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1,069 results for “Data managment”
Data from: Headache study: The management of chronic headache with referral from primary care to direct access to Magnetic Resonance Imaging (MRI) compared to Neurology services: an observational prospective study in London
<p><b>Objectives</b>. To evaluate the cost, accessibility and patient satisfaction implications of two clinical pathways used in the management of chronic headache.</p> <p><b>Intervention</b>. Management of chronic headache following referral from Primary Care that differed in the first appointment, either a Neurology appointment or an MRI brain scan.</p> <p><b>Design and setting</b>. A pragmatic, non-randomised, prospective, single-center study at a Central Hospital in London.</p> <p><b>Participants. </b>Adult patients with chronic headache referred from Primary to Secondary Care.</p> <p><b>Primary and secondary outcome measures.</b> Participants' use of health care services and costs were estimated using primary and secondary care databases and questionnaires quarterly up to 12 months post-recruitment. Cost analyses were compared using generalised linear models (GLM). Secondary outcomes assessed: access to care, patient satisfaction, headache burden and self-perceived quality of life using headache-specific (MIDAS, HIT-6) and a generic questionnaire (EQ-5D-5L).</p> <p><b>Results. </b>Mean (SD) cost up to 6 months post-recruitment per participant was £578 (£420) for the Neurology group (n=128) and £245 (£172) for the MRI group (n=95), leading to an estimated mean cost difference of £333 (95% CI £253 to £413, p<0.001). The mean cost difference at 12 months increased to £518 (95% CI £401 to £637, p<0.001). When adjusted for baseline and follow-up imbalances between groups, this remained statistically significant. The utilisation of brain MRI improved access to care compared to the Neurology group (p<0.001). Participants in the Neurology group reported higher levels of satisfaction associated with the pathway and led to greater change in care management.</p> <p><b>Conclusion. </b>Direct referral to brain MRI from Primary Care led to cost-savings and quicker access to care but lower satisfaction levels when compared with referral to Neurology services. Further research into the use of brain MRI for a subset of patient population more likely to be reassured by a negative brain scan should be considered.</p>
Data from: Contrasting vulnerability of monospecific and species-diverse forests to wind and bark beetle disturbance: The role of management
<p>The published dataset contains the results of the paper titled <strong>Contrasting vulnerability of monospecific and species-diverse forests to wind and bark beetle disturbance: The role of management, in Ecology and Evolution.</strong></p> <p>Results are based on the output of the model iLand<strong> (</strong>http://iland.boku.ac.at/startpage).</p> <p>contact: Laura Dobor; dobor.laura@gmail.com</p>
Data from: Influence of climate change and post-delisting management on long-term population viability of the conservation-reliant Kirtland's warbler
Rapid global climate change is resulting in novel abiotic and biotic conditions and interactions. Identifying management strategies that maximize probability of long-term persistence requires an understanding of the vulnerability of species to environmental changes. We sought to quantify the vulnerability of Kirtland's Warbler (Setophaga kirtlandii), a rare Neotropical migratory songbird that breeds almost exclusively in the Lower Peninsula of Michigan and winters in the Bahamian Archipelago, to projected environmental changes on the breeding and wintering grounds. We developed a population-level simulation model that incorporates the influence of annual environmental conditions on the breeding and wintering grounds, and parameterized the model using empirical relationships. We simulated independent and additive effects of reduced breeding grounds habitat quantity and quality, and wintering grounds habitat quality, on population viability. Our results indicated the Kirtland's Warbler population is stable under current environmental and management conditions. Reduced breeding grounds habitat quantity resulted in reductions of the stable population size, but did not cause extinction under the scenarios we examined. In contrast, projected large reductions in wintering grounds precipitation caused the population to decline, with risk of extinction magnified when breeding habitat quantity or quality also decreased. Our study indicates that probability of long-term persistence for Kirtland's Warbler will depend on climate change impacts to wintering grounds habitat quality, and contributes to the growing literature documenting the importance of considering the full annual cycle for understanding population dynamics of migratory species.
Data from: Prevalence and abundance of bees visiting major conventionally-managed agricultural crops in Brazil
This study brings together data from a series of local pollinator surveys undertaken in major conventionally-managed agricultural crops in Brazil to determine the presence and abundance of bees visiting flowers within crops compared with adjacent off-crop habitats. Surveys were undertaken within crops and in adjacent off-crop areas using broadly the same methodology in flowering soybean, drybean, maize, citrus, coffee, rice, and cotton and in sugarcane immediately harvest. The bee species present were assessed twice per day at three times during crop flowering (post-harvest for sugar-cane). Pan traps were used to collect species present within the crop and off-crop twice per day. Drybeans, citrus, and coffee flowers displayed a consistent medium to high abundance of honey bees based on effort-adjusted transect and spot counts. In contrast, fields with flowering soybeans and cotton showed in-crop lower abundance and rice, corn, and harvested sugar cane showed consistently low numbers or no honey bees. In almost all cases honey bees were the most prevalent and abundant flower visitors within the studied crops. Where non-Apis bees were observed they often belong to the Meliponini (primarily Trigona) or the genera Bombus or Xylocopa. The off-crop assessments of species presence using pan traps showed a far wider diversity of species with greater proportional representation of solitary bee species. Overall, whilst honey bees accounted for the majority of observed bees visiting flowers in the agricultural fields, the off-crop habitat contained a greater abundance and diversity of non-Apis bee populations.
Data from: Niche differentiation of bacterial versus archaeal soil nitrifiers induced by ammonium inhibition along a management gradient
<p>Soil nitrification, mediated mainly by ammonia oxidizing archaea (AOA) and bacteria (AOB), converts ammonium (NH4+) to nitrite (NO2−) and thence nitrate (NO3−). To better understand ecological differences between AOA and AOB, we investigated the nitrification kinetics of AOA and AOB under eight replicated cropped and unmanaged ecosystems (including two fertilized natural systems) along a long-term management intensity gradient in the upper U.S. Midwest. For five of eight ecosystems, AOB but not AOA exhibited Haldane kinetics (inhibited by high NH4+ additions), especially in perennial and successional systems. In contrast, AOA predominantly exhibited Michaelis-Menten kinetics, suggesting greater resistance to high nitrogen inputs than AOB. These responses suggest the potential for NH4+-induced niche differentiation between AOA and AOB. Additionally, long-term fertilization significantly enhanced maximum nitrification rates (Vmax) in the early successional systems for both AOA and AOB, but not in the deciduous forest systems. This was likely due to pH suppression of nitrification in the acidic forest soils, corroborated by a positive correlation of Vmax with soil pH but not with amoA gene abundance. Results also demonstrated that soil nitrification potentials were relatively stable, as there were no seasonal differences. Overall, results suggest that (1) NH4+ inhibition of AOB but not AOA could be another factor contributing to niche differentiation between AOA and AOB in soil, and (2) nitrification by both AOA and AOB can be significantly promoted by long-term nitrogen inputs.</p>
Data from: Development and testing of an environmental DNA (eDNA) assay for endangered Atlantic sturgeon to assess its potential as a monitoring and management tool
<p>Significant declines in Atlantic sturgeon (<i>Acipenser oxyrhynchus oxyrhynchus</i>) abundances along the US east coast have spurred major research efforts and management actions over the last 50 years, yet information on spawning stock abundances and habitat use is still lacking for many river systems, including in the Chesapeake Bay, USA. Here, we developed and tested a new quantitative PCR (qPCR) assay to detect Atlantic sturgeon environmental DNA (eDNA) in water samples with the goal of providing an alternative method to monitor presence and relative abundance. We also examined Atlantic sturgeon eDNA shedding rates in laboratory experiments. A qPCR-probe assay targeting Cytochrome-B was developed and showed no amplification of other related and co-occurring fishes. Pond trials at a density of ~0.2 g/L sturgeon produced relatively strong eDNA detections (~1,000-25,000 copies/L) in all seven water samples assayed. Water samples taken from two river systems in the Chesapeake Bay produced zero eDNA detections in the summer, while fall sampling during sturgeon spawning produced positive eDNA detections in 26% of samples, though at much lower concentrations (400-1,800 copies/L) compared with the pond (mesocosm) detections. Acoustic detections of sturgeon near river sampling sites were positively associated with eDNA detections. However, the eDNA assay failed to detect the presence of sturgeon in some samples when abundances were very low or when fish were in deep water. Finally, Atlantic sturgeon eDNA shedding rates were estimated to be on the order of estimates for other fish species, which suggests that relatively weak detections in the field are not necessarily driven by low rates of eDNA shedding. Overall, eDNA analysis represents a promising new monitoring tool for Atlantic sturgeon. Applying these methods in other rivers along the US east coast is an important next step in documenting Atlantic sturgeon distribution for management and conservation purposes.</p>
Data From: Characterizing patterns of genomic variation in the threatened Utah prairie dog: implications for conservation and management
<p>Utah prairie dogs (<i>Cynomys parvidens</i>) are federally threatened due to eradication campaigns, habitat destruction, and outbreaks of plague. Today, Utah prairie dogs exist in small, isolated populations, making them less demographically stable and more susceptible to erosion of genetic variation by genetic drift. We characterized patterns of genetic structure at neutral and putatively adaptive loci in order to evaluate the relative effects of genetic drift and local adaptation on population divergence. We sampled individuals across the Utah prairie dog species range and generated 2,955 single nucleotide polymorphisms (SNPs) using double digest restriction site associated DNA sequencing (ddRAD). Genetic diversity was lower in low elevation sites compared to high elevation sites. Population divergence was high among sites and followed an isolation-by-distance (IBD) model. Our results indicate that genetic drift plays a substantial role in the population divergence of the Utah prairie dog, and colonies would likely benefit from translocation of individuals between recovery units, which are characterized by distinct elevations, despite the detection of environmental associations with outlier loci. By understanding the processes that shape genetic structure, better informed decisions can be made with respect to the management of threatened species to ensure that adaptation is not stymied.</p>
Data from: Machine learning improves predictions of agricultural nitrous oxide (N2O) emissions from intensively managed cropping systems
<p><span>The potent greenhouse gas nitrous oxide (N</span><sub><span>2</span></sub><span>O) is accumulating in the atmosphere at unprecedented rates largely due to agricultural intensification, and cultivated soils contribute ~60% of the agricultural flux. Empirical models of N</span><sub><span>2</span></sub><span>O fluxes for intensively managed cropping systems are confounded by highly variable fluxes and limited </span><span><span>geographic coverage;</span></span><span> process-based biogeochemical models are rarely able to predict daily to monthly emissions with > 20% accuracy even with site-specific calibration. Here we show the promise for machine learning (ML) to significantly improve field-level flux predictions, especially when coupled with a cropping systems model to simulate unmeasured </span><span><span>soil</span></span><span> parameters. We used sub-daily N</span><sub><span>2</span></sub><span>O flux data from six years of automated flux chambers installed in a continuous corn rotation at a site in the upper U.S. Midwest (~3000 sub-daily flux observations), supplemented with weekly to biweekly manual chamber measurements (~1100 daily fluxes), to train an ML model that explained 65-89% of daily flux variance with very few input variables –soil moisture, days after fertilization, soil texture, air temperature, soil carbon, precipitation, and N fertilizer rate. When applied to a long-term test site not used to train the model, the model explained 38% of the variation observed in weekly to biweekly manual chamber measurements from corn, and 51% upon coupling the ML model with a cropping systems model that predicted daily soil N availability. </span><span><span>This represents a 2-3 times improvement over conventional process-based models and with substantially fewer input requirements.</span></span><span> This coupled approach </span><span><span>offers promise</span></span><span> for better predictions of agricultural N</span><sub><span>2</span></sub><span>O emissions and thus more precise global models and more effective </span><span><span>agricultural mitigation interventions.</span></span></p>
Data from: A multi-taxa assessment of the effectiveness of agri-environmental schemes for biodiversity management
<p>Agri-environmental schemes (AES) aim to restore biodiversity and biodiversity-mediated ecosystem services in landscapes impoverished by modern agriculture. However, a systematic, empirical evaluation of different AES types across multiple taxa and functional groups is missing. Within one orthogonal design, we studied sown flowering AES types with different temporal continuity, size, and landscape context and used calcareous grasslands as semi-natural reference habitat. We measured species richness of twelve taxonomic groups (vascular plants, cicadas, orthopterans, bees, butterflies, moths, hoverflies, flower visiting beetles, parasitoid wasps, carabid beetles, staphylinid beetles and birds) representing five trophic levels. A total of 54,955 specimens were identified using traditional taxonomic methods and bulk arthropod samples were identified through DNA metabarcoding, resulting in a total of 1077 and 2110 taxa, respectively. Species richness of most taxonomic groups as well as multidiversity and richness of pollinators increased with temporal continuity of AES types. Some groups responded to size and landscape context but multidiversity and richness of pollinators and natural enemies were not affected. AES flowering fields supported different species assemblages than calcareous grasslands, but assemblages became more similar to those in semi-natural grasslands with increasing temporal continuity. Our results indicate that AES flowering fields and semi-natural grasslands function synergistically. Flowering fields support biodiversity even when they are relatively small and in landscapes with few remaining semi-natural habitats. We, therefore, recommend a network of smaller, temporally continuous AES flowering fields of different ages combined with permanent semi-natural grasslands to maximize benefits for biodiversity conservation and ecosystem service delivery in agricultural landscapes.</p>
Appendix 3 to "The Status of Biological Invasions and their Management in South Africa in 2019"—Data on the status of pathways
<p>For more details see: http://iasreport.sanbi.org.za</p> <p>SANBI and CIB 2020. Appendix 3 to "The Status of Biological Invasions and their Management in South Africa in 2019"—Data on the status of pathways. South African National Biodiversity Institute, Kirstenbosch and DSI-NRF Centre of Excellence for Invasion Biology, Stellenbosch. http://dx.doi.org/10.5281/zenodo.3947666</p>
Appendix 1 to "The Status of Biological Invasions and their Management in South Africa in 2019"—Data sources used
<p>For more details see: http://iasreport.sanbi.org.za</p> <p>SANBI and CIB 2020. Appendix 1 to "The Status of Biological Invasions and their Management in South Africa in 2019"—Data sources used. South African National Biodiversity Institute, Kirstenbosch and DSI-NRF Centre of Excellence for Invasion Biology, Stellenbosch. http://dx.doi.org/10.5281/zenodo.3947603</p>
Data from: Fire and mechanical forest management treatments support different portions of the bird community in fire-suppressed forests
<p>Silvicultural treatments, fire, and insect outbreaks are the primary disturbance events currently affecting forests in the Sierra Nevada Mountains of California, a region where plants and wildlife are highly adapted to a frequent-fire disturbance regime that has been suppressed for decades. Although the effects of both fire and silviculture on wildlife have been studied by many, there are few studies that directly compare their long-term effects on wildlife communities. We conducted avian point counts from 2010 to 2019 at 1987 in situ field survey locations across eight national forests and collected fire and silvicultural treatment data from 1987 to 2016, resulting in a 20-year post-disturbance chronosequence. We evaluated two categories of fire severity in comparison to silvicultural management (largely pre-commercial and commercial thinning treatments) as well as undisturbed locations to model their influences on abundances of 71 breeding bird species. More species (48% of the community) reached peak abundance at moderate-high-severity-fire locations than at low-severity fire (8%), silvicultural management (16%), or undisturbed (13%) locations. Total community abundance was highest in undisturbed dense forests as well as in the first few years after silvicultural management and lowest in the first few years after moderate-high-severity fire, then abundance in all types of disturbed habitats was similar by 10 years after disturbance. Even though the total community abundance was relatively low in moderate-high-severity-fire habitats, species diversity was the highest. Moderate-high-severity fire supported a unique portion of the avian community, while low-severity fire and silvicultural management were relatively similar. We conclude that a significant portion of the bird community in the Sierra Nevada region is dependent on moderate-high-severity fire and thus recommend that a prescribed and managed wildfire program that incorporates a variety of fire effects will best maintain biodiversity in this region.</p> <p><a href="https://www.mdpi.com/1999-4907/12/2/150/htm" rel="noopener noreferrer">https://www.mdpi.com/1999-4907/12/2/150/htm</a></p>
Data from: Finding the best management policy to eradicate invasive species from spatial ecological networks with simultaneous actions
1. Spatial management of invasive species is more likely to be successful when multiple locations are treated simultaneously. However, selecting the best locations to act is difficult due to the many options available at any time. 2. We design a near-optimal policy for applying multiple actions simultaneously for faster invasive species control within a network. Our method uses a recent optimisation tool, the Graph-based Markov decision process (GMDP). Since the policy can be difficult to interpret, we extracted a simpler policy using classification trees. We applied our approach to the eradication of invasive mosquitofish (Gambusia holbrooki) from the habitat of the red-finned blue-eye (Scaturiginichthys vermeilipinnis), a critically endangered fish with a global population that is restricted to seven artesian springs in Queensland, Australia. 3. The policy returned by the GMDP was to manage springs occupied by mosquitofish and their connected neighbours, unless the neighbours were occupied by red-finned blue-eyes. 4. Simultaneous management resulted in rapid declines in simulated mosquitofish occupancy even if eradication effectiveness was low; however the cost of simultaneous eradication was high and sustained eradication effort was necessary to maintain low mosquitofish occupancy. 5. Synthesis and applications. Our paper finds a near-optimal, multi-action control policy to remove an invasive species from a multi-species spatial network. We introduce the Graph-based Markov decision process (GMDP) and apply it to a real case study – eradication of invasive mosquitofish from the habitat of the red-finned blue-eye. We find that the GMDP can generate policies for networks with extremely large state spaces, however it works best when nodes have fewer than five neighbours. We conclude that simultaneous eradications are effective for rapid control of invasive species; however, managers should consider the cost and time required for an effective eradication program.
Data from: Chaparral bird community responses to prescribed fire and shrub removal in three management seasons
Chaparral, a type of shrubland common throughout the California Floristic Province, is subject to management and removal in regions where wildfire threatens human lives and property. Management practices include conducting prescribed burns outside of the historical fire season and employing mechanical fuel reduction (mastication). As the wildland–urban interface grows, particularly in coastal California, more of this ecosystem is subject to active management. To understand the ecological implications of current California chaparral fire management practices, we studied bird species composition, abundance and foraging guilds in managed and unmanaged chaparral over 5 years. Study areas were located in Mendocino County in the coast ranges of northern California. We contrast six chaparral removal or "fuels manipulation" treatments: (1) fall fire, (2) winter fire, (3) spring fire, (4) fall mastication, (5) spring mastication and (6) untreated control. Treatments and controls were implemented in plots 2 ha or larger, and replicated four times each. We find that species richness in prescribed fire treatments reaches comparable levels to controls in the first 3 years following treatment, whereas masticated units always have lower species richness. Generalized linear mixed models additionally confirm that mastication has highly negative effects on observed abundances of birds compared to controls and to prescribed fire. The season in which fuels reduction occurred was less important to species richness, although fall fire was more beneficial to bird abundance than spring or winter fire. Fire treatments in all seasons maintain the same general bird community structure as controls, while mastication results in strongly differentiated assemblages, increasing granivores while nearly excluding foliage gleaners. Synthesis and applications. We compare two California chaparral management techniques, prescribed fire and mastication, in three seasons (fall, winter and spring) in northern California, USA. We tracked chaparral bird community response in 23 experimental units for 2–5 years. We conclude that prescribed fire and mastication are not interchangeable management techniques, and that mastication negatively impacts bird communities, altering guild structure and reducing both diversity and abundance.
Data from: Effect of management on natural capital stocks underlying ecosystem service provision: a 'provider group' approach
Land management practices directly impact on the occurrence and condition of natural capital stocks, which can be measured using species diversity and abundance metrics. Species identity and abundance drive ecosystem service supply, either through effects of local diversity and/or through the presence of service providing species. However, the influence of management practices on the provision of ecosystem services is not adequately understood. We grouped grassland plant species into six groups according to desirable attributes (palatability and nutritional value to livestock; medicinal or aromatic compounds; nectar production; pollen production; nitrogen fixation; and endemic and red listed species), which we recognise as ecosystem service 'provider groups', and tested the influence of three land management practices (abandonment of mowing, grazing, and mowing) on diversity and abundance within these groups in upland temperate grasslands of Transylvania (Romania). All three management practices favoured at least one provider group, but hay making in upland grasslands favoured more provider groups than abandonment of mowing or grazing. The effects of management on diversity and abundance within several provider groups diverged from the effects on overall species diversity and abundance. Management, through changes in species composition, favours certain provider groups, and hence ecosystem services, over others. The provider group approach is more useful than overall species diversity metrics for assessing the provision of ecosystem services from landscapes and can be used to inform the development of agri-environment schemes and conservation policies aimed at meeting priorities for ecosystem service provision.
Data from: Inferring invasive species abundance using removal data from management actions
Evaluation of the progress of management programs for invasive species is crucial for demonstrating impacts to stakeholders and strategic planning of resource allocation. Estimates of abundance before and after management activities can serve as a useful metric of population management programs. However, many methods of estimating population size are too labor intensive and costly to implement, posing restrictive levels of burden on operational programs. Removal models are a reliable method for estimating abundance before and after management using data from the removal activities exclusively, thus requiring no work in addition to management. We developed a Bayesian hierarchical model to estimate abundance from removal data accounting for varying levels of effort, and used simulations to assess the conditions under which reliable population estimates are obtained. We applied this model to estimate site-specific abundance of an invasive species, feral swine (Sus scrofa), using removal data from aerial gunning in 59 site/time-frame combinations (480–19,600 acres) throughout Oklahoma and Texas, USA. Simulations showed that abundance estimates were generally accurate when effective removal rates (removal rate accounting for total effort) were above 0.40. However, when abundances were small (<50) the effective removal rate needed to accurately estimates abundances was considerably higher (0.70). Based on our post-validation method, 78% of our site/time frame estimates were accurate. To use this modeling framework it is important to have multiple removals (more than three) within a time frame during which demographic changes are minimized (i.e., a closed population; ≤3 months for feral swine). Our results show that the probability of accurately estimating abundance from this model improves with increased sampling effort (8+ flight hours across the 3-month window is best) and increased removal rate. Based on the inverse relationship between inaccurate abundances and inaccurate removal rates, we suggest auxiliary information that could be collected and included in the model as covariates (e.g., habitat effects, differences between pilots) to improve accuracy of removal rates and hence abundance estimates.
Data from: Patterns of rangeland productivity and land ownership: implications for conservation and management
Rangelands cover 40-50% of the earth's terrestrial surface. While often characterized by limited, yet variable resource availability, rangelands are vital for humans, providing numerous ecosystem goods and services. In the conterminous United States (CONUS) the dominant component of rangeland conservation is a network of public rangelands, concentrated in the west. Public rangelands are interspersed with private and tribal rangelands resulting in a complex mosaic of land tenure and management priorities. We quantify ownership patterns of rangeland production at multiple scales across CONUS and find that both total production and average productivity of private rangelands more than doubles that of public and tribal rangelands. At finer scales, private rangelands are consistently more productive than their public counterparts. We also demonstrate an inverse relationship between public rangeland acreage and productivity. While conserving acreage is crucial to rangeland conservation, just as critical are broad scale ecological patterns and processes that sustain ecosystem services. Across CONUS, ownership regimes capture distinct elements of these patterns and services, demonstrated through disparate production dynamics. As ownership determines the range of feasible conservation actions, and the technical and financial resources available to implement them, understanding ownership-production dynamics is critical for effective and sustained conservation of rangeland ecosystem services.
Data from: Nutrient limitation in tropical secondary forests following different management practices
Secondary forests now make up more than half of all tropical forests, and constraints on their biomass accumulation will influence the strength of the terrestrial carbon (C) sink in the coming decades. However the variance in secondary tropical forest biomass for a given stand age and climate is high and our understanding of why is limited. We constructed a model of terrestrial C, nitrogen (N), and phosphorus (P) cycling to examine the influence of disturbance and management practices on nutrient limitation and biomass recovery in secondary tropical forests. The model predicted that N limited the rate of forest recovery in the first few decades following harvest, but that this limitation switched to P approximately 30-40 years after abandonment, consistent with field data on N and P cycling from secondary tropical forest chronosequences. Simulated biomass recovery agreed well with field data of biomass accumulation following harvest (R2=0.80). Model results showed that if all biomass remained on site following a severe disturbance such as blowdown, regrowth approached pre-disturbance biomass in 80-90 years, and recovery was faster following smaller disturbances such as selective logging. Field data from regrowth on abandoned pastures were consistent with simulated losses of nutrients in soil organic matter, particularly P. Following any forest disturbance that involved the removal of nutrients (i.e., except blowdown), forest regrowth produced reduced biomass relative to the initial state as a result of nutrient loss through harvest, leaching and/or sequestration by secondary minerals. Differences in nutrient availability accounted for 49-94% of the variance in secondary forest biomass C at a given stand age. Management lessons from this study are the importance of strategies that help retain nutrients on site, recognizing the role of coarse woody debris in immobilization and subsequent release of nutrients, and the potential for nutrient additions to enhance biomass growth and recovery in secondary tropical forests.
Data from: Using the Spatial Population Abundance Dynamics Engine for conservation management
1. An explicit spatial understanding of population dynamics is often critical for effective management of wild populations. Sophisticated approaches are available to simulate these dynamics, but are largely either spatially homogeneous or agent-based, and thus best suited to small spatial or temporal scales. These approaches also often ignore financial decisions crucial to choosing management approaches on the basis of cost-effectiveness. 2. We created a user-friendly and flexible modelling framework for simulating these population issues at large spatial scales – the Spatial Population Abundance Dynamics Engine (SPADE). SPADE is based on the STAR model (McMahon et al. 2010) and uses a reaction-diffusion approach to model population trajectories and a cost-benefit analysis technique to calculate optimal management strategies over long periods and across broad spatial scales. It expands on STAR by incorporating species interactions and multiple concurrent management strategies, and by allowing full user control of functional forms and parameters. 3. We used SPADE to simulate the eradication of feral domestic cats Felis catus on sub-Antarctic Marion Island (Bester et al. 2002) and compared modelled outputs to observed data. The parameters of the best-fitting model reflected the conditions of the management programme, and the model successfully simulated the observed movement of the cat population to the southern and eastern portion of the island under hunting pressure. We further demonstrated that none of the management strategies would likely have been successful within a reasonable timeframe if performed in isolation. 4. SPADE is applicable to a wide range of population management problems, and allows easy generation, modification and analysis of management scenarios. It is a useful tool for the planning, evaluation and optimisation of the management of wild populations, and can be used without specialised training.
Data from: The genetic structure of Asian corn borer, Ostrinia furnacalis, populations in China: haplotype variance in Northern populations and potential impact on management of resistance to transgenic maize
Asian corn borer, Ostrinia furnacalis (Guenée), is a severe pest that infests cultivated maize in the major production regions of China. Populations show genotype-by-environment variation in voltinism, such that populations with a single generation (univoltine) are fixed in Northern China where growing seasons are short. Low genetic differentiation was found among samples from 33 collection sites across China and one site from North Korea (n = 1,673) using variation at 6 nuclear microsatellite loci (ENA corrected global FST = 0.020; P-value < 0.05). Analysis of molecular variance (AMOVA) indicated that geographic region, number of generations or voltinism accounted for < 0.38% of the total genetic variation at nuclear loci and was corroborated by clustering of co-ancestries among genotypes using the program STRUCTURE. In contrast, a mitochondrial haplotype network identified four distinct clusters, where 70.5% of samples from univoltine populations were within a single group. Univoltine populations were also placed into a unique cluster using Population Graph and Principal Component analyses, which showed significant differentiation with multivoltine populations (ST = 0.400; P-value < 0.01). This study suggests that gene flow among O. furnacalis in China may be high among regions, with the exception of northeastern localities. Haplotype variation may be due to random genetic drift resulting from partial reproductive isolation between univoltine and multivoltine O. furnacalis populations. Such reproductive isolation might impact the potential spread of alleles that confer resistance to transgenic maize in China.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.