Variation In Population Density Research Articles

A semi-parametric geographically weighted (S-GWR) approach for modeling spatial distribution of population

Spatial Distribution of Population (SDP) has been recognized as a fundamental indicator of various studies including ecosystem assessment. To estimate SDP with fine resolution at a regional scale, an S-GWR model approach based on a land use map was developed. The model enhances SDP estimation accuracy by considering geo-spatial variation of population density and absolute accuracy in a demographic statistics unit that might introduce significant biases. The model is applied in estimating SDP of Shandong province, China, in 2000 with a resolution of 1km. It was validated against census data and two common datasets for GPWv3 and CGPD both at the prefecture scale and sub-prefecture scale. The validation revealed that the mean absolute percentage error of SDP based on the S-GWR model (GSDP) is approximately 0 at the prefecture scale, which shows better performance than the other two datasets. The validation at the sub-prefecture scale in Tancheng county shows a mean absolute percentage error of 12.79% for GSDP in 17 townships, which is less than that of CGPD (15.37%) and GPWv3 (18.76%). Furthermore, spatial analysis of the error indicated that the S-GWR model spread the error into the region of Tancheng with the least percentage of towns (35.29%) with a percentage error larger than 15%, where the percentage of CGPD and the percentage of GPWv3 are 47.06% and 58.82%, respectively. The findings from the study demonstrated the great potential and value of the S-GWR model for regional SDP estimation.

Impact of male alternative reproductive tactics on female costs of sexual conflict under variation in operational sex ratio and population density.

Sexual conflict over mating rate is both pervasive and evolutionarily costly. For females, the lifetime reproductive fitness costs that arise through interactions with potential mates will be influenced by the frequency of such interactions, and the fitness cost of each interaction. Both of these factors are likely to be influenced by variation in operational sex ratio (OSR) and population density. Variation in OSR‐ and density‐dependent male alternative reproductive tactics (ARTs) may be particularly important if the fitness costs that females experience vary with the reproductive tactics that males express. Using a simple model, we consider several examples of OSR‐ and/or density‐dependent variation in male ARTs and the frequency of male–female interactions, and find that variation in the expression of male ARTs has the potential to augment or diminish the costs of frequent male interactions for females. Accurately documenting variation in the expression of male ARTs and associated female fitness costs will benefit future work in this area.

Chagas disease vector control and Taylor's law.

BackgroundLarge spatial and temporal fluctuations in the population density of living organisms have profound consequences for biodiversity conservation, food production, pest control and disease control, especially vector-borne disease control. Chagas disease vector control based on insecticide spraying could benefit from improved concepts and methods to deal with spatial variations in vector population density.Methodology/Principal findingsWe show that Taylor's law (TL) of fluctuation scaling describes accurately the mean and variance over space of relative abundance, by habitat, of four insect vectors of Chagas disease (Triatoma infestans, Triatoma guasayana, Triatoma garciabesi and Triatoma sordida) in 33,908 searches of people's dwellings and associated habitats in 79 field surveys in four districts in the Argentine Chaco region, before and after insecticide spraying. As TL predicts, the logarithm of the sample variance of bug relative abundance closely approximates a linear function of the logarithm of the sample mean of abundance in different habitats. Slopes of TL indicate spatial aggregation or variation in habitat suitability. Predictions of new mathematical models of the effect of vector control measures on TL agree overall with field data before and after community-wide spraying of insecticide.Conclusions/SignificanceA spatial Taylor's law identifies key habitats with high average infestation and spatially highly variable infestation, providing a new instrument for the control and elimination of the vectors of a major human disease.

Developing an Index to Measure Sub-municipal Level Urban Sprawl

The present study aims to develop an index composed of different spatial variables to measure the urban sprawl levels of a municipality located in Southern Spain. According to the findings, urban sprawl can be measured not only on the metropolitan level but also on a more detailed and precise level, such as sub-municipal. A group of experts chosen for their suitability in measuring urban sprawl select six spatial variables (population density, net residential density, coverage ratio, land use types, percentage of residential land use, and average year of construction). These variables are aggregated using Choquet integral, a technique that combines interactions between those variables providing greater coherence to the complexity that is inherent in the creation of composite sprawl indexes. This methodology has been demonstrated to be valid and appropriate in evaluating urban expansion at sub-municipal level, but can also be applied to other scales once it is clearly a phenomenon in which interaction between criteria exists. The resulting composite index allows the assignment of different levels of sprawl to the urban areas consistent with their morphology and landscape.

Anticipatory flexibility: larval population density in moths determines male investment in antennae, wings and testes.

Developmental plasticity provides individuals with a distinct advantage when the reproductive environment changes dramatically. Variation in population density, in particular, can have profound effects on male reproductive success. Females may be easier to locate in dense populations, but there may be a greater risk of sperm competition. Thus, males should invest in traits that enhance fertilization success over traits that enhance mate location. Conversely, males in less dense populations should invest more in structures that will facilitate mate location. In Lepidoptera, this may result in the development of larger antennae to increase the likelihood of detecting female sex pheromones, and larger wings to fly more efficiently. We explored the effects of larval density on adult morphology in the gum-leaf skeletonizer moth, Uraba lugens, by manipulating both the number of larvae and the size of the rearing container. This experimental arrangement allowed us to reveal the cues used by larvae to assess whether absolute number or density influences adult responses. Male investment in testes size depended on the number of individuals, while male investment in wings and antennae depended upon larval density. By contrast, the size of female antennae and wings were influenced by an interaction of larval number and container size. This study demonstrates that male larvae are sensitive to cues that may reveal adult population density, and adjust investment in traits associated with fertilization success and mate detection accordingly.

Spatio-Temporal Modeling of Human Vulnerability in the Case of a Tsunami in Padang, Indonesia

Padang is known to be one of the most exposed cities in Indonesia to the threat of tsunamis. Some available models show that the urban area in the coastal zone would be inundated by a potential tsunami. Considering this threat, our objective is to estimate which areas of the city are the most endangered in order to plan an evacuation that is adapted to the daily influx of population at this local scale. To address this challenge, we propose a methodology based on a ground survey in Padang at a very fine scale. This survey is based on the hypothesis that inhabitants tend to have a common rhythm of life, which results in varying population distribution in time, according to the period and its activities. Furthermore, results of this survey are coupled with a submersion model, which provides an estimation of flood height and speed for every location, in order to propose a synthetic indicator of vulnerability, the human risk index, which combines both structural and human vulnerability. The variations in population density and potential casualties are then discussed through spatio-temporal maps that are used for designing evacuation scenarios. In particular, a measure of evacuation capability to existing vertical and topographic refuges is achieved for each of those scenarios, thus providing direction for authorities planning risk mitigation.

Normalization Strategies for Enhancing Spatio-Temporal Analysis of Social Media Responses during Extreme Events: A Case Study based on Analysis of Four Extreme Events using Socio-Environmental Data Explorer (SEDE)

Abstract. With social media becoming increasingly location-based, there has been a greater push from researchers across various domains including social science, public health, and disaster management, to tap in the spatial, temporal, and textual data available from these sources to analyze public response during extreme events such as an epidemic outbreak or a natural disaster. Studies based on demographics and other socio-economic factors suggests that social media data could be highly skewed based on the variations of population density with respect to place. To capture the spatio-temporal variations in public response during extreme events we have developed the Socio-Environmental Data Explorer (SEDE). SEDE collects and integrates social media, news and environmental data to support exploration and assessment of public response to extreme events. For this study, using SEDE, we conduct spatio-temporal social media response analysis on four major extreme events in the United States including the “North American storm complex” in December 2015, the “snowstorm Jonas” in January 2016, the “West Virginia floods” in June 2016, and the “Hurricane Matthew” in October 2016. Analysis is conducted on geo-tagged social media data from Twitter and warnings from the storm events database provided by National Centers For Environmental Information (NCEI) for analysis. Results demonstrate that, to support complex social media analyses, spatial and population-based normalization and filtering is necessary. The implications of these results suggests that, while developing software solutions to support analysis of non-conventional data sources such as social media, it is quintessential to identify the inherent biases associated with the data sources, and adapt techniques and enhance capabilities to mitigate the bias. The normalization strategies that we have developed and incorporated to SEDE will be helpful in reducing the population bias associated with social media data and will be useful for researchers and decision makers to enhance their analysis on spatio-temporal social media responses during extreme events.

Internode morphometrics and allometry of Tonkin Cane Pseudosasa amabilis.

Pseudosasa amabilis (McClure) (Poales: Gramineae) is a typical bamboo species naturally distributed in large area of south China and famous for its culm strength. Although bamboos were found to share the same development rule, the detailed internode morphology of bamboo culm was actually not fully expressed. We explored internode morphology of P. amabilis using 11 different physical parameters in different dimensions (1–4). As Taylor's power law (TPL) is generally applicable to describe relationship between mean and variance of population density, here we used TPL to evaluate the differences between internodes, and further, the relationship between dimension and TPL. Results showed that length (L), hollow radius (HR), hollow area (HA), hollow cylinder volume (HCV), total cylinder volume (TCV), density (De), and weight (W) all presented positive skewed distribution in varying degrees. For the basic one‐dimensional parameters, the 9th internode was the longest, the 7th the heaviest, while thickness (T) decreased with internodes. Diameter (D) decreased in general but with an inconspicuous local mode at the 5–6th internodes, potentially due to the rapid height growth. The longest (9th) internode was the “turning point” for T‐D and HR‐D relationships. Scatter plot changing trends of W to the one‐dimensional parameters after the heaviest (7th) internode were reversed, indicating a deceleration of growth speed. TPL was not holding well in one‐dimensional parameters (R 2: 0.5413–0.8125), but keep increasing as the parameter's dimension increasing (R 2 > 0.92 for two‐dimensional, R 2 > 0.97 for three‐dimensional, and R 2 > 0.99 for four‐dimensional parameters.), suggesting an emergence mechanism of TPL related to both the physical dimensions of morphological measures and the allometric growth of bamboo. From the physical fundamental level, all existences are the expression of energy distribution in different dimensions, implying a more general rule that energy distribution holds better TPL in higher dimension level.

Mechanisms underlying spruce budworm outbreak processes as elucidated by a 14‐year study in New Brunswick, Canada

AbstractWe conducted a 14‐yr intensive study of spruce budworm (Choristoneura fumiferana (Clem.)) survivorship at three study plots in largely balsam fir (Abies balsamea (L.) Mill.) stands in New Brunswick, Canada, to elucidate certain key mechanisms underlying spruce budworm outbreak cycles. The study covered a peak‐to‐declining phase (from 1981 and 1994) of the budworm outbreak cycle that had started in the early 1960s. Frequent sampling was carried out in each plot‐year to construct a practically continuous survivorship curve, and the annual variation in population density was estimated. We found a high level of correlation between the studied phase of the outbreak cycle and annual variations in the survivorship over the postdiapause period, suggesting that postdiapause survivorship was the chief determinant of the cycle. We found the annual changes in population density in the present study to be closely similar in pattern to those from the provincial budworm surveys conducted in much larger areas. This implies that the mechanism underlying the population process found in the few study plots in largely balsam fir stands also applies to the process in much larger areas of diverse stand types. The main source of postdiapause mortality is found to be natural enemies. The impacts of parasitoids and disease are evaluated by rearing budworm samples in the laboratory. Hymenopteran and dipteran parasitoids are by far the major sources of mortality, and microsporidians are the most prevalent pathogen. Occurrences of other entomopathogenic fungi and viruses were insignificant throughout the study. Seasonal changes in laboratory survivorship are compared with the corresponding field survivorship to estimate the effect of predation. No major mortality factor is found to singly play a predominant role in determining the outbreak cycle. Conversely, some minor factors are shown to have played significant roles. Thus, the importance of recognizing the action of natural enemies as a complex is emphasized for understanding the budworm outbreak cycle. Finally, centered on the roles played by the chronological succession of natural enemies in the present study, the results of budworm research in New Brunswick since the mid‐1940s are synthesized to outline basic mechanisms underlying the outbreak processes as a guide for further studies.

Abundance, density and habitat use of lowland paca (Cuniculus paca, Rodentia: Cuniculidae) in the Lacandon Rainforest, Chiapas, Mexico

In this study, the effect of relevant variables (availability of food and cavities, competition, predation, and hunting pressure) on the relative abundance and population density of the spotted lowland paca (Cuniculus paca) was assessed. In addition, habitat use of this species at three sites with different land use regime (Montes Azules Biosphere Reserve, community reserves, and anthropic sites) in the Lacandon Rainforest, Chiapas, Mexico was analysed. From the perspective of the source-sink systems, it was predicted that pacas selectively would use the habitat with higher food and cavity availability (source habitats), where higher densities were expected. Twelve transects were located in three sites with different land use regimes, where food availability and potential cavities used by pacas were assessed. Along these transects, 4 camera-traps were deployed every 200 meters to estimate the relative abundance of pacas and their potential competitors and predators. Photo-captured individuals were identified to estimate population density and seasonal variation in habitat use. Generalized linear models (GLM) were constructed to analyse the effects of several variables on paca abundance and density. A relative abundance of 0.05 and 0.08 paca photographs/100 camera-days were recorded in the dry and the rainy season, respectively. A density of 54 pacas/km2 was estimated in both seasons. The availability of cavities was the only variable that showed a significant effect on paca density (P = 0.04 for the dry season, and P = 0.006 for the rainy season). Community reserves were used in the dry season more than expected from their availability in the study area (x2 = 28.8; P = 0.0001). In the rainy season, all three sites were used by paca in proportion to their availability. Our results suggest that the cavities used as refuges by pacas drive their population dynamics, and constitute a key habitat resource for them in the study area. We propose that the Ejidal Reserve and Montes Azules Biosphere Reserve may be source habitats supporting higher paca densities and greater availability of adequate cavities to protect adults and their offspring. On the other hand, areas transformed into croplands and grasslands for livestock production would represent sink habitats with lower paca densities, less availability of adequate cavities, and absence of offspring. The long-term conservation and habitat management of pacas in transformed landscapes will probably rely on the distribution and connectivity between and within the different habitat types available in the study area.

Biological and statistical processes jointly drive population aggregation: using host-parasite interactions to understand Taylor's power law.

The macroecological pattern known as Taylor's power law (TPL) represents the pervasive tendency of the variance in population density to increase as a power function of the mean. Despite empirical illustrations in systems ranging from viruses to vertebrates, the biological significance of this relationship continues to be debated. Here we combined collection of a unique dataset involving 11 987 amphibian hosts and 332 684 trematode parasites with experimental measurements of core epidemiological outcomes to explicitly test the contributions of hypothesized biological processes in driving aggregation. After using feasible set theory to account for mechanisms acting indirectly on aggregation and statistical constraints inherent to the data, we detected strongly consistent influences of host and parasite species identity over 7 years of sampling. Incorporation of field-based measurements of host body size, its variance and spatial heterogeneity in host density accounted for host identity effects, while experimental quantification of infection competence (and especially virulence from the 20 most common host-parasite combinations) revealed the role of species-by-environment interactions. By uniting constraint-based theory, controlled experiments and community-based field surveys, we illustrate the joint influences of biological and statistical processes on parasite aggregation and emphasize their importance for understanding population regulation and ecological stability across a range of systems, both infectious and free-living.

Continent‐level drivers of African pyrodiversity

Pyrodiversity, which describes fire variability over space and time, is believed to increase habitat heterogeneity and thereby promote biodiversity. However, to date there is no standardised metric for quantifying pyrodiversity, and so broad geographic patterns and drivers of pyrodiversity remain unexplored. We present the first generalizable method to quantify pyrodiversity, and use it to address the fundamental questions of what drives pyrodiversity, which fire attributes constrain pyrodiversity under different conditions, and whether pyrodiversity is spatial grain‐dependent. We linked the MODIS burned area and active fire products to measure fire size, seasonal timing, return interval, and intensity for 2.2 million individual fires in sub‐Saharan Africa from 2000–2015. We then quantified pyrodiversity as a four‐dimensional hypervolume described by fire attributes within a grid cell, for any spatial grain of analysis. Environmental (rainfall, vegetation, soils, and topography) and human‐associated (cattle biomass, cropland area, and human population density) variables were assessed as potential drivers of pyrodiversity. Rainfall was the main environmental driver of pyrodiversity, with higher pyrodiversity in drier regions (< 650 mm yr–1). Pyrodiversity was not strongly associated with human‐associated variables across Africa. Rainfall and a human influence index had clear but contrasting effects on the variability of fire size, seasonal timing, return interval, and intensity. Our analyses show that fire size and seasonal timing constrain pyrodiversity in wetter regions, whereas none of the fire attributes pose a strong constraint in drier regions. We found no evidence that pyrodiversity was spatial grain‐dependent when recalculated at 5‐minute grain increments from 15 to 120 minutes. We hypothesise that the strongest positive effect of pyrodiversity on biodiversity in all its forms will occur at intermediate precipitation (650–1300 mm yr–1), where fire plays an important role in shaping vegetation structure and where pyrodiversity is still quite high.

Differential factors of fertility in South India.

This paper analyzes fertility differentials in south India in terms of economic and social development. The areas analyzed here are the 4 southern states: Andra Pradesh Kerala Karnataka and Tamil Nadu. The region is examined 1st with factors analysis using 33 variables concerning the indicators of the demographic structure of the labor force agricultural structure education medical care and religion. The analysis extracted 5 factors: 1) labor force characteristics 2) the level of social development 3) family structure 4) agricultural characteristics and 5) urbanity. The industrial structure of the region is characteristically labor-intensive agriculture. Women and children typically participate in agriculture and most of them are less educated. Regression analysis using variables from the factor analysis extracted 5 variables: 1) child labor 2) the female literacy rate and the population per doctor 3) the proportion of never married women 4) population per cultivated land and 5) the labor force participation rate in the primary industry and the proportion urban. Using these as independent variables the regression equation for the child-woman ratio is estimated. The model explains 48.4% of the total variance in the child-woman ratio in the 4 states. Among variables child labor and population density per cultivated land are statistically significant. The estimated result shows that the necessity of having a large labor force in the agricultural sector makes the fertility rate higher. 3rdly the authors estimate the regression equation including only those variables which are statistically significant in the model: child labor and population per cultivated land. The educational level is also added to these variables. The model cannot explain the regional variances of the child-woman ratio for Kerala and Tamil Nadu. In Andra Pradesh the necessity of child labor in agriculture makes fertility higher. In Karnataka education has a positive effect on fertility decline.

Citizen Science as a Tool for Mosquito Control.

In this paper, we share our findings from a 2-year citizen science program called Mosquito Stoppers. This pest-oriented citizen science project is part of a larger coupled natural-human systems project seeking to understand the fundamental drivers of mosquito population density and spatial variability in potential exposure to mosquito-borne pathogens in a matrix of human construction, urban renewal, and individual behaviors. Focusing on residents in West Baltimore, participants were recruited through neighborhood workshops and festivals. Citizen scientists participated in yard surveys of potential mosquito habitat and in evaluating mosquito nuisance. We found that citizen scientists, with minimal education and training, were able to accurately collect data that reflect trends found in a comparable researcher-generated database.

Mathematical model for the transport of fluoroquinolone and its resistant bacteria in aquatic environment.

Development of antibiotic resistance in environmental bacteria is a direct threat to public health. Therefore, it becomes necessary to understand the fate and transport of antibiotic and its resistant bacteria. This paper presents a mathematical model for spatial and temporal transport of fluoroquinolone and its resistant bacteria in the aquatic environment of the river. The model includes state variables for organic matter, fluoroquinolone, heavy metals, and susceptible and resistant bacteria in the water column and sediment bed. Resistant gene is the factor which makes bacteria resistant to a particular antibiotic and is majorly carried on plasmids. Plasmid-mediated resistance genes are transferable between different bacterial species through conjugation (horizontal resistance transfer). This model includes plasmid dynamics between susceptible and resistant bacteria by considering the rate of horizontal resistance gene transfer among bacteria and the rate of losing resistance (segregation). The model describes processes which comprise of advection, dispersion, degradation, adsorption, diffusion, settling, resuspension, microbial growth, segregation, and transfer of resistance genes. The mathematical equations were solved by using numerical methods (implicit-explicit scheme) with appropriate boundary conditions. The development of the present model was motivated by the fact that the Musi River is heavily impacted by antibiotic pollution which led to the development of antibiotic resistance in its aquatic environment. The model was simulated for hypothetical pollution scenarios to predict the future conditions under various pollution management alternatives. The simulation results of the model for different cases show that the concentration of antibiotic, the concentration of organic matter, segregation rate, and horizontal transfer rate are the governing factors in the variation of population density of resistant bacteria. The treatment of effluents for antibiotics might be costly for the bulk drug manufacturing industries, but the guidelines can be made to reduce the organic matter which can limit the growth rate of microbes and reduce the total microbial population in the river. The reduction in antibiotic concentration can reduce the selection pressure on bacteria and can limit the population of resistant culture and its influence zone in the river stretch; however, complete removal of antibiotics may not result in complete elimination of antibiotic-resistant bacteria.

An Ecological Study of the Association between Area-Level Green Space and Adult Mortality in Hong Kong

There is evidence that access to green spaces have positive effects on health, possibly through beneficial effects on exercise, air quality, urban heat islands, and stress. Few previous studies have examined the associations between green space and mortality, and they have given inconsistent results. This ecological study relates green space to mortality in Hong Kong from 2006 to 2011. The Normalized Difference Vegetation Index (NDVI), a measure of green space coverage, was measured for 199 small geographic areas in Hong Kong. Negative Binomial Regression Models were fit for mortality outcomes with NDVI, age, gender, population density, and area-level socio-economic variables as predictors, with Generalized Estimating Equations used to control for within-cluster correlation. An interquartile range (0.44 units) higher NDVI was significantly associated with lower cardiovascular (relative risk (RR) = 0.88, 95% confidence interval (CI) = 0.80, 0.98) and diabetes (RR = 0.72, 95% CI = 0.60, 0.92) mortality, and non-significantly associated with lower chronic respiratory mortality (RR = 0.90, 95% CI = 0.79, 1.02). Associations were stronger for males and low-income area residents. Lung cancer mortality had no significant association with green space. Better provision of urban green space, particularly in low-income areas, appears to have potential to reduce mortality in densely-populated Asian cities.

On fuzzy uncertainties on the logistic equation

It is recognized that handling uncertainty is essential to obtain more reliable results in modeling and computer simulation. This paper aims to discuss the logistic equation subject to fuzzy uncertainties in the initial conditions and parameters. Here we consider the population density at a specific time as a fuzzy variable in which the possibility distribution function depends on the possibility distribution functions of the environmental carrying capacity, the initial population density and the intrinsic growth rate. We provide closed-form expressions for the expected value of the fuzzy variables population density and for the time of maximum growth. We also perform some numerical simulations to illustrate our main results.

Spatial Evolution of Human Dialects

The geographical pattern of human dialects is a result of history. Here, we formulate a simple spatial model of language change which shows that the final result of this historical evolution may, to some extent, be predictable. The model shows that the boundaries of language dialect regions are controlled by a length minimizing effect analogous to surface tension, mediated by variations in population density which can induce curvature, and by the shape of coastline or similar borders. The predictability of dialect regions arises because these effects will drive many complex, randomized early states toward one of a smaller number of stable final configurations. The model is able to reproduce observations and predictions of dialectologists. These include dialect continua, isogloss bundling, fanning, the wavelike spread of dialect features from cities, and the impact of human movement on the number of dialects that an area can support. The model also provides an analytical form for Séguy’s curve giving the relationship between geographical and linguistic distance, and a generalization of the curve to account for the presence of a population center. A simple modification allows us to analytically characterize the variation of language use by age in an area undergoing linguistic change.15 MoreReceived 28 February 2017DOI:https://doi.org/10.1103/PhysRevX.7.031008Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasPatterns in complex systemsPhase separationSelf-organized systemsSocial systemsInterdisciplinary PhysicsStatistical Physics

A biogeographical perspective on the variation in mouse lemur density throughout Madagascar

Abstract Madagascar is home to the smallest primates in the world, the mouse lemurs (Microcebus species). Twenty‐four species of mouse lemur are currently recognised and are found in variable ecosystems, from dry forests and spiny deserts to humid forests. Due to their widespread distribution and the large number of sympatric species, mouse lemurs can be used as a model to understand the linkages among species richness, population density, and habitat. As all lemurs are threatened by habitat loss and fragmentation, this information can also be used to inform conservation management. We hypothesise that on an island‐wide scale, we will find higher population densities in western dry forests than in eastern humid forests because the western dry forests exhibit lower species richness, more sympatric habitat use, and lower resource stability than the eastern humid forests. We conducted a literature review of population density estimates of known mouse lemur species, and used those data to conduct a meta‐analysis and estimate overall average population density by geographic region. Our findings suggest that mouse lemur species living in western dry forest generally exhibit higher densities than those in eastern humid forests. This may be partly explained by higher habitat fragmentation in western dry forests, where species co‐occur, but is likely to be a function of the magnitude and variability in seasonally available resources in each forest type. Higher seasonality results in less constant food availability and lower levels of environmental predictability, fostering species capable of coping with environmental change and maintaining high densities throughout periods of resource paucity. Our study highlights the importance of conducting Microcebus population density research that adheres to standardised methodological approaches. We point to the need for population density estimates for several species for which data are lacking. Such knowledge is important to assess the conservation status of these species, but also to enhance our ability to identify the macro‐biogeographical and local ecological drivers of interspecific and intraspecific variability in population density.

Dispersal in dendritic networks: Ecological consequences on the spatial distribution of population densities

AbstractUnderstanding the consequences of spatial structure on ecological dynamics is a central theme in ecology. Recently, research has recognised the relevance of river and river‐analogue network structures, because these systems are not only highly diverse but also rapidly changing due to habitat modifications or species invasions.Much of the previous work on ecological and evolutionary dynamics in metapopulations and metacommunities in dendritic river networks has been either using comparative approaches or was purely theoretical. However, the use of microcosm experiments provides the unique opportunity to study large‐scale questions in a causal and experimental framework.We conducted replicated microcosm experiments, in which we manipulated the spatially explicit network configuration of a landscape and addressed how linear versus dendritic connectivity affects population dynamics, specifically the spatial distribution of population densities, and movement behaviour of the protist model organismTetrahymena pyriformis. We tracked population densities and individual‐level movement behaviour of thousands of individuals over time.At the end of the experiment, we found more variable population densities between patches in dendritic networks compared to linear networks, as predicted by theory. Specifically, in dendritic networks, population densities were higher at nodes that connected to headwaters compared to the headwaters themselves and to more central nodes in the network. These differences follow theoretical predictions and emerged from the different network topologies per se. These differences in population densities emerged despite weakly density‐dependent movement.We show that differences in network structure alone can cause characteristic spatial variation in population densities. While such differences have been postulated by theoretical work and are the underlying precondition for differential dispersal evolution in heterogeneous networks, our results may be the first experimental demonstration thereof. Furthermore, these population‐level dynamics may affect extinction risks and can upscale to previously shown metacommunity level diversity dynamics. Given that many species in natural river systems exhibit strong spatiotemporal patterns in population densities, our work suggests that abundance patterns should not only be addressed from a local environmental perspective, but may be the outcome of processes that are inherently driven by the respective habitat network structure.