Regime Shifts Research Articles

Optimizing gas lift for enhanced recovery in the Asmari formation: a case study of Abu Ghirab field in Southeastern Iraq

The gas lift technique applies gas bubble injection into the vertical wells to raise production. Gas and liquid rates, shifts in flow regimes, and system equilibrium influence this process. This study explores the efficient implementation of gas lift techniques to maximize production from the Asmari Formation in the Abu Ghirab Field, southeastern Iraq, using a continuous gas lift for maximum production rate by PIPESIM TM software. The results of the gas lift design for the four wells (AGCS-33, 26, 28, and 36) show that the Vogel method provided the best results for the gas lift design, and faults and facies distribution impact the gas lift injection and oil production rates. These will become evident with wells AGCS-33 and 36 as their proximity to faults will increase oil production rates with a gas injection rate limit of 7 MMSCF/d. Conversely, for wells 26 and 28, the limit will marginally rise, starting at 5 MMSCF/d. In addition, the effect of gas lift is clearly in the middle western of the crest, which shows an increasing percentage of oil production of 136.6% at minimum rate and 198.5% at maximum for the well AGCS-26, 89.7% and 105.7% for the well AGCS-36. Wellhead pressure has a significant impact on gas-lift performance, and improving gas-lift efficiency can be accomplished using an electric control valve. The feasibility of implementing gas lift in the Asmari Formation depends on the water cut, well location, and water saturation distribution within the Formation.

Assessing the Impact of Anthropogenic and Climate Change on Spider Diversity in Garhwal Himalaya

The state of Uttarakhand in India was created in the year 2000 with Dehradun as its capital, prompting increased human activity in the Doon Valley and dramatic shifts in land use patterns. Spiders are good indicator species for habitat quality and they can offer insights into disturbances in habitat either due to anthropogenic activities or climate change phenomenon. To assess the impact of anthropogenic activity in the Doon Valley, we conducted a long-term study, comparing it with Uttarkashi District. The study revealed 31 species and 28 genera of spiders across 13 families in the Doon Valley, while Uttarkashi District exhibited 37 species and 31 genera across 17 families, including the rare Asian Tarantulas (Haplocosmia himalayana, Pocock, 1899), a member of the Theraphosidae family. Pholcidae and Salticidae were consistently found in both regions, with Araneidae predominating. Changes in species distribution, influenced by anthropogenic activities and climate variations, indicate ongoing ecosystem shifts.

The rapid prosperity of China’s Pearl River Delta from the perspective of social–ecological coupling: implications for sustainable management

Systems theory and complex science, especially knowledge of social–ecological interdependencies, are urgently needed in planning and decision-making on sustainable urban development due to the intensification of the contradiction between human development and nature conservation. Here, we present an analytical framework, the “social–ecological coupling trajectory”, that integrates the social–ecological coupling, multi-stability, causal feedbacks and sustainable management through understanding the evolution of the urban social–ecological system (SES). This framework is applied to a typical urban SES, i.e., China’s rapidly prosperous Pearl River Delta (PRD). Our results indicate that the SES evolution in the PRD is a phased process, which is accompanied by a continuous decline in major ecosystem services (ESs) and the disproportionate decline of ecological management performance. Further analysis shows that social and economic policies have a decisive role in driving the evolution of SES and the cumulative effect of sustained human interference is directly linked to the disproportionate increase in sustainability challenges. The findings of critical slowing down and evolution patterns of SES in the PRD may provide evidence for the threshold recognition and regime shift prediction in SES. In sum, this study expands the theoretical framework and empirical knowledge of SES evolution and provides a pathway for sustainable development of regions seeking prosperity from the social–ecological coupling perspective.

Displacement residuals reveal landslide regime shifts

AbstractDespite significant progress in the development of advanced technologies for detecting and monitoring unstable slopes, accurately predicting catastrophic landslides remains a challenge. To tackle this challenge, our research integrates advanced prediction models and granular systems theory to provide insights into regime shifts within slow-moving deep-seated landslide dynamics. Our approach is designed to discern exceptional departures from historical landslide dynamics. The approach leverages the “group dynamics,” crucial for identifying precursory failure indicators, according to the generic dynamics of the precursory failure regime in granular systems. We select three different monitored slow-moving landslides as test cases. We employ an error correction cointegration vector autoregression model together with an exogenous regressor to encode historical spatiotemporal landslide dynamics and predict displacement at multiple locations by considering the historical landslide motion and relationship with external triggers. Displacement residuals are obtained by computing the difference between predicted and measured displacement for a given historical calibration time window. Threshold values for the displacement residuals are determined by analyzing the historical distribution of these residuals. Lastly, persistence in time of the threshold exceedance and the number of monitoring points that exceed the threshold at the same time are considered to encode the group dynamics. This approach offers several advantages, including the effective identification of critical regime shifts, adaptability, and transferability, and it introduces regime shift information into local landslide early warning systems. This approach can enhance confidence in the resultant alert, particularly when integrated with conventional alert systems, thereby improving the reliability of landslide warning systems.

Enhanced interaction between ENSO and the South Atlantic subtropical dipole over the past four decades

AbstractThis study investigates the relationship between sea surface temperature (SST) anomalies in the subtropical Atlantic Ocean, as represented by the Southern Atlantic subtropical dipole (SASD), and SST anomalies in the tropical Pacific Ocean, identified by the El Niño‐Southern Oscillation (ENSO). Contrary to the previously held notion of a weak relationship between SASD and ENSO as suggested by earlier literature, our analysis reveals a substantial inverse correlation between the two. This correlation exhibits significant multi‐decadal variability, which has notably intensified over the most recent two decades compared with the preceding two decades. This intensification in the SASD–ENSO inverse correlation may be attributed to the shift in ENSO regime from predominance of eastern Pacific El Niño to central Pacific El Niño events around the turn of the century. This transition triggers wavetrains that propagate along different paths, consequently influencing the South Atlantic subtropical high and inducing alterations in anomalous SST patterns in the subtropical Atlantic Ocean. These findings advance our comprehension of the interactions between South Atlantic and Pacific SST variations, which strongly influence rainfall patterns, particularly in South America and southern Africa. Understanding such teleconnection holds promise for improving sub‐seasonal to seasonal precipitation predictions in these regions.

Decadal changes in the Sea of Marmara indicate degraded ecosystem conditions and unsustainable fisheries

Globally, all marine ecosystems are under pressure by anthropogenic stressors. However, semi-enclosed seas are at a greater risk of degradation due to their limited connectivity to open seas. This leads to a greater accumulation of pollutants and abrupt regime shifts triggered by unsustainable exploitation of living resources, as ecosystems exhibit low degrees of redundancy and more frequent large-scale episodic events such as harmful algal blooms. The Sea of Marmara is a semi-enclosed marine region that has been subjected to various anthropogenic stressors since the 1990s. Recently, local and governmental authorities have employed basin-wide ecosystem management plans to control and manage point and nonpoint (diffuse) sources of pollutants. However, the management of fisheries in relation to the dynamics of the Sea of Marmara food web has attracted less attention from policymakers, even though fisheries exploitation is one of the most significant anthropogenic pressures. In this study, we capitalized on a previous static ecosystem model of the Sea of Marmara by revising and extending it to simulate the changes between 1990 and 2020. We delineated the temporal dynamics and regime shifts in the food web in terms of ecosystem structure and function by using ecological indicators and developed quantitative management advice for its fisheries. The results showed that the ecosystem has experienced three regimes since 1990, with regime shifts occurring with the onset of the 2000s and the mid 2010s. The first regime exhibited high diversity and material cycling, the second regime was characterized by low diversity and increased impact of fisheries, and the third regime culminated in a fished-down food web state. The analysis of fishery dynamics showed that the majority of harvested species were overexploited. We suggest that the implementation of quotas for exploited species should be considered an immediate solution to the unsustainable exploitation of fish stocks and can help restore ecosystem conditions.

Threshold ambiguity and sustainable resource management: A lab experiment

Overexploitation of ecosystems can cause drastic shifts to unfavourable states once ecosystems reach critical thresholds. Experimental studies have shown that the knowledge of such thresholds helps to foster sustainable resource management. However, warning resource users of a regime shift is difficult since knowledge about critical thresholds is often associated with considerable ambiguity. We conducted a continuous-time common pool resource lab experiment (N = 360; 90 groups of four participants) to assess how different levels of ambiguous information regarding the location of thresholds affect cooperation amongst resource users. Results show that groups informed only of the threshold's existence cooperate similarly to those provided with a range for the threshold, indicating that ambiguity levels do not significantly influence cooperation amongst resource users for sustaining resources at optimal levels. In addition, we analysed treatment differences once the ambiguity about the threshold location is resolved. We do not find lasting impacts of different ambiguity levels on the likelihood of avoiding crossing the threshold once the threshold location is communicated with certainty. Overall, our results suggest that the scope of providing imprecise threshold information which reduces the level of ambiguity may be limited in fostering more sustainable natural resource management.

Assessing spirlin Alburnoides bipunctatus (Bloch, 1782) as an early indicator of climate change and anthropogenic stressors using ecological modeling and machine learning

Combining single-species ecological modeling with advanced machine learning to investigate the long-term population dynamics of the rheophilic fish spirlin offers a powerful approach to understanding environmental changes and climate shifts in aquatic ecosystems. A new ESHIPPOClim model was developed by integrating climate change assessment into the ESHIPPO model. The model identifies spirlin as a potential early indicator of environmental changes, highlighting the interactive effects of climate change and anthropogenic stressors on fish populations and freshwater ecosystems. The ESHIPPOClim model reveals that 28.57 % of the spirlin's data indicates high resilience and ecological responsiveness, with 34.92 % showing medium-high adaptability, suggesting its substantial ability to withstand environmental stressors. With 36.51 % of the data in medium level and no data in the low category, spirlin may serve as a sentinel species, providing early warnings of environmental stressors before they severely impact other species or ecosystems. The results of uniform manifold approximation and projection (UMAP) and a decision tree show that pollution has the highest impact on the population dynamics of spirlin, followed by annual water temperature, overexploitation, and invasive species. Despite the obtained key drivers, higher abundance, dominance, and frequency values were detected in habitats with higher HIPPO stressors and climate change effects. Integrating state-of-the-art machine learning models has enhanced the predictive power of the ESHIPPOClim model, achieving approximately 90 % accuracy in identifying spirlin as an early indicator of climate change and anthropogenic stressors. The ESHIPPOClim model offers a holistic approach with broad practical applications using a simplified three-point scale, adaptable to various fish species, communities, and regions. The ecological modeling supported with advanced machine learning could serve as a foundation for rapid and cost-effective management of aquatic ecosystems, revealing the adaptability potential of fish species, which is crucial in rapidly changing environments.

Measuring mobility resilience with network-based simulations of flow dynamics under extreme events

Extreme events disrupt routine mobility patterns and affect citizens’ daily lives. Current disaster resilience measurements often rely on static proxies or topological analyses, failing to capture the dynamic interactions between functional organization and transportation systems, as well as critical regime shifts within the resilience process. Using big data sourced from mobile-devices, this study delineates the evolving nature of various response flows during disasters with different intensities, depicts curves illustrating shifts in maintained traffic flow proportion, maps mobility resilience heterogeneity, and examines the spatial ramifications of flow redistribution. Our findings revealed that even minor incidents prompt city-wide flow reorganization. Clusters of low resilience with gradients are caused by mobility structures rather than distance from the disaster. Arterial roads uphold connectivity for long-distance journeys, whereas branch roads facilitate shorter trips but remain vulnerable to traffic surges. Based on these findings, strategies for preparedness and emergency planning under road failure conditions are evidence-based.

Rising temperatures, falling fisheries: causes and consequences of crossing the tipping point in a small-pelagic community

Global change has profound effects on marine species, communities, and ecosystems. Among these impacts, small pelagics have emerged as valuable indicators for detecting regime shifts in fish stocks. They exhibit swift responses to changes in ocean variables, including decreased abundances, accelerated juvenile growth rates, early maturation, and reduced adult sizes in warm waters. However, each pelagic species occupies a unique local ecological niche, that reflects the sum of all environmental conditions. Consequently, their responses to environmental changes manifest in distinct ways. We explore here how global change affects small pelagics in the Madeira Archipelago (NE Atlantic Ocean) at (i) community level, by studying the effects of climate change over a 40-year (1980–2019) period on small pelagic landings, and (ii) population level, by studying the effects on the life-history traits of the two most abundant species, Scomber colias and Trachurus picturatus. Our study demonstrated that anomalies in the Sea Surface Temperature and the North Atlantic Oscillation caused a regime shift within the small pelagic community. Both environmental predictors explained 88.9% of the community landings oscillations. S. colias appears to exhibit a relatively more favorable adaptive response to climate change compared to T. picturatus. Understanding the species-specific ecological responses of small pelagic fish to global change is crucial for effective management and conservation efforts in the face of ongoing environmental scenarios.Graphical abstract

Ecosystem based approach to assess the impact of invasive or expanding species in the lower Saône River

The spread of invasive alien species is identified as one of the most important threats to freshwater ecosystems as they can modify their trophic structure, biomass and flows. The lower Saône River is one of the most biologically productive waterways in France. It has been in strong interaction with a wide range of human activities such as fisheries for at least three millennia. To implement an ecosystem based approach, an Ecopath static trophic model was used for the first time in this river to quantify the role of three invasive or expanding species over two contrasted periods (1988–1993 and 1994–2005). The parameters used in the model integrate on the one hand catch data from fishers (professional, amateur fishing gear users, and anglers), and on the other hand the available literature data on species biomass, diet and the expert assessments of scientists and managers. Species such as the filtering Asian clam Corbicula fluminea may explain the triggering of the ecosystem shift towards a functioning where summer phytoplankton blooms are rarer. In the high trophic levels, the great cormorant Phalacrocorax carbo appears to have low trophic impact while the development of a large population of European catfish Silurus glanis has a strong effect, maintaining important trophic flows in the ecosystem in substitution for the decrease in angling landings.

The critical dynamics of hippocampal seizures

Epilepsy is defined by the abrupt emergence of harmful seizures, but the nature of these regime shifts remains enigmatic. From the perspective of dynamical systems theory, such critical transitions occur upon inconspicuous perturbations in highly interconnected systems and can be modeled as mathematical bifurcations between alternative regimes. The predictability of critical transitions represents a major challenge, but the theory predicts the appearance of subtle dynamical signatures on the verge of instability. Whether such dynamical signatures can be measured before impending seizures remains uncertain. Here, we verified that predictions on bifurcations applied to the onset of hippocampal seizures, providing concordant results from in silico modeling, optogenetics experiments in male mice and intracranial EEG recordings in human patients with epilepsy. Leveraging pharmacological control over neural excitability, we showed that the boundary between physiological excitability and seizures can be inferred from dynamical signatures passively recorded or actively probed in hippocampal circuits. Of importance for the design of future neurotechnologies, active probing surpassed passive recording to decode underlying levels of neural excitability, notably when assessed from a network of propagating neural responses. Our findings provide a promising approach for predicting and preventing seizures, based on a sound understanding of their dynamics.

Poor performance of regime shift detection methods in marine ecosystems

Abstract Regime shifts have been reported as ubiquitous features across the world’s oceans. Many regime shift detection methods are available, but their performance is rarely evaluated, and the supporting evidence for regime shifts may be thin because of the nature of marine ecological time series that are often short, autocorrelated, and uncertain. In the Norwegian Sea, a regime shift has been reported to have occurred in the mid-2000s, with simultaneous changes in oceanography, plankton, and fish. Here, we evaluate the evidence for this regime shift using four commonly used regime shift detection methods (Strucchange, STARS, EnvCpt, and Chronological Clustering) on 32 annual time series that describe the main components of the Norwegian Sea ecosystem, from hydrography and primary production up to fish population metrics. We quantify the performance of each method by measuring its false-positive rate, i.e. the proportion of times the method detects a regime shift that was not present in simulated control time series. Our results show that all methods have high to very high false-positive rates. This challenges the evidence for a regime shift in the Norwegian Sea and questions earlier reviews of regime shifts across the world’s oceans.

Long-Term Cumulative Effects of Wildfires on Soil-Vegetation Dynamics in the “Baixa Limia–Serra do Xurés” Natural Park

Wildfires are recognized as major contributors to forest loss and soil degradation on a global scale. Understanding the cumulative effects of fire regimes on forest ecosystems and soil dynamics necessitates a deeper exploration of wildfire-vegetation-soil interactions over the long term. This study delves into the wildfire-landscape dynamics within the “Baixa Limia Serra do Xurés” Natural Park, a region prone to fires in Galicia, Spain. By analyzing available statistical and remote sensing data, we identified significant shifts in fire regimes and landscape dynamics between the periods of 2000–2010 and 2010–2020. Our findings indicate a potential extension of the fire season, reflecting the impacts of climate change. Despite improvements in firefighting capabilities, the occurrence of large fires is on the rise in the Natural Park, underscoring the need for proactive management strategies in such areas. Notably, significant fire events in 2011, 2016, 2017, and 2020 extensively affected wooded areas, constituting the majority of the burned area. Shrubs and forests emerged as particularly vulnerable, with varying degrees of burn severity influencing post-fire vegetation recovery rates. While shrublands expanded their coverage between 2000 and 2010, rocky areas with sparse vegetation showed an increase over the subsequent decade (2010–2020), indicating soil degradation and potential desertification in areas affected by recurrent and severe fires, especially within zones designated for the highest levels of protection (with fire rotation periods of less than 1 year). In conclusion, this study provides valuable insights into the impacts of wildfires, changes in land cover, and post-fire soil-vegetation dynamics, which can inform management and conservation efforts in fire-prone mountainous regions. Leveraging advanced remote sensing techniques enables the monitoring of cumulative soil degradation resulting from repeated wildfires over extended periods.

Changing patterns of inclusion into old age protection in the Ottoman Empire and the Republic of Turkey (1865–2020)

Who is protected by social security? This article explores this question by tracing the chronological sequence of inclusion into old age protection in the Ottoman Empire and Turkey. The focus lies on how legislation defines the groups that are covered by old age pensions. We argue that the old age protection system transformed from being aimed at protecting people working for the state, towards covering diverse societal groups and aspiring to universal social protection. The Ottoman Empire institutionalised its centuries-old system of protection of elderly state employees surprisingly early, through pension funds in the late nineteenth century. The Republic of Turkey maintained this approach for several decades, pointing to continuities between the late Ottoman Empire and the early Republic. From the mid-twentieth century onwards, the state transformed old age protection with new schemes for mostly employment-based groups. The analysis reveals intriguing parallels between political inclusion and inclusion in old age protection, with key expansions in the scope of old age protection mirroring shifts in the political regime.

Both nutrients and macrophytes regulate organic carbon burial: Insights from high-resolution spatiotemporal records of a large shallow lake (Baiyangdian) in eastern China

Both ecological regime shifts and carbon cycling in lakes have been the subject of global debates in recent years. However, the direct linkage between them is poorly understood. Lake Baiyangdian, a representative large shallow lake with the coexistence of a macrophyte-dominated area (MDA) and an algae-dominated area (ADA) in eastern China, allowing better understanding of the relationship between regime shifts and organic carbon (OC) burial in lakes. On the basis of Bayesian isotopic mixing modelling of C/N ratios and δ13C values, the sediment OC is primarily of autochthonous origin. The mean OC burial rate (OCBR) was 39 g C m−2 yr−1 before eutrophication occurred in 1990 and increased approximately 2.7-fold to 106 g C m−2 yr−1 after eutrophication. Partial least squares path modelling revealed that this change can be largely attributed to enhanced primary productivity and rapid burial as a result of intensified human perturbation. In terms of spatial patterns, the OCBR was greater in the MDA than in the ADA, which may be related to the different burial and mineralization processes of debris from macrophytes and algae. It then deduced that a decrease in the OCBR and an increase in the mineralization rate might have occurred after a shift from a macrophyte-dominated state to an algae-dominated state. Our findings highlight that eutrophication generally increases OC burial by enhancing lake primary productivity. However, once nutrient levels reach a critical range, lake ecosystems may shift from a macrophyte-dominated state to an algae-dominated state, which can lead to a significant reduction in the carbon burial capacity of lakes. Therefore, more attention should be given to avoiding shifts in eutrophic lakes, as such shifts can alter carbon cycling.

Growth, poverty trap and escape

The well-known Solow growth model is the workhorse model of the theory of economic growth, which studies capital accumulation in a model economy as a function of time with capital stock, labour and technology-based production as the basic ingredients. The capital is assumed to be in the form of manufacturing equipment and materials. Two important parameters of the model are: the saving fraction s of the output of a production function and the technology efficiency parameter A , appearing in the production function. The saved fraction of the output is fully invested in the generation of new capital and the rest is consumed. The capital stock also depreciates as a function of time due to the wearing out of old capital and the increase in the size of the labour population. We propose a stochastic Solow growth model assuming the saving fraction to be a sigmoidal function of the per capita capital kp . We derive analytically the steady state probability distribution P(kp) and demonstrate the existence of a poverty trap, of central concern in development economics. In a parameter regime, P(kp) is bimodal with the twin peaks corresponding to states of poverty and well-being, respectively. The associated potential landscape has two valleys with fluctuation-driven transitions between them. The mean exit times from the valleys are computed and one finds that the escape from a poverty trap is more favourable at higher values of A. We identify a critical value of Ac below (above) which the state of poverty (well-being) dominates and propose two early signatures of the regime shift occurring at Ac . The economic model, with conceptual foundations in nonlinear dynamics and statistical mechanics, shares universal features with dynamical models from diverse disciplines like ecology and cell biology.

Beyond resilience: Responses to changing climate and disturbance regimes in temperate forest landscapes across the Northern Hemisphere.

Climate change has profound impacts on forest ecosystem dynamics and could lead to the emergence of novel ecosystems via changes in species composition, forest structure, and potentially a complete loss of tree cover. Disturbances fundamentally shape those dynamics: the prevailing disturbance regime of a region determines the inherent variability of a system, and its climate-mediated change could accelerate forest transformation. We used the individual-based forest landscape and disturbance model iLand to investigate the resilience of three protected temperate forest landscapes on three continents-selected to represent a gradient from low to high disturbance activity-to changing climate and disturbance regimes. In scenarios of sustained strong global warming, natural disturbances increased across all landscapes regardless of projected changes in precipitation (up to a sevenfold increase in disturbance rate over the 180-year simulation period). Forests in landscapes with historically high disturbance activity had a higher chance of remaining resilient in the future, retaining their structure and composition within the range of variability inherent to the system. However, the risk of regime shift and forest loss was also highest in these systems, suggesting forests may be vulnerable to abrupt change beyond a threshold of increasing disturbance activity. Resilience generally decreased with increasing severity of climate change. Novelty in tree species composition was more common than novelty in forest structure, especially under dry climate scenarios. Forests close to the upper tree line experienced high novelty in structure across all three study systems. Our results highlight common patterns and processes of forest change, while also underlining the diverse and context-specific responses of temperate forest landscapes to climate change. Understanding past and future disturbance regimes can anticipate the magnitude and direction of forest change. Yet, even across a broad gradient of disturbance activity, we conclude that climate change mitigation is the most effective means of maintaining forest resilience.

Assessing four decades of fire behavior dynamics in the Cerrado biome (1985 to 2022)

BackgroundFire significantly transforms ecology and landscapes worldwide, impacting carbon cycling, species interactions, and ecosystem functions. In the Brazilian Cerrado, a fire-dependent savanna, the interaction between fire, society, and the environment is evident. Given that wildfires significantly contribute to greenhouse gas emissions, our study aimed to analyze four decades of burned area data to understand changes in fire dynamics, using Collection 2 of annual MapBiomas Fire maps (1985 to 2022). Our study examined spatiotemporal patterns, fire recurrence, fire distribution across land uses, temporal changes in fire scar size, burned area variations across ecoregions, and their correlation with farming areas.ResultsFrom 1985 to 2022, fire impacted 40% (792,204 km2) of the Cerrado biome, with 63% burning more than once. Natural vegetation was the most affected, primarily due to human-driven ignition during the dry season. A noticeable trend of later peaks in fire activity, concentrated towards the end of the dry season, along with an increase in patch size over time, characterized a clear shift in the Cerrado fire regime. Recently, the MATOPIBA region and the northern biome exhibited significant fire clusters, with burned areas rising alongside farming expansion. The ecoregion-based analysis identified fire hotspots, with the "Bananal" ecoregion, the largest wetland area in the biome, exhibiting increased fire recurrence and larger patch size over time.ConclusionsOur four-decade analysis of fire dynamics in the Cerrado revealed human-induced changes in the fire regime, originally shifting from July to September to a new fire season from August to October. This shift poses several environmental threats given their overlap with the driest months of the year. This study improved our understanding of changes in fire patterns and their impacts on each ecoregion and land use. Wetlands experienced the highest relative burned area, highlighting their ecological importance and increased vulnerability. In the southern Cerrado, where farming is established and natural vegetation more fragmented, fire events tend to decrease; while in the north, with recent farming expansion, fire susceptibility rises. Conservation-oriented strategies, like the Brazilian Integrated Fire Management (MIF), are crucial for mitigating impacts while enhancing the Cerrado’s resilience to climate change.

Climate variations in eastern Hudson bay over the past 3000 years

Palynological analyses of the marine sediment core AMD0509-20 collected north of Whapmagoostui-Kuujjuarapik in Nunavik were performed to investigate past changes in climate and sea-surface conditions based on pollen and spores and dinoflagellate cysts, respectively. Our results show relatively warm sea-surface temperatures before 2600 BP, about 2 °C higher than at present in summer, in addition to higher salinity suggesting relatively low freshwater inputs, thus low precipitation over the watershed. After 2400 years BP, an abrupt drop in sea-surface temperatures was recorded, followed by a decrease in salinity particularly pronounced until ∼2000 years BP. After 1600 years BP, summer sea-surface temperatures and salinity stabilized around current values. The changes recorded in surface waters during the late Holocene can be associated with a regional shift in the hydroclimatic regime that led to a gradual decline of spruce (Picea) in pollen assemblages.