Changes In Spatial Patterns Research Articles

Lockdowns, Community Mobility Patterns, and COVID-19: A Retrospective Analysis of Data from 16 Countries.

ObjectivesDuring the coronavirus disease 2019 (COVID-19) pandemic, countries around the world framed specific laws and imposed varying degrees of lockdowns to ensure the maintenance of physical distancing. Understanding changes in temporal and spatial mobility patterns may provide insights into the dynamics of this infectious disease. Therefore, we assessed the efficacy of lockdown measures in 16 countries worldwide by analyzing the relationship between community mobility patterns and the doubling time of COVID-19.MethodsWe performed a retrospective record-based analysis of population-level data on the doubling time for COVID-19 and community mobility. The doubling time for COVID-19 was calculated based on the laboratory-confirmed cases reported daily over the study period (from February 15 to May 2, 2020). Principal component analysis (PCA) of six mobility pattern-related variables was conducted. To explain the magnitude of the effect of mobility on the doubling time, a finite linear distributed lag model was fitted. The k-means clustering approach was employed to identify countries with similar patterns in the significant co-efficient of the mobility index, with the optimal number of clusters derived using Elbow’s method.ResultsThe countries analyzed had reduced mobility in commercial and social places. Reduced mobility had a significant and favorable association with the doubling time of COVID-19—specifically, the greater the mobility reduction, the longer the time taken for the COVID-19 cases to double.ConclusionsCOVID-19 lockdowns achieved the immediate objective of mobility reduction in countries with a high burden of cases.

Multi-Source Remote Sensing Data for Lake Change Detection in Xinjiang, China

Lake water resources in arid areas play an important role in regional resource and environmental management. Therefore, to master the dynamic changes in lake water resources in arid areas, the laser altimetry satellite and land resource satellite were used to interpret the changes in water level and the areas of alpine lakes and non-alpine lakes. The dynamic changes in the lake and their relationship with glacial meltwater, precipitation, and runoff of the lake basin were analyzed using the unary linear regression equation, the ratio of glacier area to lake area (G–L ratio), and the ratio of lake basin area to lake area (supply coefficient). The results were as follows: the changes in alpine lakes were closely related to the supply coefficient (basin/lake area ratio) but weakly related to the G–L ratio (glacier/lake area ratio). In addition, the spatial pattern of lake change was consistent with that of climate change. There was a strong correlation between the lake, precipitation, and temperature during the snowmelt period. Thus, it can be seen that the changes in the lake were caused by precipitation, glacial melt, snowmelt, and other multi-factors. Therefore, this study on the changes in water resources in different types of lakes and their influencing factors provides data support for water resources managers to evaluate the health and sustainable utilization of the ecological environment.

The Impact of Horizontal Resolution on Projected Sea-Level Rise Along US East Continental Shelf With the Community Earth System Model.

The Intergovernmental Panel on Climate Change Fifth Assessment Report lists sea‐level rise as one of the major future climate challenges. Based on pre‐industrial and historical‐and‐future climate simulations with the Community Earth System Model, we analyze the projected sea‐level rise in the Northwest Atlantic Ocean with two sets of simulations at different horizontal resolutions. Compared with observations, the low resolution (LR) model simulated Gulf Stream does not separate from the shore but flows northward along the entire coast, causing large biases in regional dynamic sea level (DSL). The high resolution (HR) model improves the Gulf Stream representation and reduces biases in regional DSL. Under the RCP8.5 future climate scenario, LR projects a DSL trend of 1.5–2 mm/yr along the northeast continental shelf (north of 40° N), which is 2–3 times the trend projected by HR. Along the southeast shelf (south of 35° N), HR projects a DSL trend of 0.5–1 mm/yr while the DSL trend in LR is statistically insignificant. The different spatial patterns of DSL changes are attributable to the different Gulf Stream reductions in response to a weakening Atlantic Meridional Overturning Circulation. Due to its poor representation of the Gulf Stream, LR projects larger (smaller) current decreases along the north (south) east continental slope compared to HR. This leads to larger (smaller) trends of DSL rise along the north (south) east shelf in LR than in HR. The results of this study suggest that the better resolved ocean circulations in HR can have significant impacts on regional DSL simulations and projections.

Investigating the response of leaf area index to droughts in southern African vegetation using observations and model simulations

Abstract. In many regions of the world, frequent and continual dry spells are exacerbating drought conditions, which have severe impacts on vegetation biomes. Vegetation in southern Africa is among the most affected by drought. Here, we assessed the spatiotemporal characteristics of meteorological drought in southern Africa using the standardized precipitation evapotranspiration index (SPEI) over a 30-year period (1982–2011). The severity and the effects of droughts on vegetation productiveness were examined at different drought timescales (1- to 24-month timescales). In this study, we characterized vegetation using the leaf area index (LAI) after evaluating its relationship with the normalized difference vegetation index (NDVI). Correlating the LAI with the SPEI, we found that the LAI responds strongly (r=0.6) to drought over the central and southeastern parts of the region, with weaker impacts (r<0.4) over parts of Madagascar, Angola, and the western parts of South Africa. Furthermore, the latitudinal distribution of LAI responses to drought indicates a similar temporal pattern but different magnitudes across timescales. The results of the study also showed that the seasonal response across different southern African biomes varies in magnitude and occurs mostly at shorter to intermediate timescales. The semi-desert biome strongly correlates (r=0.95) to drought as characterized by the SPEI at a 6-month timescale in the MAM (March–May; summer) season, while the tropical forest biome shows the weakest response (r=0.35) at a 6-month timescale in the DJF (December–February; hot and rainy) season. In addition, we found that the spatial pattern of change of LAI and SPEI are mostly similar during extremely dry and wet years, with the highest anomaly observed in the dry year of 1991, and we found different temporal variability in global and regional responses across different biomes. We also examined how well an ensemble of state-of-the-art dynamic global vegetation models (DGVMs) simulate the LAI and its response to drought. The spatial and seasonal response of the LAI to drought is mostly overestimated in the DGVM multimodel ensemble compared to the response calculated for the observation-based data. The correlation coefficient values for the multimodel ensemble are as high as 0.76 (annual) over South Africa and 0.98 in the MAM season over the temperate grassland biome. Furthermore, the DGVM model ensemble shows positive biases (3 months or longer) in the simulation of spatial distribution of drought timescales and overestimates the seasonal distribution timescales. The results of this study highlight the areas to target for further development of DGVMs and can be used to improve the models' capability in simulating the drought–vegetation relationship.

Spatial Pattern and Dynamic Change of Vegetation Greenness From 2001 to 2020 in Tibet, China.

Due to the cold climate and dramatically undulating altitude, the identification of dynamic vegetation trends and main drivers is essential to maintain the ecological balance in Tibet. The normalized difference vegetation index (NDVI), as the most commonly used greenness index, can effectively evaluate vegetation health and spatial patterns. MODIS-NDVI (Moderate-resolution Imaging Spectroradiometer-NDVI) data for Tibet from 2001 to 2020 were obtained and preprocessed on the Google Earth Engine (GEE) cloud platform. The Theil–Sen median method and Mann–Kendall test method were employed to investigate dynamic NDVI changes, and the Hurst exponent was used to predict future vegetation trends. In addition, the main drivers of NDVI changes were analyzed. The results indicated that (1) the vegetation NDVI in Tibet significantly increased from 2001 to 2020, and the annual average NDVI value fluctuated between 0.31 and 0.34 at an increase rate of 0.0007 year−1; (2) the vegetation improvement area accounted for the largest share of the study area at 56.6%, followed by stable unchanged and degraded areas, with proportions of 27.5 and 15.9%, respectively. The overall variation coefficient of the NDVI in Tibet was low, with a mean value of 0.13; (3) The mean value of the Hurst exponent was 0.53, and the area of continuously improving regions accounted for 41.2% of the study area, indicating that the vegetation change trend was continuous in most areas; (4) The NDVI in Tibet indicated a high degree of spatial agglomeration. However, there existed obvious differences in the spatial distribution of NDVI aggregation areas, and the aggregation types mainly included the high-high and low-low types; and (5) Precipitation and population growth significantly contributed to vegetation cover improvement in western Tibet. In addition, the use of the GEE to obtain remote sensing data combined with time-series data analysis provides the potential to quickly obtain large-scale vegetation change trends.

Spatial analysis of soil water depletion and biomass production in the transition zone between a Eucalyptus camaldulensis stand and a maize field in Ethiopia

Growth depressions in crops grown adjacent to Eucalyptus stands are often reported. The reasons for this observation range from competition for the resources light, nutrients and water to allelopathic effects. We investigated the effect of a Eucalyptus camaldulensis stand on soil water relations of an adjacent field of Zea mays. We used a geostatistical network spanning the Eucalyptus camaldulensis stand and the maize field. We measured changes in soil water storage in high spatial resolution (356 sample points over 3700 m²) in weekly to monthly intervals. In addition, an intensive root inventory of the Eucalyptus, covering a depth of 3.1 m, as well as aboveground biomass inventories in both land use forms were carried out. The majority of the fine root biomass of the Eucalyptus (70.5%) was found in the first 60 cm soil depth, which corresponded to the depth of the soil moisture measurements. Soil water depletion in the maize field was greatest up to 20 m from the forest edge, which coincided with the zone of least maize biomass production. In contrast, the water depletion across the first 6 m into the forest was 34% lower than in the border zone on the field side. Growth of the Eucalyptus was greatest at the forest edge, and the increased biomass production of the Eucalyptus balanced the decrease in maize production found in the first 20 m of the field. These changes in spatial growth patterns are explained by intense competition for soil water between the Eucalyptus and the maize.

The influence of city development on urban pedodiversity

The aim of this study was to use a pedodiversity index (PI) to assess changes in the spatial structure of soil cover in Inowrocław, Poland during the twentieth and twenty-first centuries. An original cartographic approach based on landscape metrics was implemented using GIS techniques and statistical calculations. Based on maps of urban soil complexes and pedodiversity, it was revealed that land and soil cover changes in two studied periods (1934–1978 and 1978–2016) significantly affected pedodiversity in the city. In general, the spatio-temporal increase of the pedodiversity index was observed. The percentage of highest values of the PI ranged from 15.9% in 1934, 17.3% in 1978 to 20.9% in 2016. We revealed that pedodiversity index (PI) values are highly spatially and temporally variable and are associated with urban development and changes in the city’s internal structure. The applied approach allowed for the identification of both spatial patterns of changes in soil cover that closely reflect the successive stages of the city's development, and problem areas that require revitalization and the implementation of the principles of sustainable development. Therefore, the proposed method can be recommended for landscape monitoring and in determining ecosystem services in urban and landscape planning, and environmental management.

Simulated sea levels during 1948–2009 in a global ocean-sea ice model for OMIP

This paper assesses the ability of the State Key Laboratory of Atmospheric Science and Geophysical Fluid Dynamics of the Institute of Atmospheric Physics (LASG/IAP) Climate System Ocean Model version 3 (LICOM3) to simulate sea levels. For the time series of global changes, most of the global mean steric sea level (SSL) changes were dominated by thermosteric sea level (TSSL) changes in the upper 700 m, with a relatively small contribution from halosteric sea level (HSSL). LICOM3 can reproduce the observed dynamic sea level (DSL) in most regions to reflect the spatial patterns of regional changes. Deviations between LICOM3 and observations were mainly concentrated in the western boundary current and the tropical eastern Pacific. The departure in the western boundary current was primarily related to the model resolution. LICOM3 could not depict DSL changes in the high latitudes where the mesoscale eddies were active. The excessive negative trend in the tropical eastern Pacific was mainly caused by the trend error in the CORE-II forcing products. For the sea level variability, the analysis results of different DSL periods showed that the LICOM3 model could simulate interannual and decadal variability and the satellite altimeter period trend. At least 50 years of data were used to separate the decadal variability and long-term trend. The decadal variability had no significant effect on the 50-year long-term trend change in the DSL in the tropical western Pacific.Analysis of sea level component contributions showed that the changes in global time series, spatial patterns, and sea level variability mainly resulted from the change in TSSL. The TSSL changes in the upper 700 m could roughly reflect the TSSL changes for the whole depth, except for the North Atlantic and the Southern Ocean. In the Atlantic, the contribution of HSSL was comparable to and compensated by TSSL. When compared with reanalysis, the simulation generated differences in the Southern Ocean and North Atlantic. The linear trend of TSSL simulated by LICOM3 was much stronger than that simulated by reanalysis. The deviation of the Southern Ocean may be related to the CORE-II forcing product. The lack of observations in the Southern Ocean led to the uncertainty of the CORE-II forcing product.

Regional Selectivity of Neuromelanin Changes in the Substantia Nigra in Atypical Parkinsonism.

Neurodegeneration in the substantia nigra pars compacta (SNc) in parkinsonian syndromes may affect the nigral territories differently. The objective of this study was to investigate the regional selectivity of neurodegenerative changes in the SNc in patients with Parkinson's disease (PD) and atypical parkinsonism using neuromelanin-sensitive magnetic resonance imaging (MRI). A total of 22 healthy controls (HC), 38 patients with PD, 22 patients with progressive supranuclear palsy (PSP), 20 patients with multiple system atrophy (MSA, 13 with the parkinsonian variant, 7 with the cerebellar variant), 7 patients with dementia with Lewy body (DLB), and 4 patients with corticobasal syndrome were analyzed. volume and signal-to-noise ratio (SNR) values of the SNc were derived from neuromelanin-sensitive MRI in the whole SNc. Analysis of signal changes was performed in the sensorimotor, associative, and limbic territories of the SNc. SNc volume and corrected volume were significantly reduced in PD, PSP, and MSA versus HC. Patients with PSP had lower volume, corrected volume, SNR, and contrast-to-noise ratio than HC and patients with PD and MSA. Patients with PSP had greater SNR reduction in the associative region than HC and patients with PD and MSA. Patients with PD had reduced SNR in the sensorimotor territory, unlike patients with PSP. Patients with MSA did not differ from patients with PD. This study provides the first MRI comparison of the topography of neuromelanin changes in parkinsonism. The spatial pattern of changes differed between PSP and synucleinopathies. These nigral topographical differences are consistent with the topography of the extranigral involvement in parkinsonian syndromes. © 2022 International Parkinson and Movement Disorder Society.

Temporal and Spatial Coupling Characteristics of Tourism and Urbanization with Mechanism of High-Quality Development in the Yangtze River Delta Urban Agglomeration, China

The Chinese economy has entered the phase of high-quality development. Urbanization is an important driving factor in promoting the domestic economic cycle, while tourism is an emerging force in the development of urbanization. The convergence of these two factors will contribute to the high-quality development of regional economies. By constructing an evaluation index system of tourism development and urbanization level, 26 cities in the Yangtze River Delta Urban Agglomeration have been identified as the study area. The study has adopted the entropy method and the coupling coordination model to analyze the comprehensive development level of tourism and urbanization and the coupling coordination relationship between them from 2008 to 2018. The results show that the Yangtze River Delta presents a spatial pattern of orderly changes in the development of tourism, forming a spatial structure of “one pole and many centers”, with Shanghai as the core. In terms of spatial distribution, it generally presents the spatial trend characteristics of “high in the east and low in the west” in the east–west direction, and “protruding in the middle and lower at both ends” in the south–north direction. Coordination and interaction are steadily developing to a high level, with significant spatial dependence and spillover effects. Based on the research results, the study applies a new development vision to explore the coupling coordination high-quality development mechanism of tourism and urbanization in the Yangtze River Delta region; the corresponding policy recommendations are discussed.

Future wildfire extent and frequency determined by the longest fire-conducive weather spell

Great efforts have been made to understand the impacts of a changing climate on fire activity; however, a reliable approach with high prediction confidence has yet to be found. By establishing linkages between the longest duration of fire-conducive weather spell and fire activity parameters, this study projected annual area burned (AAB), annual number of fires (ANF), and annual maximum fire size (MFS) into the future. We found that even though the rates of change differ, the spatial pattern of changes for all three parameters are similar by Canadian ecozone. Areas with the lowest fire activity may see higher rates of change in comparison to high fire activity areas. By end of the century, the changes of AAB and MFS for the study area are projected to be about four and five times that of the baseline respectively, while ANF could almost double.

Spatiotemporal variability in Swedish lake ecosystems.

Studying ecosystem dynamics is critical to monitoring and managing linked systems of humans and nature. Due to the growth of tools and techniques for collecting data, information on the condition of these systems is more widely available. While there are a variety of approaches for mining and assessing data, there is a need for methods to detect latent characteristics in ecosystems linked to temporal and spatial patterns of change. Resilience-based approaches have been effective at not only identifying environmental change but also providing warning in advance of critical transitions in social-ecological systems (SES). In this study, we examine the usefulness of one such method, Fisher Information (FI) for spatiotemporal analysis. FI is used to assess patterns in data and has been established as an effective tool for capturing complex system dynamics to include regimes and regime shifts. We employed FI to assess the biophysical condition of eighty-five Swedish lakes from 1996–2018. Results showed that FI captured spatiotemporal changes in the Swedish lakes and identified distinct spatial patterns above and below the Limes Norrlandicus, a hard ecotone boundary which separates northern and southern ecoregions in Sweden. Further, it revealed that spatial variance changed approaching this boundary. Our results demonstrate the utility of this resilience-based approach for spatiotemporal and spatial regimes analyses linked to monitoring and managing critical watersheds and waterbodies impacted by accelerating environmental change.

The use of multisource spatial data for determining the proliferation of stingless bees in Kenya

ABSTRACT Stingless/meliponine bees are eusocial insects whose polylactic nature enables interaction with a wide variety of wild plants and crops that enhance pollination and, hence, support ecosystem services. However, their true potential regarding pollination services and honey production is yet to be fully recognized. Worldwide, there are over 800 species of meliponine bees, with over 20 species documented on the African continent. Out of these, only 12 species have been well documented in Kenya. Moreover, interest on meliponine bees has increased amid climate change, agricultural intensification, and other anthropogenic effects. Generally, stingless bees are under-researched, with no previous documented evidence of their ecological niche (EN) distribution in most African countries. Hence, this study sought to establish the influence of bioclimatic, topographic, and vegetation phenology on their spatial distribution and change patterns. Stingless response variables from 490 sample points were collected and used in conjunction with 11 non-conflating features to build stingless ecological niche models. Six machine learning-based EN models were used to predict the distribution of seven stingless bees’ species combined. The results from the EN models showed that annual precipitation was the most influential variable to stingless bee distribution (contributing 43.09% logit), while potential evapotranspiration and temperature seasonality contributed 21.18% of the information needed to predict the spatial distribution of stingless bees. Vegetation phenology (21.36%) and topography (14.36%) had moderate effect on stingless bees’ distribution. On the other hand, high seasonality in precipitation and temperature indicated high stingless niche variability in the future (i.e. 2055). The performance of six EN algorithms used to predict distribution of stingless bees was found to be “excellent” for random forest (true skills statistics (TSS) = 0.91) and ranger (TSS = 0.90) and “good” for generalized additive models (TSS = 0.87), multivariate adaptive regression spline (TSS = 0.80), and boosted regression trees (TSS = 0.80), while they were “fair” for recursive portioning and regression trees (TSS = 0.79). These EN models could be utilized to inform stingless bee farming and insects pollinated crops by highlighting regions that provide highly suitable conditions for stingless bees. Additionally, the findings could be harnessed to increase both bee and agricultural productivity and forest conservation efforts through supplementary pollination services.

Spatial Analysis and Modeling of the Housing Value Changes in the U.S. during the COVID-19 Pandemic

COVID-19 has affected almost all sectors of the economy, including the real estate markets across different countries in the world. A rich body of literature has emerged in analyzing real estate market trends and revealing important information. However, few studies have used a spatial perspective to investigate the impact of COVID-19 on property values. The main purposes of this study are as follows: (1) to explore the spatial distribution and spatial patterns of housing price changes during the COVID-19 pandemic crisis in the U.S. real estate market and (2) to model the spatially nonstationary relationships between the housing price change and COVID-19 characteristics. We find that housing price changes differ across space and appear associated with the spatial distribution of the COVID-19 case rates. The housing market volatility is amplified by the uneven distribution of some socioeconomic factors. The spatially uneven housing price changes may bring an uneven spillover effect to the rest of the economy and lead to divergence in economic growth across different areas.

Does Disabling Cloud Radiative Feedbacks Change Spatial Patterns of Surface Greenhouse Warming and Cooling?

AbstractThe processes controlling idealized warming and cooling patterns are examined in 150-yr-long fully coupled Community Earth System Model, version 1 (CESM1), experiments under abrupt CO2forcing. By simulation end, 2 × CO2global warming was 20% larger than 0.5 × CO2global cooling. Not only was the absolute global effective radiative forcing ∼10% larger for 2 × CO2than for 0.5 × CO2, global feedbacks were also less negative for 2 × CO2than for 0.5 × CO2. Specifically, more positive shortwave cloud feedbacks led to more 2 × CO2global warming than 0.5 × CO2global cooling. Over high-latitude oceans, differences between 2 × CO2warming and 0.5 × CO2cooling were amplified by familiar linked positive surface albedo and lapse rate feedbacks associated with sea ice change. At low latitudes, 2 × CO2warming exceeded 0.5 × CO2cooling almost everywhere. Tropical Pacific cloud feedbacks amplified the following: 1) more fast warming than fast cooling in the west, and 2) slow pattern differences between 2 × CO2warming and 0.5 × CO2cooling in the east. Motivated to quantify cloud influence, a companion suite of experiments was run without cloud radiative feedbacks. Disabling cloud radiative feedbacks reduced the effective radiative forcing and surface temperature responses for both 2 × CO2and 0.5 × CO2. Notably, 20% more global warming than global cooling occurred regardless of whether cloud feedbacks were enabled or disabled. This surprising consistency resulted from the cloud influence on non-cloud feedbacks and circulation. With the exception of the tropical Pacific, disabling cloud feedbacks did little to change surface temperature response patterns including the large high-latitude responses driven by non-cloud feedbacks. The findings provide new insights into the regional processes controlling the response to greenhouse gas forcing, especially for clouds.Significance StatementWe analyze the processing controlling idealized warming and cooling under abrupt CO2forcing using a modern and highly vetted fully coupled climate model. We were especially interested to compare simulations with and without cloud radiative feedbacks. Notably, 20% more global warming than global cooling occurred regardless of whether cloud feedbacks were enabled or disabled. This surprising consistency resulted from the cloud influence on forcing, non-cloud feedbacks, and circulation. With the exception of the tropical Pacific, disabling cloud feedbacks did little to change surface temperature response patterns including the large high-latitude responses driven by non-cloud feedbacks. The findings provide new insights into the regional processes controlling the response to greenhouse gas forcing, especially for clouds. When combined with estimates of cooling at the Last Glacial Maximum, the findings also help rule out large (4+ K) values of equilibrium climate sensitivity.

A Bibliometric Analysis on the Effects of Land Use Change on Ecosystem Services: Current Status, Progress, and Future Directions

Land use changes cause significant alterations in the land surface structure and significantly impact ecosystem services. Research on land use change (LUC) and ecosystem services has become one of the hotspots of interdisciplinary research in ecology and geography. Based on 1860 publications collected from the Web of Science Core CollectionTM (WoS), the top authors, top organizations, top journals, and subject categories were discussed in detail. For the number of published articles, Sustainability ranks first with 86 publications, providing significant contributions in domain. The keywords could be classified into six categories: land use/land cover change, conservation, biodiversity, policies and programmers, environmental change, and agriculture. Citations and reference co-citations were analyzed, and popular literature and co-cited literature in the field were identified. In the discussion, we focus on four important issues, including land use area changes, land use pattern changes, land use spatial pattern changes, and land use changes at different scales. The research framework in the field and the shortcomings of existing research are discussed as well. The main aim of the paper is to assist researchers in identifying potential gaps in the research that should be addressed in future research.

Spatial and Temporal Patterns of Low-Flow Changes in Lowland Rivers

At the beginning of the 21st century, ongoing climate change led to research into extreme streamflow phenomena. This study aimed to assess the patterns of low-flow changes in different hydrological regions of Lithuania using selected hydrological indices (the annual minimum 30-day flow (m3 s−1) of the warm period—30Q), its duration, and deficit volume (below the 80th and 95th percentile flow: 30Q80 and 30Q95). Differences in low-flow indices in separate hydrological regions and over different periods (1961–2020, 1961–1990, 1991–2020) were analyzed, applying the HydroOffice tool, the TREND software package, and mapping using the Kriging interpolation. The highest specific indices of 30Q were estimated in the Southeastern hydrological region (3.97 L/s·km2) and the lowest in the Central hydrological region (1.47 L/s·km2). In general, the 30Q values in the periods 1961–2020 and 1991–2020 had no trends. In 1961–1990, trends in 30Q data were significantly positive, and positive in most investigated rivers of the Western and Central hydrological regions. The average number of dry days at both thresholds decreased in the Western and Southeastern hydrological regions and increased in the Central hydrological region comparing two subperiods.

Seasonal circulation regimes in the North Atlantic: Towards a new seasonality

AbstractEuropean climate variability is shaped by atmospheric dynamics over the North Atlantic and local processes. Better understanding their future seasonality is essential to anticipate changes in weather conditions for human and natural systems. We explore atmospheric seasonality over 1979–2017 and 1979–2100 with seasonal circulation regimes (SCRs), by clustering year‐round daily fields of Z500 from the ERA‐Interim reanalysis and 12 Coupled Model Intercomparison Project phase 5 (CMIP5) climate models (historical and RCP8.5 runs). The spatial and temporal variability of SCR structures and associated patterns of surface air temperature are investigated. Climate models have biases but reproduce structures and evolutions of SCRs similar to the reanalysis over 1979–2017: decreasing frequency of winter conditions (starting later and ending earlier in the year) and the opposite for summer conditions. These changes are stronger over 1979–2100 than over 1979–2017, associated with a large increase of North Atlantic seasonal mean Z500 and temperature. When using more SCRs (more freedom in definition of seasonality), the changes over 1979–2100 correspond to a long‐term swap between SCRs, resulting in similar structures (annual cycle and spatial patterns) relative to the evolution of seasonal mean Z500 and temperature. To understand whether the evolution of SCRs is linked to uniform warming, or to changes in circulation patterns, we remove the calendar trend in the Z500 regional average to define SCRs based on detrended data (d‐SCRs). The temporal properties of d‐SCRs appear almost constant whereas their spatial patterns change, indicating that the calendar Z500 regional trend drives the evolutions of SCRs, and that changing spatial patterns in d‐SCRs account for the heterogeneity of this trend. Our study suggests that historical winter conditions will continue to decrease in the future while historical summer conditions continue to increase. However, it also suggests that the spatial and temporal patterns of SCRs would remain similar, relatively to the year‐round Z500 increase.

Indigenous brigades change the spatial patterns of wildfires, and the influence of climate on fire regimes

Abstract Indigenous people have been managing fire‐prone landscapes for millennia, especially in tropical savannas, thereby maintaining carbon stocks and pyrodiversity and ensuring food security. In some indigenous lands in Brazil, fire brigades are composed of indigenous people, integrating their traditional knowledge in Brazilian fire management policies; however, the effectiveness of their management is largely undocumented. Nevertheless, we need to know the effectiveness of indigenous fire brigades and their influence on fire patterns. Here, we evaluate an 18‐year historical series of fire patterns and burn scars, comparing periods with and without indigenous brigade activity, to describe the role of indigenous fire brigades in the Kadiwéu Indigenous Territory. In this Indigenous Territory, fire brigades composed of indigenous people have been instituted, trained and maintained by the National Center of Prevention and Combat of Wildfire (PREVFOGO/IBAMA) since 2009. These brigades are responsible for fire management throughout the Kadiwéu Indigenous Territory using controlled burning, prescribed burning and combating wildfires. We found that fire management by the indigenous brigades has reduced fire frequency by 80% in the areas with high fire frequency (over 70% of the analysed time). Management also reduced the size of the area burned by 53% and the influence of climate over the total area burned. According to our models, the area affected by fires is mainly influenced by annual rainfall in the absence of indigenous brigades; in contrast, climatic factors could not explain the variation in the burned area in the period without indigenous brigades. Synthesis and applications. The fire management realized by the indigenous brigades can modify the fire regime. These changes in the fire regime can include: changes in spatial patterns, the magnitude of fires and reduction in the influence of climate on fire regimes. Hence, the management carried out by the indigenous brigades can be considered an important tool for fire management. In addition to demonstrating the importance of programs that integrate traditional indigenous knowledge with fire management policies, such as the Integrated Fire Management (IFM), to construct effective management strategies.

Evaluation of spatial interpolation methods and spatiotemporal modeling of rainfall distribution in Peninsular Malaysia

Spatial interpolation is important for visualizing changes of parameters over space. Interpolation methods for the spatiotemporal analysis of rainfall pattern changes of Peninsular Malaysia due to climate change were evaluated. Inverse Distance Weighting (IDW) and Ordinary Kriging (OK), Geographical Weighted Regression (GWR) and Multi-scale Geographical Weighted Regression (MGWR) methods were used. Based on the statistic results of RMSE, MAE and R 2 , the MGWR was the best performing model. To investigate the spatial interpolations with the MGWR, the period considered was arbitrarily and conveniently divided into six 5-year sub-periods for spatiotemporal analysis. Monthly Rainfall, Number of Wet Days and Maximum Daily Rainfall were parameters identified for the analyses. The results showed that the Peninsular Malaysia generally receives relatively higher rainfall amounts and intensities over the northern part of the East Coast region, while lower values were commonly received at the Central region. Changes in spatial pattern were also observed in the maps generated for the onset and withdrawal months of both the Northeast Monsoons and the Southwest Monsoons. The sub-period analyses also showed that Peninsular Malaysia has gradual increase of rainfall intensity due to climate change and is susceptible and vulnerable to El Nino/La Nina events. Hence, in the future Peninsular Malaysia is likely to have increasing occurrence of extreme rainfall events.