The contributions of climate and land use/cover changes to water yield services considering geographic scale.

Background: Water yield services are critical for maintaining ecological sustainability and regional economies. Climate change and land use/cover change (LUCC) significantly affect regional water yield, but the spatiotemporal variability of water yield services has been overlooked in previous studies. This study aims to explore the relative contributions of climate and land use/cover changes to water yield services at both grid and subwatershed scales. Methods: This study employed the InVEST model to calculate the water yield in the study area and employed a multi-scenario simulation approach to investigate the impacts of climate change and LUCC on water yield at both grid and subwatershed scales. Furthermore, the contributions of these two types of changes to water yield were quantified. Results: Firstly, upstream areas experience significantly lower annual average precipitation, temperature, and potential evapotranspiration than downstream areas, with worsening drought severity. Secondly, urbanization led to significant LUCC, with decreases in farmland and grassland and increases in forest, water, building land, and unused land. Thirdly, the spatial heterogeneity of water yield services remains consistent across different scales, but more pronounced spatial clustering is observed at the subwatershed scale. Fourthly, climate change is the primary factor affecting regional water yield services, surpassing the influence of LUCC. Lastly, LUCC significantly impacts water cycling in watersheds, with vegetation coverage being a critical factor affecting water yield. Conclusion: These findings highlight the need to consider the complex relationships between climate change, LUCC, and water yield services at multiple scales in water resource management.

Population density: What does it really mean in geographical health studies?

Population density is an indicator in many studies, but often with only a cursory explanation of why. Unfortunately, elected officials and the media draw misleading conclusions about population density and public health. After providing three reasons why population density is linked to human health outcomes, using state, county, municipal and neighborhood scale data, we show that population density serves as a surrogate for explaining the geographical distribution of life expectancy and broadband access. However, population density loses its unique contribution when other factors influencing health are included. We urge authors to explain why they include population density in their studies.

Investigation of mechanisms underlying chaotic genetic patchiness in the intertidal marbled crab Pachygrapsus marmoratus (Brachyura: Grapsidae) across the Ligurian Sea.

BACKGROUND: Studies on marine community dynamics and population structures are limited by the lack of exhaustive knowledge on the larval dispersal component of connectivity. Genetic data represents a powerful tool in understanding such processes in the marine realm. When dealing with dispersion and connectivity in marine ecosystems, many evidences show patterns of genetic structure that cannot be explained by any clear geographic trend and may show temporal instability. This scenario is usually referred to as chaotic genetic patchiness, whose driving mechanisms are recognized to be selection, temporal shifts in local population dynamics, sweepstakes reproductive success and collective dispersal. In this study we focused on the marbled crab Pachygrapsus marmoratus that inhabits the rocky shores of the Mediterranean Sea, Black Sea and East Atlantic Ocean, and disperses through planktonic larvae for about 1 month. P. marmoratus exhibits unexpectedly low connectivity levels at local scale, although well-defined phylogeographic patterns across the species' distribution range were described. This has been explained as an effect of subtle geographic barriers or due to sweepstake reproductive success. In order to verify a chaotic genetic patchiness scenario, and to explore mechanisms underlying it, we planned our investigation within the Ligurian Sea, an isolated basin of the western Mediterranean Sea, and we genotyped 321 individuals at 11 microsatellite loci. RESULTS: We recorded genetic heterogeneity among our Ligurian Sea samples with the occurrence of genetic clusters not matching the original populations and a slight inter-population divergence, with the geographically most distant populations being the genetically most similar ones. Moreover, individuals from each site were assigned to all the genetic clusters. We also recorded evidences of self-recruitment and a higher than expected within-site kinship. CONCLUSIONS: Overall, our results suggest that the chaotic genetic patchiness we found in P. marmoratus Ligurian Sea populations is the result of a combination of differences in reproductive success, en masse larval dispersion and local larval retention. This study defines P. marmoratus as an example of marine spawner whose genetic pool is not homogenous at population level, but rather split in a chaotic mosaic of slightly differentiated genetic patches derived from complex and dynamic ecological processes.

Repeatability of Adaptive Radiation Depends on Spatial Scale: Regional Versus Global Replicates of Stickleback in Lake Versus Stream Habitats.

The repeatability of adaptive radiation is expected to be scale-dependent, with determinism decreasing as greater spatial separation among "replicates" leads to their increased genetic and ecological independence. Threespine stickleback (Gasterosteus aculeatus) provide an opportunity to test whether this expectation holds for the early stages of adaptive radiation-their diversification in freshwater ecosystems has been replicated many times. To better understand the repeatability of that adaptive radiation, we examined the influence of geographic scale on levels of parallel evolution by quantifying phenotypic and genetic divergence between lake and stream stickleback pairs sampled at regional (Vancouver Island) and global (North America and Europe) scales. We measured phenotypes known to show lake-stream divergence and used reduced representation genome-wide sequencing to estimate genetic divergence. We assessed the scale dependence of parallel evolution by comparing effect sizes from multivariate models and also the direction and magnitude of lake-stream divergence vectors. At the phenotypic level, parallelism was greater at the regional than the global scale. At the genetic level, putative selected loci showed greater lake-stream parallelism at the regional than the global scale. Generally, the level of parallel evolution was low at both scales, except for some key univariate traits. Divergence vectors were often orthogonal, highlighting possible ecological and genetic constraints on parallel evolution at both scales. Overall, our results confirm that the repeatability of adaptive radiation decreases at increasing spatial scales. We suggest that greater environmental heterogeneity at larger scales imposes different selection regimes, thus generating lower repeatability of adaptive radiation at larger spatial scales.

O uso da escala geográfica na saúde pública: as escalas da leishmaniose visceral / The use of the geographic scale in health: the scales of visceral leishmaniasis

Resumo A escala geográfica tem sido amplamente discutida na tentativa de formar um conceito que dê conta de explicar as diferentes realidades do espaço. Nos diversos seguimentos de planejamento em saúde, faz-se uma adoção das categorias e conceitos geográficos sem entender os problemas inerentes à escala geográfica, o que afeta diretamente nas políticas públicas implantadas e, consequentemente, na vida das pessoas. O objetivo deste artigo foi discutir o conceito de escala a partir dos seus diferentes níveis, e debater a dificuldade de articulá-los por meio da atuação dos órgãos de vigilância em saúde pública brasileira que lidam com a leishmaniose visceral. Realizamos uma revisão de literatura para demonstrar como o debate do conceito de escala geográfica com a saúde é ainda incipiente. Utilizamos conceitos geográficos, integrando as políticas municipais, estaduais e nacional sob a ótica da escala geográfica. Dessa forma, acreditamos que seja possível uma articulação dos órgãos dos sistemas de saúde com a sociedade na transposição de escalas, num acontecer solidário, produzindo um sistema de saúde mais eficaz. A discussão não será aqui esgotada, mas permitirá uma reflexão nas opções teórico-metodológicas em pesquisas e em saúde pública.

Abstract The geographical scale has been broadly discussed in an attempt to formulate a concept that succeeds in explaining different space-related realities. In the various sectors of health planning, geographic categories and concepts have been adopted without understanding the problems inherent to the geographical scale, which directly affects public policies implemented and, consequently, people's lives. The scope of this paper was to discuss the concept of scale based on the different scale levels and the difficulty of their implementation by means of the activities of the organs that operate in public health surveillance that deal with visceral leishmaniasis. A systematic review of the literature was conducted to show how the debate about geographical scale and health is still incipient. Geographical concepts were used, integrating municipal, state and national policies from the perspective of the geographic scale. Thus, the contention is that cooperation between health agencies and society is possible by the transposition of scales, creating an environment of solidarity and a more effective health system. The discussion does not end here, but it will make it viable to reflect on the theoretical and methodological options in research and in public health.

Scale matters: a survey of the concepts of scale used in spatial disciplines.

Scale is a critical factor when studying patterns and the processes that cause them. A variety of approaches have been used to define the concept of scale but confusion and ambiguities remain regarding scale types and their definitions. The objectives of this study were therefore (1) to review existing types and definitions of scale, and (2) to systematically investigate the ambiguities in scale definitions and to determine the applicability of the various scale types and definitions. Through a comprehensive literature review, we identified seven types of scales and designed a survey for the seven definitions of scale and interviewed 150 scientists. The results show that the more cartography related types of scale are relatively well known while the more abstract dimensions are less known and are most ambiguous. Based on graphical examples, participants were asked which spatial scales are most relevant for their work. Surprisingly, composite objects such as a forest stand were most relevant followed by individual objects such as single trees and, lastly, more generalized categorizes or meta-objects such as "forested area". We have drawn some conclusions that will help to clarify the different types of scale in regard to their practical use.

Transforming geographic scale: a comparison of combined population and areal weighting to other interpolation methods.

BACKGROUND: Transforming spatial data from one scale to another is a challenge in geographic analysis. As part of a larger, primary study to determine a possible association between travel barriers to pediatric cancer facilities and adolescent cancer mortality across the United States, we examined methods to estimate mortality within zones at varying distances from these facilities: (1) geographic centroid assignment, (2) population-weighted centroid assignment, (3) simple areal weighting, (4) combined population and areal weighting, and (5) geostatistical areal interpolation. For the primary study, we used county mortality counts from the National Center for Health Statistics (NCHS) and population data by census tract for the United States to estimate zone mortality. In this paper, to evaluate the five mortality estimation methods, we employed address-level mortality data from the state of Georgia in conjunction with census data. Our objective here is to identify the simplest method that returns accurate mortality estimates. RESULTS: The distribution of Georgia county adolescent cancer mortality counts mirrors the Poisson distribution of the NCHS counts for the U.S. Likewise, zone value patterns, along with the error measures of hierarchy and fit, are similar for the state and the nation. Therefore, Georgia data are suitable for methods testing. The mean absolute value arithmetic differences between the observed counts for Georgia and the five methods were 5.50, 5.00, 4.17, 2.74, and 3.43, respectively. Comparing the methods through paired t-tests of absolute value arithmetic differences showed no statistical difference among the methods. However, we found a strong positive correlation (r = 0.63) between estimated Georgia mortality rates and combined weighting rates at zone level. Most importantly, Bland-Altman plots indicated acceptable agreement between paired arithmetic differences of Georgia rates and combined population and areal weighting rates. CONCLUSIONS: This research contributes to the literature on areal interpolation, demonstrating that combined population and areal weighting, compared to other tested methods, returns the most accurate estimates of mortality in transforming small counts by county to aggregated counts for large, non-standard study zones. This conceptually simple cartographic method should be of interest to public health practitioners and researchers limited to analysis of data for relatively large enumeration units.

Scale effects in food environment research: Implications from assessing socioeconomic dimensions of supermarket accessibility in an eight-county region of South Carolina.

Choice of neighborhood scale affects associations between environmental attributes and health-related outcomes. This phenomenon, a part of the modifiable areal unit problem, has been described fully in geography but not as it relates to food environment research. Using two administrative-based geographic boundaries (census tracts and block groups), supermarket geographic measures (density, cumulative opportunity and distance to nearest) were created to examine differences by scale and associations between three common U.S. Census-based socioeconomic status (SES) characteristics (median household income, percentage of population living below poverty and percentage of population with at least a high school education) and a summary neighborhood SES z-score in an eight-county region of South Carolina. General linear mixed-models were used. Overall, both supermarket density and cumulative opportunity were higher when using census tract boundaries compared to block groups. In analytic models, higher median household income was significantly associated with lower neighborhood supermarket density and lower cumulative opportunity using either the census tract or block group boundaries, and neighborhood poverty was positively associated with supermarket density and cumulative opportunity. Both median household income and percent high school education were positively associated with distance to nearest supermarket using either boundary definition, whereas neighborhood poverty had an inverse association. Findings from this study support the premise that supermarket measures can differ by choice of geographic scale and can influence associations between measures. Researchers should consider the most appropriate geographic scale carefully when conducting food environment studies.

Hierarchical Distributed-Lag Models: Exploring Varying Geographic Scale and Magnitude in Associations Between the Built Environment and Health.

It is well known that associations between features of the built environment and health depend on the geographic scale used to construct environmental attributes. In the built environment literature, it has long been argued that geographic scales may vary across study locations. However, this hypothesized variation has not been systematically examined due to a lack of available statistical methods. We propose a hierarchical distributed-lag model (HDLM) for estimating the underlying overall shape of food environment-health associations as a function of distance from locations of interest. This method enables indirect assessment of relevant geographic scales and captures area-level heterogeneity in the magnitudes of associations, along with relevant distances within areas. The proposed model was used to systematically examine area-level variation in the association between availability of convenience stores around schools and children's weights. For this case study, body mass index (weight kg)/height (m)2) z scores (BMIz) for 7th grade children collected via California's 2001-2009 FitnessGram testing program were linked to a commercial database that contained locations of food outlets statewide. Findings suggested that convenience store availability may influence BMIz only in some places and at varying distances from schools. Future research should examine localized environmental or policy differences that may explain the heterogeneity in convenience store-BMIz associations.

Spatial distribution of end-stage renal disease (ESRD) and social inequalities in mixed urban and rural areas: a study in the Bretagne administrative region of France.

BACKGROUND: Several studies have investigated the implication of biological and environmental factors on geographic variations of end-stage renal disease (ESRD) incidence at large area scales, but none of them assessed the implication of neighbourhood characteristics (healthcare supply, socio-economic level and urbanization degree) on spatial repartition of ESRD. We evaluated the spatial implications of adjustment for neighbourhood characteristics on the spatial distribution of ESRD incidence at the smallest geographic unit in France. METHODS: All adult patients living in Bretagne and beginning renal replacement therapy during the 2004-09 period were included. Their residential address was geocoded at the census block level. Each census block was characterized by socio-economic deprivation index, healthcare supply and rural/urban typology. Using a spatial scan statistic, we examined whether there were significant clusters of high risk of ESRD incidence. RESULTS: The ESRD incidence was non-randomly spatially distributed, with a cluster of high risk in the western Bretagne region (relative risk, RR = 1.28, P-value = 0.0003). Adjustment for sex, age and neighbourhood characteristics induced cluster shifts. After these adjustments, a significant cluster (P = 0.013) persisted. CONCLUSIONS: Our spatial analysis of ESRD incidence at a fine scale, across a mixed rural/urban area, indicated that, beyond age and sex, neighbourhood characteristics explained a great part of spatial distribution of ESRD incidence. However, to better understand spatial variation of ESRD incidence, it would be necessary to research and adjust for other determinants of ESRD.

Identification of the impact of crime on physical activity depends upon neighbourhood scale: multilevel evidence from 203,883 Australians.

Equivocal findings on crime as a deterrent for physical activity may be due to effects of geographic scale on exposure measurement. To investigate this hypothesis, physical activity was measured in 203,883 Australians and linked to standardised crime counts within small ('Census Collection Districts'; approx. 330 residents) and larger areas ('Statistical Local Areas'; approx. 32,000 residents). A median rate ratio of 2.26 indicated substantive geographic variation in moderate-to-vigorous physical activity (MVPA). Adjusting for confounders, multilevel negative binomial regression reported lower MVPA with more crime consistently in small, but not in larger areas. Reducing small pockets of local crime may encourage more physically active lifestyles.