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64 results for “Seasonal environment”
Many roads to success: Different combinations of life-history traits provide accurate germination timing in seasonally dry environments
Germination timing is determined by several plant life-history traits. Seed dormancy regulates the time and place of early plant development and spreads recruitment risks over time. Dispersal phenology and syndrome can influence germination timing and buffer spatial heterogeneity. The ecological requirements for germination (the germination niche) can also influence when and where germination takes place. To date, the relative importance of each of these four traits to ensure the phenological adaptation of individual species in diverse communities remains unexplored. Here, we investigated the functional interactions among them and their relevance in heterogenous, seasonally dry environments. We collected seed dispersal phenology and syndrome for 82 species of the Brazilian savanna (cerrado) and evaluated the dormancy and germination behavior of the seeds of every taxon. Based on these data, we developed two new ecological indexes to estimate the likelihood of a non-dormant seed to germinate upon dispersal (∆G) and the overall variability of germination through time (σT). We then evaluated the influence of each trait on germination timing within a phylogenetically controlled framework. Our results show that even though germination is concentrated at the beginning of the rainy season, seed dispersal takes place year-round. Non-dormant seeds released during the dry season were characterized by high ∆G values that delayed their germination until the onset of the favorable season. Simultaneously, seed dormancy and spatial dispersal (i.e., the two risk-reduction mechanisms) were negatively correlated as dormancy and high σT values were only prevalent in seeds with reduced spatial dispersal ability. We conclude that the timing of seed germination is ultimately the net outcome of adaptive interactions among life-history traits, which can result in multiple functionally equivalent phenotypes. It is possible that this might contribute to community diversity by providing opportunities for the coexistence of different species.
Data from: Causes and consequences of avian within-season dispersal decisions in a dynamic grassland environment
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Data from: thyroid hormone concentrations in female baboons: metabolic consequences of living in a highly seasonal environment
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Hydrological connectivity and local environment alternately drive spatial structure of floodplain aquatic community across season
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Variation in the resource environment affects patterns of seasonal adaptation at phenotypic and genomic levels in <em>Drosophila melanogaster</em>
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Seasonal dynamics in the mammalian microbiome between disparate environments
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Data from: Light environment and seasonal variation in the visual system of the red shiner (Cyprinella lutrensis)
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Many roads to success: Different combinations of life-history traits provide accurate germination timing in seasonally dry environments
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Data from: Acclimation of leaf traits in seasonal light environments: are non-native species more plastic?
1. In temperate deciduous forests, understory light environments vary dramatically throughout spring, summer, and autumn due to tree canopy leaf display. This variability in light level is a physiological challenge for understory species that produce sun-adapted leaves in the spring before being shaded by the tree canopy. Similarly, some understory species display leaves late into autumn after the tree canopy senesces. 2. Many species in North American deciduous forests with extended leaf display are not native to North America. Since many non-native species have been shown to have greater plasticity than natives, we hypothesized that leaves of non-native species may be more plastic with respect to seasonal light changes than natives, and that this plasticity may allow them to assimilate more carbon in the same environment. 3. We measured leaf traits and photosynthetic capacity of 17 native and 13 non-native understory shrub species in a common garden in Syracuse, New York, during spring, summer, and autumn. We tested for the contribution of seasonal mean and variance (plasticity) of leaf traits to a species' average photosynthetic rate and total leaf production. We also analyzed the extent to which leaf adjustments depended on whether plants continued to produce new leaves over the growing season. 4. Leaf traits of both native and non-native species varied seasonally, but plasticity varied in extent and contribution to overall carbon gain. Non-native species had the highest seasonal plasticity, but, contrary to our hypothesis, such plasticity did not contribute to their overall carbon gain. However, leaf trait plasticity was adaptive for native species that continued to produce leaves throughout the year, primarily due to increases in quantum efficiency and electron transport rate in leaves produced mid-year compared to leaves produced early in the year. 5. Synthesis. Despite large adjustments in leaf traits across seasonal light environments for both native species and non-native species, we found little evidence that leaf-level plasticity drives non-native invasion or contributes strongly to annual carbon gain or productivity in understory species. Instead, differences in mean leaf traits across seasons are sufficient to explain carbon gain advantages of non-native woody species in deciduous forests.
Data from: Seasonal differences in baseline innate immune function are better explained by environment than annual cycle stage in a year-round breeding tropical songbird
1. Seasonal variation in innate immunity is often attributed to either temporal environmental variation or to life history trade-offs that arise from specific annual cycle stages but decoupling them is difficult in natural populations. 2. Here, we effectively decouple seasonal environmental variation from annual cycle stage effects by exploiting cross-seasonal breeding and moult in the tropical Common Bulbul Pycnonotus barbatus. We test how annual cycle stage interacts with a key seasonal environmental variable, rainfall, to determine immunity at population and individual level. If immune challenge varies with precipitation, we might expect immune function to be higher in the wet season due to increased environmental productivity. If breeding or moult imposes resource constraints on birds, depending on or independent of precipitation, we might expect lower immune indices during breeding or moult. 3. We sampled blood from 818 birds in four annual cycle stage categories: breeding, moult, simultaneous breeding and moulting, or neither. We quantified indices of innate immunity (haptoglobin, nitric oxide (NOx) and ovotransferrin concentrations, and haemagglutination and haemolysis titres) over two annual cycles of wet and dry seasons. 4. Environment (but not annual cycle stage or interactions between both) explained variation in all immune indices, except NOx. NOx concentration differed between annual cycle stages but not between seasons. However, within the wet season, haptoglobin, NOx, ovotransferrin and haemolysis differed significantly between breeding and non-breeding females. Aside from some recorded inconsistences, population level results were largely similar to results within individuals that were measured repeatedly. Unexpectedly, most immune indices were higher in the dry season and during breeding. 5. Higher immune indices may be explained if fewer or poorer quality resources force birds to increase social contact, thereby exposing individuals to novel antigens and increased infection risk, independently of environmental productivity. Breeding birds may also show higher immunity if less immune-competent and/or infected females omit breeding. We conclude that seasonal environmental variation impacts immunity more directly in natural animal populations than via resource trade-offs. In addition, immune indices were more often variable within than among individuals, but some indices are characteristic of individuals, and so may offer selective advantages if heritable.
Genomic prediction applied to multiple traits and environments in second season maize hybrids
<p>Genomic selection has become a reality in plant breeding programs with the reduction in genotyping costs. Especially in maize breeding programs, it emerges as a promising tool for predicting hybrid performance. The dynamics of a commercial breeding program involve the evaluation of several traits simultaneously in a large set of target environments. Therefore, multi-trait multi-environment (MTME) genomic prediction models can leverage these data sets by exploring the correlation between traits and Genotype-by-Environment (G×E) interaction. Herein, we assess predictive abilities of univariate and multivariate genomic prediction models in a maize breeding program. To this end, we used data from 415 maize hybrids evaluated in four years of second season field trials for the traits grain yield, number of ears and grain moisture. Genotypes of these hybrids were inferred <i>in silico</i> based on their parental inbred lines using Single Nucleotide Polymorphisms (SNPs) markers obtained via genotyping-by-sequencing (GBS). Because genotypic information was available for only 257 hybrids, we used the genomic and pedigree relationship matrices to obtain the <b>H</b> matrix for all 415 hybrids. Our results demonstrated that in the single-environment context the use of multi-trait models was always superior in comparison to their univariate counterparts. Besides that, although MTME models were not particularly successful in predicting hybrid performance in untested years, they improved the ability to predict the performance of hybrids that had not been evaluated in any environment. However, the computational requirements of this kind of model could represent a limitation to its practical implementation and further investigation is necessary.</p>
Data from: Temporal variation in plant-pollinator networks from seasonal tropical environments: higher specialization when resources are scarce
The temporal dynamics of plant phenology and pollinator abundance across seasons should influence the structure of plant-pollinator interaction networks. Nevertheless, such dynamics are seldom considered, especially for diverse tropical networks. Here, we evaluated the temporal variation of four plant-pollinator networks in two seasonal ecosystems in Central Brazil (Cerrado and Pantanal). Data were gathered on a monthly basis over one year for each network. We characterized seasonal and temporal shifts in plant-pollinator interactions, using temporally discrete networks. We predicted that the greater floral availability in the rainy season would allow for finer partitioning of the floral niche by the pollinators, i.e., higher specialization patterns as previously described across large spatial gradients. Contrary to these expectations, we found that dry season networks, although characterized by lower floral resource richness and abundance, showed higher levels of network-wide interaction partitioning (complementary specialization and modularity). For nestedness and species level indices, though, this between-seasons difference was not consistent. Reduced resource availability in the dry season may promote higher interspecific competition among pollinators leading to reduced niche overlap, thus explaining the increase in specialization. Importantly, we also show that targeted data collection during peak flowering generates higher estimates of network specialization. Hence, depending on the period of data collection, different structural values for the networks of interactions may be found. Synthesis: Our study suggests that networks of tropical environments have structural properties that vary according to seasons, which should be taken into account in the description of the complex systems of interactions between plants and their pollinators in these areas.
Data from: Weak whole-plant trait coordination in a seasonally dry South American stressful environment
A core question involving both plant physiology and community ecology is whether traits from different organs are coordinated across species, beyond pairwise trait correlations. The strength of within-community trait coordination has been hypothesized to increase along gradients of environmental harshness, due to the cost of adopting ecological strategies out of the viable niche space supported by the abiotic conditions. We evaluated the strength of trait relationship and coordination in a stressful environment using 21 leaf and stem traits of 21 deciduous and evergreen woody species from a heath vegetation growing on coastal sandy plain in northeastern South America. The study region faces marked dry season, high soil salinity and acidity, and poor nutritional conditions. Results from multiple factor analyses supported two weak and independent axes of trait coordination, which accounted for 25%–29% of the trait variance using phylogenetically independent contrasts. Trait correlations on the multiple factor analyses main axis fit well with the global plant economic spectrum, with species investing in small leaves and dense stems as opposed to species with softer stems and large leaves. The species' positions on the main functional axis corresponded to the competitor-stress-tolerant side of Grime's CSR triangle of plant strategies. The weak degree of trait coordination displayed by the heath vegetation species contradicted our expectation of high trait coordination in stressful environmental habitats. The distinct biogeographic origins of the species occurring in the study region and the prevalence of a regional environmental filter coupled with local homogeneous conditions could account for prevalence of trait independence we observed.
Data from: Ecology of the growth of Anolis nebulosus (Squamata: Dactyloidae) in a seasonal tropical environment in the Chamela region, Jalisco, Mexico
Juvenile growth rates are thought to be restricted by available food resources. In animals that grow throughout the year, such as tropical lizards, growth is therefore predicted to be faster during the rainy season. We test this prediction using a population of Anolis nebulosus by describing the growth trajectories of both sexes using nonlinear regression models, and we then correlate the growth rates of individuals with food available in the environment, precipitation and temperature. The Von Bertalanffy model fit the growth rates of the females better, while the logistic-by-length model fit the males better. According to both models, the males grew faster than females, reaching slightly smaller sizes at adulthood. Males reached sexual maturity when 35 mm long, at an age of seven months, and females matured at 37 mm (SVL), taking nine months to reach this size. In 1989, juvenile males and females grew more in both seasons (rainy and dry) than adults; for 1990 there were no differences by season or between age classes. These results are interesting since in the 1989 and 1990 rainy seasons, practically the same orders of prey and the greatest abundance of prey available in the environment were registered. A possible explanation could be that predation was more intense in 1990 than in 1989. The influence of food, temperature and humidity in A. nebulosus shows little evidence to support our working hypothesis, mainly due to the low growth variation observed in 1990, so, we believe that the growth pattern of this species can be a complex combination of ecological and genetic factors.
Seasonal particle responses to near-bed shear stress in a shallow, wave- and current-driven environment
<p>Novel analysis of in-situ acoustic and optical data collected in a shallow, wave- and current-driven environment enabled determination of: (1) particle characteristics that were most affected by near-bed physical forcing over seasonal scales, and (2) characteristic shear stress, t<sub>char</sub>, at which the rate of change to particle characteristics was most pronounced. Near-bed forcing and particle responses varied by season. Results indicated that moderate t<sub>char</sub> values of 0.125 Pa drove changes in particle composition during summer. In winter, particle concentration effects were most affected at t<sub>char</sub> of 0.05 Pa, suggesting dominance of fluff layer resuspension. Changes to particle size were most relevant during a biologically productive springtime period, with initiation of particle disaggregation occurring most commonly at t<sub>char</sub> of 0.25 Pa. These results suggest that it may be more important to parameterize t<sub>char</sub>, as opposed to critical shear stress for erosion, for sediment transport models.</p>
Evaluation of Thermal Comfort Conditions in The Working Environments of Seasonal Agricultural Workers in Csa Koppen Climate Type
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Data from: Pseudomonas putida and Pseudomonas fluorescens species group recovery from human homes varies seasonally and by environment
By shedding light on variation in time as well as in space, long-term biogeographic studies can help us define organisms' distribution patterns and understand their underlying drivers. Here we examine distributions of Pseudomonas in and around 15 human homes, focusing on the P. putida and P. fluorescens species groups. We describe recovery from 10,941 samples collected during up to 8 visits per home, occurring on average 2.6 times per year. We collected a mean of 141 samples per visit, from sites in most rooms of the house, from the surrounding yards, and from human and pet occupants. We recovered Pseudomonas in 9.7% of samples, with the majority of isolates being from the P. putida and P. fluorescens species groups (approximately 62% and 23% of Pseudomonas samples recovered respectively). Although representatives of both groups were recovered from every season, every house, and every type of environment sampled, recovery was highly variable across houses and samplings. Whereas recovery of P. putida group was higher in summer and fall than in winter and spring, P. fluorescens group isolates were most often recovered in spring. P. putida group recovery from soils was substantially higher than its recovery from all other environment types, while higher P. fluorescens group recovery from soils than from other sites was much less pronounced. Both species groups were recovered from skin and upper respiratory tract samples from healthy humans and pets, although this occurred infrequently. This study indicates that even species that are able to survive under a broad range of conditions can be rare and variable in their distributions in space and in time. For such groups, determining patterns and causes of stochastic and seasonal variability may be more important for understanding the processes driving their biogeography than the identity of the types of environments in which they can be found.
Data from: Pseudomonas putida and Pseudomonas fluorescens species group recovery from human homes varies seasonally and by environment
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Data from: Temporal variation in plant-pollinator networks from seasonal tropical environments: higher specialization when resources are scarce
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Data from: Weak whole-plant trait coordination in a seasonally dry South American stressful environment
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.