Ten facts about land systems for sustainability

Proceedings of the National Academy of Sciences, Journal Year: 2022, Volume and Issue: 119(7)

Published: Feb. 7, 2022

Land use is central to addressing sustainability issues, including biodiversity conservation, climate change, food security, poverty alleviation, and sustainable energy. In this paper, we synthesize knowledge accumulated in land system science, the integrated study of terrestrial social-ecological systems, into 10 hard truths that have strong, general, empirical support. These facts help explain challenges achieving thus also point toward solutions. The are as follows: 1) Meanings values socially constructed contested; 2) systems exhibit complex behaviors with abrupt, hard-to-predict changes; 3) irreversible changes path dependence common features systems; 4) some uses a small footprint but very large impacts; 5) drivers impacts land-use change globally interconnected spill over distant locations; 6) humanity lives on used planet where all provides benefits societies; 7) usually entails trade-offs between different benefits—"win–wins" rare; 8) tenure claims often unclear, overlapping, 9) burdens from unequally distributed; 10) users multiple, sometimes conflicting, ideas what social environmental justice entails. implications for governance, do not provide fixed answers. Instead they constitute set core principles which can guide scientists, policy makers, practitioners meeting use.

Language: Английский

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Placing Brazil's grasslands and savannas on the map of science and conservation

Perspectives in Plant Ecology Evolution and Systematics, Journal Year: 2022, Volume and Issue: 56, P. 125687 - 125687

Published: June 4, 2022

Language: Английский

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Human–environment interactions in population and ecosystem health

Proceedings of the National Academy of Sciences, Journal Year: 2016, Volume and Issue: 113(51), P. 14502 - 14506

Published: Dec. 8, 2016

As the global human population continues to grow, so too does our impact on environment. The ingenuity with which species has harnessed natural resources fulfill needs is dazzling. Even as we tighten grip environment, however, escalating extent of anthropogenic actions destabilizes long-standing ecological balances (1, 2). dangers mining, refining, and fossil fuel consumption now extend beyond occupational or proximate risks climate change (3). Among a plethora environmental problems, extreme events are intensifying (4, 5). Storms, droughts, floods cause direct destruction, but also have pervasive repercussions food security, infectious disease transmission, economic stability that take their toll for many years. For example, within weeks catastrophic wind flood damage from 2016 Hurricane Matthew in Haiti, there was dramatic surge cholera, among other devastating (6, 7). In world where 1% possesses 50% wealth (8), those worst affected by climatic aftermath least able rebound. Compounding disasters, progressively more intimate interactions fragmented environments (9) given rise an era emergence re-emergence at unprecedented rates, exemplified recent outbreaks Ebola Zika viruses. Furthermore, globalization includes airline travel over eight million people every day enabled such disseminate rapidly pose threat far areas origin (10). Addressing these challenges requires understanding coupled human–environment dynamics, whereby activity modifies system (often detrimentally), resulting then humans. turn, impacts can potentially spur shift toward protection restoration. … [↵][1]1To whom correspondence should be addressed. Email: alison.galvani{at}yale.edu. [1]: #xref-corresp-1-1

Language: Английский

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Conditions for a Second Wave of COVID-19 Due to Interactions Between Disease Dynamics and Social Processes

Frontiers in Physics, Journal Year: 2020, Volume and Issue: 8

Published: Oct. 9, 2020

In May 2020, many jurisdictions around the world began lifting physical distancing restrictions against spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This gave rise to concerns about a possible second wave disease 2019 (COVID-19). These were imposed in response presence COVID-19 populations, usually with broad support affected populations. However, is also population accumulating socio-economic impacts restrictions, and expected increase number cases, turn. suggests that pandemic exemplifies coupled behaviour-disease system where dynamics social are locked mutual feedback loop. Here we develop minimal mathematical model interaction between for school workplace closure transmission SARS-CoV-2. We find occurs across range plausible input parameters governing epidemiological conditions, on account instabilities generated by interactions. The tends have higher peak than first when efficacy greater 40% basic reproduction R_0 less 2.4. Surprisingly, found lower value makes more likely, behavioural (although does not necessarily cause infections, total). conclude waves can be interpreted as outcome nonlinear interactions behaviour. suggest further development models exploring could help us better understand how conditions together determine pandemics unfold.

Language: Английский

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Charting pathways to climate change mitigation in a coupled socio-climate model

PLoS Computational Biology, Journal Year: 2019, Volume and Issue: 15(6), P. e1007000 - e1007000

Published: June 6, 2019

Geophysical models of climate change are becoming increasingly sophisticated, yet less effort is devoted to modelling the human systems causing and how two coupled. Here, we develop a simple socio-climate model by coupling an Earth system social dynamics model. We treat processes endogenously-emerging from rules governing individuals learn socially norms develop-as well as being influenced mitigation costs. Our goal gain qualitative insights into scenarios potential illustrate such can generate new research questions. find that learning rate strongly influential, point variation its value within empirically plausible ranges changes peak global temperature anomaly more than 1°C. Conversely, reinforce majority behaviour therefore may not provide help when most need it because they suppress early spread mitigative behaviour. Finally, exploring model's parameter space for cost suggests optimal intervention pathways mitigation. prioritising increase in first step, followed reduction costs provides efficient route reduced anomaly. conclude should be included ensemble used project change.

Language: Английский

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Climate adaptation of biodiversity conservation in managed forest landscapes

Conservation Biology, Journal Year: 2021, Volume and Issue: 36(3)

Published: Oct. 9, 2021

Abstract Conservation of biodiversity in managed forest landscapes needs to be complemented with new approaches given the threat from rapid climate change. Most frameworks for adaptation conservation change include two major strategies. The first is resistance strategy, which focuses on actions increase capacity species and communities resist second transformation strategy includes that ease a set are well adapted novel environmental conditions. We suggest number concrete policy makers managers can take. Under five tools introduced, including: identifying protecting refugia cold‐favored species; reducing effects drought by hydrological network; actively removing competitors when they threaten species. we three tools, enhancing conditions favored climate, but currently disfavored management, planting them at suitable sites outside their main range; increasing connectivity across landscape enhance expansion warm‐favored have become suitable. Finally, applying perspective simultaneously managing both retreating expanding different strategies (resistance transformation) should seen as complementary ways maintain rich future ecosystems.

Language: Английский

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Modelling coupled human–environment complexity for the future of the biosphere: strengths, gaps and promising directions

Philosophical Transactions of the Royal Society B Biological Sciences, Journal Year: 2022, Volume and Issue: 377(1857)

Published: June 27, 2022

Humans and the environment form a single complex system where humans not only influence ecosystems but also react to them. Despite this, there are far fewer coupled human–environment (CHES) mathematical models than of uncoupled ecosystems. We argue that these essential understand impacts social interventions their potential avoid catastrophic environmental events support sustainable trajectories on multi-decadal timescales. A brief history CHES modelling is presented, followed by review spanning recent systems including forests land use, coral reefs fishing climate change mitigation. The ability capture dynamic two-way feedback confers advantages, such as represent ecosystem dynamics more realistically at longer timescales, allowing insights cannot be generated using ecological models. discuss examples key from research. However, this strength brings with it challenges model complexity tractability, need for appropriate data parameterize validate Finally, we suggest opportunities improve sustainability in future research topics natural disturbances, structure, media data, discovery early warning signals. This article part theme issue ‘Ecological biosphere: next 30 years’.

Language: Английский

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Predicting discrete-time bifurcations with deep learning

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Oct. 10, 2023

Many natural and man-made systems are prone to critical transitions-abrupt potentially devastating changes in dynamics. Deep learning classifiers can provide an early warning signal for transitions by generic features of bifurcations from large simulated training data sets. So far, have only been trained predict continuous-time bifurcations, ignoring rich dynamics unique discrete-time bifurcations. Here, we train a deep classifier the five local codimension-one. We test on simulation models used physiology, economics ecology, as well experimental spontaneously beating chick-heart aggregates that undergo period-doubling bifurcation. The shows higher sensitivity specificity than commonly signals under wide range noise intensities rates approach It also predicts correct bifurcation most cases, with particularly high accuracy period-doubling, Neimark-Sacker fold tool prediction is still its nascence has potential transform way monitor transitions.

Language: Английский

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The impact of rare but severe vaccine adverse events on behaviour-disease dynamics: a network model

Scientific Reports, Journal Year: 2019, Volume and Issue: 9(1)

Published: May 9, 2019

Abstract The propagation of rumours about rare but severe adverse vaccination or infection events through social networks can strongly impact uptake. Here we model a coupled behaviour-disease system where individual risk perception regarding vaccines and are shaped by their personal experiences the others. Information either propagates network becomes available globally sources. Dynamics studied on range types. Individuals choose to vaccinate according information prevalence. We study ranging from common mild, rare. find that vaccine have asymmetric impacts. Vaccine (but not infection) may significantly prolong tail an outbreak. Similarly, introducing small event cause steep decline in coverage, especially scale-free networks. Global dissemination prevalence boosts coverage more than local dissemination. Taken together, these findings highlight dangers associated with rumour such as those exhibited online media, well benefits disseminating public health mass media.

Language: Английский

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Numerical performances based artificial neural networks to deal with the computer viruses spread on the complex networks

International Journal of Computer Mathematics, Journal Year: 2024, Volume and Issue: 101(3), P. 314 - 330

Published: March 3, 2024

This paper shows the outcomes of computer virus propagation (CVP) model, represented with susceptible, exposed, infected, quarantine and recovered computers (SEIRQ), classes based mathematical model using stochastic procedures. The systematic study CVP SEIRQ represents that equilibrium state virus-free is stable globally reproduction not more than one, while viral symmetry attractive globally. numerical performances are presented by computational framework on artificial neural networks (ANNs) together Levenberg-Marquardt backpropagation (LBMB) called as ANNs-LBMB. learning procedures via ANNs-LBMB for solving implemented to indorse statics testing, authorization, training. Thirteen numbers neurons data selection training 72%, testing 12% validation 16% selected solve model. For ANNs-LBMB, a dataset considered through Adams approach. accuracy reliability scheme values absolute error (AE) along observations transitions (STs), regression, mean square (MSE) histograms (EHs).

Language: Английский

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