Spatial scale effects on the value of ecosystem services in China's terrestrial area.

Identifying the response characteristics of ecosystem service value (ESV) to changes in spatial scales, known as spatial scale effects, is crucial in guiding the development of corresponding management strategies. This paper examines ESV in China's terrestrial area during the year 2020, revealing the spatial aggregation characteristics of ESV and the trade-off and synergistic relationships of ecosystem services at different spatial scales, ranging from 1 km × 1 km-10 km × 10 km, with a gradient of 1 km. The results indicate: 1) The distribution pattern of ESV in China's terrestrial area is "high in the southeast and low in the northwest." 2) The spatial characteristics of ESV in China's terrestrial area undergo a distinct transition at the 3 km × 3 km scale. In detail, the spatial clustering features show a trend of first rising and then falling with the increase in spatial scale, while the synergistic relationships between different ecosystem services strengthen and the trade-off relationships weaken with the increase of the spatial scale. These findings can inform the formulation of differentiated ecological protection compensation policies and enable cross-area trading of ecological values in China.

Integrating very high resolution environmental proxies in genotype-environment association studies.

Landscape genomic analyses associating genetic variation with environmental variables are powerful tools for studying molecular signatures of species' local adaptation and for detecting candidate genes under selection. The development of landscape genomics over the past decade has been spurred by improvements in resolutions of genomic and environmental datasets, allegedly increasing the power to identify putative genes underlying local adaptation in non-model organisms. Although these associations have been successfully applied to numerous species across a diverse array of taxa, the spatial scale of environmental predictor variables has been largely overlooked, potentially limiting conclusions to be reached with these methods. To address this knowledge gap, we systematically evaluated performances of genotype-environment association (GEA) models using predictor variables at multiple spatial resolutions. Specifically, we used multivariate redundancy analyses to associate whole-genome sequence data from the plant Arabis alpina L. collected across four neighboring valleys in the western Swiss Alps, with very high-resolution topographic variables derived from digital elevation models of grain sizes between 0.5 m and 16 m. These comparisons highlight the sensitivity of landscape genomic models to spatial resolution, where the optimal grain sizes were specific to variable type, terrain characteristics, and study extent. To assist in selecting variables at appropriate spatial resolutions, we demonstrate a practical approach to produce, select, and integrate multiscale variables into GEA models. After generalizing fine-grained variables to multiple spatial resolutions, a forward selection procedure is applied to retain only the most relevant variables for a particular context. Depending on the spatial resolution, the relevance for topographic variables in GEA studies calls for integrating multiple spatial scales into landscape genomic models. By carefully considering spatial resolutions, candidate genes under selection by a more realistic range of pressures can be detected for downstream analyses, with important applied implications for experimental research and conservation management of natural populations.

[Spatial Patterns of Soil Bacterial Communities and N-cycling Functional Groups Along an Altitude Gradient in Datong River Basin].

The altitude distribution patterns of soil microorganisms and their driving mechanisms are crucial for understanding the consequences of climate change on terrestrial ecosystems. There is an obvious altitude difference in Datong River Basin in the Qilian Mountains. Two spatial scale transections were set up along the mountain slope (with altitude spanning 1 000 m) and the mainstream direction (with altitude spanning 300-500 m), respectively. The distribution characteristics of the soil bacterial community structure and diversity along the altitude gradients were examined using high-throughput sequencing technology. Based on the FAPROTAX database, the altitude distribution patterns of nitrogen cycling functional groups were analyzed to investigate the major environmental factors influencing the altitude distribution patterns of soil bacterial communities. The findings revealed that:① Soil physicochemical characteristics varied significantly with altitude. The content of total nitrogen (TN) and nitrate nitrogen (NO3-) were positively correlated with the altitude (P < 0.01), whereas the soil bulk density and pH were negatively connected (P < 0.001). ② The abundance of OTU increased significantly along the altitude (P < 0.01), and the richness and diversity indices increased along the altitude, although the trend was not statistically significant (P > 0.05). ③ The predominant bacterial communities were Acidobacteria, Proteobacteria, and Bacteroidetes, and as altitude climbed, their relative abundances varied between increasing, decreasing, and slightly decreasing, respectively. ④ The nitrogen cycling processes involved 13 functional groups, primarily nitrification, aerobic ammonia oxidation, aerobic nitrite oxidation, etc. As the altitude increased, the response law changed, with an increase in the abundance of nitrobacteria (P < 0.01), a slight increase in the abundance of aerobic ammonia-oxidizing bacteria and nitrite-oxidizing bacteria, and a hump-back tendency in bacteria abundance for nitrogen respiration. ⑤ Redundancy analysis revealed that the key determinants influencing soil bacterial populations at the phylum level were altitude, pH, and the content of NH4+. Mantel analysis showed that the dominant groups of soil bacterial nitrogen cycling were all statistically and significantly driven by altitude (P < 0.01). ⑥ The α-diversity of the bacterial community with increasing altitude were both increased along the mountain slope and the mainstream direction, but the soil properties, the abundance of N-cycling functional groups, and the main environmental factors differed. Therefore, it is of great significance to explore the altitude distribution pattern of soil microorganisms at different spatial scales.

[Spatial scale effects of landscape patterns on non-point source pollution: A case study of Taizi River Basin in Northeast China]. / éžç‚¹æºæ±¡æŸ“å¯¹æ™¯è§‚æ ¼å±€å“åº”çš„ç©ºé—´å°ºåº¦æ•ˆåº”­­ä»¥ä¸œåŒ—太子河流域为例.

River water quality is influenced by natural processes and human activities. Multi-scale landscape patterns can affect river water quality by altering the generation and transport processes of pollutants at different spatial scales. Taking Taizi River Basin in Northeast China as an example, we analyzed the relationship between landscape patterns and non-point source pollution in rivers based on water quality monitoring data and land use data by using correlation analysis and redundancy analysis methods. We aimed to determine the key spatial scales for the responses of landscape patterns to non-point source pollution and identify the key landscape indices influencing river non-point source pollution. The results showed that water quality of Taizi River Basin had seasonal differences, with better water quality during the flood season than non-flood season. Spatially, total nitrogen (TN) and total phosphorus (TP) were higher at the confluence points of tributaries and downstream areas. The impact of landscape patterns on non-point source pollution was stronger during the non-flood season than the flood season, while the influence on TN was stronger than on TP. At the spatial scale of within 500 m buffer zone during the flood season and at the sub-watershed scale during the non-flood season, landscape patterns showed the highest explanatory power for the variations of TN and TP. At the type level, built-up land, cropland, and bare land were positively correlated with TN and TP, while forest was negatively correlated with TN and TP, which were the key types influencing non-point source pollution. At the landscape level, patch density, percentage of like adjacencies, and contagion index were key indicators affecting watershed water quality. Lower patch density was associated with better connectivity and aggregation of "sink" landscapes, leading to better purification effects on TN, but more pronounced retention effects on TP. Conversely, higher landscape diversity and denser pattern of multiple types would cause the deterioration of water quality. Our results suggested that rational allocation of landscape types within the watershed and riparian buffer zones, appropriately enriching landscape diversity, and optimizing landscape aggregation and connectivity would be effective measures for improving water quality and achieving sustainable ecological management.

The Impact of Scale on Extracting Individual Mobility Patterns from Location-Based Social Media.

Understanding human movement patterns is crucial for comprehending how a city functions. It is also important for city planners and policymakers to create more efficient plans and policies for urban areas. Traditionally, human movement patterns were analyzed using origin-destination surveys, travel diaries, and other methods. Now, these patterns can be identified from various geospatial big data sources, such as mobile phone data, floating car data, and location-based social media (LBSM) data. These extensive datasets primarily identify individual or collective human movement patterns. However, the impact of spatial scale on the analysis of human movement patterns from these large geospatial data sources has not been sufficiently studied. Changes in spatial scale can significantly affect the results when calculating human movement patterns from these data. In this study, we utilized Weibo datasets for three different cities in China including Beijing, Guangzhou, and Shanghai. We aimed to identify the effect of different spatial scales on individual human movement patterns as calculated from LBSM data. For our analysis, we employed two indicators as follows: an external activity space indicator, the radius of gyration (ROG), and an internal activity space indicator, entropy. These indicators were chosen based on previous studies demonstrating their efficiency in analyzing sparse datasets like LBSM data. Additionally, we used two different ranges of spatial scales-10-100 m and 100-3000 m-to illustrate changes in individual activity space at both fine and coarse spatial scales. Our results indicate that although the ROG values show an overall increasing trend and the entropy values show an overall decreasing trend with the increase in spatial scale size, different local factors influence the ROG and entropy values at both finer and coarser scales. These findings will help to comprehend the dynamics of human movement across different scales. Such insights are invaluable for enhancing overall urban mobility and optimizing transportation systems.

Variation in fine-scale water table depth drives abundance of a unique semi-terrestrial crayfish species.

With anthropogenic changes altering the environment and the subsequent decline of natural habitats, it can be challenging to predict essential habitats for elusive and difficult to study taxa. Primary burrowing crayfish are one such group due to the complexity in sampling their semi-terrestrial, subterranean habitat. Sampling burrows usually requires a labor-intensive, time-consuming excavation or trapping process. However, limited information on burrowing crayfish suggests that fine-scale habitat variation may drive burrowing crayfish habitat choice. This project aimed to evaluate the fine-scale habitat characteristics that influence burrowing crayfish presence and abundance at a large, restored-remnant grassland preserve in north-central Illinois. We documented burrow abundance and quadrat-specific habitat variables such as root biomass, canopy cover, apparent seasonal high-water table (water table) depth and dominant vegetation at sites with and without burrowing crayfish populations. Data was recorded at every quadrat and analyzed using generalized linear mixed models. A total of 21 models were created to determine what habitat variables affected burrow presence and abundance. We found that the water table depth was a significant driver of burrow presence and abundance. Root biomass and vegetation cover were not significant drivers, although they did show up in the final models, explaining the data. These findings demonstrate empirical support for previous observations from other burrowing crayfish research and demonstrate the influence of fine-scale habitat when modeling elusive taxa requirements.

Spatial distribution of benthic taxonomic and functional diversity in the Yellow River Basin: From ecological processes to associated determinant factors.

One of the fundamental objectives in ecology is to investigate the ecological processes and associated factors governing the abundance and spatial distribution patterns of biodiversity. However, the reaction of biological communities to environmental degradation remains relatively unknown, even for ecologically crucial communities like macroinvertebrates in aquatic ecosystems. Here, we sampled 117 locations to quantify relative contributions of geographical and environmental factors, including water quality, land use, climate, and hydrological factors, to determine the absolute and relative compositions of macroinvertebrate communities and their spatial distribution in the Yellow River Basin (YRB), the sixth-longest river system on Earth. We assessed relative roles of species sorting and dispersal in determining macroinvertebrate community structure along YRB. Our results demonstrated that alpha and beta diversity indices showed an increase from the up- to low-reaches of YRB. The middle and low-reaches exhibited elevated species diversity and both regions exhibited relatively stable community compositions. The biodiversity of macroinvertebrates was influenced by a combination of geographical factors and environmental variables, with environmental factors predominantly serving as the principal determinants. Results of multiple linear regression and variance decomposition showed that the effect of environmental factors was approximately three times greater than that of spatial factors. These findings provide support for the hypothesis that species sorting, driven by environmental gradients, plays a significant role in shaping the community structure of macroinvertebrates in running water ecosystems at the basin scales. Moreover, the factors contributing to substantial shifts in biodiversity across different segments of YRB indicate that distinct river sections have been influenced by varying stressors, with downstream areas being more susceptible to the impacts of water pollution and urbanization resulting from human activities.

Variability of soft-bottom macrobenthic invertebrates at different spatial scales: Comparisons between habitats and seasons.

Studies focusing on patterns of spatial variation in marine soft-bottom assemblages suggest that variability is mainly concentrated at small spatial scale (from tens of centimeters to few meters), but there is still a lack of knowledge about the consistency of this spatial pattern across habitats and seasons. To address this issue, we quantified the variability in the structure of macrozoobenthic assemblages and in the abundance of dominant macroinvertebrate species in the Mellah Lagoon (Algeria) at three spatial scales, i.e., Plot (meters apart), Station (10's m apart) and Site (kms apart) scale, in Ruppia maritima (Ruppia) beds and unvegetated sediments (Unvegetated), and in two dates in winter and two dates in summer 2016. Spatial variability of the most dominant bivalve Mytilaster marioni varied significantly between habitats, but consistent across the two seasons, with a more heterogeneous distribution in Ruppia than in Unvegetated at the Station scale. Furthermore, a second-order interaction among the hierarchical nature of spatial variability, season and habitat emerged for the assemblage structure. Spatial variability between habitats varied significantly in winter, with the largest variation at the Plot scale in Unvegetated and more heterogenous assemblages at the Plot and Site scales than at the Station scale in Ruppia, but did not vary in summer when most of the variance was at the Site scale. We demonstrate that the scales of influence of the processes operating in the Mellah Lagoon are contingent on the specific habitat and/or period of the year at which the study was conducted, highlighting the importance of examining all these sources of variation simultaneously to increase the accuracy of explanatory models derived from the observed patterns in sedimentary environments.

Spatial difference on nitrogen removal in the water based on different resolutions for Sanhuanpao wetland, Northeast China.

The research on the deviations caused by different resolutions is relevant to the study of spatial scale effects. In 2018, spatial interpolations were performed using the removal ratios of the TN, NH4-N, and NO3-N of the layers of different resolutions, respectively. Based on the mean and the standard deviation, the area, shape, and position were obtained for four levels related to the removal ratios of the three nitrogen forms. The linear and 6th function fitting methods were used to reveal the differences in nitrogen removal in wetland water at different spatial resolutions. The results showed that a resolution of 25 times the original was the key scale of the spatial effects. Due to the fact that 52 of the 72 functions did not reach a significant level (P < 0.05), the spatial scale effect of the nitrogen removal was mainly characterized by disorderly fluctuations. The results have a certain extrapolation value for the analysis of spatial scale effects. PRACTITIONER POINTS: The resolution difference was not sufficient to change the spatial pattern of the geographic phenomena. The resolution of 25 times the original was the important scale for determining spatial effects. When studying the spatial scale effects caused by differences in resolution, it was necessary to comprehensively consider various resolutions.

[Effects of Land Use Structure and Spatial Pattern at Different Temporal and Spatial Scales on Water Quality in Suzhou Creek].

Relationships between land use and water quality of rivers and lakes vary spatially and temporally. These variations were analyzed using spatial analysis and mathematical statistical methods for the Suzhou Creek in Shanghai. Based on the data of water quality and land use in 2001， 2005， 2010， 2015， and 2020， five spatial scales （200， 500， 1 000， 2 000， and 5 000 m reach buffer） of the landscape pattern were extracted using correlation and redundancy analysis to explore the impact of land use composition and spatial pattern on water quality at different spatial and temporal scales. The results showed that： ① the water quality of Suzhou Creek has gradually improved in the past 20 years； other indicators were between Class II to Class IV in 2020 except TN， and TN was the main pollutant. ② The main land use type of the buffer zone was construction land， and the proportion of greenland and woodland showed a small growth trend. ③ The water quality was closely related to landscape pattern， showing temporal and spatial scale effects. On the time scale， indicators such as construction land， agricultural land， landscape dominance， aggregation， and diversity had significant correlations with various water quality parameters， and there was an inverse correlation in 2010 compared with that in other years for NH4+-N， TP， and TN. The landscape pattern in 2001 had the greatest explanation for water quality， with an explanation rate of 93.65%. The impact of greenland and woodland on water quality has begun to emerge in the past 10 years. ④ On the spatial scale， there were significant correlations between greenland and woodland， patch number， landscape shape index， diversity index， and water quality. There was a strong positive regulatory effect of greenland and woodland on NH4+-N， TP， and TN at the scale of 2 000 m. The patch number and landscape shape index had relatively strong regulatory effects on water quality on a larger spatial scale， whereas the Shannon diversity index had a better positive regulatory effect on water quality on a small scale. The landscape pattern within a buffer of 2 000 m had the highest interpretation degree for all factors， with an explanation rate of 68.47%. The study showed that rationally planning the proportion of greenland and woodland within the 2 000 m buffer zone and optimizing its landscape configuration is an important measure to purify the surface water quality of Suzhou Creek.

Effects of landscape pattern on water quality at multi-spatial scales in Wuding River Basin, China.

Urbanization and agricultural land use have led to water quality deterioration. Studies have been conducted on the relationship between landscape patterns and river water quality; however, the Wuding River Basin (WDRB), which is a complex ecosystem structure, is facing resource problems in river basins. Thus, the multi-scale effects of landscape patterns on river water quality in the WDRB must be quantified. This study explored the spatial and seasonal effects of land use distribution on river water quality. Using the data of 22 samples and land use images from the WDRB for 2022, we quantitatively described the correlation between river water quality and land use at spatial and seasonal scales. Stepwise multiple linear regression (SMLR) and redundancy analyses (RDA) were used to quantitatively screen and compare the relationships between land use structure, landscape patterns, and water quality at different spatial scales. The results showed that the sub-watershed scale is the best spatial scale model that explains the relationship between land use and water quality. With the gradual narrowing of the spatial scale range, cultivated land, grassland, and construction land had strong water quality interpretation abilities. The influence of land use type on water quality parameter variables was more distinct in rainy season than in the dry season. Therefore, in the layout of watershed management, reasonably adjusting the proportion relationship of vegetation and artificial building land in the sub-basin scale and basin scope can realize the effective control of water quality optimization.

Access to automated external defibrillators and first responders: Associations with socioeconomic factors and income inequality at small spatial scales.

Aim: The 2021 European Resuscitation Council (ERC) guidelines recommend two automated external defibrillators (AEDs)/km2 and at least 10 first responders/km2. We examined 1) access to AEDs and volunteer first responders in line with these guidelines and 2) its associations with socioeconomic factors and income inequality, focusing on small spatial scales. Method: We considered data on 776 AEDs in February 2022 and 1,173 out-of-hospital cardiac arrests (OHCAs) including 713 OHCA with app-alerted volunteer first responders from February to September 2022 in Berlin. We fit multilevel models to analyse AED area coverage and Poisson models to examine first responder availability across 12 districts and 536 neighbourhoods. Results: Median AED area coverage according to the 2021 ERC guidelines was 43.1% (interquartile range (IQR) 2.3-87.2) at the neighbourhood level and median number of available first responders per OHCA case was one (IQR 0.0-1.0). AED area coverage showed a positive association with average income tax per capita, with better coverage in the highest compared to the lowest quartile neighbourhoods (coefficient: 0.13, 95% confidence interval (CI): 0.01-0.25). First responder availability was not associated with income tax. AED area coverage and first responder availability were positively associated with income inequality, with better coverage (coefficient: 0.13, 95% CI: 0.04-0.23) and availability (rate ratio: 1.31, 95% CI: 1.03-1.67) in quartiles of highest as compared to lowest inequality. Conclusion: Access to resuscitation resources is neither equitable nor in accordance with the 2021 ERC guidelines. Ensuring better access necessitates understanding of socioeconomic factors and income inequality at small spatial scales.

Spatial scale effects on associations between built environment and cognitive function: Multi-Ethnic Study of Atherosclerosis.

Built environments have the potential to favorably support cognitive function. Despite growing work on this topic, most of the work has ignored variation in the spatial scale of the effect. The issue with spatial scale effects is that the size and shape of the areal unit within which built environment characteristics are measured naturally influence the built environment exposure metric and thus the estimated associations with health. We used spatial distributed lag modeling (DLM) to estimate how associations between built environment exposures (walkable destinations [WD], social destinations [SD]) and change in cognition varied across distance of these destinations from participants' residences. Cognition was assessed as maintained/improved processing speed (PS) and global cognition (GC). Person-level data from Exam 5 (2010-2012) and Exam 6 (2016-2018) of the Multi-Ethnic Study of Atherosclerosis was used (N = 1380, mean age 67). Built environment data were derived from the National Establishment Time Series. Higher availability of walkable and social destinations at closer distance from participants' residence was associated with maintained/improved PS. The adjusted associations between maintained/improved PS and destinations waned with increasing distance from the residence; associations were evident until approximately 1.9-km for WD and 1.5-km for SD. Associations were most apparent for participants living in areas with high population density. We found little evidence for associations between change in GC and built environment at any distance. These results highlight the importance of identifying appropriate spatial scale to understand the mechanisms for built environment-cognition associations.

From individual leaves to forest stands: importance of niche, distance decay, and stochasticity vary by ecosystem type and functional group for fungal community composition.

Community assembly is influenced by environmental niche processes as well as stochastic processes that can be spatially dependent (e.g. dispersal limitation) or independent (e.g. priority effects). Here, we sampled senesced tree leaves as unit habitats to investigate fungal community assembly at two spatial scales: (i) small neighborhoods of overlapping leaves from differing tree species and (ii) forest stands of differing ecosystem types. Among forest stands, ecosystem type explained the most variation in community composition. Among adjacent leaves within stands, variability in fungal composition was surprisingly high. Leaf type was more important in stands with high soil fertility and dominated by differing tree mycorrhizal types (sugar maple vs. basswood or red oak), whereas distance decay was more important in oak-dominated forest stands with low soil fertility. Abundance of functional groups was explained by environmental factors, but predictors of taxonomic composition within differing functional groups were highly variable. These results suggest that fungal community assembly processes are clearest for functional group abundances and large spatial scales. Understanding fungal community assembly at smaller spatial scales will benefit from further study focusing on differences in drivers for different ecosystems and functional groups, as well as the importance of spatially independent factors such as priority effects.

Microscale dispersion of intertidal seagrass macrofauna.

Previous studies of dispersion of intertidal seagrass-associated macrobenthos in subtropical Moreton Bay, Queensland, showed that patchiness characterised its assemblage abundance with scale-invariant magnitude across areas ranging from >8000 to 0.1 m2. Those studies were here continued across the smaller scales (down to 0.014 m2) arguably more relevant to the dominant 2-10 mm long animals, using 16 replicate blocks of 5x5 contiguous 0.0024 m2 cores nested within the previously studied site. At microscales ≥0.09 m2, the earlier congruence of conclusions derived from patchiness indices and spatial autocorrelation broke down. At >0.014 m2, adjacent points (cores) no longer together formed larger spatial units of related abundance (i.e. showed no autocorrelation), but point abundances were still highly disparate (as reflected in patchiness indices). Congruent indications of patchiness only manifested at 0.014 m2 spatial scales. Assemblage dispersion pattern was partly consequent on one microgastropod (Pseudoliotia) occurring superabundantly in scattered 0.0024 m2 hotspots.

Biodiversity patterns of the benthic macrofaunal communities across the intertidal sedimentary shores of two Antarctic islands.

Antarctic benthic ecosystems support a unique fauna characterized by high levels of diversity and endemism. However, our knowledge of the macrofauna communities across the Antarctic intertidal sedimentary shore is limited, and their fundamental ecological features, including spatial variability, remain poorly understood. This study aimed to investigate the abundance, community structure (i.e. taxa-specific abundance), and biodiversity patterns (α-, ß-, and λ-diversity) of benthic macrofauna communities on intertidal sedimentary shores of two Antarctic islands (South Shetland archipelago, N of Antarctic Peninsula): Livingston and Deception. We conducted a quantitative sampling during two Austral summer campaigns (2004 and 2005), studying eleven intertidal sites, with five sites located on Livingston and six on Deception. Our results demonstrated a significantly higher abundance of intertidal benthic macrofauna communities on Livingston than on Deception. Furthermore, significant differences in community structure were observed between the two islands. In terms of biodiversity patterns, there were no significant differences in the number of taxa within communities (α-diversity) between the two islands. However, significant differences in the variation of community composition (determined by the number and identity of taxa) between intertidal sites (ß-diversity) were observed, shedding light on the higher total taxa count (λ-diversity) on Livingston compared to Deception. We suggest that the island-specific characteristics (e.g., granulometric characteristics, ice disturbance, sedimentation rates, and geothermal activity) determine the differences observed in macrofauna communities. However, other ecological processes and factors are operating on different spatial and temporal scales (e.g., population dynamics, biotic interactions, oceanographic conditions, and climate change) that influence the occurrence and abundance of macrofaunal taxa. Our findings contribute to the fundamental understanding of the spatial variability of these communities and provide essential information for better management decisions and conservation practices in Antarctic coastal ecosystems.

Understanding how environmental degradation, microclimate, and management shape honey production across different spatial scales.

Although the abundance, survival, and pollination performance of honeybees are sensitive to changes in habitat and climate conditions, the processes by which these effects are transmitted to honey production and interact with beekeeping management are not completely understood. Climate change, habitat degradation, and beekeeping management affect honey yields, and may also interact among themselves resulting in indirect effects across spatial scales. We conducted a 2-year, multi-scale study on Chiloe Island (northern Patagonia), where we evaluated the most relevant environmental and management drivers of honey produced by stationary beekeepers. We found that the effects of microclimate, habitat, and management variables changed with the spatial scale. Among the environmental variables, minimum temperature, and cover of the invasive shrub, gorse (Ulex europaeus) had the strongest detrimental impacts on honey production at spatial scales finer than 4 km. Specialized beekeepers who adopted conventional beekeeping and had more mother colonies were more productive. Mean and minimum temperatures interacted with the percentage of mother colonies, urban cover, and beekeeping income. The gorse cover increased by the combination of high temperatures and the expansion of urban lands, while landscape attributes, such as Eucalyptus plantation cover, influenced beekeeping management. Results suggest that higher temperatures change the available forage or cause thermal stress to honeybees, while invasive shrubs are indicators of degraded habitats. Climate change and habitat degradation are two interrelated environmental phenomena whose effects on beekeeping can be mitigated through adaptive management and habitat restoration.

Multi-scale response relationship between water quality of rivers entering lakes from different pollution source areas and land use intensity: a case study of the three lakes in central Yunnan.

As the main supply source of lakes, the water quality of the rivers entering the lakes directly determines the water safety and sustainable development of the lakes. Human activities are the direct cause of changes in the water quality of rivers entering lakes, and land use intensity is the direct manifestation of human activities on the land surface. Although significant progress has been made in studying the relationship between land use changes and water quality in lakes, there is still a lack of research on exploring the relationship between land use intensity and water quality at multiple scales, especially in comparative studies of different pollution source areas. To address this problem, this study used Pearson's correlation analysis and land use intensity index method to explore the response relationship between river water quality and land use intensity at different spatial and temporal scales and different pollution source areas using three lakes in central Yunnan as examples. The results showed that land use intensity was generally positively correlated with water quality, but the response relationship between land use intensity and different water quality indicators was significantly different at different scales and for different pollution source areas. Compared to non-urban areas, the impact of land use intensity on water quality is more significant in urban areas. Compared to the rainy season, the correlation between CODNa, TP, and NH3-N values and land use intensity is stronger during the dry season, while the correlation between COD, TN, and land use intensity is weaker during the dry season. When viewed at different scales, different water quality indicators have different scale effects, but overall, the larger the scale, the stronger the correlation. Therefore, in the work of lake water environmental governance, it is necessary to consider comprehensively from multiple scales and perspectives and adopt measures that are more suitable for regional water pollution prevention and control.

Evaluation of impact of land use and landscape metrics on surface water quality in the northeastern part along Lake Tanganyika, Africa.

As the second deepest lake in Africa, Lake Tanganyika plays an important role in supplying fish protein for the catchment's residents and is irreplaceable in global biodiversity. However, the lake's water environment is threatened by socioeconomic development and rapid population growth along the lake. This study analyzed the spatial scale effects and seasonal dependence of land use types and landscape metrics on water quality in 16 sub-basins along northeastern Lake Tanganyika at different levels of urbanization. The results revealed that land use types had a higher influence on water quality in urban areas than that in rural areas; the explanatory variance in the urban area was 0.78-0.96, while it was 0.21-0.70 in the rural area. The explanatory ability of land use types on water quality was better at the buffer scale than at the sub-watershed scale, and the 500 m buffer scale had the highest explanatory ability in the urban area and rural area both in the rainy season and dry season, and artificial surface and arable land were the main contributing factors. And this phenomenon was more obvious in dry season than in rainy season. We identified that CONTAG was the key landscape metric in urban area and was positively correlated with nutrient variables, indicating that water quality degraded in less fragmented landscapes. The sub-watershed scale had the highest explained ability, while in rural area, the 1500 m buffer scale had the highest explained ability and IJI had the highest explanatory variance, which had a negative effect on water quality. Research on the relationship between land use and water quality would help assess the water quality in the unmonitored watershed as monitoring is expensive and time-consuming in low-income area. This knowledge would provide guideline to watershed managers and policymakers to prioritize the future land use development within Lake Tanganyika basin.

Host-Parasite Coevolution in Continuous Space Leads to Variation in Local Adaptation across Spatial Scales.

AbstractPrevious host-parasite coevolutionary theory has focused on understanding the determinants of local adaptation using spatially discrete models. However, these studies fall short of describing patterns of host-parasite local adaptation across spatial scales. In contrast, empirical work demonstrates that patterns of adaptation depend on the scale at which they are measured. Here, we propose a mathematical model of host-parasite coevolution in continuous space that naturally leads to a scale-dependent definition of local adaptation. In agreement with empirical research, we find that patterns of adaptation vary across spatial scales. In some cases, not only the magnitude of local adaptation but also the identity of the locally adapted species will depend on the spatial scale at which measurements are taken. Building on our results, we suggest a way to consistently measure parasite local adaptation when continuous space is the driver of cross-scale variation. We also describe a way to test whether continuous space is driving cross-scale variation. Taken together, our results provide a new perspective that can be used to understand empirical observations previously unexplained by theoretical expectations and deepens our understanding of the mechanics of host-parasite local adaptation.