Changes In Population Distribution Research Articles

Multi-scale population analysis unit construction method considering scene feature variability and long/short-term patterns in spatiotemporal population activities

ABSTRACT Differences in the spatial scale and component elements of urban scenes affect the analysis of spatiotemporal changes in population distribution (PD) patterns. Fixed scales and geometric forms constrained previous analyses of PD and spatiotemporal changes, which neglected the realistic characteristics of urban scenarios. These limitations hinder the ability to capture the diversity and spatiotemporal representation of PD patterns across multiple spatial scales. This study developed a multi-spatial scale population analysis unit (PAU) construction method considering the scenario heterogeneity and long/short-term patterns of spatiotemporal population changes (PC). Initially, we decompose the multi-scale changes in population time series patterns and their relationships with scene features along the temporal dimension to analyze the primary and secondary factors. Starting from the temporal characteristics of the PD and PC, we established a validation and correction method for the factors. Finally, combined with a multi-feature clustering method, a multi-scale PAU construction method driven by scene feature factors is proposed. Experiments were conducted at different spatial scales in both routine and emergent scenarios. The results indicated that this method can help to obtain more homogeneous analysis regions and enhance the stability and phase pattern representations of changes in PDs, thereby improving the interpretability of analytical results.

Intraspecific divergence in a coastal plant, Euphorbia jolkinii, at a major biogeographic boundary in East Asia.

Quaternary climatic fluctuations and long-distance seed dispersal across the sea are critical factors affecting the distribution of coastal plants, but the spatiotemporal nature of population expansion and distribution change of East Asian coastal plants during this period are rarely examined. To explore this process, we investigated the genome-wide phylogenetic patterns of Euphorbia jolkinii Boiss. (Euphorbiaceae), which grows widely on littoral areas of Japan, Korea, and Taiwan. We used plastome sequences and genome-wide single nucleotide polymorphisms in samples across the species range to reveal phylogeographic patterns and spatiotemporal distributional changes. We conducted ecological niche modeling for the present and the last glacial maximum (LGM). Genetic differentiation was observed between the northern and southern populations of E. jolkinii, separated by the major biogeographic boundary, the Tokara Gap. These two groups of populations differentiated during the glacial period and subsequently intermingled in the intermorainic areas of the central Ryukyu Islands after the LGM. Ecological niche models suggested that the potential range of E. jolkinii was restricted to southern Kyushu; however, it was widespread in the southern Ryukyu Islands and Taiwan during the LGM. This study provides evidence of genetic differentiation among coastal plant populations separated by the prominent biogeographical boundary. Although coastal plants are typically expected to maintain population connectivity through sea-drifted seed dispersal, our findings suggest that genetic differences may arise because of a combination of limited gene flow and changes in climate during the glacial period.

Understanding the effects of climate and anthropogenic stresses on distribution variability of Setipinna taty in the Yellow Sea

Setipinna taty is one of the pivotal fishes in the Yellow Sea large marine ecosystem, and detecting and analyzing changes in the patterns of its distribution under multiple stresses is important in understanding its population dynamics and potential shifts in its ecological role. In this study, eight alternative spatio-temporal models were developed for S. taty using the Vector Autoregressive Spatio-Temporal (VAST) framework to analyse winter trawl survey data in the Yellow Sea from 2001–2021. These models included different combinations of local sea temperature, climate index and fishing pressure as explanatory variables. The model selected, based on Akaike's Information Criterion (AIC) and spatio-temporal variation explanation rate, indicated that the spatio-temporal distribution patterns of the population were driven by a combination of local temperature, climatic pressure, and fishing intensity. Among these factors, sea temperature is purportedly the most important driver. Results from the chosen model showed that the effective area occupied by the population decreased significantly during the study period (p<0.05). Prior to 2010, the climate and marine environment were relatively stable, and distribution changes were consistent with the basin model (BM, supported by density-dependent habitat selection theory), that individuals move to preferred habitats as biomass declines under fishing pressure (i.e. S. taty individuals were concentrated within the core distribution area as biomass declines). The climate and its driving oceanographic conditions (temperature) changed significantly after 2010 and, as a result, population distribution changes became complex (non-significant relationship between abundance and distribution area) and were no longer supported by BM, corresponding to a significant northward shift of the center of gravity (p<0.05) and a northward expansion of the northern population boundary. Our study highlights the synergistic drive of multiple stresses on spatio-temporal distribution patterns of the S. taty population. Future research should focus on developing a mechanistic understanding of the synergies between climate and anthropogenic stresses and how they affect population dynamics (distribution patterns), which is key to the successful management of the S. taty fishery and other fisheries in this ecosystem.

Acute Exposure to High-Altitude Results in Changes to Immune Cell Populations

High altitude is a challenging environment due to the reduced atmospheric pressure and oxygen availability, increased ultraviolet radiation, and reduced temperature relative to sea level. Previous studies in individuals who travel to high altitude demonstrate differential expression of genes involved in inflammation and innate immune system activation. This study aims to extend these findings by defining changes in immune cell population distributions and cell phenotypes during travel to high altitude. We hypothesized that acute high-altitude exposure would lead to shifts in immune cell populations toward a pro-inflammatory phenotype due to cellular stress caused by hypoxemia and tissue hypoxia. Participants (N=17) traveled to Barcroft Station in the White Mountain Research Center (3800 m). Whole blood was collected during fasting at sea level on the morning of ascent and each morning at high altitude for three days. Cells in whole blood were fixed and stained within 1-2 hours of collection and were processed via flow cytometry upon return to sea level. We observed a decrease in classical monocytes on the first (p=0.010) and second (p=0.003) mornings of high-altitude acclimatization to sea-level baseline, and an increase in intermediate monocytes on the first (p=0.013) and second (p=0.014) mornings at high altitude. We also observed an increase in B cells on the second (p=0.004) and third (p=0.004) mornings at high altitude compared to sea-level baseline (mean: 3.53%, SD: ±1.82). These results indicate that acute high altitude exposure results in a shift toward a pro-inflammatory monocyte phenotype and supports prior research suggesting a significant role of hypoxia in modulating B cell function. This research was supported through funding provided by a private donor. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Historical changes in the distribution of the Sichuan golden snub-nosed monkey (Rhinopithecus roxellana) in Sichuan Province, China.

The Sichuan golden snub-nosed monkey (Rhinopithecus roxellana) is a rare and endangered primate species endemic to China. Conducting research on the population distribution changes of the Sichuan golden snub-nosed monkey holds paramount importance for its conservation. Our study represented a comprehensive investigation into the population distribution of the Sichuan snub-nosed monkey by integrating data acquired from field surveys, protected areas, and historical records and using Geographic Information Systems (GIS) to explore changes in distribution across various time periods, including the historical (the Mid-to-Late Pleistocene), recent (1980-2000), and current (2001-2023). The research findings demonstrate a significant shift in the distribution range of the Sichuan golden snub-nosed monkey compared to historical time frames. Notably, between 1980 and 2000, there was a sharp decline in distribution area. Analyses revealed that the southernmost distribution county for the Sichuan golden snub-nosed monkey in Sichuan Province has shifted northward from Huili to Kangding. Furthermore, distribution changes in Sichuan Province are not solely characterized by a reduction in habitat area but also by a decrease in vertical distribution zones. Regions in the northeastern part of Sichuan with elevations below 1000 m, such as Guang'an City, Bazhong City, Dazhou City, and Nanchong City, no longer support the presence of the Sichuan golden snub-nosed monkey. At present, the distribution range is confined to elevations between 1000 and 4000 m in the two major mountain ranges of Qionglai and Minshan. A holistic approach is required to safeguard this species. The establishment of movement corridors can play a critical role in enhancing the overall connectivity of current distribution areas. Additionally, we propose implementing a hierarchical approach to protect current habitats. Spatially differentiated conservation measures should be implemented to prioritize the protection of key habitats while simultaneously monitoring anthropogenic activities in non-key habitats to prevent further fragmentation and isolation of the monkey's distribution areas.

Biological and environmental covariates of juvenile sockeye salmon distribution and abundance in the southeastern Bering Sea, 2002-2018.

Climate change is altering the distribution and abundance of marine species, especially in Arctic and sub-Arctic regions. In the eastern Bering Sea, home of the world's largest run of sockeye salmon (Oncorhynchus nerka), juvenile sockeye salmon abundance has increased and their migration path shifted north with warming, 2002-2018. The reasons for these changes are poorly understood. For these sockeye salmon, we quantify environmental and biological covariate effects within spatio-temporal species distribution models. Spatio-temporally, with respect to juvenile sockeye salmon densities: (1) sea surface temperature had a nonlinear effect, (2) large copepod, Calanus, a minor prey item, had no effect, (3) age-0 pollock (Gadus chalcogrammus), a major prey item during warm years, had a positive linear effect, and (4) juvenile pink salmon (O. gorbuscha) had a positive linear effect. Temporally, annual biomass of juvenile sockeye salmon was nonlinearly related to sea temperature and positively related to age-0 pollock and juvenile pink salmon abundance. Results indicate that sockeye salmon distributed with and increased in abundance with increases in prey, and reached a threshold for optimal temperatures in the eastern Bering Sea. Changes in population dynamics and distribution of sockeye salmon in response to environmental variability have potential implications for projecting specific future food securities and management of fisheries in Arctic waters.

Investigation of Spatiotemporal Patterns of Harbour Porpoise (Phocoena phocoena) Strandings in Swedish Waters for Improved Monitoring and Management

Harbour porpoises (Phocoena phocoena) are the only cetacean residents found year-round in Swedish waters and they are exposed to numerous natural and anthropogenic threats. Since the in situ monitoring of cetaceans can be difficult, invasive and often expensive, investigation of stranding patterns and examination of stranded animals can be used as a cost-effective source of data to study these elusive animals. The aim of this study was to investigate the spatiotemporal patterns of harbour porpoise stranding reports and the possible underlying causes in Swedish waters over a ten-year period (2014–2023). Additionally, the Swedish stranding network plays a key role in the collection of stranded carcasses for health and disease surveillance, and geographic coverage of the network also was analysed. When making spatial comparisons, the ten-year period was divided into two five-year blocks. Data on 854 stranded harbour porpoises were analysed from the coasts of the Skagerrak, Kattegat, and Baltic Seas. Both significant spatial and temporal patterns could be identified. Strandings peaked in July through September and hotspots occurred along most of the Swedish west coast, with the most frequent hotspots located around Öresund and especially the area around the Kullen peninsula. The spatial patterns of strandings found in this study are consistent with data on porpoise abundance, prey abundance, and gillnet fisheries’ efforts. The latter is known to be one of the primary causes of porpoise mortality. Furthermore, the coverage of the Swedish stranding network increased between the two periods, likely reflecting an increased awareness of the carcass-based surveillance program, and gaps requiring network expansion efforts were identified. These results also provide baseline data to enable the continued monitoring of stranding trends, as changes may indicate changes in population distribution, size or mortality rates.

Long‐term occupancy monitoring reveals value of moderate disturbance for an open‐habitat specialist, the Stephens' kangaroo rat (Dipodomys stephensi)

AbstractFor species of conservation concern, long‐term monitoring is vital to properly characterize changes in population distribution and abundance over time. In addition, long‐term monitoring guides management decisions by informing and evaluating the efficacy of management actions. A long‐term monitoring initiative for the federally threatened Stephens' Kangaroo rat (Dipodomys stephensi, SKR) was established in 2005, across 628 hectares within Marine Corps Base Camp Pendleton (MCBCP), San Diego, California, USA. From 2005 to 2018, we tracked trends in area occupied by SKR, trends in relative SKR densities within occupied habitat, and modeled probabilities of SKR occupancy, colonization, extinction, with habitat, climate, and disturbance covariates. Area occupied by SKR increased almost 2‐fold from 2005 to 2018 on MCBCP, while density in occupied habitat increased almost 3‐fold. Increased area occupied was correlated with increases in estimated density among years, indicating SKR population growth occurs by expansion into suitable habitat patches, as well as increases in numbers within occupied habitat. SKR occupancy was positively associated with gentle slopes (&lt;10%) and moderate open ground (40–80%) and forb cover (&gt;40%). They were more likely to colonize previously unoccupied habitat when there were moderate levels of open ground (40–80%) and low shrub cover (&lt;20%), while more likely to go locally extinct in areas with high slopes (&gt;10%), less open ground (&lt;20%), and increased non‐native grass cover (&gt;40%). Additionally, probabilities of SKR occupancy and colonization were higher in areas with moderate levels of disturbance, which was positively associated with open ground and forb cover. We conclude that long‐term occupancy and density monitoring is effective in informing status and trends of spatially dynamic species and that moderate habitat‐based disturbance is compatible with the management of SKR.

Spatial and temporal changes in population distribution and population projection at county level in China

Counties in China play a pivotal role in economic and social development, acting as essential leadership hubs for large and medium-sized cities, contributing to rural revitalization, and facilitating urban-rural integration. Using ArcGIS spatial analysis, this study examines the population distribution spatial and dispersion patterns in Chinese counties based on 40 years of data from the first to the seventh national population census. Results reveal noticeable growth trends and regional disparities in county populations, with an increase in large-population counties and a decrease in small-population ones. Recent population growth concentrates in urban agglomerations, metropolitan areas, and southeastern coastal regions, while reductions occur in the northeastern and Inner Mongolia border areas. Furthermore, the study identifies “high-high” agglomerations around provincial capitals and “low-low” agglomerations in economically underdeveloped western and northeastern border regions. China’s population distribution spatial agglomeration has been increasing, with acceleration toward specific areas. The first through seventh census show rapid growth at low density, followed by growth at medium density, stable growth, and eventually negative growth. This suggests a likely slowdown and potential reversal in China’s future population growth. Additionally, an Auto Regression Integrated Moving Average (ARIMA) model is employed to forecast China’s total population, projecting a decline to 1343.68 million by 2035. The emergence of “population loss counties” in contemporary China underscores the need for a rational understanding of their development status and trends to optimize population development strategies and promote economic and social progress.

Research on the Changes in Distribution and Habitat Suitability of the Chinese Red Panda Population

The study of the dynamics of species habitat is of great significance for maintaining or adjusting the current habitat protection management strategy. However, the current research on the Chinese red panda’s habitat is limited to the analysis of a single period, which makes it difficult to quantify the changes in its habitat on a temporal scale and greatly hinders the formulation of the overall protection and management strategies that are to be used for the Chinese red panda. This study simulated habitat suitability at different temporal scales to quantify the trend of changes in habitat quality and analyzed the reasons for the changes in habitat suitability in certain regions. The results showed that the overall suitability of the Chinese red panda’s habitat increased and that the area of suitable habitats expanded. Suitable Chinese red panda habitats in the mountains of Qionglai (1662.73 km2), Daxiangling (230.30 km2), Xiaoxiangling (549.47 km2), and Liangshan (50.39 km2) increased by a total of 2452.89 km2. The suitability of habitats in the central part of the Liangshan Mountains has declined significantly, which is positively correlated with changes in temperature seasonality (BIO4, R = 0.18) and negatively correlated with changes in annual average temperature (BIO1, R = −0.03) as well as changes in the proportion of farmland (FARMLAND, R = −0.14). The local extinction of isolated populations of Chinese red pandas in the Minshan Mountains is the main factor leading to their distribution retreat rather than a decrease in habitat quality. The research results help us to provide a scientific basis for the formulation of conservation and management strategies for Chinese red pandas at different scales.

An ANN-based method for population Dasymetric mapping to avoid the scale heterogeneity: A case study in Hong Kong, 2016–2021

A comprehensive understanding of population distribution is critical for assessing socio-economic issues. However, the widely used dasymetric mapping method relies on models built at a coarse administrative scale and estimates population at a fine-gridded scale. This difference in scale between the training and estimating domains results in significant heterogeneity in data distribution. To address this issue, we proposed a scale heterogeneity-avoided method based on artificial neural networks that can take population density as an independent variable and gridded properties, including remote sensing images, digital terrain models, road networks, building footprints, and land use, as dependent variables. Our experiments in Hong Kong in 2016 and 2021 showed significant advantages of the proposed method. Compared to commonly used methods, our approach demonstrated a 19.4% improvement in the root mean square error. Furthermore, the advantages of our method became more apparent at larger census units, and the accuracy of the pre-trained model for directly estimating population in other temporal phases was satisfactory. Among the geospatial data variables, land use was the most significant in accurately estimating population. Replacing land use data with random numbers led to a decrease in accuracy by over 89.0%, while other properties only resulted in decreases of 2.7% to 13.9%. We further investigated spatiotemporal changes in population distribution from 2016 to 2021, finding that population growth mainly occurred in new built-up areas, while larger population decreases occurred in old towns. Throughout the study period, the population tended to concentrate more, as the average population density increased while the median population density decreased.

Long-term changes in population size and distribution of Stercorarius maccormicki (Stercorariidae, Charadriiformes) on the Haswell Islands, East Antarctica

Long-term studies are crucial in ecology, environmental change assessment, resource management and biodiversity conservation. Stercorarius maccormicki (hereinafter – south polar skua) are predators that can threaten populations of bird species of the orders Sphenisciformes and Procellariiformes. At many places in Antarctica, abundance trends for the skua are not known or have not been updated. This study is an attempt to answer the question: how did a south polar skua population react to changes in environmental conditions during 1956–2013? The objectives of the study was (1) to establish the dynamics of the breeding skua population on the Haswell Islands, i.e. Haswell Island and the small islands of the Haswell Archipelago during 1956–2013, and (2) to explain the reasons of the changes in the studied population. A secondary research question was whether there were changes in the spatial distribution of the breeding skua population on the Haswell Archipelago during the study period? The studies have been carried out on the Haswell Archipelago (Davis Sea), mainly in Antarctic Specially Protected Area №127 «Haswell Island and adjacent emperor penguin rookery on fast ice». Ground count was the main method for determining the size of bird colonies. South polar skua bred on 3–8 islands of the Haswell Archipelago. In the study period, the population size of the south polar skua has changed on the Haswell Archipelago. A decrease in the number of individuals (-52%) was observed between 1956–1957 and 1966–1967 breeding seasons. Between 1966–1967 and 1999–2000 breeding seasons, the skua population declined by 30.7% and reached the lowest value of 18 pairs. Population growth (344.4%) was recorded between 1999–2000 and 2009–2010 breeding seasons, with an increase of 33.8% and reaching the maximum value (83 pairs) in 2010–2011 breeding season. By 2012–2013 breeding season, the south polar skua population has declined by 13.2%. On Haswell Island, between 1956–1957 and 2012–2013 breeding seasons, there was a change in skua abundance that was similar to the change in the total breeding population on Haswell Archipelago during the entire period. On the small islands of the Haswell Archipelago, the number of breeding south polar skuas declined (-80%) between 1956–1957 and 1962–1963 breeding seasons. The breeding seasons of 1962–1963, 1966–1967 and 1999–2000 were characterised by the lowest number of individuals. Between 1999–2000 and 2009–2010 breeding seasons, the number of south polar skuas increased by 400%. A decrease in abundance (-41.6%) occurred between 2009–2010 and 2010–2011, followed by the consequent increase (by 36.3%) by 2012–2013 breeding season. During the study period, changes in the abundance of south polar skuas on the Haswell Archipelago were independent of changes in average daily November temperatures between 1956–1957 and 2012–2013 breeding seasons (Mann-Whitney test U = 0, p = 0.0017, n = 7 (asymptotic (2-sided))), when they were laying eggs and heating them. The number of south polar skuas changed independently of changes in the number of individuals of their prey, represented by Aptenodytes forsteri, Pygoscelis adeliae, and Fulmarus glacialoides (respectively U = 49, p = 0.0006, n = 7; U = 16, p = 0.029, n = 4; U = 16, p = 0.029, n = 4 (asymptotic (2-sided))). The high mortality of eggs, chicks and local weather conditions could influence the breeding success of the south polar skua, which could have a delayed effect on their long-term dynamics. Human activities have influenced the skua population, but have not been studied quantitatively. On the Haswell Archipelago, the reasons for historical changes in abundance of the breeding skua population remain largely unclear.

Using POI and multisource satellite datasets for mainland China's population spatialization and spatiotemporal changes based on regional heterogeneity

Geospatial big data and remote sensing data are widely used in population spatialization studies. However, the relationship between them and population distribution has regional heterogeneity in different geographic contexts. It is necessary to improve data processing methods and spatialization models in areas with large geographical differences. We used land cover data to extract human activity, nighttime light and point-of-interest (POI) data to represent human activity intensity, and considered differences in geographical context to divide mainland China into northern, southern and western regions. We constructed random forest models to generate gridded population distribution datasets with a resolution of 500 m, and quantitatively evaluated the importance of auxiliary data in different geographical contexts. The street-level accuracy assessment showed that our population dataset is more accurate than WorldPop, with a higher R2 and smaller deviation. The improved datasets provided broad potential for exploring the spatial-temporal changes in grid-level population distribution in China from 2010 to 2020. The results indicated that the population density and settlement area have increased, and the overall pattern of population distribution has remained highly stable, but there are significant differences in population change patterns among cities with different urbanization processes. The importance of the ancillary data to the models varied significantly, with POI contributing the most to the southern region and the least to the western region. Moreover, POI had relatively less influence on model improvement in undeveloped areas. Our study could provide a reference for predicting social and economic spatialized data in different geographical context areas using POI and multisource satellite data.

A new phase Ⅱ risk-adjusted CUSUM chart for monitoring surgical performance

In recent years, the use of risk-adjusted control charts for monitoring surgical performance has gained significant attention among researchers. However, many existing monitoring methods only consider patient risk factors that impact surgical performance, and fail to account for other risk factors, such as the surgeon's level of experience. This study presents a new phase II risk-adjusted cumulative sum (CUSUM) chart based on the score test statistic, which includes a risk-adjusted mortality model with dummy variables. This new control chart not only monitors shifts in location and scale parameters related to surgical performance, but also accounts for changes in the risk distribution of the patient population by using dynamic probability control limits (DPCLs). The proposed method is further elaborated and validated through simulations in a practical context, and simulation results indicate that this method is more sensitive to small abnormal changes.

Transportation Resilience Modeling and Bridge Reconstruction Planning Based on Time-Evolving Travel Demand during Post-Earthquake Recovery Period

After major earthquakes, communities may experience time-evolving population in terms of size and distribution, and varying travel demands, along with the displacement and recovery of residents caused by the damage and restoration of dwelling units. Community transportation can be significantly affected if the changes in population size and distribution are considerable. As a result, the post-earthquake infrastructure reconstruction process is essentially like urban replanning to meet the realistic traffic needs of the remaining and recovering residents and further maximize the sustainability of the community. To fill the gap in existing studies that considered the travel demand as fixed during the long-term recovery stage, it is important to investigate the effects of time-evolving travel demand on transportation resilience modeling and bridge reconstruction planning during the post-earthquake recovery period. A new methodology is proposed to analyze such impact by assessing the time-dependent resilience performance of transportation networks during the post-earthquake recovery stage. Traffic efficiency and safety are the two resilience performance indicators used to evaluate the transportation network. Post-earthquake infrastructure restoration planning is conducted using a heuristic algorithm based on the time-dependent resilience performance indicator. A demonstrative case study is carried out at Shelby County, Tennessee.

Predatory walls may impair climate warming-associated population expansion.

Climate change has a profound impact on species distribution and abundance globally, as well as local diversity, which affects ecosystem functioning. In particular, changes in population distribution and abundance may lead to changes in trophic interactions. Although species can often shift their spatial distribution when suitable habitats are available, it has been suggested that predator presence can be a constraint on climate-related distribution shifts. We test this using two well-studied and data-rich marine environments. Focusing on a pair of sympatric fishes, Atlantic haddock Melanogrammus aeglefinus and cod Gadus morhua, we study the effect of the presence and abundance of the latter on the former distribution. We found that the distribution of cod and increased abundance may limit the expansion of haddock to new areas and could consequently buffer ecosystem changes due to climate change. Though marine species may track the rate and direction of climate shifts, our results demonstrate that the presence of predators may limit their expansion to thermally suitable habitats. By integrating climatic and ecological data at scales that can resolve predator-prey relationships, this analysis demonstrates the usefulness of considering trophic interactions to gain a more comprehensive understanding and to mitigate the effects of climate change on species distributions.

PRESENT-DAY POLICIES CONCERNING INDIGENOUS LANGUAGES IN THE AMERICAS: A GEOGRAPHICAL APPROACH

Global changes in policies regarding Indigenous people, observed in the last decades, have had a strong impact on language policies in the Americas. They are aimed at increasing protection of Indigenous languages, especially in countries with a higher number and percentage of Native people and Indigenous language speakers (ILS). However, it is argued in the paper that the scope of these policies is often not adapted to changes in spatial distribution of Autochthonous populations, while their effective implementation in many cases seems outright impossible. The first part of the paper sums up an analysis concerning the number and spatial distribution of Indigenous people and ILS in countries and dependent territories of the Americas. The second part shows the evolution of policies towards Indigenous languages in the Americas from the colonial era to our times. The last part studies spatial aspects of the situation of Indigenous languages in Mexico City, based primarily on qualitative data obtained from interviews and observations carried out during field research. The paper concludes: that a clear progress has been made in language policies in the last decades in the analysed region, especially in Latin America; that there is no obvious difference in the implementation of these policies between unitary and federal states; and that, based on the case of Mexico City, the implementation of a relevant language policy may be seriously hindered by such factors as insufficient financing, political disputes, and a deeply embedded discrimination against Indigenous languages.

Chir pine forest and pre-monsoon drought determine spatial, and temporal patterns of forest fires in Uttarakhand Himalaya.

The online version contains supplementary material available at 10.1007/s42965-023-00306-9.

ДЕМОГРАФИЧЕСКАЯ ДИНАМИКА И ТРАНСФОРМАЦИЯ СИСТЕМЫ РАССЕЛЕНИЯ НА СЕВЕРЕ РОССИИ В КООРДИНАТАХ ПЕРЕПИСИ НАСЕЛЕНИЯ 2021 ГОДА

Over the past decades, the population of the North of Russia has decreased by more than a quarter. The leading cause is migration outflow, with natural population movement also contributing to the overall population decline. Comparing the data of the last two censuses will make it possible to understand the full depth of the transformational processes. The purpose of the study is to analyze the demographic trends and changes in population distribution in the North of Russia based on the results of the 2021 All-Russian Population Census. The originality of the article lies in the fact that the analysis was carried out at all levels: the macro level, regions, municipalities, and urban settlements. The article shows that with a general population decline, there is further urbanization of the northern regions and a reduction in the number and proportion of rural residents. Particularly high population decline is demonstrated by such regions of the European North as the republics of Komi and Karelia as well as the Arkhangelsk and Murmansk regions. The authors have identified trends in population distribution, such as an increase in the proportion of the population of large cities and a decrease in the average population of towns and urban-type settlements. Population distribution in the North of Russia is influenced by factors such as the size of the settlement, economic specialization, ethnic composition, and geographical location of the settlement. With the help of spatial analysis, the study identified the clusters of municipalities and settlements with the best and worst trends since 2010. Using Lorenz curves and the Gini coefficient, the authors studied the unevenness of population distribution and economic activity. The study also revealed that in the vast majority of municipalities in the North, the proportion of men has decreased, which may adversely affect local labor markets. The results of the study may find application in public administration and the development of strategies and programs for the socioeconomic development of the northern territories. Further research should consider such characteristics of the population as age, ethnic composition, place of birth, length of residence, number of children, and housing conditions.

Boosting the efficiency of transient photoluminescence microscopy using cylindrical lenses.

Transient Photoluminescence Microscopy (TPLM) allows for the direct visualization of carrier transport in semiconductor materials with sub nanosecond and few nanometer resolution. The technique is based on measuring changes in the spatial distribution of a diffraction limited population of carriers using spatiotemporal detection of the radiative decay of the carriers. The spatial resolution of TPLM is therefore primarily determined by the signal-to-noise-ratio (SNR). Here we present a method using cylindrical lenses to boost the signal acquisition in TPLM experiments. The resulting asymmetric magnification of the photoluminescence emission of the diffraction limited spot can increase the collection efficiency by more than a factor of 10, significantly reducing acquisition times and further boosting spatial resolution.