks and an ontology of them founded on the reasons behind their lack of robust evaluation. These consist of risks missing owing to delays in sharing knowledge and expertise across disciplines, spatial and temporal variations of climate impacts, feedbacks and interactions between risks, deep uncertainty in our knowledge, and currently unidentified risks. We highlight collaboration needs within and between the natural and social science communities to address these gaps. We also provide an approach for integrating assessments or speculations of these risks in a way that accounts for interdependencies, avoids double counting and makes assumptions clear. Multiple paths exist for engaging with these missing risks, with both model-based quantification and non-model-based qualitative assessments playing crucial roles. A wide range of climate impacts are understudied or challenging to quantify, and are missing from current evaluations of the climate risks to lives and livelihoods. Strong interdisciplinary collaboration and deeper engagement with uncertainty is needed to properly inform policymakers and the public about climate risks.

Estimating a social cost of carbon for global energy consumption.

Estimates of global economic damage caused by carbon dioxide (CO2) emissions can inform climate policy1-3. The social cost of carbon (SCC) quantifies these damages by characterizing how additional CO2 emissions today impact future economic outcomes through altering the climate4-6. Previous estimates have suggested that large, warming-driven increases in energy expenditures could dominate the SCC7,8, but they rely on models9-11 that are spatially coarse and not tightly linked to data2,3,6,7,12,13. Here we show that the release of one ton of CO2 today is projected to reduce total future energy expenditures, with most estimates valued between -US$3 and -US$1, depending on discount rates. Our results are based on an architecture that integrates global data, econometrics and climate science to estimate local damages worldwide. Notably, we project that emerging economies in the tropics will dramatically increase electricity consumption owing to warming, which requires critical infrastructure planning. However, heating reductions in colder countries offset this increase globally. We estimate that 2099 annual global electricity consumption increases by about 4.5 exajoules (7 per cent of current global consumption) per one-degree-Celsius increase in global mean surface temperature (GMST), whereas direct consumption of other fuels declines by about 11.3 exajoules (7 per cent of current global consumption) per one-degree-Celsius increase in GMST. Our finding of net savings contradicts previous research7,8, because global data indicate that many populations will remain too poor for most of the twenty-first century to substantially increase energy consumption in response to warming. Importantly, damage estimates would differ if poorer populations were given greater weight14.

Economic impacts of tipping points in the climate system.

Climate scientists have long emphasized the importance of climate tipping points like thawing permafrost, ice sheet disintegration, and changes in atmospheric circulation. Yet, save for a few fragmented studies, climate economics has either ignored them or represented them in highly stylized ways. We provide unified estimates of the economic impacts of all eight climate tipping points covered in the economic literature so far using a meta-analytic integrated assessment model (IAM) with a modular structure. The model includes national-level climate damages from rising temperatures and sea levels for 180 countries, calibrated on detailed econometric evidence and simulation modeling. Collectively, climate tipping points increase the social cost of carbon (SCC) by ∼25% in our main specification. The distribution is positively skewed, however. We estimate an ∼10% chance of climate tipping points more than doubling the SCC. Accordingly, climate tipping points increase global economic risk. A spatial analysis shows that they increase economic losses almost everywhere. The tipping points with the largest effects are dissociation of ocean methane hydrates and thawing permafrost. Most of our numbers are probable underestimates, given that some tipping points, tipping point interactions, and impact channels have not been covered in the literature so far; however, our method of structural meta-analysis means that future modeling of climate tipping points can be integrated with relative ease, and we present a reduced-form tipping points damage function that could be incorporated in other IAMs.

Crop switching reduces agricultural losses from climate change in the United States by half under RCP 8.5.

A key strategy for agriculture to adapt to climate change is by switching crops and relocating crop production. We develop an approach to estimate the economic potential of crop reallocation using a Bayesian hierarchical model of yields. We apply the model to six crops in the United States, and show that it outperforms traditional empirical models under cross-validation. The fitted model parameters provide evidence of considerable existing climate adaptation across counties. If crop locations are held constant in the future, total agriculture profits for the six crops will drop by 31% for the temperature patterns of 2070 under RCP 8.5. When crop lands are reallocated to avoid yield decreases and take advantage of yield increases, half of these losses are avoided (16% loss), but 57% of counties are allocated crops different from those currently planted. Our results provide a framework for identifying crop adaptation opportunities, but suggest limits to their potential.

Behavioral, morphological, and ecological trait evolution in two clades of New World Sparrows (Aimophila and Peucaea, Passerellidae).

The New World sparrows (Passerellidae) are a large, diverse group of songbirds that vary in morphology, behavior, and ecology. Thus, they are excellent for studying trait evolution in a phylogenetic framework. We examined lability versus conservatism in morphological and behavioral traits in two related clades of sparrows (Aimophila, Peucaea), and assessed whether habitat has played an important role in trait evolution. We first inferred a multi-locus phylogeny which we used to reconstruct ancestral states, and then quantified phylogenetic signal among morphological and behavioral traits in these clades and in New World sparrows more broadly. Behavioral traits have a stronger phylogenetic signal than morphological traits. Specifically, vocal duets and song structure are the most highly conserved traits, and nesting behavior appears to be maintained within clades. Furthermore, we found a strong correlation between open habitat and unpatterned plumage, complex song, and ground nesting. However, even within lineages that share the same habitat type, species vary in nesting, plumage pattern, song complexity, and duetting. Our findings highlight trade-offs between behavior, morphology, and ecology in sparrow diversification.

The small world of global marine fisheries: The cross-boundary consequences of larval dispersal.

Fish stocks are managed within national boundaries and by regional organizations, but the interdependence of stocks between these jurisdictions, especially as a result of larval dispersal, remains poorly explored. We examined the international connectivity of 747 commercially fished taxonomic groups by building a global network of fish larval dispersal. We found that the world's fisheries are highly interconnected, forming a small-world network, emphasizing the need for international cooperation. We quantify each country's dependence on its neighbors in terms of landed value, food security, and jobs. We estimate that more than $10 billion in annual catch from 2005 to 2014 is attributable to these international flows of larvae. The economic risks associated with these dependencies is greatest in the tropics.

Mimi-PAGE, an open-source implementation of the PAGE09 integrated assessment model.

Integrated Assessment Models (IAMs) have become critical tools for assessing the costs and benefits of policies to reduce greenhouse gas emissions. Three models currently inform the social cost of carbon dioxide (SCCO2, the net present value of damages from one additional ton of CO2) used by the US federal government, several states, and Canada. Here we present a new open-source implementation of one of these models (PAGE09) in the Julia programming language using a modular modeling framework (Mimi). Mimi-PAGE was coded using best coding practices (such as multiple code reviews by different individuals during development, automated testing of newly-committed code, and provision of documentation and usage notes) and is publicly available in a GitHub repository for community inspection and use under an open source license. In this paper we describe the Julia implementation of PAGE09, show that output from Mimi-PAGE matches that of the original model, and perform comparisons of the run time between the two implementations.

Estimating economic damage from climate change in the United States.

Estimates of climate change damage are central to the design of climate policies. Here, we develop a flexible architecture for computing damages that integrates climate science, econometric analyses, and process models. We use this approach to construct spatially explicit, probabilistic, and empirically derived estimates of economic damage in the United States from climate change. The combined value of market and nonmarket damage across analyzed sectors-agriculture, crime, coastal storms, energy, human mortality, and labor-increases quadratically in global mean temperature, costing roughly 1.2% of gross domestic product per +1°C on average. Importantly, risk is distributed unequally across locations, generating a large transfer of value northward and westward that increases economic inequality. By the late 21st century, the poorest third of counties are projected to experience damages between 2 and 20% of county income (90% chance) under business-as-usual emissions (Representative Concentration Pathway 8.5).