Forecasting the El Niño-Southern Oscillation (ENSO) has been a subject of vigorous research due to the important role of the phenomenon in climate dynamics and its worldwide socioeconomic impacts. Over the past decades, numerous models for ENSO prediction have been developed, among which statistical models approximating ENSO evolution by linear dynamics have received significant attention owing to their simplicity and comparable forecast skill to first-principles models at short lead times. Yet, due to highly nonlinear and chaotic dynamics (particularly during ENSO initiation), such models have limited skill for longer-term forecasts beyond half a year. To resolve this limitation, here we employ a new nonparametric statistical approach based on analog forecasting, called kernel analog forecasting (KAF), which avoids assumptions on the underlying dynamics through the use of nonlinear kernel methods for machine learning and dimension reduction of high-dimensional datasets. Through a rigorous connection with Koopman operator theory for dynamical systems, KAF yields statistically optimal predictions of future ENSO states as conditional expectations, given noisy and potentially incomplete data at forecast initialization. Here, using industrial-era Indo-Pacific sea surface temperature (SST) as training data, the method is shown to successfully predict the Niño 3.4 index in a 1998–2017 verification period out to a 10-month lead, which corresponds to an increase of 3–8 months (depending on the decade) over a benchmark linear inverse model (LIM), while significantly improving upon the ENSO predictability “spring barrier”. In particular, KAF successfully predicts the historic 2015/16 El Niño at initialization times as early as June 2015, which is comparable to the skill of current dynamical models. An analysis of a 1300-yr control integration of a comprehensive climate model (CCSM4) further demonstrates that the enhanced predictability afforded by KAF holds over potentially much longer leads, extending to 24 months versus 18 months in the benchmark LIM. Probabilistic forecasts for the occurrence of El Niño/La Niña events are also performed and assessed via information-theoretic metrics, showing an improvement of skill over LIM approaches, thus opening an avenue for environmental risk assessment relevant in a variety of contexts.
The world is facing new environmental challenges that may trigger the collapse of some social-ecological systems (SES). More extreme weather events may be much more common in the decades to come due to climate change. Although we have an idea of what climatic events to expect in each region, we know less about how SES can cope with these challenges. We study The Peruvian Piura Basin, which has been exposed to harsh environmental events associated with the El Niño Southern Oscillation (ENSO) for centuries. The Piura basin was home to the ancient Moche civilization, which collapsed due to a combination of factors, but strong El Niño events likely played a significant role. To analyze the resilience of The Piura Basin to flood events, we used as guidance the Robustness Framework and different propositions from prominent collapse theories to carry out a longitudinal study based on both primary and collected secondary data. We found that the Piura basin is very fragile based on almost all of the predictions of collapse theories (especially with respect to selfish elites, centralized governance, systems interconnection, anticipation capacity and sensitive dependence on resources), but the biggest strength is its growing stock of social capital. In small steps, user associations have been collectively working towards solutions for water conservation and public-infrastructure maintenance. There is a long way to go, but with the right policies to encourage the strengthening of these associations, the Piura basin could become more resilient to future El Niño events. This study also provides methodological and theoretical insights that can contribute to theory building for the resilience of SES.
more » « less- NSF-PAR ID:
- 10170921
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Environmental Research Letters
- Volume:
- 15
- Issue:
- 7
- ISSN:
- 1748-9326
- Page Range / eLocation ID:
- Article No. 075008
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract This paper synthesizes the contemporary challenges for the sustainability of the social-environmental system (SES) across a geographically, environmentally, and geopolitically diverse region—the Asian Drylands Belt (ADB). This region includes 18 political entities, covering 10.3% of global land area and 30% of total global drylands. At the present time, the ADB is confronted with a unique set of environmental and socioeconomic changes including water shortage-related environmental challenges and dramatic institutional changes since the collapse of the Union of Soviet Socialist Republics. The SES of the ADB is assessed using a conceptual framework rooted in the three pillars of sustainability science: social, economic, and ecological systems. The complex dynamics are explored with biophysical, socioeconomic, institutional, and local context-dependent mechanisms with a focus on institutions and land use and land cover change (LULCC) as important drivers of SES dynamics. This paper also discusses the following five pressing, practical challenges for the sustainability of the ADB SES: (a) reduced water quantity and quality under warming, drying, and escalating extreme events, (b) continued, if not intensifying, geopolitical conflicts, (c) volatile, uncertain, and shifting socioeconomic structures, (d) globalization and cross-country influences, and (e) intensification and shifts in LULCC. To meet the varied challenges across the region, place-based, context-dependent transdisciplinary approaches are needed to focus on the human-environment interactions within and between regional landscapes with explicit consideration of specific forcings and regulatory mechanisms. Future work focused on this region should also assess the role of the following mechanisms that may moderate SES dynamics: socioeconomic regulating mechanisms, biophysical regulating mechanisms, regional and national institutional regulating mechanisms, and localized institutional regulating mechanisms.more » « less
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Abstract Infectious disease emergence has increased significantly over the last 30 years, with mass mortality events (MMEs) associated with epizootics becoming increasingly common. Factors influencing these events have been widely studied in terrestrial systems, but remain relatively unexplored in marine mammals. Infectious disease‐induced MMEs (ID MMEs) have not been reported ubiquitously among marine mammal species, indicating that intrinsic (host) and/or extrinsic (environmental) ecological factors may influence this heterogeneity. We assess the occurrence of ID MMEs (1955–2018) across extant marine mammals (
n = 129) in relation to key life‐history characteristics (sociality, trophic level, habitat breadth) and environmental variables (season, sea surface temperature [SST] anomalies, El Niño occurrence). Our results show that ID MMEs have been reported in 14% of marine mammal species (95% CI 9%–21%), with 72% (n = 36; 95% CI 56%–84%) of these events caused predominantly by viruses, primarily morbillivirus and influenza A. Bacterial pathogens caused 25% (95% CI 14%–41%) of MMEs, with only one being the result of a protozoan pathogen. Overall, virus‐induced MMEs involved a greater number of fatalities per event compared to other pathogens. No association was detected between the occurrence of ID MMEs and host characteristics, such as sociality or trophic level, but ID MMEs did occur more frequently in semiaquatic species (pinnipeds) compared to obligate ocean dwellers (cetaceans; χ2 = 9.6,p = .002). In contrast, extrinsic factors significantly influenced ID MMEs, with seasonality linked to frequency (χ2 = 19.85,p = .0002) and severity of these events, and global yearly SST anomalies positively correlated with their temporal occurrence (Z = 3.43,p = 2.7e‐04). No significant association was identified between El Niño and ID MME occurrence (Z = 0.28,p = .81). With climate change forecasted to increase SSTs and the frequency of extreme seasonal weather events, epizootics causing MMEs are likely to intensify with significant consequences for marine mammal survival. -
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Abstract Aim Land ownership norms are well documented and play a central role in social–ecological systems. Yet only recently has the spatial and temporal distribution of land ownership been examined using biogeographical and evolutionary approaches. We incorporate biogeographical and evolutionary modelling to test associations between land ownership and environmental, subsistence and cultural contact predictors.
Location Africa.
Taxon Bantu and Bantoid ethnolinguistic groups (73 societies).
Methods Based on ethnographies for 73 societies, we coded land ownership norms as none, group, kin or individual. We paired these data with language phylogenies, and measured phylogenetic and geographical signal and modelled alternative evolutionary trajectories using maximum likelihood methods. We tested the influence of environmental, subsistence and cultural predictors on spatial variation in land ownership, using a multi‐model inference approach based on logistic regression.
Results Bantu land ownership norms likely evolved on a unilinear trajectory (i.e. societies progress or regress along a series of ownership types), but not one requiring consistent increase in exclusivity (i.e. restrictions towards ownership by smaller groups) as suggested by prior theory. Our biogeographical analyses suggest land ownership is more likely where neighbours also own land and resource productivity is predictable. Reliance on agriculture has relatively small effect sizes and low importance in the model.
Main Conclusions We find support for multiple evolutionary pathways. Lack of resolution may be due to localized horizontal transfer of norms consistent with the influence of neighbours we find from biogeographical analyses. We cannot rule out other untested mechanisms. Although long‐standing theories propose links between subsistence practices and land ownership, our results suggest subsistence plays only a modest role. Our results also support resource defensibility theory (i.e. land ownership is more likely where environmental productivity is predictable). Overall, we demonstrate the value of combining analytical approaches from evolution and biogeography to test hypotheses on the spatial and temporal variation of human cultural traits.
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