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Article ; Online: Good and bad news for ocean predators.

Burgess, Matthew G / Becker, Sarah L

2022 Volume 378, Issue 6620, Page(s) 596–597

Abstract: Some tunas and billfishes are recovering, but sharks continue to decline. ...

Abstract	Some tunas and billfishes are recovering, but sharks continue to decline.
MeSH term(s)	Animals ; Oceans and Seas ; Sharks ; Tuna ; Food Chain ; Endangered Species ; Extinction, Biological ; Population Growth
Language	English
Publishing date	2022-11-10
Publishing country	United States
Document type	Journal Article ; Comment
ZDB-ID	128410-1
ISSN	1095-9203 ; 0036-8075
ISSN (online)	1095-9203
ISSN	0036-8075
DOI	10.1126/science.add0342
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Article: Advancing bipartisan decarbonization policies: lessons from state-level successes and failures.

Marshall, Renae / Burgess, Matthew G

Climatic change

2022 Volume 171, Issue 1-2, Page(s) 17

Abstract: U.S. political polarization is at a high point since the Civil War, and is a significant barrier to coordinated national action addressing climate change. To examine where common ground may exist, here we comprehensively review and characterize successes ...

Abstract	U.S. political polarization is at a high point since the Civil War, and is a significant barrier to coordinated national action addressing climate change. To examine where common ground may exist, here we comprehensively review and characterize successes and failures of recent state-level decarbonization legislation, focusing especially on bipartisanship. We analyze 418 major state-government-enacted bills and 450 failed bills from 2015 to 2020, as well as the political contexts in which they were passed or defeated. We use bivariate analyses and regressions to explore correlations and partial correlations between the policy characteristics and political contexts of bills, and their passage or failure, their bipartisanship, and vote shares they received. Key results include (i) nearly one-third of these state-level decarbonization bills were passed by Republican-controlled governments. (ii) Bipartisan or Republican co-sponsors disproportionately passed financial incentives for renewable energy, and legislation that expands consumer or business choices in context of decarbonization goals; Democrat-only co-sponsors disproportionately passed bills that restricted consumer and business choice, such as mandatory Renewable Energy and Efficiency Portfolio Standards (REEPS) and emissions standards. (iii) Bipartisan bills were disproportionately proposed in "divided" states, did not restrict consumer and business choice, had environmental justice components framed economically, and lacked environmental justice components framed either using academic social-justice jargon or non-neutrally with respect to immutable characteristics such as race. (iv) Bills that expand consumer or business choice were disproportionately enacted. Though climate change is a polarized issue, our results provide tangible insights for future bipartisan successes. Supplementary information: The online version contains supplementary material available at 10.1007/s10584-022-03335-w.
Language	English
Publishing date	2022-03-31
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	751086-x
ISSN	0165-0009
ISSN	0165-0009
DOI	10.1007/s10584-022-03335-w
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Article ; Online: Catastrophic climate risks should be neither understated nor overstated.

Burgess, Matthew G / Pielke, Roger / Ritchie, Justin

Proceedings of the National Academy of Sciences of the United States of America

2022 Volume 119, Issue 42, Page(s) e2214347119

MeSH term(s)	Climate ; Climate Change
Language	English
Publishing date	2022-10-10
Publishing country	United States
Document type	Letter ; Comment
ZDB-ID	209104-5
ISSN	1091-6490 ; 0027-8424
ISSN (online)	1091-6490
ISSN	0027-8424
DOI	10.1073/pnas.2214347119
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Article ; Online: Empirically classifying network mechanisms.

Langendorf, Ryan E / Burgess, Matthew G

Scientific reports

2021 Volume 11, Issue 1, Page(s) 20501

Abstract: Network data are often explained by assuming a generating mechanism and estimating related parameters. Without a way to test the relevance of assumed mechanisms, conclusions from such models may be misleading. Here we introduce a simple empirical ... ...

Abstract	Network data are often explained by assuming a generating mechanism and estimating related parameters. Without a way to test the relevance of assumed mechanisms, conclusions from such models may be misleading. Here we introduce a simple empirical approach to mechanistically classify arbitrary network data as originating from any of a set of candidate mechanisms or none of them. We tested our approach on simulated data from five of the most widely studied network mechanisms, and found it to be highly accurate. We then tested 1284 empirical networks spanning 17 different kinds of systems against these five widely studied mechanisms. We found that 387 (30%) of these empirical networks were classified as unlike any of the mechanisms, and only 1% or fewer of the networks classified as each of the mechanisms for which our approach was most sensitive. Based on this, we use Bayes' theorem to show that most of the 70% of empirical networks our approach classified as a mechanism could be false positives, because of the high sensitivity required of a test to detect rarely occurring mechanisms. Thus, it is possible that very few of our empirical networks are described by any of these five widely studied mechanisms. Additionally, 93 networks (7%) were classified as plausibly being governed by each of multiple mechanisms. This raises the possibility that some systems are governed by mixtures of mechanisms. We show that mixtures are often unidentifiable because different mixtures can produce structurally equivalent networks, but that we can still accurately predict out-of-sample functional properties.
Language	English
Publishing date	2021-10-15
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-99251-7
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Article: Advancing bipartisan decarbonization policies: lessons from state-level successes and failures

Marshall, Renae / Burgess, Matthew G.

Climatic change. 2022 Mar., v. 171, no. 1-2

2022

Abstract	U.S. political polarization is at a high point since the Civil War, and is a significant barrier to coordinated national action addressing climate change. To examine where common ground may exist, here we comprehensively review and characterize successes and failures of recent state-level decarbonization legislation, focusing especially on bipartisanship. We analyze 418 major state-government-enacted bills and 450 failed bills from 2015 to 2020, as well as the political contexts in which they were passed or defeated. We use bivariate analyses and regressions to explore correlations and partial correlations between the policy characteristics and political contexts of bills, and their passage or failure, their bipartisanship, and vote shares they received. Key results include (i) nearly one-third of these state-level decarbonization bills were passed by Republican-controlled governments. (ii) Bipartisan or Republican co-sponsors disproportionately passed financial incentives for renewable energy, and legislation that expands consumer or business choices in context of decarbonization goals; Democrat-only co-sponsors disproportionately passed bills that restricted consumer and business choice, such as mandatory Renewable Energy and Efficiency Portfolio Standards (REEPS) and emissions standards. (iii) Bipartisan bills were disproportionately proposed in “divided” states, did not restrict consumer and business choice, had environmental justice components framed economically, and lacked environmental justice components framed either using academic social-justice jargon or non-neutrally with respect to immutable characteristics such as race. (iv) Bills that expand consumer or business choice were disproportionately enacted. Though climate change is a polarized issue, our results provide tangible insights for future bipartisan successes.
Keywords	climate change ; issues and policy ; politics ; renewable energy sources ; social justice
Language	English
Dates of publication	2022-03
Size	p. 17.
Publishing place	Springer Netherlands
Document type	Article
ZDB-ID	751086-x
ISSN	0165-0009
ISSN	0165-0009
DOI	10.1007/s10584-022-03335-w
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: The scale of life and its lessons for humanity.

Burgess, Matthew G / Gaines, Steven D

Proceedings of the National Academy of Sciences of the United States of America

2018 Volume 115, Issue 25, Page(s) 6328–6330

MeSH term(s)	Life
Language	English
Publishing date	2018-05-23
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Comment
ZDB-ID	209104-5
ISSN	1091-6490 ; 0027-8424
ISSN (online)	1091-6490
ISSN	0027-8424
DOI	10.1073/pnas.1807019115
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Article ; Online: The Difficult Airway Redefined.

Burgess, Matthew B / Schauer, Steven G / Hood, R Lyle / De Lorenzo, Robert A

Prehospital and disaster medicine

2022 Volume 37, Issue 6, Page(s) 723–726

Abstract: There is no all-encompassing or universally accepted definition of the difficult airway, and it has traditionally been approached as a problem chiefly rooted in anesthesiology. However, with airway obstruction reported as the second leading cause of ... ...

Abstract	There is no all-encompassing or universally accepted definition of the difficult airway, and it has traditionally been approached as a problem chiefly rooted in anesthesiology. However, with airway obstruction reported as the second leading cause of mortality on the battlefield and first-pass success (FPS) rates for out-of-hospital endotracheal intubation (ETI) as low as 46.4%, the need to better understand the difficult airway in the context of the prehospital setting is clear. In this review, we seek to redefine the concept of the "difficult airway" so that future research can target solutions better tailored for prehospital, and more specifically, combat casualty care. Contrasting the most common definitions, which narrow the scope of practice to physicians and a handful of interventions, we propose that the difficult airway is simply one that cannot be quickly obtained. This implies that it is a situation arrived at through a multitude of factors, namely the Patient, Operator, Setting, and Technology (POST), but also more importantly, the interplay between these elements. Using this amended definition and approach to the difficult to manage airway, we outline a target-specific approach to new research questions rooted in this system-based approach to better address the difficult airway in the prehospital and combat casualty care settings.
Language	English
Publishing date	2022-11-09
Publishing country	United States
Document type	Journal Article
ZDB-ID	1025975-2
ISSN	1945-1938 ; 1049-023X
ISSN (online)	1945-1938
ISSN	1049-023X
DOI	10.1017/S1049023X22001455
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Article ; Online: Rebound effects could offset more than half of avoided food loss and waste.

Hegwood, Margaret / Burgess, Matthew G / Costigliolo, Erin M / Smith, Pete / Bajželj, Bojana / Saunders, Harry / Davis, Steven J

Nature food

2023 Volume 4, Issue 7, Page(s) 585–595

Abstract: Reducing food loss and waste (FLW) could lessen the environmental impacts of food systems and improve food security. However, rebound effects-whereby efficiency improvements cause price decreases and consumption increases-may offset some avoided FLW. ... ...

Abstract	Reducing food loss and waste (FLW) could lessen the environmental impacts of food systems and improve food security. However, rebound effects-whereby efficiency improvements cause price decreases and consumption increases-may offset some avoided FLW. Here we model rebounds in food consumption under a scenario of costless FLW reduction. We project that consumption rebound could offset 53-71% of avoided FLW. Such rebounds would imply similar percentage reductions in environmental benefits (carbon emissions, land use, water use) and improvements in food security benefits (increased calorie availability), highlighting a tension between these two objectives. Evidence from energy systems suggests that indirect effects not included in our analysis could further increase rebounds. However, costs of reducing FLW would reduce rebounds. Rebound effects are therefore important to consider in efforts aimed at reducing FLW.
MeSH term(s)	Environment ; Food ; Food Supply
Language	English
Publishing date	2023-07-20
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ISSN	2662-1355
ISSN (online)	2662-1355
DOI	10.1038/s43016-023-00792-z
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Article ; Online: Orbital-use fees could more than quadruple the value of the space industry.

Rao, Akhil / Burgess, Matthew G / Kaffine, Daniel

Proceedings of the National Academy of Sciences of the United States of America

2020 Volume 117, Issue 23, Page(s) 12756–12762

Abstract: The space industry's rapid recent growth represents the latest tragedy of the commons. Satellites launched into orbit contribute to-and risk damage from-a growing buildup of space debris and other satellites. Collision risk from this orbital congestion ... ...

Abstract	The space industry's rapid recent growth represents the latest tragedy of the commons. Satellites launched into orbit contribute to-and risk damage from-a growing buildup of space debris and other satellites. Collision risk from this orbital congestion is costly to satellite operators. Technological and managerial solutions-such as active debris removal or end-of-life satellite deorbit guidelines-are currently being explored by regulatory authorities. However, none of these approaches address the underlying incentive problem: satellite operators do not account for costs they impose on each other via collision risk. Here, we show that an internationally harmonized orbital-use fee can correct these incentives and substantially increase the value of the space industry. We construct and analyze a coupled physical-economic model of commercial launches and debris accumulation in low-Earth orbit. Similar to carbon taxes, our model projects an optimal fee that rises at a rate of 14% per year, equal to roughly $235,000 per satellite-year in 2040. The long-run value of the satellite industry would more than quadruple by 2040-increasing from around $600 billion under business as usual to around $3 trillion. In contrast, we project that purely technological solutions are unlikely to fully address the problem of orbital congestion. Indeed, we find debris removal sometimes worsens economic damages from congestion by increasing launch incentives. In other sectors, addressing the tragedy of the commons has often been a game of catch-up with substantial social costs. The infant space industry can avert these costs before they escalate.
Language	English
Publishing date	2020-05-26
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	209104-5
ISSN	1091-6490 ; 0027-8424
ISSN (online)	1091-6490
ISSN	0027-8424
DOI	10.1073/pnas.1921260117
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Book ; Online: Empirically Classifying Network Mechanisms

Langendorf, Ryan E. / Burgess, Matthew G.

2020

Abstract: Network models are used to study interconnected systems across many physical, biological, and social disciplines. Such models often assume a particular network-generating mechanism, which when fit to data produces estimates of mechanism-specific ... ...

Abstract	Network models are used to study interconnected systems across many physical, biological, and social disciplines. Such models often assume a particular network-generating mechanism, which when fit to data produces estimates of mechanism-specific parameters that describe how systems function. For instance, a social network model might assume new individuals connect to others with probability proportional to their number of pre-existing connections ('preferential attachment'), and then estimate the disparity in interactions between famous and obscure individuals with similar qualifications. However, without a means of testing the relevance of the assumed mechanism, conclusions from such models could be misleading. Here we introduce a simple empirical approach which can mechanistically classify arbitrary network data. Our approach compares empirical networks to model networks from a user-provided candidate set of mechanisms, and classifies each network--with high accuracy--as originating from either one of the mechanisms or none of them. We tested 373 empirical networks against five of the most widely studied network mechanisms and found that most (228) were unlike any of these mechanisms. This raises the possibility that some empirical networks arise from mixtures of mechanisms. We show that mixtures are often unidentifiable because different mixtures can produce functionally equivalent networks. In such systems, which are governed by multiple mechanisms, our approach can still accurately predict out-of-sample functional properties. Comment: 5 pages, 2 figures, 2 ancillary files
Keywords	Computer Science - Social and Information Networks ; Computer Science - Machine Learning ; Statistics - Computation
Subject code	303
Publishing date	2020-12-21
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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