Spatial Scale Of Observation Research Articles

Moving towards a comprehensive view of the spatial processes in seed dispersal networks: Embracing metacommunities.

The current biodiversity crisis requires efficient approaches to address the ongoing impoverishment of natural communities and the depletion of ecosystem services and functions. In this sense, identifying key species that promote the functioning of ecological processes can be strategic to guide actions aiming at the conservation and restoration of biodiversity. Node-level metrics in interaction networks can be helpful to identify those key species, as they measure the role each species plays in organizing the interactions. Moreover, ecological correlates of species structural roles may vary between local and global networks of interactions, reflecting distinct mechanisms acting at different spatial scales. By studying local seed dispersal networks and one global meta-network combining those local networks, Moulatlet et al. identified the most important traits explaining bird species centrality at varying spatial scales. They found that body mass was the main trait explaining centrality at the local scale, whereas range size was the main predictor of species centrality at the global scale. In this contribution, besides assessing local interaction networks, Moulatlet et al. adopt a biogeographical perspective to seed dispersal systems, extending our knowledge about the possible mechanisms that underlie the organization of interacting assemblages when changing the spatial scale of observation. Future efforts on this field could include an intermediate scale, comprising the level of metacommunities, shedding light on the interplay between local and spatial processes, both embedded in biogeographical realms, when determining the organization of interactions and the ecological correlates of species roles.

The effect of turbulence in brain dynamics information transfer measured with magnetoencephalography

Fast, efficient information transfer is essential for the brain to ensure survival. As recently shown in functional magnetic resonance imaging with high spatial resolution, turbulence appears to offer a fundamental way to facilitate energy and information transfer across spatiotemporal scales in brain dynamics. However, given that this imaging modality is comparably slow and not directly linked with neuronal activity, here we investigated the existence of turbulence in fast whole-brain neural dynamics measured with magnetoencephalography (MEG). The coarse spatial observations in MEG necessitated that we created and validated a empirical measure of turbulence. We found that the measure of edge-centric metastability perfectly detected turbulence in a ring of non-local coupled oscillators where the ground-truth was analytically known, even at a coarse spatial scale of observations. This allowed us to use this measure in the spatially coarse, empirical large-scale MEG data from 89 human participants. We demonstrated turbulence in fast neuronal dynamics and used this to quantify information transfer in the brain. The results demonstrate that the necessary efficiency of brain function is dependent on an underlying turbulent regime.

Extreme event impacts on terrestrial and freshwater biota in the arctic: A synthesis of knowledge and opportunities

Extreme weather events are increasing in frequency and intensity across the Arctic, one of the planet’s most rapidly warming regions. Studies from southern latitudes have revealed that the ecological impacts of extreme events on living organisms can be severe and long-lasting, yet data and evidence from within the terrestrial Arctic biome appear underrepresented. By synthesizing a total of 48 research articles, published over the past 25 years, we highlight the occurrence of a wide variety of extreme events throughout the Arctic, with multiple and divergent impacts on local biota. Extreme event impacts were quantified using a myriad of approaches ranging from circumpolar modelling to fine-scale experimental studies. We also identified a research bias towards the quantification of impacts related to a few extreme event types in the same geographic location (e.g. rain-on-snow events in Svalbard). Moreover, research investigating extreme event impacts on the ecology of arthropods and especially freshwater biota were scant, highlighting important knowledge gaps. While current data allow for hypotheses development, many uncertainties about the long-term consequences of extreme events to Arctic ecosystems remain. To advance extreme event research in the terrestrial Arctic biome, we suggest that future studies i) objectively define what is extreme in terms of events and ecological impacts using long-term monitoring data, ii) move beyond single-impact studies and single spatial scales of observation by taking advantage of pan-Arctic science-based monitoring networks and iii) consider predictive and mechanistic modelling to estimate ecosystem-level impacts and recovery.

Sediment macrofaunal response to the diel oxygen cycle

Infauna exhibit a range of behavioral responses to declining dissolved oxygen concentrations that affect their burrowing and feeding behaviors. Diel oxygen cycles, common in shallow coastal areas, may drive changes in faunal behavior that affect sediment mixing. In this laboratory study we exposed 3 species, the burrowing ophiuroid Hemipholis cordifera, the tube-dwelling polychaete Owenia fusiformis, and the burrowing clam Ameritella versicolor, to 60 h of diel cycling dissolved oxygen in the overlying water, with oxygen concentration varying between 2 and 7 mg l-1. We observed the study organisms’ behaviors and evaluated their sediment mixing activity using luminophores applied to the sediment surface. We found that sediment mixing activity of all 3 taxa, measured as percent decrease in luminophore coverage, varied proportionally with dissolved oxygen concentration during the diel cycle. Observations of animal behavior did not reveal a diel pattern, though this was likely due to the temporal and spatial scale of observations. Our results also indicated that diel cycling oxygen may change faunal effects on the sediment in ways that only emerge after more than a single cycle. Measuring sediment mixing in sustained full oxygen saturation may produce misleading estimates over time, and future research should investigate how faunal responses to short-term variability can scale to have longer-term effects.

Reef fish community structure along the southeastern US Atlantic continental shelf break and upper slope appears resistant to increasing lionfish (Pterois volitans/miles) density

Temperate reefs host diverse fish communities along the southeast United States Atlantic coast (SEUS), yet the sustainable management of reef fishes faces myriad challenges. One challenge has been the introduction of Indo-Pacific lionfish (Pterois volitans/miles; hereafter "lionfish"), which have spread quickly throughout the SEUS since their introduction in the late 1900s. We analyzed long- term (2001–2019) video data along the continental shelf break and upper slope (45–125 m deep) of the SEUS to assess changes in lionfish densities over time, characterize reef fish community structure, and determine if native reef fish community structure has changed due to lionfish. Lionfish densities increased substantially during the study, from zero individuals observed in 2001 to approximately 1.2 individuals observed per 100 m 3 (and present in all included transects) by 2019, yet no fish community metrics were negatively related to lionfish density. Demersal habitat influenced fish community structure more than any other variable examined, with more individuals and different fish communities occurring on high-relief compared to low-relief hardbottom habitats. The effects of latitude, depth, and bottom temperature on reef fish community structure were generally weak or nonexistent. Although previous empirical work has found that lionfish negatively affect native fishes at small scales (<30 km2), it is unclear why we did not find similar results in our larger- scale study. It may be related to vagaries of the spatial scale of observation, lionfish effects being primarily limited to high- relief habitats, time lags, or lionfish densities not being high enough yet to cause observable ecological effects.

Arboreality drives heat tolerance while elevation drives cold tolerance in tropical rainforest ants.

Determining how species thermal limits correlate with climate is important for understanding biogeographic patterns and assessing vulnerability to climate change. Such analyses need to consider thermal gradients at multiple spatial scales. Here we relate thermal traits of rainforest ants to microclimate conditions from ground to canopy (microgeographic scale) along an elevation gradient (mesogeographic scale) and calculate warming tolerance to assess climate change vulnerability in the Australian Wet Tropics Bioregion. We test the thermal adaptation and thermal niche asymmetry hypotheses to explain interspecific patterns of thermal tolerance at these two spatial scales. We tested cold tolerance (CTmin ), heat tolerance (CTmax ), and calculated thermal tolerance range (CTrange ), using ramping assays for 74 colonies of 40 ant species collected from terrestrial and arboreal habitats at lowland and upland elevation sites and recorded microclimatic conditions for one year. Within sites, arboreal ants were exposed to hotter microclimates and on average had a 4.2°C (95% CI: 2.7-5.6°C) higher CTmax and 5.3°C (95% CI: 3.5-7°C) broader CTrange than ground-dwelling ants. This pattern was consistent across the elevation gradient, whether it be the hotter lowlands or the cooler uplands. Across elevation, upland ants could tolerate significantly colder temperatures than lowland ants, whereas the change in CTmax was less pronounced, and CTrange did not change over elevation. Differential exposure to microclimates, due to localized niche preferences, drives divergence in CTmax , while environmental temperatures along the elevation gradient drive divergence in CTmin . Our results suggest that both processes of thermal adaptation and thermal niche asymmetry are at play, depending on the spatial scale of observation, and we discuss potential mechanisms underlying these patterns. Despite the broad thermal tolerance range of arboreal rainforest ants, lowland arboreal ants had the lowest warming tolerance and may be most vulnerable to climate change.

Soil microbiome predictability increases with spatial and taxonomic scale.

Soil microorganisms shape ecosystem function, yet it remains an open question whether we can predict the composition of the soil microbiome in places before observing it. Furthermore, it is unclear whether the predictability of microbial life exhibits taxonomic- and spatial-scale dependence, as it does for macrobiological communities. Here, we leverage multiple large-scale soil microbiome surveys to develop predictive models of bacterial and fungal community composition in soil, then test these models against independent soil microbial community surveys from across the continental United States. We find remarkable scale dependence in community predictability. The predictability of bacterial and fungal communities increases with the spatial scale of observation, and fungal predictability increases with taxonomic scale. These patterns suggest that there is an increasing importance of deterministic versus stochastic processes with scale, consistent with findings in plant and animal communities, suggesting a general scaling relationship across biology. Biogeochemical functional groups and high-level taxonomic groups of microorganisms were equally predictable, indicating that traits and taxonomy are both powerful lenses for understanding soil communities. By focusing on out-of-sample prediction, these findings suggest an emerging generality in our understanding of the soil microbiome, and that this understanding is fundamentally scale dependent.

Influence of larval transport and temperature on recruitment dynamics of North Sea cod (Gadus morhua) across spatial scales of observation

AbstractThe survival of fish eggs and larvae, and therefore recruitment success, can be critically affected by transport in ocean currents. Combining a model of early‐life stage dispersal with statistical stock–recruitment models, we investigated the role of larval transport for recruitment variability across spatial scales for the population complex of North Sea cod (Gadus morhua). By using a coupled physical–biological model, we estimated the egg and larval transport over a 44‐year period. The oceanographic component of the model, capable of capturing the interannual variability of temperature and ocean current patterns, was coupled to the biological component, an individual‐based model (IBM) that simulated the cod eggs and larvae development and mortality. This study proposes a novel method to account for larval transport and success in stock–recruitment models: weighting the spawning stock biomass by retention rate and, in the case of multiple populations, their connectivity. Our method provides an estimate of the stock biomass contributing to recruitment and the effect of larval transport on recruitment variability. Our results indicate an effect, albeit small, in some populations at the local level. Including transport anomaly as an environmental covariate in traditional stock–recruitment models in turn captures recruitment variability at larger scales. Our study aims to quantify the role of larval transport for recruitment across spatial scales, and disentangle the roles of temperature and larval transport on effective connectivity between populations, thus informing about the potential impacts of climate change on the cod population structure in the North Sea.

From Transient to Sedentary? Changes in the Home Range Size and Environmental Patterns of Movements of European Eels (Anguilla anguilla) in a Mediterranean River

Abstract: The habitat use of eels during the development of sedentary behavior, which depends on the animals’ body size, is unknown. Our objective was to analyze, for two years, the changes in the home range of a population of European eel (Anguilla anguilla, Linnaeus, 1758) in Southern Europe in relation to the animals’ body length (TL), and the influence of environmental factors (water temperature and flow) on the local movements of this population through observation of their sedentary behavior. We used a previously-validated mark–recapture methodology, obtaining a low deviation in the estimation of the extension of the eels’ movements. Our results revealed relatively short movements in relation to other populations, and we hypothesize that this could be related to the high habitat diversity and low eel population density in the study area. The home range size showed a high variability and dispersion among the smallest eels, however, as TL increased, the variability of home range size decreased, and home ranges were larger. These changes could be associated with the acquisition of a sedentary lifestyle. Once eels had become sedentary, an environmental pattern was observed between their movements and the water temperature and flow, with larger movements observed as the flow increased and water temperature decreased. This suggests that the temporal and spatial scales of observation are of crucial importance for monitoring eel populations and for the study of population size structure, population dynamics, and biology, which can be used to improve conservation strategies.

Testing the link between species interactions and species co‐occurrence in a trophic network

Species interactions are dynamic processes that vary across environmental and ecological contexts, and operate across scale boundaries, making them difficult to quantify. Nevertheless, ecologists are increasingly interested in inferring species interactions from observational data using statistical analyses of their spatial co‐occurrence patterns. Trophic interactions present a particular challenge, as predators and prey may frequently or rarely co‐occur, depending on the spatial or temporal scale of observation. In this study, we investigate the accuracy of inferred interactions among species that both compete and trophically interact. We utilized a long‐term dataset of pond‐breeding amphibian co‐occurrences from Mt Rainier National Park (Washington, USA) and compiled a new dataset of their empirical interactions from the literature. We compared the accuracy of four statistical methods in inferring these known species interactions from spatial associations. We then used the best performing statistical method, the Markov network, to further investigate the sensitivity of interaction inference to spatial scale‐dependence and the presence of predators. We show that co‐occurrence methods are generally inaccurate when estimating trophic interactions. Further the strength and sign of inferred interactions were dependent upon the spatial scale of observation and predator presence influenced the detectability of competitive interactions among prey species. However, co‐occurrence analysis revealed new patterns of spatial association among pairs of species with known interactions. Overall, our study highlights a limiting frontier in co‐occurrence theory and the disconnect between widely implemented methodologies and their ability to accurately infer interactions in trophically‐structured communities.

The geographical variation of network structure is scale dependent: understanding the biotic specialization of host-parasitoid networks.

Research on the structure of ecological networks suggests that a number of universal patterns exist. Historically, biotic specialization has been thought to increase towards the Equator. Yet, recent studies have challenged this view showing non-conclusive results. Most studies analysing the geographical variation in biotic specialization focus, however, only on the local scale. Little is known about how the geographical variation of network structure depends on the spatial scale of observation (i.e., from local to regional spatial scales). This should be remedied, as network structure changes as the spatial scale of observation changes, and the magnitude and shape of these changes can elucidate the mechanisms behind the geographical variation in biotic specialization. Here we analyse four facets of biotic specialization in host-parasitoid networks along gradients of climatic constancy, classifying the networks according to their spatial extension (local or regional). Namely, we analyse network connectance, consumer diet overlap, consumer diet breadth, and resource vulnerability at both local and regional scales along the gradients of both current climatic constancy and historical climatic change. While at the regional scale none of the climatic variables are associated to biotic specialization, at the local scale, network connectance, consumer diet overlap, and resource vulnerability decrease with current climatic constancy, whereas consumer generalism increases (i.e., broader diet breadths in tropical areas). Similar patterns are observed along the gradient of historical climatic change. We provide an explanation based on different beta-diversity for consumers and resources across the geographical gradients. Our results show that the geographical gradient of biotic specialization is not universal. It depends on both the facet of biotic specialization and the spatial scale of observation.

Classifying development stages of primeval European beech forests: is clustering a useful tool?

BackgroundOld-growth and primeval forests are passing through a natural development cycle with recurring stages of forest development. Several methods for assigning patches of different structure and size to forest development stages or phases do exist. All currently existing classification methods have in common that a priori assumptions about the characteristics of certain stand structural attributes such as deadwood amount are made. We tested the hypothesis that multivariate datasets of primeval beech forest stand structure possess an inherent, aggregated configuration of data points with individual clusters representing forest development stages. From two completely mapped primeval beech forests in Albania, seven ecologically important stand structural attributes characterizing stand density, regeneration, stem diameter variation and amount of deadwood are derived at 8216 and 9666 virtual sampling points (moving window, focal filtering). K-means clustering is used to detect clusters in the datasets (number of clusters (k) between 2 and 5). The quality of the single clustering solutions is analyzed with average silhouette width as a measure for clustering quality. In a sensitivity analysis, clustering is done with datasets of four different spatial scales of observation (200, 500, 1000 and 1500 m2, circular virtual plot area around sampling points) and with two different kernels (equal weighting of all objects within a plot vs. weighting by distance to the virtual plot center).ResultsThe clustering solutions succeeded in detecting and mapping areas with homogeneous stand structure. The areas had extensions of more than 200 m2, but differences between clusters were very small with average silhouette widths of less than 0.28. The obtained datasets had a homogeneous configuration with only very weak trends for clustering.ConclusionsOur results imply that forest development takes place on a continuous scale and that discrimination between development stages in primeval beech forests is splitting continuous datasets at selected thresholds. For the analysis of the forest development cycle, direct quantification of relevant structural features or processes might be more appropriate than classification. If, however, the study design demands classification, our results can justify the application of conventional forest development stage classification schemes rather than clustering.

Effectiveness of camera traps for quantifying daytime and nighttime visitation by vertebrate pollinators.

Identification of pollen vectors is a fundamental objective of pollination biology. The foraging and social behavior of these pollinators has profound effects on plant mating, making quantification of their behavior critical for understanding the ecological and evolutionary consequences of different pollinators for the plants they visit. However, accurate quantification of visitation may be problematic, especially for shy animals and/or when the temporal and spatial scale of observation desired is large. Sophisticated heat‐ and movement‐triggered motion‐sensor cameras (“camera trapping”) provide new, underutilized tools to address these challenges. However, to date, there has been no rigorous evaluation of the sampling considerations needed for using camera trapping in pollination research.We measured the effectiveness of camera trapping for identifying vertebrate visitors and quantifying their visitation rates and foraging behavior on Banksia menziesii (Proteaceae). Multiple still cameras (Reconyx HC 500) and a video camera (Little Acorn LTL5210A) were deployed.From 2,753 recorded visits by vertebrates, we identified five species of nectarivorous honeyeater (Meliphagidae) and the honey possum (Tarsipedidae), with significant variation in the species composition of visitors among inflorescences. Species of floral visitor showed significant variation in their time of peak activity, duration of visits, and numbers of flowers probed per visit. Where multiple cameras were deployed on individual inflorescences, effectiveness of individual still cameras varied from 15% to 86% of all recorded visits. Methodological issues and solutions, and the future uses of camera traps in pollination biology, are discussed. Conclusions and wider implications: Motion‐triggered cameras are promising tools for the quantification of vertebrate visitation and some aspects of behavior on flowers. However, researchers need to be mindful of the variation in effectiveness of individual camera traps in detecting animals. Pollinator studies using camera traps are in their infancy, and the full potential of this developing technology is yet to be realized.

P 33 Different spatial observation scales in the analysis of an fMRI language task lead to substantially differing functional interpretations

In the last two decades, neuroimaging research has provided important insights into structure-function relationships in the human brain. In this period, more than 40,000 studies using functional magnetic resonance imaging (fMRI) have been published in peer-reviewed academic journals. Recently, however, the methods and software used for analyzing fMRI data have come under increased scrutiny. From these investigations several lines of enquiry emerge: the cross-software comparability ( Pauli, 2016 ), the validity of statistical inference ( Eklund et al., 2016 , Wager et al., 2009 ) and interpretation, and the influence of the spatial filter on the anatomical assignment of activation peaks ( Ball, 2012 , White, 2001 ). Here, we use a wide range of Gaussian filters from 1 to 20 mm at full-width half maximum (FWHM) in analyzing fMRI data from a speech repetition paradigm in 25 subjects to investigate the scale-dependent variability of the fMRI analysis. We analyzed the data both at the coordinate level and at the level of regions-of-interests defined by particular contrasts in individuals and at the group level. We show that depending on the filter size, the results from fMRI analyses and their functional interpretation vary substantially ( Figs. 1 A and B, Figs. 2 A and B). We demonstrate how small spatial filter kernels bias the results towards subcortical and cerebellar activation clusters ( Fig. 1 B and B. We also show how the atlas-based anatomical assignment of regions shifts in relation to the filter size and how this may lead to substantially different functional interpretations of networks for language processing ( Fig. 1 A and 1B). Furthermore, we found substantially different scale-dependent cluster size dynamics between cortical and cerebellar clusters ( Fig. 2 D). We conclude that multiple spatial single-scale analyses expose the inter-individual anatomical variability of fMRI group data and may inform the interpretation of structure-function relationships. We propose to develop true spatial multiscale analyses to fully explore the deep structure of brain activations across Gaussian scale space.

Bias associated with the detectability of the coral-eating pest crown-of-thorns seastar and implications for reef management.

Outbreaks of the predator crown-of-thorns seastar (COTS) Acanthaster planci cause widespread coral mortality across the Indo-Pacific. Like many marine invertebrates, COTS is a nocturnal species whose cryptic behaviour during the day can affect its detectability, particularly in structurally complex reef habitats that provide many refuges for benthic creatures. We performed extensive day and night surveys of COTS populations in coral reef habitats showing differing levels of structural complexity and COTS abundance. We tested whether estimations of COTS density varied between day and night observations, and if the differences were related to changes in COTS abundance, reef structural complexity and the spatial scale of observation. Estimations of COTS density were on average 27% higher at night than during the day. Differences in COTS detection varied with changing seastar abundance but not reef structural complexity or scale of observation. Underestimation of COTS abundance in daytime was significant for a broad seastar density range, thus potentially affecting most outbreak events. Our study suggests that portions of COTS populations can be undetected during conventional surveys and control campaigns, which are exclusively conducted by day, and significantly affect the trajectory of coral reefs. Accounting for bias in COTS detection can strengthen coral reef management broadly.

General spatial spectral variation in rocky intertidal communities from three biogeographical regions

Aim Understanding general spatial patterns of multiple species is a central aim of biogeography. Spatial analyses of coastal marine assemblages have shown an emergent pattern in that the variability in population abundances increases with increasing spatial scale of observation; i.e. a “red” spectrum of variation in population abundances. However, the generalization of these patterns to other ecological levels and across biogeographical regions remains unexplored. Here, we evaluate the consistency of a reddened relationship between the scale of observation and the variance in ecosystem properties in sessile intertidal rocky-shore assemblages across three biogeographical regions. Location Replicate sites located in temperate (southern-central Chile), sub-Antarctic (Chilean South Patagonia) and Antarctic (West Antarctic Peninsula) regions. Methods A total of 16,225 photo-quadrants were used to analyse local patterns of total community cover, bare substratum, total algal cover and total invertebrate cover. We used spectral analyses in which the spatial variance of each property was decomposed along a gradient of increasing distances between observations. Cross-semivariograms were used to analyse the spatial covariation of dominant taxa. Results The analysed ecosystem properties showed a general reddened spectrum of variation that resembled patchy configurations of local communities. Additionally, cross-semivariance analyses indicated mainly negative relationships of covariation between the abundances dominant sessile species at each site, suggesting a general trend of spatial asynchrony between competing species. Main conclusions To the best of our knowledge, this is the first study showing a general reddened pattern of spatial variation in relevant ecosystem-level properties across the Pacific shore of South America, southern Patagonia and West Antarctic Peninsula. These patterns reflect the result of multiple biotic and abiotic processes that interact across spatial scales. In particular, we suggest that processes that generate spatial asynchrony between competing species, such as compensatory dynamics, are relevant to maintain the spatial structure of rocky-shore communities.

High-frequency side-scan sonar fish reconnaissance by autonomous underwater vehicles

A dichotomy between depth penetration and resolution as a function of sonar frequency, draw resolution, and beam spread challenges fish target classification from sonar. Moving high-frequency sources to depth using autonomous underwater vehicles (AUVs) mitigates this and also co-locates transducers with other AUV-mounted short-range sensors to allow a holistic approach to ecological surveys. This widely available tool with a pedigree for bottom mapping is not commonly applied to fish reconnaissance and requires the development of an interpretation of pelagic reflective features, revisitation of count methods, image-processing rather than wave-form recognition for automation, and an understanding of bias. In a series of AUV mission test cases, side-scan sonar (600 and 900 kHz) returns often resolved individual school members, spacing, size, behavior, and (infrequently) species from anatomical features and could be intuitively classified by ecologists — but also produced artifacts. Fish often followed the AUV and thus were videographed, but in doing so removed themselves from the sonar aperture. AUV-supported high-frequency side-scan holds particular promise for survey of scarce, large species or for synergistic investigation of predators and their prey because the spatial scale of observations may be similar to those of predators.

The influence of habitat structure, at different spatial scales, on the ecological distribution of macroalgal communities in streams

Habitat heterogeneity influences the composition and structure of macroalgal communities in lotic environments. However, depending on the spatial scale, different environmental characteristics may exert more or less influence. This study aimed to evaluate, at different spatial scales of observation, the influences of local and regional environmental variables on ecological distribution of macroalgae in stream ecosystems. The field work was conducted during the months of June and July 2007 in streams of two river basins located in southern Brazil. The spatial scales used were drainage basin, shading, mesohabitat, and microhabitat. According to the results, there are few differences regarding abiotic variables between spatial scales, however, suggesting that sunlight and, consequently, the shading scale have a strong impact on the distribution pattern of stream macroalgae. The mesohabitat scale at the current velocity proved to be an important factor in structuring communities of macroalgae. Finally, microenvironmental factors (e.g., substrate, current velocity, and light availability) appear to exert their direct influence on the spatial distribution of stream macroalgae, generating particular features in each spatial scale of observation, although regional abiotic parameters (e.g., temperature, pH, and conductivity) should also be considered for the structural characterization of these organisms.

Transport infrastructure shapes foraging habitat in a raptor community.

Transport infrastructure elements are widespread and increasing in size and length in many countries, with the subsequent alteration of landscapes and wildlife communities. Nonetheless, their effects on habitat selection by raptors are still poorly understood. In this paper, we analyzed raptors’ foraging habitat selection in response to conventional roads and high capacity motorways at the landscape scale, and compared their effects with those of other variables, such as habitat structure, food availability, and presence of potential interspecific competitors. We also analyzed whether the raptors’ response towards infrastructure depends on the spatial scale of observation, comparing the attraction or avoidance behavior of the species at the landscape scale with the response of individuals observed in the proximity of the infrastructure. Based on ecological hypotheses for foraging habitat selection, we built generalized linear mixed models, selected the best models according to Akaike Information Criterion and assessed variable importance by Akaike weights. At the community level, the traffic volume was the most relevant variable in the landscape for foraging habitat selection. Abundance, richness, and diversity values reached their maximum at medium traffic volumes and decreased at highest traffic volumes. Individual species showed different degrees of tolerance toward traffic, from higher abundance in areas with high traffic values to avoidance of it. Medium-sized opportunistic raptors increased their abundance near the traffic infrastructures, large scavenger raptors avoided areas with higher traffic values, and other species showed no direct response to traffic but to the presence of prey. Finally, our cross-scale analysis revealed that the effect of transport infrastructures on the behavior of some species might be detectable only at a broad scale. Also, food availability may attract raptor species to risky areas such as motorways.

Coordinated approaches for studying long-term ecosystem responses to global change.

be distinguished from long-term ‘experiments’ that permit the formulation of theory on ecophysiological and popula-tion-to-community-scale processes, and testing of that the-ory. In other words, we must conceive and conduct experi-ments at large enough spatial and temporal scales, and with sufficient complexity to effectively define ecosystem-level feedbacks (Osmond et al. 2004; Baldocchi et al. 2001).In more recent years, we have had access to process-based models that provide a useful means of generating hypotheses that can be tested by observations and expe-riential work. This permitted us to conduct experiments in silico: searching for optimal fits between theory and observations using models and maximum likelihood statis-tics. The models used for long-term assessments are usu-ally built upon knowledge of ecosystem processes, and are often parameterized by short-term observations and experi-mental manipulation data. While this is still necessary, we can now go beyond this and use observations in ways other than for parameterization. Observations can now be used to test the adequacy for theory to represent processes, and provide validation through the assimilation of observations into the models with robust statistical tests of how well the theory permits the model to match the data (e.g., Zobitz et al. 2011; Leuzinger et al. 2011).The third component of global change ecological studies refers to the large-scale context of the study and its envi-ronmental representation. This may require large facili-ties, extensive instrumentation, and a large spatial scale of observation (e.g., remote sensing; Sellers 1993), networks of research sites (e.g., Baldocchi et al. 2001), or large-scale experimental systems (Gonzalez-Meler et al. 2014). While these requirements are often recognized individually, they are rarely discussed in an integrative manner within national or international research frameworks conducting global change research (Osmond et al. 2004).