A highly resolved network reveals the role of terrestrial herbivory in structuring aboveground food webs.

Comparative studies suggest remarkable similarities among food webs across habitats, including systematic changes in their structure with diversity and complexity (scale-dependence). However, historic aboveground terrestrial food webs (ATFWs) have coarsely grouped plants and insects such that these webs are generally small, and herbivory is disproportionately under-represented compared to vertebrate predator-prey interactions. Furthermore, terrestrial herbivory is thought to be structured by unique processes compared to size-structured feeding in other systems. Here, we present the richest ATFW to date, including approximately 580 000 feeding links among approximately 3800 taxonomic species, sourced from approximately 27 000 expert-vetted interaction records annotated as feeding upon one of six different resource types: leaves, flowers, seeds, wood, prey and carrion. By comparison to historical ATFWs and null ecological hypotheses, we show that our temperate forest web displays a potentially unique structure characterized by two properties: (i) a large fraction of carnivory interactions dominated by a small number of hyper-generalist, opportunistic bird and bat predators; and (ii) a smaller fraction of herbivory interactions dominated by a hyper-rich community of insects with variably sized but highly specific diets. We attribute our findings to the large-scale, even resolution of vertebrate, insect and plant guilds in our food web.This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Multidimensional beta-diversity across local and regional scales in a Chinese subtropical forest: The role of forest structure.

Beta-diversity, or the spatio-temporal variation in community composition, can be partitioned into turnover and nestedness components in a multidimensional framework. Forest structure, including comprehensive characteristics of vertical and horizontal complexity, strongly affects species composition and its spatial variation. However, the effects of forest structure on beta-diversity patterns in multidimensional and multiple-scale contexts are poorly understood. Here, we assessed beta-diversity at local (a 20-ha forest dynamics plot) and regional (a plot network composed of 19 1-ha plots) scales in a Chinese subtropical evergreen broad-leaved forest. We then evaluated the relative importance of forest structure, topography, and spatial structure on beta-diversity and its turnover and nestedness components in taxonomic, functional, and phylogenetic dimensions at local and regional scales. We derived forest structural parameters from both unmanned aerial vehicle light detection and ranging (UAV LiDAR) data and plot inventory data. Turnover component dominated total beta-diversity for all dimensions at the two scales. With the exception of some components (taxonomic and functional turnover at the local scale; functional nestedness at the regional scale), environmental factors (i.e., topography and forest structure) contributed more than pure spatial variation. Explanations of forest structure for beta-diversity and its component patterns at the local scale were higher than those at the regional scale. The joint effects of spatial structure and forest structure influenced component patterns in all dimensions (except for functional turnover) to some extent at the local scale, while pure forest structure influenced taxonomic and phylogenetic nestedness patterns to some extent at the regional scale. Our results highlight the importance and scale dependence of forest structure in shaping multidimensional beta-diversity and its component patterns. Clearly, further studies need to link forest structure directly to ecological processes (e.g., asymmetric light competition and disturbance dynamics) and explore its roles in biodiversity maintenance.

Quantifying the scale-dependent relationships of PM2.5 and O3 on meteorological factors and their influencing factors in the Beijing-Tianjin-Hebei region and surrounding areas.

To investigate the variations of PM2.5 and O3 and their synergistic effects with influencing factors at different time scales, we employed Bayesian estimator of abrupt seasonal and trend change to analyze the nonlinear variation process of PM2.5 and O3. Wavelet coherence and multiple wavelet coherence were utilized to quantify the coupling oscillation relationships of PM2.5 and O3 on single/multiple meteorological factors in the time-frequency domain. Furthermore, we combined this analysis with the partial wavelet coherence to quantitatively evaluate the influence of atmospheric teleconnection factors on the response relationships. The results obtained from this comprehensive analysis are as follows: (1) The seasonal component of PM2.5 exhibited a change point, which was most likely to occur in January 2017. The trend component showed a discontinuous decline and had a change point, which was most likely to appear in February 2017. The seasonal component of O3 did not exhibit a change point, while the trend component showed a discontinuous rise with two change points, which were most likely to occur in July 2018 and May 2017. (2) The phase and coherence relationships of PM2.5 and O3 on meteorological factors varied across different time scales. Stable phase relationships were observed on both small- and large-time scales, whereas no stable phase relationship was formed on medium scales. On all-time scales, sunshine duration was the best single variable for explaining PM2.5 variations and precipitation was the best single variable explaining O3 variations. When compared to single meteorological factors, the combination of multiple meteorological factors significantly improved the ability to explain variations in PM2.5 and O3 on small-time scales. (3) Atmospheric teleconnection factors were important driving factors affecting the response relationships of PM2.5 and O3 on meteorological factors and they had greater impact on the relationship at medium-time scales compared to small- and large-time scales.

The Material Properties of the Cell Nucleus: A Matter of Scale.

Chromatin regulatory processes physically take place in the environment of the cell nucleus, which is filled with the chromosomes and a plethora of smaller biomolecules. The nucleus contains macromolecular assemblies of different sizes, from nanometer-sized protein complexes to micrometer-sized biomolecular condensates, chromosome territories, and nuclear bodies. This multiscale organization impacts the transport processes within the nuclear interior, the global mechanical properties of the nucleus, and the way the nucleus senses and reacts to mechanical stimuli. Here, we discuss recent work on these aspects, including microrheology and micromanipulation experiments assessing the material properties of the nucleus and its subcomponents. We summarize how the properties of multiscale media depend on the time and length scales probed in the experiment, and we reconcile seemingly contradictory observations made on different scales. We also revisit the concept of liquid-like and solid-like material properties for complex media such as the nucleus. We propose that the nucleus can be considered a multiscale viscoelastic medium composed of three major components with distinct properties: the lamina, the chromatin network, and the nucleoplasmic fluid. This multicomponent organization enables the nucleus to serve its different functions as a reaction medium on the nanoscale and as a mechanosensor and structural scaffold on the microscale.

A multiscale analysis of the spatially heterogeneous relationships between non-point source pollution-related processes and their main drivers in Chaohu Lake watershed, China.

A better understanding of the relationships between non-point source (NPS) pollution-related processes and their drivers will help to develop scientific watershed management measures. Although various studies have explored the drivers' impact on NPS pollution-related processes, quantitative knowledge of the properties within these relationships is still needed. This study uses the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to produce three related processes of NPS pollution, quick flow (QF), nitrogen export (NE), and sediment export (SE), in the upstream watershed of Chaohu Lake, China. The spatial distributions of QF, NE, and SE and their responses to multiple natural-socioeconomic drivers at nine spatial scales (1 km2, 10 km2, 20 km2, 30 km2, 50 km2, 75 km2, 100 km2, 200 km2, and town) were compared. The results showed that the spatial scale has little impact on the spatial distributions of NPS pollution-related processes. Across the nine scales, the socioeconomic drivers related to agricultural activities, area proportions of cultivated land (cultivated) and paddy field (paddy), have dominant impacts on NE, while the topographical drivers, the connectivity index (IC) and slope, have dominant impacts on both SE and QF. The magnitudes of single and paired natural-socioeconomic drivers' impacts on NPS pollution-related processes increase logarithmically or linearly with increasing spatial scale, but they tend to reach a stable threshold at a certain coarse scale. Our results emphasized the necessity and importance of embracing spatial scale effects in watershed water environmental management.

The temporal and spatial dimensions of plant-soil feedbacks.

Feedbacks between plants and soil microbes form a keystone to terrestrial community and ecosystem dynamics. Recent advances in dissecting the spatial and temporal dynamics of plant-soil feedbacks (PSFs) have challenged longstanding assumptions of spatially well-mixed microbial communities and exceedingly fast microbial assembly dynamics relative to plant lifespans. Instead, PSFs emerge from interactions that are inherently mismatched in spatial and temporal scales, and explicitly considering these spatial and temporal dynamics is crucial to understanding the contribution of PSFs to foundational ecological patterns. I propose a synthetic spatiotemporal framework for future research that pairs experimental and modeling approaches grounded in mechanism to improve predictability and generalizability of PSFs.

Domains of scale in cumulative effects of energy sector development on boreal birds.

Context: Industrial development in Canada's boreal forest creates cumulative environmental effects on biodiversity. Some effects may be scale-dependent, creating uncertainty in understanding and hindering effective management. Objectives: We estimated cumulative effects of energy sector development on distributions of sixteen migratory songbird species at multiple spatial scales within the boreal region of Alberta, Canada, and evaluated evidence for scale domains in species responses. Methods: We used a hierarchical, multi-scale sampling and modelling framework to compare effects of oil and gas footprint on songbirds at five spatial scales. We used Bayesian Lasso to facilitate direct comparison of parameter estimates across scales, and tested for differences in grouped parameter estimates among species. Results: We found consistent scale-dependent patterns across species, showing variable responses to development occurring at the smallest scale, little effect at intermediate scales, and stronger, mainly positive effects at the largest scales. Differences in grouped parameter estimates across scales showed strong evidence for scale domains in the response of songbirds to energy sector development. Conclusions: We concluded that variable effects at the smallest scale represented individual habitat selection, while larger scale positive effects reflected expanding distributions of open habitat- and disturbance-associated species in areas of high oil and gas footprint. Our results show that single-scale analyses do not reflect population processes occurring at other scales. Future research on linking patterns at different scales is required to fully understand cumulative effects of land use change on wildlife populations. Supplementary Information: The online version contains supplementary material available at 10.1007/s10980-023-01779-8.

Seasonality, density dependence, and spatial population synchrony.

Studies of spatial population synchrony constitute a central approach for understanding the drivers of ecological dynamics. Recently, identifying the ecological impacts of climate change has emerged as a new important focus in population synchrony studies. However, while it is well known that climatic seasonality and sequential density dependence influences local population dynamics, the role of season-specific density dependence in shaping large-scale population synchrony has not received attention. Here, we present a widely applicable analytical protocol that allows us to account for both season and geographic context-specific density dependence to better elucidate the relative roles of deterministic and stochastic sources of population synchrony, including the renowned Moran effect. We exemplify our protocol by analyzing time series of seasonal (spring and fall) abundance estimates of cyclic rodent populations, revealing that season-specific density dependence is a major component of population synchrony. By accounting for deterministic sources of synchrony (in particular season-specific density dependence), we are able to identify stochastic components. These stochastic components include mild winter weather events, which are expected to increase in frequency under climate warming in boreal and Arctic ecosystems. Interestingly, these weather effects act both directly and delayed on the vole populations, thus enhancing the Moran effect. Our study demonstrates how different drivers of population synchrony, presently altered by climate warming, can be disentangled based on seasonally sampled population time-series data and adequate population models.

Land-use diversity can better predict urban spontaneous plant richness than impervious surface coverage at finer spatial scales.

Urban spontaneous plants, that are not intentionally propagated by humans and do not belong to the remnants of the natural habitats, not only occur in green spaces but are also distributed in diverse microhabitats in impervious surface areas. Impervious surface coverage is commonly used in studies on spontaneous plant diversity patterns in human-dominated landscapes; however, the role of habitat diversity (i.e., land-use diversity) has been overlooked. Here, we surveyed spontaneous plant composition and land uses (12 types) in 321 0.25 ha sampling sites on the Chongming District islands, Shanghai, to determine the role of land-use diversity in explaining species richness. We examined the linear relationships between species richness and land-use diversity, and quantified the importance of impervious surface coverage and land-use diversity using the random forest (RF) method. All these analyses were conducted for spatial scales from 0.25 to 5 ha in 0.25 ha increments. We found an overall positive relationship between species richness and land-use diversity, and the RF model predicted approximately 50% of the species richness variation at the smallest spatial scale. However, the positive relationship weakened with spatial scale increase, and a rapid decline in explanatory power occurred for all predictor variables in the RF model. Besides impervious surface coverage, both the vegetated and non-vegetated land-use diversity contributed substantially to the prediction of species richness at finer spatial scales. The findings clarify how land-use diversity, both in green spaces and impervious surface areas, affect urban spontaneous plant richness and should be considered in urban biodiversity conservation strategies at the neighborhood scale.

Assessing scale-dependent effects on Forest biomass productivity based on machine learning.

Estimating forest above-ground biomass (AGB) productivity constitutes one of the most fundamental topics in forest ecological research. Based on a 30-ha permanent field plot in Northeastern China, we modeled AGB productivity as output, and topography, species diversity, stand structure, and a stand density variable as input across a series of area scales using the Random Forest (RF) algorithm. As the grain size increased from 10 to 200 m, we found that the relative importance of explanatory variables that drove the variation of biomass productivity varied a lot, and the model accuracy was gradually improved. The minimum sampling area for biomass productivity modeling in this region was 140 × 140 m. Our study shows that the relationship of topography, species diversity, stand structure, and stand density variables with biomass productivity modeled using the RF algorithm changes when moving from scales typical of forest surveys (10 m) to larger scales (200 m) within a controlled methodology. These results should be of considerable interest to scientists concerned with forest assessment.

The scale-dependence of spatial distribution of reservoir plankton communities in subtropical and tropical China.

Distance-decay relationships (DDRs) represent a very useful approach to describing the spatial distribution of biological communities. However, plankton DDR patterns and community assembly mechanisms are still poorly understood at different spatial scales in reservoir ecosystems. We collected phytoplankton, zooplankton and water samples in 24 reservoirs from subtropical and tropical China from July to August 2018. We examined DDR patterns across three distinct spatial scales, i.e., within-reservoir, within-drainage (but between reservoirs) and between drainages. We tested whether the rate of change (i.e., slope) of DDRs is consistent across different spatial scales. We assessed the relative importance of spatial and environmental variables in shaping the community distribution of plankton and quantitatively distinguished the community assembly mechanisms. We observed significant DDR curves in phytoplankton and zooplankton communities, in which slopes of the DDRs were steepest at the smallest spatial scale. Both spatial and environmental factors had significant impacts on DDR and dispersal assembly was a slightly stronger process in reservoir phytoplankton and zooplankton community assembly than niche-based process. We conclude that DDRs of reservoir phytoplankton and zooplankton vary with spatial scale. Our data shed light on how spatial and environmental variables contribute to plankton community assembly together. However, we revealed that dispersal process contributes to the biogeography of reservoir plankton slightly more strongly than environmental filtering. Collectively, this study enhances the understanding of plankton biogeography and distribution at multiple spatial scales.

Coupling of plant and mycorrhizal fungal diversity: its occurrence, relevance, and possible implications under global change.

First principles predict that diversity at one trophic level often begets diversity at other levels, suggesting plant and mycorrhizal fungal diversity should be coupled. Local-scale studies have shown positive coupling between the two, but the association is less consistent when extended to larger spatial and temporal scales. These inconsistencies are likely due to divergent relationships of different mycorrhizal fungal guilds to plant diversity, scale dependency, and a lack of coordinated sampling efforts. Given that mycorrhizal fungi play a central role in plant productivity and nutrient cycling, as well as ecosystem responses to global change, an improved understanding of the coupling between plant and mycorrhizal fungal diversity across scales will reduce uncertainties in predicting the ecosystem consequences of species gains and losses.

Comparing edge and fragmentation effects within seagrass communities: A meta-analysis.

Examining community responses to habitat configuration across scales informs basic and applied models of ecosystem function. Responses to patch-scale edge effects (i.e., ecological differences between patch edges and interiors) are hypothesized to underpin the effects of landscape-scale fragmentation (i.e., mosaics of multipatch habitat and matrix). Conceptually, this appears justifiable because fragmented habitats typically have a greater proportion of edge than continuous habitats. To critically inspect whether patch-scale edge effects translate consistently (i.e., scale up) into patterns observed in fragmented landscapes, we conducted a meta-analysis on community relationships in seagrass ecosystems to synthesize evidence of edge and fragmentation effects on shoot density, faunal densities, and predation rates. We determined effect sizes by calculating log response ratios for responses within patch edges versus interiors to quantify edge effects, and fragmented versus continuous landscapes to quantify fragmentation effects. We found that both edge and fragmentation effects reduced seagrass shoot densities, although the effect of edge was statistically stronger. By contrast, fauna often exhibited higher densities in patch edges, while fragmentation responses varied directionally across taxa. Fish densities trended higher in patch edges and fragmented landscapes. Benthic fishes responded more positively than benthopelagic fishes to edge effects, although neither guild strongly responded to fragmentation. Invertebrate densities increased in patch edges and trended lower in fragmented landscapes; however, these were small effect sizes due to the offsetting responses of two dominant epifaunal guilds: decapods and smaller crustaceans. Edge and fragmentation affected predation similarly, with prey survival trending lower in patch edges and fragmented landscapes. Overall, several similarities suggested that edge effects conform with patterns of community dynamics in fragmented seagrass. However, across all metrics except fish densities, variability in fragmentation effects was twice that of edge effects. Variance patterns combined with generally stronger responses to edge than fragmentation, warrant caution in unilaterally "scaling-up" edge effects to describe fragmentation effects. Alternatively, fragmentation includes additional factors (e.g., matrix effects, patch number, mean patch size, isolation) that may enhance or offset edge effects. Fragmentation and increased edge are syndromes of habitat degradation, therefore this analysis informs mechanistic models of community change in altered terrestrial and marine systems.

Decreased spatial variation and deterministic processes of bacterial community assembly in the rhizosphere of Phragmites australis across the Middle-Lower Yangtze plain.

Comparison of the spatial distribution and assembly processes between bulk and rhizosphere bacterial communities at multiple spatial scales is vital for understanding the generation and maintenance of microbial diversity under the influence of plants. However, biogeographical patterns and the underlying mechanisms of microbial communities in bulk and rhizosphere sediments of aquatic ecosystems remain unclear. Here, we collected 140 bulk and rhizosphere sediment samples of Phragmites australis from 14 lakeshore zones across a 510-km transect in the Middle-Lower Yangtze plain. We performed high-throughput sequencing to investigate the bacterial diversity, composition, spatial distribution and assembly processes of these samples. Bacterial communities in the rhizosphere sediment exhibited higher alpha diversity but lower beta diversity than those in the bulk sediment. Both bulk and rhizosphere sediment bacterial communities had significant distance-decay relationships, but spatial turnover of the rhizosphere sediment bacterial community was strikingly lower than that of bulk sediment. Despite variable selection dominating the assembly processes of bacterial communities in bulk sediment, the rhizosphere of P. australis enhanced the role of dispersal limitation in governing bacterial communities. The relative importance of different ecological processes in determining bacterial assembly presented distinct patterns of increasing or decreasing linearly with an increase of scale. This investigation highlights the convergent selection of the aquatic plant rhizosphere for surrounding bacterial communities and emphasizes the importance of different ecological processes on bacterial community assembly in sediment environments over different scales. Furthermore, we provide a preliminary framework for exploring the scale dependence of microbial community assembly in aquatic ecosystems.

Exploring the likely relationship between soil carbon change and environmental controls using nonrevisited temporal data sets: Mapping soil carbon dynamics across China.

The prediction of soil organic carbon (SOC) changes in response to environmental change is often limited by a scarcity of revisited temporal data, which constrains scientific understanding and realistic predictions of soil carbon change. The present study improved the potential of nonrevisited temporal data in the prediction of SOC stocks (SOCS) variations. We proposed a method to develop predictions of SOCS change using two independent temporal data sets (pertaining to the 1980s and 2010s) in China based on the digital soil mapping technique. Changes in SOCS over time at the site level were analyzed via the interpolation of missing SOCS values in each data set. Quantitative SOCS change predictions were generated by modeling the relationship between SOCS change and variables that represent changes in climate, vegetation indices, and land cover. The scale-dependent response of SOCS change to these environmental dynamics was assessed. On average, a slight increase was observed from 3.70 kg m-2 in the 1980s to 4.53 kg m-2 in the 2010s. The proposed approach attained moderate accuracy with an R2 value of 0.32 and a root mean squared error (RMSE) of 1.73 kg m-2. We found that changes in climate factors were dominant controls of SOCS change over time at the country scale. At the regional scale, the controlling factors of SOCS change were distinct and variable. Our case study may be of value in the application of independent temporal data sets to analyze soil carbon change on multiple scales. The method may be used to resolve questions of soil carbon change projections and provide an alternative solution to predict likely changes in soil carbon in response to future environmental change when no temporal data are available.

Grazing-induced biodiversity loss impairs grassland ecosystem stability at multiple scales.

Livestock grazing is a major driver shaping grassland biodiversity, functioning and stability. Whether grazing impacts on grassland ecosystems are scale-dependent remains unclear. Here, we conducted a sheep-grazing experiment in a temperate grassland to test grazing effects on the temporal stability of productivity across scales. We found that grazing increased species stability but substantially decreased local community stability due to reduced asynchronous dynamics among species within communities. The negative effect of grazing on local community stability propagated to reduce stability at larger spatial scales. By decreasing biodiversity both within and across communities, grazing reduced biological insurance effects and hence the upscaling of stability from species to communities and further to larger spatial scales. Our study provides the first evidence for the scale dependence of grazing effects on grassland stability through biodiversity. We suggest that ecosystem management should strive to maintain biodiversity across scales to achieve sustainability of grassland ecosystem functions and services.

Functional trait sorting increases over succession in metacommunity mosaics of fish assemblages.

Metacommunity theory predicts that the relative importance of regional and local processes structuring communities will change over time since initiation of community assembly. Determining effects of these processes on species and trait diversity over succession remains largely unaddressed in metacommunity ecology to date, yet could confer an improved mechanistic understanding of community assembly. To test theoretical predictions of the increasing importance of local processes in structuring communities over successional stages in metacommunities, we evaluated fish species and trait diversity in three pond metacommunities undergoing secondary succession from beaver (Castor canadensis) disturbance. Processes influencing taxonomic and trait diversity were contrasted across pond communities of different ages and in reference streams. Counter to predictions, the local environment became less important in structuring communities over succession but did exert a stronger effect on trait sorting. Beta diversity and trait richness declined over succession while there was no influence on species richness or trait dispersion. The trait filtering in older habitats was likely a response to the larger and deeper pond ecosystems characteristic of late succession. In contrast to these observed effects in ponds, the local environment primarily structured species and trait diversity in streams. Analyses of the relative importance of regional and local processes in structuring fish assemblages within each pond metacommunity suggests that habitat age and connectivity were more important than the environment in structuring communities but contributions were region and scale-dependent. Together, these findings highlight that regional and local processes can differentially influence taxonomic and trait diversity in successional metacommunity mosaics.

Multi-scale mosaics in top-down pest control by ants from natural coffee forests to plantations.

While top-down control plays an important role in shaping both natural and agricultural food webs, we lack insights into how top-down control effects vary across spatial scales. We used a multi-scale survey of top-down control of coffee pests and diseases by arboreal ants to examine if colony location creates a small-scale mosaic in top-down control around trees and if the strength of that control varies between sites at the landscape scale. We investigated pest and disease levels on coffee shrubs at different distances from shade trees with and without a Crematogaster spp. ant colony in 59 sites along a coffee management intensity gradient in southwestern Ethiopia. Within sites, ants significantly suppressed herbivory and coffee leaf rust at distances less than 10 m from nesting trees. Top-down control varied between sites, with stronger top-down control of free-feeding herbivory near ant colonies at sites with lower management intensity and stronger top-down control of a skeletonizer at sites with higher canopy cover. We conclude that the strength of top-down control by ants is highly heterogeneous across spatial scales, as a consequence of the biology of the predator at the small scale and herbivore density or changes in herbivore-ant interactions at the landscape scale.

Direct effects of selection on aboveground biomass contrast with indirect structure-mediated effects of complementarity in a subtropical forest.

Understanding the multiple biotic and abiotic controls of aboveground biomass (AGB) is important for projecting the consequences of global change and to effectively manage carbon storage. Although large-scale studies have identified the major environmental and biological controls of AGB, drivers of local-scale variation are less well known. Additionally, involvement of multiple causal paths and scale dependence in effect sizes potentially confounds comparisons among studies differing in methodology and sampling grain. We tested for scale dependence in evidence supporting selection, complementarity and environmental factors as the main determinants of AGB variation over a 50 ha study extent in subtropical China, modelling this at four sampling grains (0.01, 0.04, 0.25 and 1 ha). At each grain, we used piecewise structural equation models to quantify the direct and indirect effects of environmental (topographic and edaphic properties) and forest attributes (structure, diversity and functional traits) on AGB, while controlling for spatial autocorrelation. Direct scale-invariant effects on AGB were evident for structure and community-mean traits, supporting dominance of selection effects. However, diversity had strong indirect effects on AGB via forest structure, particularly at larger sampling grains (≥ 0.25 ha), while direct effects only emerged at the smallest grain size (0.01 ha). The direct and indirect effects of edaphic and topographic factors were also important for explaining both forest attributes and AGB across all scales. Although selection effects appeared to be more influential on ecosystem function, ignoring indirect causal pathways for diversity via structural attributes risks overlooking the importance of complementarity on ecosystem functioning, particularly as sampling grain increases.

Influence of landscape features on urban land surface temperature: Scale and neighborhood effects.

Higher land surface temperature (LST) in cities than its surrounding areas presents a major sustainability challenge for cities. Adaptation and mitigation of the increased LST require in-depth understanding of the impacts of landscape features on LST. We studied the influences of different landscape features on LST in five large cities across China to investigate how the features of a specific urban landscape (endogenous features), and neighboring environments (exogenous features) impact its LST across a continuum of spatial scales. Surprisingly, results show that the influence of endogenous landscape features (Eendo) on LST can be described consistently across all cities as a nonlinear function of grain size (gs) and neighbor size (ns) (Eendo = ßnsgs-0.5, where ß is a city-specific constant) while the influence of exogenous features (Eexo) depends only on neighbor size (ns) (Eexo = Î³-εns0.5, where γ and ε are city-specific constants). In addition, a simple relationship describing the relative strength of endogenous and exogenous impacts of landscape features on LST was found (Eendo > Eexo if ns > kgs2/5, where k is a city-specific parameter; otherwise, Eendo < Eexo). Overall, vegetation alleviates 40%-60% of the warming effect of built-up while surface wetness intensifies or reduces it depending on climate conditions. This study reveals a set of unifying quantitative relationships that effectively describes landscape impacts on LST across cities, grain and neighbor sizes, which can be instrumental towards the design of sustainable cities to deal with increasing temperature.