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publicJun 2017View details →

Data from: Evidence of local adaptation to fine- and coarse-grained environmental variability in Poa alpina in the Swiss Alps

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publicAug 2021View details →

Foraging in a dynamic environment: response of four sympatric sub-Antarctic albatross species to interannual environmental variability

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publicApr 2019View details →

Data from: A functional diversity approach of crop sequences reveals that weed diversity and abundance show different responses to environmental variability

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publicDec 2016View details →

Data from:Intraspecific variability improves environmental matching, but does not increase ecological breadth along a wet-to-dry ecotone

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publicMar 2025View details →

Dataset of biofouling epibionts on microalgae compiled from literature and environmental variables from open access databases

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publicMar 2020View details →

Connecting species’ geographical distributions to environmental variables: range maps versus observed points of occurrence

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opencc-by-4.0Mar 2020View details →

Supplementary Data: "Environmental variables determining the distribution of an avian parasite: the case of the Philornis torquans complex (Diptera: Muscidae) in South America"

Supplementary material in the work "Environmental variables determining the presence of an avian parasite: the case of the Philornis torquans complex (Diptera: Muscidae) in South America"

opencc-zeroDec 2015View details →

Data from: Estimating fish abundance and biomass from eDNA concentrations: variability among capture methods and environmental conditions

Environmental DNA (eDNA) promises to ease non-invasive quantification of fish biomass or abundance, but its integration within conservation and fisheries management is currently limited by a lack of understanding of the influence of eDNA collection method and environmental conditions on eDNA concentrations in water samples. Water temperature is known to influence the metabolism of fish and consequently could strongly affect eDNA release rate. As water temperature varies in temperate regions (both seasonally and geographically), the unknown effect of water temperature on eDNA concentrations poses practical limitations on quantifying fish populations using eDNA from water samples. This study aims to clarify how water temperature and the eDNA capture method alter the relationships between eDNA concentration and fish abundance/biomass. Water samples (1 L) were collected from 30 aquaria including triplicate of 0, 5, 10, 15 and 20 Brook Charr specimens at two different temperatures. Water samples were filtered with five different types of filters. The eDNA concentration obtained by quantitative PCR (qPCR) varied significantly with fish abundance and biomass and type of filters (Mixed-design ANOVA, P < 0.001). Results also show that fish released more eDNA in warm water than cold water and that eDNA concentration better reflects fish abundance/biomass at high temperature. From a technical standpoint, higher levels of eDNA were captured with glass fiber (GF) than mixed cellulose ester (MCE) filters and support the importance of adequate filters to quantify fish abundance based on the eDNA method. This study supports the importance of including water temperature in fish abundance/biomass prediction models based on eDNA.

opencc-zeroDec 2013View details →

Data from: Correlative changes in life history variables in response to environmental change in a model organism

Global change alters the environment, including increases in the frequency of (un)favorable events and shifts in environmental noise color. However, how these changes impact the dynamics of populations, and whether these can be predicted accurately has been largely unexamined. Here we combine recently developed population modeling approaches and theory in stochastic demography to explore how life history, morphology, and average fitness respond to changes in the frequency of favorable environmental conditions and in the color of environmental noise in a model organism (an acarid mite). We predict that different life-history variables respond correlatively to changes in the environment, and we identify different life-history variables, including lifetime reproductive success, as indicators of average fitness and life-history speed across stochastic environments. Depending on the shape of adult survival rate, generation time can be used as an indicator of the response of populations to stochastic change, as in the deterministic case. This work is a useful step toward understanding population dynamics in stochastic environments, including how stochastic change may shape the evolution of life histories.

opencc-zeroDec 2013View details →

Data from: Environmental variability counteracts priority effects to facilitate species coexistence: evidence from nectar microbes

The order of species arrival during community assembly can greatly affect species coexistence, but the strength of these effects, known as priority effects, appears highly variable across species and ecosystems. Furthermore, the causes of this variation remain unclear despite their fundamental importance in understanding species coexistence. Here, we show that one potential cause is environmental variability. In laboratory experiments using nectar-inhabiting microorganisms as a model system, we manipulated spatial and temporal variability of temperature, and examined consequences for priority effects. If species arrived sequentially, multiple species coexisted under variable temperature, but not under constant temperature. Temperature variability prevented extinction of late-arriving species that would have been excluded owing to priority effects if temperature had been constant. By contrast, if species arrived simultaneously, species coexisted under both variable and constant temperatures. We propose possible mechanisms underlying these results using a mathematical model that incorporates contrasting effects of microbial species on nectar pH and amino acids. Overall, our findings suggest that understanding consequences of priority effects for species coexistence requires explicit consideration of environmental variability.

opencc-zeroDec 2017View details →

Data from: Environmental determinism, and not interspecific competition, drive morphological variability in Australasian warblers (Acanthizidae)

Interspecific competition is thought to play a key role in determining the coexistence of closely related species within adaptive radiations. Competition for ecological resources can lead to different outcomes from character displacement to, ultimately, competitive exclusion. Accordingly, divergent natural selection should disfavor those species that are the most similar to their competitor in resource use, thereby increasing morphological disparity. Here we examined ecomorphological variability within an Australo-Papuan bird radiation, the Acanthizidae, which include both allopatric and sympatric complexes. In addition, we investigated whether morphological similarities between species are related to environmental factors at fine- (foraging niche) and/or large-scale (climate). Contrary to that predicted by the competition hypothesis, we did not find a significant correlation between the morphological similarities found between species and their degree of range overlap. Comparative modelling based on both a priori and data-driven identification of selective regimes suggested that foraging niche is a poor predictor of morphological variability in acanthizids. By contrast, our results indicate that climatic conditions were an important factor in the formation of morphological variation. We found a significant negative correlation between species scores for PC1 (positively associated to tarsus length and tail length) and both temperature and precipitation, whereas PC2 (positively associated to bill length and wing length) correlated positively with precipitation. In addition, we found that species inhabiting the same region are closer to each other in morphospace than to species outside that region regardless of genus to which they belong or its foraging strategy. Our results indicate that the conservative body form of acanthizids is one that can work under a wide variety of environments (an all-purpose morphology) and the observed interspecific similarity is probably driven by the common response to environment.

opencc-zeroDec 2015View details →

Data from: Intraspecific variability in growth response to environmental fluctuations modulates the stabilizing effect of species diversity on forest growth

1.Differences between species in their response to environmental fluctuations cause asynchronized growth series, suggesting that species diversity may help communities buffer the effects of environmental fluctuations. However, within-species variability of responses may impact the stabilizing effect of growth asynchrony. 2.We used tree ring data to investigate the diversity-stability relationship and its underlying mechanisms within the temperate and boreal mixed woods of Eastern Canada. We worked at the individual tree level to take into account the intraspecific variability of responses to environmental fluctuations. 3.We found that species diversity stabilized growth in forest ecosystems. The asynchrony of species' response to climatic fluctuations and to insect outbreaks explained this effect. We also found that the intraspecific variability of responses to environmental fluctuations was high, making the stabilizing effect of diversity highly variable. 4.Synthesis. Our results are consistent with previous studies suggesting that the asynchrony of species' response to environmental fluctuations drives the stabilizing effect of diversity. The intraspecific variability of these responses modulates the stabilizing effect of species diversity. Interactions between individuals, variation in tree size and spatial heterogeneity of environmental conditions could play a critical role in the stabilizing effect of diversity.

opencc-zeroDec 2014View details →

Data from: Disentangling environmental drivers of metabolic flexibility in birds: the importance of temperature extremes versus temperature variability

Examining physiological traits across large spatial scales can shed light on the environmental factors driving physiological variation. For endotherms, flexibility in aerobic metabolism is especially important for coping with thermally challenging environments and recent research has shown that aerobic metabolic scope [the difference between maximum thermogenic capacity (Msum) and basal metabolic rate (BMR)] increases with latitude in mammals. One explanation for this pattern is the climatic variability hypothesis, which predicts that flexibility in aerobic metabolism should increase as a function of local temperature variability. An alternative explanation is the cold adaptation hypothesis, which predicts that cold temperature extremes may also be an important driver of variation in metabolic scope. To determine the thermal drivers of aerobic metabolic flexibility in birds, we combined data on metabolic scope from 40 bird species sampled across a range of environments with several indices of local ambient temperature. Using phylogenetically-informed analyses, we found that minimum winter temperature was the best predictor of variation in avian metabolic scope, outperforming all other thermal variables. Additionally, Msum was a better predictor of latitudinal patterns of metabolic scope than BMR, with species inhabiting colder environments exhibiting increased Msum over their counterparts in warmer environments. Taken together, these results suggest that cold temperature extremes drive latitudinal patterns of metabolic scope via selection for enhanced thermogenic performance in cold environments, supporting the cold adaptation hypothesis. Temperature extremes may therefore be an important selective pressure driving macrophysiological trends of aerobic performance in endotherms.

opencc-by-4.0Nov 2024View details →

Environmental variables and occurrence points of Solenopsis geminata

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opencc-zeroFeb 2022View details →

Myxophies species location and environmental variables

1. Species distribution modeling, which allows users to predict the spatial distribution of species with the use of environmental covariates, has become increasingly popular, with many software platforms providing tools to fit such models. However, the species observations used can have varying levels of quality and can have incomplete information, such as uncertain or unknown species identity. 2. In this paper, we develop two algorithms to classify observations with unknown species identities which simultaneously predict several species distributions using spatial point processes. Through simulations, we compare the performance of these algorithms using 7 different initializations to the performance of models fitted using only the observations with known species identity. 3. We show that performance varies with differences in correlation among species distributions, species abundance, and the proportion of observations with unknown species identities. Additionally, some of the methods developed here outperformed the models that didn't use the misspecified data. We applied the best-performing methods to a dataset of three frog species (Mixophyes). 4. These models represent a helpful and promising tool for opportunistic surveys where misidentification is possible or for the distribution of species newly separated in their taxonomy.

opencc-zeroMar 2022View details →

Data and climate variable selection from: Effects of density, species interactions and environmental stochasticity on the dynamics of British bird communities

Our knowledge of the factors affecting species abundances is mainly based on time-series analyses of a few well-studied species at single or few localities, but we know little about whether results from such analyses can be extrapolated to the community level. We apply a Joint Species Distribution Model to long-term time-series data on British bird communities to examine the relative contribution of intra- and interspecific density dependence at different spatial scales, as well as the influence of environmental stochasticity, to spatio-temporal interspecific variation in abundance. Intraspecific density dependence has the major structuring effect on these bird communities. In addition, environmental fluctuations affect spatiotemporal differences in abundance. In contrast, species interactions had a minor impact on variation in abundance. Thus, important drivers of single-species dynamics are also strongly affecting dynamics of communities in time and space.

opencc-zeroJun 2022View details →

Number of terrestrial leeches with human-bait method and environmental variables in peninsular Malaysia

This is the data on the number of terrestrial leeches (brown Haemadipsa sp.) collected and environmental variables at the sampling site in Endau Rompin National Park in Malaysia. We investigated relative abundance of terrestrial leeches repeatedly at 99 sampling points in the tourism area of ERNP from February 2019 to September 2020. We counted the number of leeches at each sampling point based on the human-bait method, wherein the researcher is considered as the bait (Schnell et al. 2015, Fahmy et al. 2019). To activate the leeches before sampling, the leaf litter was blown upon and stirred with a twig in a 1.5-m radius from the sampling point. A researcher then stood at the sampling point and collected all the leeches attracted and attached to the body in a five-minute sampling session (Kendall, 2012). We collected the leeches in a vial and measured the diameter of the sucking cup of each individual as a proxy for leech size: <1.5 mm = small, 1.5–3.0 mm = medium, and >3.0 mm = large. At the start of the sampling session, any leeches on the researcher's body were removed and discarded. The leeches collected in the vial were all released at the sampling point after being counted and measured. Since leeches could detect host up to 2.0 m in our pilot survey, the relative abundance here can be regarded as a rough estimate of density of active leeches per 12.6 m2 (an area within 2-m radius). The microenvironmental variables at each sampling point and time were measured to examine their effects on active leech relative abundance. These variables included air humidity, air temperature (°C), light intensity (lux), altitude (m), distance to the nearest river (m), distance to the nearest rain flow path (i.e., small valley through which water would flow in heavy rain) (m), percentage of bare ground (%), percentage of canopy openness (%), mean litter layer depth (mm), and topsoil moisture (%). Air humidity, air temperature, and light intensity were measured using a handheld Illuminance UV recorder (TR-74Ui). The distances to the nearest stream and river were calculated using ArcMap 10.2.2. (ESRI Inc.). The altitude was measured using a handheld Garmin geographic positioning system (GPS). The percentage of canopy openness and bare ground were measured using hemispherical photography via smartphone cameras equipped with "fisheye" lenses (Bianchi et al. 2017) in the near-vertical skyward and downward directions, respectively. The litter layer depths were visually measured using a ruler. Soil moisture was measured directly at every sampling point using a soil moisture meter (Takemura Soil Moisture Meter DM 18). The percentages of bare ground, canopy openness, litter layer depth, and topsoil moisture, were recorded three times at randomly selected points around the sampling point, and the average value was considered for the analyses. To measure human and wildlife relative abundance, we installed passive infrared camera traps (O'Connell et al. 2011) (Ltl Acorn Ltl-6210MC, Cams Co., Ltd., Tokyo, Japan), which were triggered automatically by movement, at 24 on-trail sampling points. The camera was operated from February 2019 to September 2020 (560 days and 8,230 trap nights). The sampling points included trails with a gradient of tourist-use frequency. Each camera was mounted approximately 30–40 cm above the ground (Luo et al. 2019) to capture a wide range of animals of different sizes (Mugerwa et al. 2013). The cameras were set up in video mode with 15 s in video length and 30 s in the interval between videos, which was sufficient to record the group activity of potential hosts (wildlife or humans). The number of individuals in each video was counted. To prevent double-counting individuals, a one-hour interval sequence was introduced between videos of a specific individual of the same species (Azlan & Sharma 2006). Each animal in the videos was identified at the species level, based on Francis (2008). Due to low image resolution, we could not identify smaller animals, such as bats and rats at the species level.

opencc-zeroJun 2022View details →

Environmental variables and occurrence of 13 fish species

Species-environment relationships were studied between the occurrence of 13 fish and lamprey species and 9 mainly map-based environmental variables of Finnish boreal small streams. A self-organizing map (SOM) analysis showed strong relationships between the fish species and environmental variables in a single model (explained variance 55.9%). Besides basic environmental variables such as altitude, catchment size, and mean temperature, landcover variables were also explored. A logistic regression analysis indicated that the occurrence probability of brown trout, Salmo trutta L., decreased with an increasing percentage of peatland ditch drainage in the upper catchment. Ninespine stickleback, Pungitius pungitius (L.), and three-spined stickleback, Gasterosteus aculeatus L., seemed to benefit from urban areas in the upper catchment. Discovered relationships between fish species occurrence and land-use attributes are encouraging for the development of fish-based bioassessment for small streams. The presented ordination of the fish species in the mean temperature gradient will help in predicting fish community responses to climate change.

opencc-by-4.0Mar 2016View details →

Fig. 4 in Wing shape is influenced by environmental variability in Polietina orbitalis (Stein) (Diptera: Muscidae)

Fig. 4. Graphic reconstruction of the wing shape of individuals with (A) positive and (B) negative scores on the first canonical axis (CV1, increased 10 times). The lines in gray represent the average configuration of the wing, and those in black represent the canonical first variable.