Drivers Of Spatial Variability Research Articles

Guidelines for the use of spatially varying coefficients in species distribution models

AbstractAimSpecies distribution models (SDMs) are increasingly applied across macroscales using detection‐nondetection data. These models typically assume that a single set of regression coefficients can adequately describe species–environment relationships and/or population trends. However, such relationships often show nonlinear and/or spatially varying patterns that arise from complex interactions with abiotic and biotic processes that operate at different scales. Spatially varying coefficient (SVC) models can readily account for variability in the effects of environmental covariates. Yet, their use in ecology is relatively scarce due to gaps in understanding the inferential benefits that SVC models can provide compared to simpler frameworks.InnovationHere we demonstrate the inferential benefits of SVC SDMs, with a particular focus on how this approach can be used to generate and test ecological hypotheses regarding the drivers of spatial variability in population trends and species–environment relationships. We illustrate the inferential benefits of SVC SDMs with simulations and two case studies: one that assesses spatially varying trends of 51 forest bird species in the eastern United States over two decades and a second that evaluates spatial variability in the effects of five decades of land cover change on grasshopper sparrow (Ammodramus savannarum) occurrence across the continental United States.Main conclusionsWe found strong support for SVC SDMs compared to simpler alternatives in both empirical case studies. Factors operating at fine spatial scales, accounted for by the SVCs, were the primary divers of spatial variability in forest bird occurrence trends. Additionally, SVCs revealed complex species–habitat relationships with grassland and cropland area for grasshopper sparrow, providing nuanced insights into how future land use change may shape its distribution. These applications display the utility of SVC SDMs to help reveal the environmental factors that drive species distributions across both local and broad scales. We conclude by discussing the potential applications of SVC SDMs in ecology and conservation.

Elevation Changes in Restored Marshes at Poplar Island, Chesapeake Bay, MD: I. Trends and Drivers of Spatial Variability

AbstractTidal marshes provide numerous ecosystem services, but are threatened by recent increases in global sea level rise (SLR). Marsh restoration and creation are important strategies for mitigating marsh loss, restoring ecosystem services, increasing coastal community resilience, and providing much needed habitat for threatened species. Dredged material resulting from navigation channel maintenance can provide a substrate for these restoration projects. Few studies, however, have addressed the sustainability of these marshes. The Paul S. Sarbanes Ecosystem Restoration Project at Poplar Island, where fine-grained, nutrient-rich dredged material from upper Chesapeake Bay is being used to create > 302 ha of tidal marshes, provides a case study. The low supply of inorganic sediment is counteracted by abundant nutrients, stimulating high rates of organic matter production and elevation change. Using > 10 years of data from 39 surface elevation tables, we found that the mean low marsh rate of elevation change (7.7 ± 3.21 mm year−1) was double the mean high marsh rate (3.6 ± 0.47 mm year−1) and exceeded the natural reference marsh (3.0 ± 2.28 mm year−1) and relative SLR (5.7 mm year−1). By stimulating organic matter production, the high nutrient substrate appears to offset the low inorganic sediment inputs in mid-Chesapeake Bay. Spatial variability was correlated with initial elevation, but was also influenced by local factors that may affect sediment redistribution within the marshes.

Spatial-Temporal Evolution and Prediction of Carbon Storage in Jiuquan City Ecosystem Based on PLUS-InVEST Model

Based on the background of carbon peaking and carbon neutrality goal strategies, it is important to explore the impact of land use change on carbon storage and the drivers of spatial variation in carbon storage in the Northwest Arid Zone, which is vital to improve the carbon sink increment of the regional ecosystem and promote the regional carbon breakeven. The arid region of northwest China is an extremely fragile natural ecology, and with the rapid advancement of new urbanization, the rate of land use change has accelerated significantly, which has a certain impact on the carbon storage and fixation capacity of ecosystems. The PLUS-InVEST model was used to simulate the spatial and temporal evolution characteristics of carbon storage under natural development, intensive development, water resource constraint, and ecological protection scenarios in Jiuquan City in 2035, and the parameter optimal geographic detector model was used to analyze the spatial divergence drivers of carbon storage. The results showed that:① the area of cultivated land, watershed, and construction land in Jiuquan City showed a significant increasing trend from 1990 to 2020, whereas the area of the remaining land use types showed a decreasing trend. ② The carbon storage in Jiuquan City increased from 7 722 808.1 t to 7 784 371 t from 1990 to 2020, and the conversion of grassland into unused land was the main cause of the loss of regional carbon storage, accounting for 85% of the total loss. ③ All four development scenarios in 2035 showed an increasing trend of carbon storage, among which the ecological protection scenario had the most significant increase, with an increment of 76 989.29 t. ④ The degree of land use, population density, GDP density, and NDVI were the main driving factors of the spatial variation in carbon storage in Jiuquan City, among which the degree of land use had the strongest explanatory power (q value of 0.849), and the interaction of natural and anthropogenic factors enhanced the explanatory power of each factor on the spatial variation in carbon storage. The results of the study can provide a scientific basis and decision basis for the integrated ecosystem management and territorial space optimization in Jiuquan City.

Vector species richness predicts local mortality rates from Chagas disease

Vector species richness may drive the prevalence of vector-borne diseases by influencing pathogen transmission rates. The dilution effect hypothesis predicts that higher biodiversity reduces disease prevalence, but with inconclusive evidence. In contrast, the amplification effect hypothesis suggests that higher vector diversity may result in greater disease transmission by increasing and diversifying the transmission pathways. The relationship between vector diversity and pathogen transmission remains unclear and requires further study. Chagas disease is a vector-borne disease most prevalent in Brazil and transmitted by multiple species of insect vectors of the subfamily Triatominae, yet the drivers of spatial variation in its impact on human populations remain unresolved. We tested whether triatomine species richness, latitude, bioclimatic variables, human host population density, and socioeconomic variables predict Chagas disease mortality rates across over 5000 spatial grid cells covering all of Brazil. Results show that species richness of triatomine vectors is a good predictor of mortality rates caused by Chagas disease, which supports the amplification effect hypothesis. Vector richness and the impact of Chagas disease may also be driven by latitudinal components of climate and human socioeconomic factors. We provide evidence that vector diversity is a strong predictor of disease prevalence and give support to the amplification effect hypothesis.

Localized uplift, widespread subsidence, and implications for sea level rise in the NewYork City metropolitan area.

Regional relative sea level rise is exacerbating flooding hazards in the coastal zone. In addition to changes in the ocean, vertical land motion (VLM) is a driver of spatial variation in sea level change that can either diminish or enhance flood risk. Here, we apply state-of-the-art interferometric synthetic aperture radar and global navigation satellite system time series analysis to estimate velocities and corresponding uncertainties at 30-m resolution in the NewYork City metropolitan area, revealing VLM with unprecedented detail. We find broad subsidence of 1.6 mm/year, consistent with glacial isostatic adjustment to the melting of the former ice sheets, and previously undocumented hot spots of both subsidence and uplift that can be physically explained in some locations. Our results inform ongoing efforts to adapt to sea level rise and reveal points of VLM that motivate both future scientific investigations into surface geology and assessments of engineering projects.

Oceanographic controls on Southern Ocean dimethyl sulfide distributions revealed by machine learning algorithms

AbstractWe developed two machine learning models to map the Southern Ocean distribution of the climate‐active gas dimethyl sulfide (DMS) at 20 km resolution. Results obtained from ensembles of random forest regressions and artificial neural networks reproduce observed DMS distributions with significantly higher accuracy than traditional statistical techniques, and are less prone to biases and spatial distortions than existing interpolation‐based climatologies. Both models predict persistently low offshore DMS concentrations associated with the Antarctic circumpolar current, suggesting that wind‐driven overturning mixing is the dominant regional control on DMS distributions. In addition, 60% of the variance in DMS seasonality is explained by changes in mixed layer depth and sea surface temperature, with a significant correlation between DMS concentrations and sea‐ice cover in coastal waters. We further identify the tracer Si* (defined as ) as a potentially important predictor for regional DMS distributions in Southern Ocean waters. At finer scales, our models capture various oceanographic features, including eddies, hydrographic fronts and jets that appear to play a role in driving DMS variability. Our results yield an estimated Southern Ocean sea‐air DMS flux of 8.7 ± 2.1 Tg S integrated across the phytoplankton growing season (October to April), representing 30.8% of total global oceanic S emissions, and highlighting the region's importance to the marine sulfur cycle. Our work provides new insights into the drivers of spatial variability in Southern Ocean DMS concentrations and sea‐air fluxes, and their potential responses to future climate‐dependent changes.

Spatial modelling of temporal dynamics in stream fish communities under anthropogenic change

AbstractAimUnderstanding temporal changes in aquatic communities is essential to address the freshwater biodiversity crisis. In particular, it is important to understand the patterns and drivers of spatial variation in local community dynamics, generalizing temporal trends from discrete locations to entire landscapes that are the main focus of management. Here, we present a framework for producing spatially continuous views of community dynamics, focusing on stream fish affected by hydropower development.LocationRiver Sabor, NE Portugal.MethodsWe sampled stream fish at thirty sites between 2012 and 2019. Community trajectory analysis was used to quantify the directionality and velocity of community change, and the geometric resemblance of community trajectories between sites. Geostatistical models for stream networks were used to relate metrics describing community dynamics to environmental variables, while controlling for Euclidean and hydrologic spatial dependencies, and to map spatial variation in community dynamics across the watershed.ResultsTrajectories in multivariate space underlined strong temporal dynamics, with local communities deviating and returning to previous states, but without evidence for directional changes. Accordingly, directionality values were low and not consistently affected by environmental variables. The velocity of community change varied markedly across the watershed and it was strongly affected by stream order and elevation, with faster changes observed in lowland streams draining into hydroelectric reservoirs and with a high proportion of exotic species. Pairwise distances between community trajectories were strongly related to hydrologic and environmental distances between sites.Main conclusionsLocal stream fish communities were in a loose equilibrium across the watershed, but they fluctuated at a faster rate closer to a hydroelectric reservoir. Integrating community trajectory analysis and geostatistical modelling provides a relatively simple framework to understand how, where and why temporal community dynamics vary across dendritic stream networks and to visualize spatial patterns of community change over time in relation to anthropogenic impacts.

Shore-fish assemblage structure in the central Philippines from shallow coral reefs to the mesophotic zone

Connectivity between shallow coral reefs and adjacent deeper habitats may be crucial to reef ecosystem stability. However, deeper habitats such as mesophotic coral ecosystems (MCEs) remain understudied. We investigated the depth structuring of shore-fish assemblages in the central Philippines across shallow (10-30 m) and mesophotic (upper: 30-60 m, lower: 60-90 m) depth zones. Baited video surveys in two coastal sites similar to 30 km apart showed strong declines with depth in fish species richness and abundance including fishery target species. Corallivores, herbivores/detritivores, omnivores and planktivores showed the strongest declines. Invertivores and generalist carnivores dominated abundance at mesophotic depths. Data from the coastal sites were analysed with published data from an offshore island (Apo Island) < 25 km away to provide broader insights on spatial variability of shore-fish depth structuring. The percentages of species that overlapped shallow and mesophotic depths were much lower in coastal sites (9-13%, 9-11%) than the island (20-26%), suggesting higher potential vertical connectivity in the latter. Mean assemblage similarities (Bray-Curtis) between shallow and mesophotic depth zones were found to be low at all sites (0.3-19.6) and decreased with depth. Fish assemblages gradually differed across depth zones at coastal sites but mesophotic assemblages at the island were more similar to the shallow coastal assemblages. Strong correlations between fish assemblages and benthic habitat were detected, suggesting that higher cover of rocky substratum at mesophotic depths facilitates vertical connectivity at the island. Our findings highlight benthic habitat as a driver of spatial variation in the depth structuring and vertical connectivity of shore-fish assemblages.

GRACE: Gravity Recovery and Climate Experiment long-term trend investigation over the Nile River Basin: Spatial variability drivers

GRACE (Gravity Recovery and Climate Experiment) long-term terrestrial water storage anomaly (TWSA) is attributed to the complex interaction of climatic, physical and anthropogenic drivers. This paper, therefore, explores how different hydroclimatic and anthropogenic processes interact and combine over “space” to produce the mass variations that GRACE-TWSA detects. Using the Nile River Basin (NRB) as a case study, it explicitly analyzes nine hydroclimatic and anthropogenic processes, as well as their relationship to the TWSA in different climatic zones. The analytic method employed the long-term trends derived for both the dependent (TWSA) and independent (explanatory) variables via applying two geographically multiple regression (GMR) approaches: (i) an ordinary least square regression (OLS) model in which the contributions of all variables to TWSA variability are deemed equal at all locations; and (ii) a geographically weighted regression (GWR) which assigns a weight to each variable at different locations based on clustering occurrences. The models’ efficacy was investigated using standard goodness of fit diagnostics. The OLS explains that the basin at large TWSA spatial variability significantly attributed to five variables, i.e., precipitation, runoff, surface water storage, soil moisture storage, and population density, (p < 0.0001). The OLS model, however, produced an R2 value of 0.14 with skewed standardized residuals. In contrast, the GWR model retained varying explanatory variables by different climate zone. For instance, the results showed that all nine variables contribute significantly, with varying ranking, to the trend in TWSA in the tropical zone. The evapotranspiration (ET) and population density are the only significant variables in the semiarid zone; population density contributes significantly to TWSA variability in all zones. The GWR model yielded R2 values with a median of 0.71 and normally distributed standard residuals. To evaluate the robustness of the GWR approach, the basin-wide TWSA pattern was simulated using the GWR model outputs. Herein, the GWR highlights the importance of the spatial locations to attribute the spatial variability in GRACE TSWA long-term trends. This spatial information, therefore, is critical for developing robust statistical models for reconstructing time series of proxy GRACE anomalies that predate the launch of the GRACE and for gap-filling between GRACE and GRACE Follow-On (GRACE-FO) mission.

Environmental and spatial variables determine the taxonomic but not functional structure patterns of microbial communities in alpine grasslands

There is considerable debate regarding how the taxonomic diversity of microbial communities relates to the functional diversity across space while similar questions have been explored in macro-organism communities. Here, we investigated the taxonomic and functional diversity patterns of soil microbial communities by coupling the data obtained from marker genes sequencing and functional gene surveys. Meanwhile, we evaluated the relative effects of environment and geographic distance on shaping these patterns in alpine grasslands of northern China. Although the taxonomic diversity and composition of microbial communities varied across sites, we found no consistent changes in the functional structure. Both the environmental factors and geographic distance concurrently affected the taxonomic diversity patterns but they had no effects on the spatial variations in functional genes. The functional alpha diversity was weakly correlated to the taxonomic alpha diversity across sites. Moreover, we found no significant relationship between the taxonomic and functional composition similarity among microbial communities. Together, our results provide evidence that spatial variation in microbial functions could be independent of their variations in taxonomic diversity. Even the drivers of spatial variations in the functional structure could be totally different from those of taxonomic variations such as environmental differences and dispersal limitation. Our findings suggest that spatial variations of microbial function structure within a community would not follow the variations of taxonomic structures due to different drivers between both of them over space.

Drivers of spatial variability in greendown within an oak-hickory forest landscape

Declining near-infrared (NIR) surface reflectance between early and late summer, here termed greendown, is a common, yet poorly understood phenomena in remote sensing time series of temperate deciduous forests. As revealed by phenology analysis of Landsat satellite data, there are strong spatial patterns in the rate of greendown across temperate deciduous forest landscapes, and analyzing these patterns could help advance our understanding of surface reflectance drivers. Within an oak-hickory (Quercus spp. – Carya spp.) forest landscape in western Maryland, USA, we tested how spatial patterns in greendown related to potential drivers at the landscape-, tree crown- and leaf-levels. We found that 50% of the spatial variability in greendown was explained by landscape variables, with greendown particularly higher in locations with higher maximum greenness, more southerly aspects, or locations with greater abundance of white oak (Quercus alba). The importance of species composition as a driver of greendown was supported at the tree crown level, where, relative to three other tree species, white oak exhibited the most consistent trend toward more vertical leaf angles later in the season. At the leaf level, NIR reflectance decreased in productive sites where %N increased, and δ13C decreased, through the season. However, among all sites, there were no consistent seasonal trends in foliar NIR reflectance, and we found no correlation among leaf-level NIR reflectance and satellite-observed greendown. Collectively, these results suggest that the spatial variability of greendown in this oak-hickory forest is most strongly controlled by an interaction of topographic and species compositional drivers operating at the landscape and tree crown levels. We found spatial analysis of greendown to be a useful approach to explore landscape-, tree crown-, and leaf-level controls on surface reflectance, and thereby help translate land surface phenology data into predictions of ecosystem structure and functioning.

Estimating Spatial Differences in Methane Emissions to Identify Sustainable Rice Sources

Core Ideas Commercial rice buyers and consumers are starting to demand more environmentally sustainable rice.This study uses historical data to estimate spatial differences in GHG emissions in rice production.Soil texture is the largest driver of methane emissions in rice production.Increased yields cannot make up for loss in methane use efficiencies when producing rice on loamy soils. Commercial rice (Oryza sativa L.) buyers and a growing consumer market for sustainable agricultural products are driving agriculture to be more conscious about production practices and associated environmental effects, such as greenhouse gas emissions. Globally rice production has been identified as a significant source of atmospheric methane (CH4) emissions. This study extends current knowledge by using a procedure to quantify spatial differences in CH4 emissions as well as CH4 efficiency levels (kg rice [kg CH4–C]‐1) across the mid‐southern United States, where over 75% of all US rice is produced. This study focuses on existing rice production practices that are known to directly affect CH4 emissions: variety selection, crop rotation, and soil texture. Historical data on varietal selection, crop rotations, and soil texture were used to estimate CH4 emissions from 2005 through 2014. Results showed that rice produced on clay‐textured soils with a rice–soybean rotation sown with a hybrid variety has the largest CH4 emissions efficiency among the management practice combinations evaluated. Results also demonstrated that any deviation from this optimal combination cannot be mitigated through realistic increases in yields, as it would take a 177% increase in yield for the hybrid–clay–rice to achieve the same efficiency as the hybrid–clay–soybean [Glycine max (L.) Merr.] combination. Results of this study provide commercial rice buyers, producers, and consumers with critical information regarding the drivers of spatial variations in sustainable rice production. Furthermore, these results give insights to producers and policymakers regarding which production practices and locations could benefit from increased demand for sustainable products and more restrictive environmental policies.

CO2 evasion from boreal lakes: Revised estimate, drivers of spatial variability, and future projections.

Lakes (including reservoirs) are an important component of the global carbon (C) cycle, as acknowledged by the fifth assessment report of the IPCC. In the context of lakes, the boreal region is disproportionately important contributing to 27% of the worldwide lake area, despite representing just 14% of global land surface area. In this study, we used a statistical approach to derive a prediction equationfor the partial pressure of CO2 (pCO2 ) in lakes as a function of lake area, terrestrial net primary productivity (NPP), and precipitation (r2 =.56), and to create the first high-resolution, circumboreal map (0.5°) of lake pCO2 . The map ofpCO2 was combined with lake area from the recently published GLOWABO database and three different estimates of the gas transfer velocity k to produce a resulting map of CO2 evasion (FCO2 ). For the boreal region, we estimate an average, lake area weighted, pCO2 of 966 (678-1,325) μatm and a totalFCO2 of 189 (74-347) TgCyear-1 , and evaluate the corresponding uncertainties based on Monte Carlo simulation. Our estimate of FCO2 is approximately twofold greater than previous estimates, as a result of methodological and data source differences. We use our results along with published estimates of the other C fluxes through inland waters to derive a C budget for the boreal region, and find that FCO2 from lakes is the most significant flux of the land-ocean aquatic continuum, and of a similar magnitude as emissions from forest fires. Using the model and applying it to spatially resolved projections of terrestrial NPP and precipitation while keeping everything else constant, we predict a 107% increase in boreal lake FCO2 under emission scenario RCP8.5 by 2100. Our projections are largely driven by increases in terrestrial NPP over the same period, showing the very close connection between the terrestrial and aquatic C cycle.

Soil respiration across a permafrost transition zone: spatial structure and environmental correlates

Abstract. Soil respiration is a key ecosystem function whereby shifts in respiration rates can shift systems from carbon sinks to sources. Soil respiration in permafrost-associated systems is particularly important given climate change driven permafrost thaw that leads to significant uncertainty in resulting ecosystem carbon dynamics. Here we characterize the spatial structure and environmental drivers of soil respiration across a permafrost transition zone. We find that soil respiration is characterized by a non-linear threshold that occurs at active-layer depths greater than 140 cm. We also find that within each season, tree basal area is a dominant driver of soil respiration regardless of spatial scale, but only in spatial domains with significant spatial variability in basal area. Our analyses further show that spatial variation (the coefficient of variation) and mean-variance power-law scaling of soil respiration in our boreal system are consistent with previous work in other ecosystems (e.g., tropical forests) and in population ecology, respectively. Comparing our results to those in other ecosystems suggests that temporally stable features such as tree-stand structure are often primary drivers of spatial variation in soil respiration. If so, this provides an opportunity to better estimate the magnitude and spatial variation in soil respiration through remote sensing. Combining such an approach with broader knowledge of thresholding behavior – here related to active layer depth – would provide empirical constraints on models aimed at predicting ecosystem responses to ongoing permafrost thaw.

Human activities as a driver of spatial variation in the trophic structure of fish communities on Pacific coral reefs.

Anthropogenic activities such as land-use change, pollution and fishing impact the trophic structure of coral reef fishes, which can influence ecosystem health and function. Although these impacts may be ubiquitous, they are not consistent across the tropical Pacific Ocean. Using an extensive database of fish biomass sampled using underwater visual transects on coral reefs, we modelled the impact of human activities on food webs at Pacific-wide and regional (1,000s-10,000skm) scales. We found significantly lower biomass of sharks and carnivores, where there were higher densities of human populations (hereafter referred to as human activity); however, these patterns were not spatially consistent as there were significant differences in the trophic structures of fishes among biogeographic regions. Additionally, we found significant changes in the benthic structure of reef environments, notably a decline in coral cover where there was more human activity. Direct human impacts were the strongest in the upper part of the food web, where we found that in a majority of the Pacific, the biomass of reef sharks and carnivores were significantly and negatively associated with human activity. Finally, although human-induced stressors varied in strength and significance throughout the coral reef food web across the Pacific, socioeconomic variables explained more variation in reef fish trophic structure than habitat variables in a majority of the biogeographic regions. Notably, economic development (measured as GDP per capita) did not guarantee healthy reef ecosystems (high coral cover and greater fish biomass). Our results indicate that human activities are significantly shaping patterns of trophic structure of reef fishes in a spatially nonuniform manner across the Pacific Ocean, by altering processes that organize communities in both "top-down" (fishing of predators) and "bottom-up" (degradation of benthic communities) contexts.

Biogeographical drivers of ragweed pollen concentrations in Europe

The drivers of spatial variation in ragweed pollen concentrations, contributing to severe allergic rhinitis and asthma, are poorly quantified. We analysed the spatiotemporal variability in 16-year (1995–2010) annual total (66 stations) and annual total (2010) (162 stations) ragweed pollen counts and 8 independent variables (start, end and duration of the ragweed pollen season, maximum daily and calendar day of the maximum daily ragweed pollen counts, last frost day in spring, first frost day in fall and duration of the frost-free period) for Europe (16 years, 1995–2010) as a function of geographical coordinates. Then annual total pollen counts, annual daily peak pollen counts and date of this peak were regressed against frost-related variables, daily mean temperatures and daily precipitation amounts. To achieve this, we assembled the largest ragweed pollen data set to date for Europe. The dependence of the annual total ragweed pollen counts and the eight independent variables against geographical coordinates clearly distinguishes the three highly infected areas: the Pannonian Plain, Western Lombardy and the Rhone-Alpes region. All the eight variables are sensitive to longitude through its temperature dependence. They are also sensitive to altitude, due to the progressively colder climate with increasing altitude. Both annual total pollen counts and the maximum daily pollen counts depend on the start and the duration of the ragweed pollen season. However, no significant changes were detected in either the eight independent variables as a function of increasing latitude. This is probably due to a mixed climate induced by strong geomorphological inhomogeneities in Europe.

Plant δ15 N reflects the high landscape-scale heterogeneity of soil fertility and vegetation productivity in a Mediterranean semiarid ecosystem.

We investigated the magnitude and drivers of spatial variability in soil and plant δ15 N across the landscape in a topographically complex semiarid ecosystem. We hypothesized that large spatial heterogeneity in water availability, soil fertility and vegetation cover would be positively linked to high local-scale variability in δ15 N. We measured foliar δ15 N in three dominant plant species representing contrasting plant functional types (tree, shrub, grass) and mycorrhizal association types (ectomycorrhizal or arbuscular mycorrhizal). This allowed us to investigate whether δ15 N responds to landscape-scale environmental heterogeneity in a consistent way across species. Leaf δ15 N varied greatly within species across the landscape and was strongly spatially correlated among co-occurring individuals of the three species. Plant δ15 N correlated tightly with soil δ15 N and key measures of soil fertility, water availability and vegetation productivity, including soil nitrogen (N), organic carbon (C), plant-available phosphorus (P), water-holding capacity, topographic moisture indices and normalized difference vegetation index. Multiple regression models accounted for 62-83% of within-species variation in δ15 N across the landscape. The tight spatial coupling and interdependence of the water, N and C cycles in drylands may allow the use of leaf δ15 N as an integrative measure of variations in moisture availability, biogeochemical activity, soil fertility and vegetation productivity (or 'site quality') across the landscape.

Drivers of Spatial Variation in the Role of Ants as Secondary Seed Dispersers.

The spatial variation in the outcome of the interaction between secondary dispersers and seeds is superimposed upon the variation produced by primary dispersers. Investigating the factors that drive the outcome of the interactions with secondary seed dispersers thus represents an essential refinement to our understanding of the complete seed dispersal process. We studied the interactions between two ponerine ants (Pachycondyla striata Smith, 1858 and Odontomachus chelifer (Latreille, 1802)) with fruits experimentally set on the ground, and estimated the effects of ants on seedling establishment in three areas distributed along a 2-km stretch of a Brazilian Atlantic rainforest that differ in soil properties and vegetation physiognomies. We tested the hypothesis that interactions are more frequent, resulting in greater seedling establishment at the site with harsher abiotic and biotic conditions. Both ant species removed fruits frequently and have a positive effect on seedling establishment in all study areas, but fruit removal did not differ among areas, while seedling establishment was more pronounced at the site with stressful abiotic conditions. The two ant species differed in important aspects of their seed dispersal services, including the propensity to interact with seeds. As a result, both the species of ant and abiotic conditions interact at the scale of 2 km to determine the fate of seeds interacting with ants, thus creating a mosaic of outcomes with variable benefits to plants.

Environment, but not genetic divergence, influences geographic variation in colour morph frequencies in a lizard.

BackgroundIdentifying the causes of intraspecific phenotypic variation is essential for understanding evolutionary processes that maintain diversity and promote speciation. In polymorphic species, the relative frequencies of discrete morphs often vary geographically; yet the drivers of spatial variation in morph frequencies are seldom known. Here, we test the relative importance of gene flow and natural selection to identify the causes of geographic variation in colour morph frequencies in the Australian tawny dragon lizard, Ctenophorus decresii.ResultsPopulations of C. decresii are polymorphic for male throat coloration and all populations surveyed shared the same four morphs but differed in the relative frequencies of morphs. Despite genetic structure among populations, there was no relationship between genetic similarity or geographic proximity and similarity in morph frequencies. However, we detected remarkably strong associations between morph frequencies and two environmental variables (mean annual aridity index and vegetation cover), which together explained approximately 45 % of the total variance in morph frequencies.ConclusionsSpatial variation in selection appears to play an important role in shaping morph frequency patterns in C. decresii. Selection associated with differences in local environmental conditions, combined with relatively low levels of gene flow, is expected to favour population divergence in morph composition, but may be counteracted by negative frequency-dependent selection favouring rare morphs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12862-015-0442-x) contains supplementary material, which is available to authorized users.

Organophosphorus flame retardants in the European eel in Flanders, Belgium: Occurrence, fate and human health risk

The present study investigated the levels, profiles and human health risk of organophosphorus flame retardants and plasticizers (PFRs) in wild European eels (Anguilla anguilla) from freshwater bodies in the highly populated and industrial Flanders region (Belgium). Yellow eels (n=170) were collected at 26 locations between 2000 and 2009 and for each site, muscle samples of 3–10 eels were pooled and analyzed (n=26). Muscle lipid percentages varied widely between 2.4% and 21%, with a median value of 10%. PFRs were detected in all pooled samples in the order of tris-2-chloroisopropyl phosphate (TCIPP)>triphenyl phosphate (TPHP)>2-ethylhexyl diphenyl phosphate (EHDPHP)>tris-2-butoxyethyl phosphate (TBOEP)>tris-2-chloroethyl phosphate (TCEP)>tris-1,3-dichloro-2-propyl phosphate (TDCIPP). The median sum PFR concentration for all 26 sites was 44ng/g lw (8.4ng/g ww), and levels ranged between 7.0 and 330ng/g lw (3.5 and 45ng/g ww). Levels and profiles of PFRs in eels showed that sampling locations and river basin catchments are possible drivers of spatial variation in the aquatic environment. Median PFR concentrations were lower than those of polybrominated diphenyl ethers (PBDEs) and hexabromocyclododecanes (HBCDs). No correlation was observed between the PFR concentrations and lipid contents, suggesting that the accumulation of PFRs is not primarily associated with lipids. Human exposure to PFRs, due to consumption of wild eels, seems to be of minor importance compared to other potential sources, such as inhalation and ingestion of indoor dust. Nevertheless, considering the very limited data available on PFRs in human dietary items and their expected increasing use after the phase out of PBDEs and HBCDs, further investigations on PFRs in biota and human food items are warranted.