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248 results for “landscape dynamics”
Data from: Network ecology in dynamic landscapes
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Data from: Epidemic and endemic pathogen dynamics correspond to distinct host population microbiomes at a landscape scale
Infectious diseases have serious impacts on human and wildlife populations, but the effects of a disease can vary, even among individuals or populations of the same host species. Identifying the reasons for this variation is key to understanding disease dynamics and mitigating infectious disease impacts, but disentangling cause and correlation during natural outbreaks is extremely challenging. This study aims to understand associations between symbiotic bacterial communities and an infectious disease, and examines multiple host populations before or after pathogen invasion to infer likely causal links. The results show that symbiotic bacteria are linked to fundamentally different outcomes of pathogen infection: host–pathogen coexistence (endemic infection) or host population extirpation (epidemic infection). Diversity and composition of skin-associated bacteria differed between populations of the frog, Rana sierrae, that coexist with or were extirpated by the fungal pathogen, Batrachochytrium dendrobatidis (Bd). Data from multiple populations sampled before or after pathogen invasion were used to infer cause and effect in the relationship between the fungal pathogen and symbiotic bacteria. Among host populations, variation in the composition of the skin microbiome was most strongly predicted by pathogen infection severity, even in analyses where the outcome of infection did not vary. This result suggests that pathogen infection shapes variation in the skin microbiome across host populations that coexist with or are driven to extirpation by the pathogen. By contrast, microbiome richness was largely unaffected by pathogen infection intensity, but was strongly predicted by geographical region of the host population, indicating the importance of environmental or host genetic factors in shaping microbiome richness. Thus, while both richness and composition of the microbiome differed between endemic and epidemic host populations, the underlying causes are most likely different: pathogen infection appears to shape microbiome composition, while microbiome richness was less sensitive to pathogen-induced disturbance. Because higher richness was correlated with host persistence in the presence of Bd, and richness appeared relatively stable to Bd infection, microbiome richness may contribute to disease resistance, although the latter remains to be directly tested.
Dynamic energy landscapes of predators and the implications for modifying prey risk
<p>Landscapes of fear describe a spatial representation of an animal's perceived risk of predation and the associated foraging costs, while energy landscapes describe the spatial representation of their energetic cost of moving and foraging. Fear landscapes are often dynamic and change based on predator presence and behavior, and variation in abiotic conditions that modify risk. Energy landscapes are also dynamic and can change across diel, seasonal, and climatic timescales based on variability in temperature, snowfall, wind/current speeds etc.</p> <p>Recently, it was suggested that fear and energy landscapes should be integrated. In this paradigm, the interaction between the landscapes relates to prey being forced into areas of the energy landscape they would avoid if risk were not a factor. However, dynamic energy landscapes experienced by predators must also be considered since they can affect their ability to forage, irrespective of variation in prey behavior. We propose an additional component to the fear and dynamic energy landscape paradigm that integrates landscapes of both prey and predators, where predator foraging behavior is modulated by changes in their energyscape.</p> <p>Specifically, we integrate the predators' energy landscape into foraging theory that predicts prey patch-leaving decisions under the threat of predation. We predict that as a predator's energetic cost of foraging increases in a habitat, then the prey's foraging costs of predation and patch quitting harvest rate will decrease. Prey may also decrease their vigilance in response to increased energetic foraging cost for predators, which will lower prey-giving-up densities.</p> <p>We then provide examples in terrestrial, aerial and marine ecosystems where we might expect to see these effects. These include birds, sharks which use updrafts that vary based on wind and current speeds, tidal state, or temperature and terrestrial predators (e.g. wolves) whose landscapes vary seasonally with snow depth or ice cover which may influence their foraging success and even diet selection.</p> <p>A predator perspective is critical to considering the combination of these landscapes and their ecological consequences. Dynamic predator energy landscapes could add a spatiotemporal component to risk effects which may cascade through food webs.</p>
Cougars, wolves, and humans drive a dynamic landscape of fear for elk
<p>To manage predation risk, prey navigate a dynamic landscape of fear, or spatiotemporal variation in risk perception, reflecting predator distributions, traits, and activity cycles. Prey may seek to reduce risk across this landscape by using habitat at times and in places when predators are less active. In multi-predator landscapes, avoiding one predator could increase vulnerability to another, making the landscape of fear difficult to predict and navigate. Additionally, humans may shape interactions between predators and prey, and induce new sources of risk. Humans can function as a shield, providing a refuge for prey from human-averse carnivores, and as a predator, causing mortality through hunting and vehicle collisions and eliciting a fear response that can exceed that of carnivores. We used telemetry data collected between 2017 and 2021 from 63 GPS-collared elk (Cervus canadensis), 42 cougars (Puma concolor) and 16 wolves (Canis lupus) to examine how elk habitat selection changed in relation to carnivores and humans in northeastern Washington, USA. Using step-selection functions, we evaluated elk habitat use in relation to cougars, wolves, and humans, diel period (daytime vs. nighttime), season (summer calving season vs. fall hunting season), and habitat structure (open vs. closed habitat). The diel cycle was critical to understanding elk movement, allowing elk to reduce encounters with predators where and when they would be the largest threat. Elk strongly avoided cougars at night but had a near neutral response to cougars in the day, whereas elk avoided wolves at all times of day. Elk generally used more open habitat where cougars and wolves were most active, rather than altering use of habitat structure depending on the predator species. Elk avoided humans during the day and ~ 80% of adult female mortality was human caused, suggesting that humans functioned as a "super predator" in this system. Simultaneously, elk leveraged the human shield against wolves but not cougars at night, and no elk were confirmed to have been killed by wolves. Our results add to the mounting evidence that humans profoundly affect predator-prey interactions, highlighting the importance of studying these dynamics in anthropogenic areas.</p>
Data from "Allostery and evolution: a molecular journey throught the structural and dynamical landscape of an enzyme super family."
<p>This data accompanies the paper entitled Allostery and evolution: a molecular journey throught the structural and dynamical landscape of an enzyme super family.</p> <p>The zip archive contains: </p> <p>1- Starting configurations of the proteins after equilibration in PDB format and trajectories of unrestrained molecular dynamics simulations with the positions of the proteins every 100 ps in XTC gromacs format are provided for all systems. </p> <p>2- The free energy profiles and histograms are provided for all umbrella sampling simulations and the scripts used to run it with gromacs.</p>
Moving in the landscape: omnidirectional connectivity dynamics in China from 1985 to 2020
<p><span>Global changes in human land use have profoundly transformed natural landscapes, leading to significant habitat fragmentation and threatening key ecosystem functions. To address this issue, we employed morphological methods and circuit theory to evaluate the dynamics of ecological corridors and their connectivity in China from 1985 to 2020.</span></p>
Dataset and scripts from: Predicting organismal response to marine heatwaves using dynamic thermal tolerance landscape models
<p>Marine heatwaves (MHWs) can cause thermal stress in marine organisms, experienced as extreme 'pulses' against the gradual trend of anthropogenic warming. When thermal stress exceeds organismal capacity to maintain homeostasis, organism survival becomes time-limited and can result in mass mortality events. Current methods of detecting and categorizing MHWs rely on statistical analysis of historic climatology, and do not consider biological effects as a basis of MHW severity. The reemergence of ectotherm thermal tolerance landscape models provides a physiological framework for assessing the lethal effects of MHWs by accounting for both the magnitude and duration of extreme heat events. Here, we used a simulation approach to understand the effects of a suite of MHW profiles on organism survival probability across 1) three thermal tolerance adaptive strategies, 2) interannual temperature variation, and 3) seasonal timing of MHWs. We identified survival isoclines across MHW magnitude and duration where acute (short duration-high magnitude) and chronic (long duration-low magnitude) events had equivalent lethal effects on marine organisms. While most research attention has focused on chronic MHW events, we show similar lethal effects can be experienced by more common but neglected acute marine heat spikes. Critically, a statistical definition of MHWs does not accurately categorize biological mortality. By letting organism responses define the extremeness of a MHW event, we can build a mechanistic understanding of MHW effects from a physiological basis. Organism responses can then be transferred across scales of ecological organization and better predict marine ecosystem shifts to MHWs. </p>
Development of human pancreatic cancer avatars as a model for dynamic immune landscape profiling and personalised therapy
<div> <div> <div> <p>Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer, a disease with dismal overall survival. Advances in treatment are hindered by a lack of preclinical models. Here we show how a personalised organotypic 'avatar' created from resected tissue, allows spatial and temporal reporting on a complete in situ tumour microenvironment, and mirrors clinical responses. Our perfusion culture method extends tumour slice viability, maintaining stable tumour content, metabolism, stromal composition, and immune cell populations for 12 days. Using multiplexed immunofluorescence and spatial transcriptomics, we identify immune neighbourhoods and potential for immunotherapy. We employed avatars to assess the impact of a pre-clinically validated metabolic therapy and show recovery of stromal and immune phenotypes and tumour re-differentiation. To determine clinical relevance, we monitored avatar response to gemcitabine treatment and identified a patient avatar-predicable response from clinical follow-up. Thus, avatars provide valuable information for the syngeneic testing of novel therapeutics and a truly personalised therapeutic assessment platform for patients.</p> </div> </div> </div>
Two decades of annual landscape-scale tree growth and dynamics in old-growth tropical rainforest in the CARBONO Project, La Selva Biological Station, 1997-2018
<p>Here we present the complete data series from a 21-yr study of the annual growth and dynamics of trees, palms and lianas in the old-growth tropical rainforest at the La Selva Biological Station in Costa Rica. These observations were part of the CARBONO Project, a multidisciplinary team study of forest carbon cycling. The project was designed to assess forest processes at the landscape scale by sampling with replication across the within-landscape edaphic heterogeneity typical of tropical forests. Through more than two decades, forest growth and dynamics were assessed annually. The annual time-step used in the CARBONO Project effectively captured forest responses to major disturbances and to interannual and climatic variation. Annual measurements also enhanced the accuracy and long-term consistency of the data. To our knowledge, the resulting records are unique for tropical forests, where the dominant approach to studying the dynamics of a given forest has been to use a single plot and multi-year inter-census intervals. To date these CARBONO Project data have revealed: multi-decadal forest stability in spite of the short-term changes in forest structure resulting from major natural disturbances (e.g., the 1997-1998 Strong El Niño, and the extreme windstorm of May 2018); the dynamics and importance of large trees; and the responses of a major component of ecosystem productivity, aboveground wood production, to interannual and long-term climatic and atmospheric change. These data have also contributed to many remote-sensing studies.</p> <p>The data set consists of annual observations through the period 1997–2018 of the floristics, survival, recruitment, and growth of all woody stems (diameter <u>></u> 10 cm) in a landscape-scale plot network. At completion of the study, the data spanned 6705 individuals and 21 years. The data set is complete and has been through extensive internal checks for quality assurance. Detailed data documentation and an emphasis on measurement repeatability were prioritized through the study. The metadata include an extensive README file describing the data files and the methods, a document detailing the data management and qa/qc, and the scanned original field data-sheets for the 22 annual censuses.</p> <p>We gratefully acknowledge the careful long-term field work and data entry and checking by paraforesters Leonel Campos Otoya and William Miranda Conejo. Logistical support and the long-term protection of the La Selva reserve were provided by the Organization for Tropical Studies. The Ministerio de Ambiente y Energía of Costa Rica granted permits to carry out this study through the years of the study (most recently: Resolución No. 037-2018-ACCVC-PI).</p>
Data from dissertation: 'Landscape and Aboveground Biomass Dynamics of Brazilian Savanna using airborne LIDAR and MapBiomas datasets : case study of Rio Vermelho Watershed, Brazil'
<p>This dissertation was submitted to University of Manchester as part of MSc GIS program</p> <p>This repository contains:</p> <p>1) Contains the R language code used in the dissertation (CHM_&_LiDAR_metric.R; Landscape_metric.R; Generalized_Linear_Model.R; Random_Forest_Model.R).</p> <p><br> 2) Canopy Height Model (CHM) and 56 LiDAR metric raster files with a resolution of 1m (CHM_&_LiDAR_metric_2014.zip; CHM_&_LiDAR_metric_2018.zip), the original LiDAR data come from Brazil project supported by the Brazilian Agricultural Research Corporation (EMBRAPA), the US Forest Service, USAID, and the US Department of State.</p> <p><br> 3) AGB raster files with a resolution of 10m (AGB_2014.tif; AGB_2018.tif; AGB_dynamic.tif), field plots used for AGB estimation come from Sabrinado Couto de Miranda from University of Goiás State (UEG), Brazil, and her team.</p> <p><br> 4) Landscape metric interpolation raster file (SHDI.tif; SHEI.tif; AREA_CV.tif; CIRCLE_MN.tif; SHAPE_MN.tif) with a resolution of 10m, land cover map Map come from Biomas team for landscape metric calculation.</p>
Landscape-scale dynamics of a threatened species respond to local-scale conservation management
<p><span>Landscape-scale approaches are increasingly advocated for species conservation but ensuring landscape level persistence by enlarging the size of patches or increasing their physical connectivity is often impractical. Here, we test how such barriers can be overcome by management of habitat at the local (site-based) level, using a rare butterfly as an exemplar. We used four surveys of the entire UK distribution of the Lulworth Skipper (<em>Thymelicus</em> <em>acteon</em>) over 40 years to test how local habitat influences population density and colonization / extinction dynamics, and parameterized, validated and applied a metapopulation model to simulate effects of varying local habitat quality on regional persistence. We found the total number of populations in four distribution snapshots between 1978 and 2017 varied between 59–84, and from 1997 to 2017, 34% of local populations showed turnover (colonization or extinction). Population density was closely linked to vegetation characteristics indicative of management, namely height and food plant frequency, both of which changed through time. Simulating effects of habitat quality on metapopulation dynamics 40 years into the future suggests coordinated changes to two key components of quality (vegetation height and food plant frequency) would increase patch occupancy above the range observed in the past 40 years (50–80%). In contrast, deterioration of either component below threshold levels leads to metapopulation retraction to core sub-networks of patches, or eventual extirpation. Our results indicate that changes to habitat quality can overcome constraints imposed by habitat patch area and spatial location on relative rates of colonization and local extinction, demonstrating the sensitivity of regional dynamics to targeted in situ management. Local habitat management therefore plays a key role in landscape-scale conservation. Monitoring of population density, and the monitoring and management of local (site-level) habitat quality, therefore represent effective and important components of conservation strategies in fragmented landscapes.</span></p>
Data for: Surrounding landscape, habitat and hybridization dynamics drive population structure and genetic diversity in the Saltmarsh Sparrow (Ammospiza caudacuta)
<p class="MsoNormal">Determining factors that shape a species' population genetic structure is beneficial for identifying effective conservation practices. We assessed population structure and genetic diversity for Saltmarsh Sparrow (<em>Ammospiza caudacuta</em>), an imperiled tidal marsh specialist, using 13 microsatellite markers and 964 individuals sampled from 24 marshes across the breeding range. We show that Saltmarsh Sparrow populations are structured regionally by isolation-by-distance, with gene flow occurring among marshes within ~110-135 km of one another. Isolation-by-resistance and isolation-by-environment also shape genetic variation; several habitat and landscape features are associated with genetic diversity and genetic divergence among populations. Human development in the surrounding landscape isolates breeding marshes, reducing genetic diversity and increasing population genetic divergence, while surrounding marshland and patch habitat quality (proportion high marsh and sea-level-rise trend) have the opposite effect. The distance of the breeding marsh to the Atlantic Ocean also influences genetic variation, with marshes farther inland being more divergent than coastal marshes. In northern marshes, hybridization with Nelson's Sparrow (<em>A. nelsoni</em>) strongly influences Saltmarsh Sparrow genetic variation, by increasing genetic diversity in the population; this has a concomitant effect of increasing genetic differentiation of marshes with high levels of introgression. From a conservation perspective, we found that the majority of population clusters have low effective population sizes, suggesting a lack of resiliency. To conserve the representative breadth of genetic and ecological diversity and to ensure redundancy of populations, it will be important to protect a diversity of marsh types across the latitudinal gradient of the species range, including multiple inland, coastal and urban populations, which we have shown to exhibit signals of genetic differentiation. It will also require maintaining connectivity at a regional level, by promoting high marsh habitat at the scale of gene flow (~130 km), while also ensuring "stepping stone" populations across the range. </p>
Data from: Dynamic shifts in predator diel activity patterns across landscapes and threat levels
<p>Understanding the constraints dominant predators impose on subordinate species is important for predicting ecosystem dynamics and anticipating outcomes of predator management. Subordinate predators may avoid dominant predators in time or space, making it difficult to quantify antipredator behaviours unless joint spatiotemporal analyses are used. Here, we tested whether an invasive dominant predator (red fox <em>Vulpes vulpes</em>) alters the spatiotemporal activity of an invasive subordinate predator (feral cat <em>Felis catus</em>). We collated records of both species from 3,667 camera-traps deployed experimentally across two regions of south-eastern Australia with simplified predator guilds. Foxes were poison-baited in some landscapes within each region. We used generalised additive models to quantify changes in predator spatiotemporal activity across geographic space, vegetation types, human footprint and (artificially manipulated) gradients of dominant predator activity. Foxes and cats had similar diel activity patterns when averaged across all sites, however there was important differentiation at a finer scale cats did not reduce their spatial activity but shifted diel patterns when localised fox activity was high. Cats were crepuscular on average. However, across dry vegetation types of both regions (where foxes were nocturnal), cats shifted to diurnal behaviour with increasing fox activity. In contrast, fox activity was relatively consistent throughout the daily cycle in the wet forest; here cats avoided dawn when fox activity was high. Changes in cat diel activity patterns may facilitate spatial coexistence between these two invasive predators, potentially shifting feral cat impacts onto different native prey. It is well-appreciated that predator activity varies spatially and fluctuates throughout the daily cycle. However, our study demonstrates that diel activity patterns also vary across space, likely mediated by both landscape-context and fear. Dominant predator avoidance in time appears to be spatially dynamic a key nuance which is overlooked when simply comparing the average activity overlap between two species.</p>
Spatio-temporal dynamics of insect communities in constructed and natural tidal marshes with distinct landscape positions
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Data from: Changing flight and flocking dynamics of homing pigeons (<em>Columba livia d.</em>) over heterogeneous landscapes
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Two decades of annual landscape-scale tree growth and dynamics in old-growth tropical rainforest in the CARBONO Project, La Selva Biological Station, 1997-2018
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Data from: Persistent effects of landscape context on recruitment dynamics during secondary succession of tropical forests
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Data from: Intraguild dynamics of understudied carnivores in a human-altered landscape
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Data from: Epidemic and endemic pathogen dynamics correspond to distinct host population microbiomes at a landscape scale
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Data for: Surrounding landscape, habitat and hybridization dynamics drive population structure and genetic diversity in the Saltmarsh Sparrow (Ammospiza caudacuta)
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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.