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92 results for “ecological processes”
Sub-speciation processes of equids in the Iberian Peninsula: ecological strategies and refuge areas
<p>Metrical raw data of teeth and bones of Equus caballus and Equus hydruntinus from Canyars (Catalunya, Spain)</p> <p>They document the publication : Uzunidis, Sanz, Daura, 2024, Sub-speciation processes of equids in the Iberian Peninsula: ecological strategies and refuge areas, Quaternary Science Reviews, 325, 108473. https://www.sciencedirect.com/science/article/abs/pii/S0277379123005218</p>
Pitfalls of ignoring trait resolution when drawing conclusions about ecological processes
<p><strong>Aim:</strong> Understanding how ecological communities are assembled remains a grand challenge in ecology with direct implications for charting the future of biodiversity. Trait-based methods have emerged as the leading approach for quantifying functional community structure (convergence, divergence) but their potential for inferring assembly processes rests on accurately measuring functional dissimilarity among community members. Here, we argue that trait resolution (from finest-resolution continuous measurements to coarsest-resolution binary categories) remains a critically overlooked methodological variable, even though categorical classification is known to mask functional variability and inflate functional redundancy among species or individuals.</p> <p><strong>Innovation:</strong> We present the first detailed predictions of trait resolution biases and demonstrate, with simulations, how the distortion of signal strength by increasingly coarse-resolution traits can fundamentally alter functional structure patterns and the interpretation of causative ecological processes (e.g., abiotic filters, biotic interactions). We show that coarser trait data impart different impacts on the signals of divergence and convergence, implying that the role of biotic interactions may be underestimated when using coarser traits. Furthermore, in some systems, coarser traits may overestimate the strength of trait convergence, leading to erroneous support for abiotic processes as the primary drivers of community assembly or change.</p> <p><strong>Main conclusions:</strong> Inferences of assembly processes must account for trait resolution to ensure robust conclusions, especially for broad-scale studies of comparative community assembly and biodiversity change. Despite recent improvements in the collection and availability of trait data, great disparities continue to exist among taxa in the number and availability of continuous traits, which are more difficult to acquire for large numbers of species than coarse categorial assignments. Based on our simulations, we urge the consideration of trait resolution in the design and interpretation of community assembly studies and suggest a suite of practical solutions to address the pitfalls of trait resolution biases.</p>
Data from: Fractal triads efficiently sample ecological diversity and processes across spatial scales
<p>The relative influence of ecological assembly processes, such as environmental filtering, competition, and dispersal, vary across spatial scales. Changes in phylogenetic and taxonomic diversity across environments provide insight into these processes, however, it is challenging to assess the effect of spatial scale on these metrics. Here, we outline a nested sampling design that fractally spaces sampling locations to concentrate statistical power across spatial scales in a study area. We test this design in northeast Utah, at a study site with distinct vegetation types (including sagebrush steppe and mixed conifer forest), that vary across environmental gradients. We demonstrate the power of this design to detect changes in community phylogenetic diversity across environmental gradients and assess the spatial scale at which the sampling design captures the most variation in empirical data. We find clear evidence of broad-scale changes in multiple features of phylogenetic and taxonomic diversity across aspect. At finer scales, we find additional variation in phylodiversity, highlighting the power of our fractal sampling design to efficiently detect patterns across multiple spatial scales. Thus, our fractal sampling design and analysis effectively identify important environmental gradients and spatial scales that drive community phylogenetic structure. We discuss the insights this gives us into the ecological assembly processes that differentiate plant communities found in northeast Utah.</p>
Pitfalls of ignoring trait resolution when drawing conclusions about ecological processes
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Data from: Fractal triads efficiently sample ecological diversity and processes across spatial scales
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Ecological network structure in response to community assembly processes over evolutionary time
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Reliably predicting pollinator abundance: challenges of calibrating process-based ecological models
<p>1. Pollination is a key ecosystem service for global agriculture but evidence of pollinator population declines is growing. Reliable spatial modelling of pollinator abundance is essential if we are to identify areas at risk of pollination service deficit and effectively target resources to support pollinator populations. Many models exist which predict pollinator abundance but few have been calibrated against observational data from multiple habitats to ensure their predictions are accurate.</p> <p>2. We selected the most advanced process-based pollinator abundance model available and calibrated it for bumblebees and solitary bees using survey data collected at 239 sites across Great Britain. We compared three versions of the model: one parameterised using estimates based on expert opinion, one where the parameters are calibrated using a purely data-driven approach and one where we allow the expert opinion estimates to inform the calibration process.</p> <p>3. All three model versions showed significant agreement with the survey data, demonstrating this model's potential to reliably map pollinator abundance. However, there were significant differences between the nesting/floral attractiveness scores obtained by the two calibration methods and from the original expert opinion scores.</p> <p>4. Our results highlight a key universal challenge of calibrating spatially-explicit, process-based ecological models. Notably, the desire to reliably represent complex ecological processes in finely mapped landscapes necessarily generates a large number of parameters, which are challenging to calibrate with ecological and geographical data that is often noisy, biased, asynchronous and sometimes inaccurate. Purely data-driven calibration can therefore result in unrealistic parameter values, despite appearing to improve model-data agreement over initial expert opinion estimates. We therefore advocate a combined approach where data-driven calibration and expert opinion are integrated into an iterative Delphi-like process, which simultaneously combines model calibration and credibility assessment. This may provide the best opportunity to obtain realistic parameter estimates and reliable model predictions for ecological systems with expert knowledge gaps and patchy ecological data.</p>
Ecological and evolutionary processes shape belowground springtail communities along an elevational gradient
<p> The data sets were analyzed during the current study. Data from: Ecological and evolutionary processes shape belowground springtail communities along an elevational gradient</p>
Underlying microevolutionary processes parallel macroevolutionary patterns in ancient Neotropical Mountains - Ecological Niche Modeling and Corridors files
<p><b>Aim</b></p> <p>Ancient climatic fluctuations are invoked as the main driving force that generates the astonishing biodiversity in ancient mountains. As a result, endemism and spatial turnover are usually high and few species are widespread among entire mountain ranges, precluding the understanding of origins of macroevolutionary patterns. Here, we used a species endemic to, but widespread in, one of the most species-rich ancient mountains on the globe to test how environmental changes acted on them and how their macroevolutionary patterns were shaped.</p> <p><b>Location</b></p> <p>Espinhaço Range, Eastern Brazil.</p> <p><b>Taxon</b></p> <p><i>Vriesea oligantha </i>species complex (Bromeliaceae).</p> <p><b>Methods</b></p> <p>We compiled data for plastidial regions and nuclear microsatellites to assess genetic diversity, population structure, migration rates and phylogenetic relationships. Using temperature and precipitation variables we modeled suitable areas for the present and the past, estimating corridors between isolated populations. We also implemented Bayesian demographic analyses to estimate ancient populations dynamics. Finally, we tested if population structure is driven by isolation by environment or by distance using a Bayesian modeling approach.</p> <p><b>Results</b></p> <p>Our results showed that the intraspecific divergence events of <i>V. oligantha</i> are older than those associated with the latest Pleistocene climatic oscillations, supporting the view that Quaternary climatic fluctuations are key components for understanding its population differentiation processes. Species distribution modeling estimated corridors between populations in the past, as also shown in the demographic analyses, depicting a major spatial reorganization during colder climates. Besides, the high genetic structure estimated results from both models of isolation by distance and by environment.</p> <p><b>Main conclusions</b></p> <p><i>V. oligantha</i> is a remarkable model to test the effects of climatic oscillations over the biological community, since this species originated in the early-Pleistocene, prevailing over several cycles of climatic fluctuations until today. The estimated demographic dynamics of <i>V. oligantha</i> agrees with the species-pump mechanism, suggesting it as the main cause of speciation within the Espinhaço Range. Moreover, the phylogeographic patterns of <i>V. oligantha</i> reflect previously recognized spatial and temporal macroevolutionary patterns in the Espinhaço Range, providing insights into how microevolutionary processes may have given rise to this astonishing mountain biodiversity.</p> <p> </p>
Spatial phylogenetic and phenotypic patterns reveal ontogenetic shifts in ecological processes of plant community assembly
The analysis of spatial phylogenetic and phenotypic structure of plant communities provides insight into the underlying processes and interactions governing their assembly, and how these may change during plant ontogeny. We used point pattern analysis to find out if saplings and adult plants are surrounded by phylogenetically and phenotypically more similar or dissimilar neighbours than expected by chance, and whether these associations change from the sapling to the adult stage. To this end, we combined information on the phylogenetic structure and eight phenotypic traits of 15 woody plant species in two Mediterranean mixed forests of southeastern Spain. At the community level, we found that the sapling bank at both sites did not show phylogenetic or phenotypic spatial patterns, but adults showed phylogenetic clustering (i.e., heterospecific neighbours were more similar than expected). At the species level, we found frequently repulsive patterns in the sapling bank of less abundant species (i.e., heterospecific sapling or adult neighbours were more dissimilar than expected) in both, phylogenetic and phenotypic analyses. For the adult stage, we found phylogenetic attraction (i.e., more similar neighbours) in just one species and phenotypic clustering in four species. The processes driving the assembly of the communities of saplings and adults leave detectable signals in the spatial phylogenetic and phenotypic structure of our two forest communities. Our findings reinforce the existence of ontogenetic shifts in the mechanisms involved in plant community assembly. Facilitation between phylogenetically distant and phenotypically divergent species favours the recruitment of less abundant species. However, processes acting later in the ontogeny ameliorate the competition between close relatives and determine the spatial structure of adult plants. Nevertheless, the role of phenotype in shaping adult-adult interactions was context- and trait-dependent. The use of spatial point pattern analysis allowed a nuanced interpretation of the phylogenetic and phenotypic structures of the plant community.
Data from: Severity of topsoil compaction controls the impact of skid trails on soil ecological processes
<p>Skid trails are a major management-induced disturbance in temperate forest ecosystems with considerable impact on soil ecological processes that are so far poorly understood. In German forests, skid trails comprise 10 – 20 % of the forest area that is potentially affected by soil compaction through heavy machinery. We systematically investigated the influence of skid trails on physical, chemical, and microbiological soil parameters at 84 paired plots across four Central European forest types. In low mountain forests with steeper topography, skid trails had more drastic effects than in lowland forests. Skid trails in low mountain areas showed a decrease in the C to N ratio of microbial biomass (MBC/MBN), as well as increased microbial (MBC/SOC) and enzyme activities leading to faster carbon turnover (lower C/N, EOC/EN) and increased CO<sub>2</sub> losses (CO<sub>2</sub>/SOC) from the soil. The overall effects of the skid trails in lowland forests were small. On base-poor soils, we found an increase in the MBC/MBN ratio, while skid trails in base-rich lowland soils showed a reduction in CO<sub>2</sub>/SOC, suggesting a proportional increase in soil carbon storage. Regardless of region-specific effects, the relative increase in the bulk density of the fine soil was identified as a 'golden trait' that determined the effects of skid trails on many soil parameters, as shown by negative correlations with SOC, N, MBC, MBN, MBP, MBC/SOC and CO<sub>2</sub>/SOC and positive ones with the activities of certain hydrolytic enzymes.</p> <p>Synthesis and Applications: Our data clearly showed that carbon conversion processes and soil respiration leading to significant carbon and nutrient losses increased significantly on skid trails in low mountain regions with relatively steep slopes, which was in sharp contrast to lowland sites. The strong context dependence of our findings suggests that the mapping of soil conditions in terms of slope, substrate and moisture with high spatial resolution is mandatory to assess the vulnerability of sites to soil compaction by heavy machinery. Based on such vulnerability analysis, negative impacts can be minimized through the designation of permanently fixed skid trails, the technical adaptation of vehicles (e.g., wide base tyres) as well as careful planning and timing of management operations that should be restricted to dry weather and soil moisture conditions or periods of frost.</p>
Evolutionary and ecological processes determining properties of the $\bm G$-matrix
<p>The $\bm G$-matrix is the matrix of additive genetic variances and covariances for a vector of phenotypes. Here we apply the classical theory for the balance between selection drift and mutations to find the contributions to $\bm G$ from each locus. The fitness is approximated by a linear function of phenotypes. Fluctuations in the environment generate variation in the coefficients of the fitness function. We show that the $\bm G$-matrix can be decomposed into 4 additive components generated by selection, drift, mutations and environmental fluctuations. Selection is on average counteracted by the other three processes included in Fisher's concept of the deterioration of the environment, in accordance with Frank's approximate conservation law proposing that the response to selection at stasis on average is canceled by effects of drift and mutations. The theory illustrates that Fisher's fundamental theorem cannot be used to accumulate selection through time to describe adaption unless the other effects are corrected for. Another implication of the analyses is that the factor loadings to the eigenvector of the $\bm G$-matrix with the least eigenvalue are likely to indicate which characters contributing the most to the fitness function. This is information notoriously difficult to obtain in natural populations. </p>
Complex ecological phenotypes on phylogenetic trees: a Markov process model for comparative analysis of multivariate count data
The evolutionary dynamics of complex ecological traits – including multistate representations of diet, habitat, and behavior – remain poorly understood. Reconstructing the tempo, mode, and historical sequence of transitions involving such traits poses many challenges for comparative biologists, owing to their multidimensional nature. Continuous-time Markov chains (CTMC) are commonly used to model ecological niche evolution on phylogenetic trees but are limited by the assumption that taxa are monomorphic and that states are univariate categorical variables. A necessary first step in the analysis of many complex traits is therefore to categorize species into a pre-determined number of univariate ecological states, but this procedure can lead to distortion and loss of information. This approach also confounds interpretation of state assignments with effects of sampling variation because it does not directly incorporate empirical observations for individual species into the statistical inference model. In this study, we develop a Dirichlet-multinomial framework to model resource use evolution on phylogenetic trees. Our approach is expressly designed to model ecological traits that are multidimensional and to account for uncertainty in state assignments of terminal taxa arising from effects of sampling variation. The method uses multivariate count data for individual species to simultaneously infer the number of ecological states, the proportional utilization of different resources by different states, and the phylogenetic distribution of ecological states among living species and their ancestors. The method is general and may be applied to any data expressible as a set of observational counts from different categories.
Data from: The roles of non-production vegetation in agroecosystems: a research framework for filling process knowledge gaps in a social-ecological context
<p>1. An ever-expanding human population, climatic changes, and the spread of intensive farming practices is putting increasing pressure on agroecosystems and their inherent biodiversity. Non-production vegetation elements, such as woody patches, riparian margins, and restoration plantings, are vital for conserving agroecosystem biodiversity. Further, such elements are key building blocks that are manipulated via land management, thereby influencing the biotic and abiotic processes that underpin functioning agroecosystems.</p> <p>2. Despite this critical role, there has been a lack of synthesis on which types of vegetation elements drive and/or support ecological processes, and the mechanisms by which this occurs. Using a systematic, quantitative literature review of 342 articles, we asked: what are the effects of non-production vegetation on agroecosystem processes and how are these processes measured within global agroecosystems?</p> <p>3. Woody patches, hedgerows and borders, riparian margins, and shelterbelts were the most studied types of non-production vegetation. The majority (61%) of studies showed positive effects of non-production vegetation on ecological processes, where the presence, level or rate of the studied process was increased or enhanced.</p> <p>4. However, four key research gaps were revealed: (1) most studies (83%) used proxies for, instead of direct measurements of, ecosystem processes related to non-production vegetation; (2) study designs used to investigate non-production vegetation effects on ecosystem processes directly were largely limited to observational comparisons of non-production vegetation types, farm-scale vegetation configurations, and different proximities to vegetation in terms of the effect on ecological processes; relatively few studies used manipulative experiments (3) the relatively few studies directly measuring ecosystem processes were dominated by four process categories: invertebrate biocontrol, predator and natural enemy spillover, animal movement, and ecosystem cycling, and (4) the methods used to directly measure non-production vegetation effects comprised a surprisingly limited set of approaches.</p> <p>5. To fill key research gaps that will inform the use of non-production vegetation to enhance agroecosystem processes, we present a framework for future research that emphasises the need to combine an understanding of human decision making with carefully-designed and targeted investigations into the roles of taxa, ecosystem processes, and landscape heterogeneity related to non-production vegetation, at multiple spatial scales within agroecosystems.</p>
Biodiversity components mediate the response to forest loss and the effect on ecological processes of plant-frugivore assemblages
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Evolutionary and ecological processes determining properties of the $\bm G$-matrix
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Data from: Severity of topsoil compaction controls the impact of skid trails on soil ecological processes
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Data from: The roles of non-production vegetation in agroecosystems: a research framework for filling process knowledge gaps in a social-ecological context
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Reliably predicting pollinator abundance: challenges of calibrating process-based ecological models
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Underlying microevolutionary processes parallel macroevolutionary patterns in ancient Neotropical Mountains - Ecological Niche Modeling and Corridors files
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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.