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87 results for “cascade effects”
Cascade Project at North Temperate Lakes LTER: Aquatic heatwave effects on chlorophyll 2008-2019
Temperature and chlorophyll data were collated from multiple datasets to identify the effects of aquatic heatwaves on phytoplankton in three north temperate lakes, Peter Lake, Paul Lake, and Tuesday Lake between 2008 and 2019. Heatwaves were identified using a water temperature model constructed from temperature data from Sparkling Lake and Woodruff Airport between 1989 and 2022. Heatwave characteristics, water color, nutrients, grazing, and lake stability data are included to relate chlorophyll response to heatwaves to other conditions associated with a set of whole-lake experiments. The food web of Peter Lake was manipulated with largemouth bass additions between 2008 and 2011. Nutrient additions were made to Peter Lake and Tuesday Lake between 2013 and 2015, and again in Peter Lake in 2019. Paul Lake was always maintained as an unmanipulated reference lake. Full descriptions of the experiments can be found in Szydlowski et al., "Aquatic heatwaves increase surface chlorophyll concentrations in experimental and reference lakes."
Data from: Cascading effects of apex predator recovery on rodent foraging activity and seed predation
This dataset was collected to examine the effects of apex predator presence on post-dispersal seed predation and rodent foraging behavior in Mediterranean ecosystems of southern Spain. The study focused on the Iberian lynx (Lynx pardinus) as a top predator capable of altering mesopredator and small mammal communities through cascading interactions. We used the fleshy-fruited tree Pyrus bourgaeana as a model species and conducted a seed predation experiment in two areas with and without lynx presence. A total of 1152 seeds were placed in 144 seed depots across forest and open habitats and three microhabitat types (rock, shrub, and open ground). Rodent activity and foraging behavior were monitored using 36 camera traps installed at a subset of seed depots, and rodent abundance was estimated with live trapping one week later. The dataset includes seed predation counts, camera-trap records of rodent visits, live-trapping results, and vegetation cover estimates. These data allow investigation of how predation risk and habitat structure influence rodent activity and post-dispersal seed predation dynamics in Mediterranean landscapes.
Cascading effects augment the direct impact of CO2 on phytoplankton growth in a biogeochemical model, links to model results
<p>This dataset provides the output of eight model simulations with the global ocean biogeochemical model FESOM-REcoM necessary to reproduce the findings of Seifert et al. (2022). In addition to information on the mesh, the dataset contains 1) 5-year means of global phytoplankton biomass, chlorophyll, net primary production, growth rates, limitations, calcification, grazing rates, calcite concentrations, zooplankton biomass, export fluxes as well as CO<sub>2(aq)</sub>, HCO<sub>3</sub><sup>-</sup> and nutrient concentrations, and 2) a time series of global and North Atlantic coccolithophore biomass, temperature, and CO<sub>2(aq)</sub> concentrations from 1958 to 2018.</p> <p>File names refer to the Figures and Tables in the paper where the respective data are used. See “readme” for detailed information on the dataset and separate files.</p>
Data from: The more you get, the more you give: Positive cascading effects shape the evolutionary potential of prenatal maternal investment
<p>Data from 'The more you get, the more you give: Positive cascading effects shape the evolutionary potential of prenatal maternal investment'</p> <p> </p> <p>Description of variables in CME_dat.csv</p> <p>egg.mass - mean offspring egg mass (grams)</p> <p>maternal.line - selection line of mother (H- high investment, L - low investment)</p> <p>paternal.line - selection lines of father (H- high investment, L - low investment)</p> <p>replicate - selection line replicate</p> <p>animal - animal id (links with data from Pick et al. 2016 on dryad)</p> <p>mother - mother id</p> <p>father - father id</p> <p>maternal.egg.mass - mean maternal egg mass (grams)</p>
Data from: Wildfire disturbance and ecological cascades: teasing apart the direct and indirect effects of fire on tick populations
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Macroinvertebrate habitat use and the cascading effects of a native and non-native species
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Cascading effects of insecticides and road salt on wetland communities, outdoor mesocosm experiment, New York, USA, 2015
Novel stressors introduced by human activities increasingly threaten freshwater ecosystems. The annual application of more than 2.3 billion kg of pesticide active ingredient and 22 billion kg of road salt has led to the contamination of temperate waterways. While pesticides and road salt are known to cause direct and indirect effects in aquatic communities, their possible interactive effects remain widely unknown. Using outdoor mesocosms, we created wetland communities consisting of zooplankton, phytoplankton, periphyton, and leopard frog (Rana pipiens) tadpoles. We evaluated the toxic effects of six broad- spectrum insecticides from three families (neonicotinoids: thiamethoxam, imidacloprid; organophosphates: chlorpyrifos, malathion; pyrethroids: cypermethrin, permethrin), as well as the potentially interactive effects of four of these insecticides with three concentrations of road salt (NaCl; 44, 160, 1600 Cl- mg/L). Organophosphate exposure decreased zooplankton abundance, elevated phytoplankton biomass, and reduced tadpole mass whereas exposure to neonicotinoids and pyrethroids decreased zooplankton abundance but had no significant effect on phytoplankton abundance or tadpole mass. While organophosphates decreased zooplankton abundance at all salt concentrations, effects on phytoplankton abundance and tadpole mass were dependent upon salt concentration. In contrast, while pyrethroids had no effects in the absence of salt, they decreased zooplankton and phytoplankton density under increased salt concentrations. Our results highlight the importance of multiple-stressor research under natural conditions. As human activities continue to imperil freshwater systems, it is vital to move beyond single-stressor experiments that exclude potentially interactive effects of chemical contaminants.
Effect of thinning pole stands on soil processes in southern Oregon, central Coast Range, and central western Cascades of Oregon (1994-1995 BLM Study)
This study was conducted in different regions to determine if climatic regimes alter the effects of thinning pole stands. Forest managers are currently faced with increasingly complex demands in designing sulvicultural approaches that fulfill the need to maintain and in some cases, enhance forest health. As mature and old-growth forests with their high degree of structural heterogeneity are replaced by younger plantations with much simpler structure, there is concern that key habitat components are being lost for a number of plants and animals. A silviculture technique that could be used to increase the structural complexity of young stands to thin them; encouraging the development of higher structural complexity. The main purposes of this study is to determine how thinning pole stands influence below-ground processes. The central research question was whether or not this manipulation brings soil characteristics closer to those found in old-growth forests; in essence, accelerating the onset of old-growth-like characteristics via forest management.
Data from: Cascading effects of climate variability on the breeding success of an edge population of an apex predator
<p>1. Large-scale environmental forces can influence biodiversity at different levels of biological organization. Climate, in particular, is often associated to species distributions and diversity gradients. However, its mechanistic link to population dynamics is still poorly understood.</p> <p>2. Here, we unraveled the full mechanistic path by which a climatic driver, the Atlantic trade winds, determines the viability of a bird population.</p> <p>3. We monitored the breeding population of Eleonora's falcons in the Canary Islands for over a decade (2007-2017) and integrated different methods and data to reconstruct how the availability of their prey (migratory birds) is regulated by trade winds. We tracked foraging movements of breeding adults using GPS, monitored departure of migratory birds using weather radar, and simulated their migration trajectories using an individual-based, spatially explicit model.</p> <p>4. We demonstrate that regional easterly winds regulate the flux of migratory birds that is available to hunting falcons, determining food availability for their chicks and consequent breeding success. By reconstructing how migratory birds are pushed towards the Canary Islands by trade winds, we explain most of the variation (up to 86%) in annual productivity for over a decade.</p> <p>5. This study unequivocally illustrates how a climatic driver can influence local-scale demographic processes, while providing novel evidence of wind as a major determinant of population fitness in a top predator. 06-Jul-2020</p>
Effects of habitat modification on a tritrophic cascade in a lowland tropical rainforest
<b>Description: </b><p>The impact of anthropogenic disturbance of tropical rainforests on ecosystem processes is poorly understood. In this study I investigate how habitat modification in tropical rainforests may mediate a tritrophic cascade with resultant effects on herbivory, a key ecosystem process. I adopt a stepwise approach through the trophic levels, assessing the relationships between forest quality and the bird community assemblage, and corresponding impacts on predation rates and herbivory. I measured the bird community across a forest quality gradient, surveying 24 sites within a modified lowland tropical rainforest in Borneo. At each sampling location I established two treatments, one using a large (2 x 2 x 1.5m) cage designed to exclude vertebrates, and the second a control where no vertebrate exclusion was in place. I measured predation rates using dummy caterpillars, and herbivory rates on selected leaves in each treatment at all sampling locations. I used piecewise structural equation modelling to develop a path model between predictor and response variables. I established a significant pathway between increasing forest quality, increased richness of the bird community and higher vertebrate predation rates. Conversely, invertebrate predation rates declined with increasing forest quality. The effect of increasing forest quality did not mediate a trophic cascade bringing about an increase in herbivory. However, the effect of vertebrate exclusion mediated a trophic cascade and an increase in herbivory in higher forest quality, where invertebrate predation levels are lower. The results of the study therefore reflect the dampening of the tritrophic cascade across a forest quality gradient, and high functional redundancy in predatory function in forests of low quality. The study also highlights the importance of avian predatory function in forests of higher quality. A reduction in large vertebrate predators in undisturbed tropical rainforests may therefore result in cascading effects on herbivory, which may in turn have implications for primary productivity and nutrient cycling. These findings have significant implications for tropical forest conservation and management. Further research should place emphasis on addressing the effects of the loss of apex predators on key ecosystem processes.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/201"><b>The effects of habitat modification on a tritrophic cascade in a lowland tropical rainforest</b></a></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (SABC) (Research licence JKN/MBS.1000-2/2 JLD.8 (66))</li><li>Sabah Biodiversity Centre (SABC) (Research licence JKM/MBS.1000-2/2 JLD.8 (61) )</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3981222">here</a></p><p><b>Files: </b>This dataset consists of 2 files: FraserExclusionPlots_AFedit_150820.xlsx, FraserAdam_TFE_2019_SAFE_AudioFiles.zip</p><p><b>FraserExclusionPlots_AFedit_150820.xlsx</b></p><p>This file contains dataset metadata and 3 data tables:</p><ol><li><p><b>Bird point counts</b> (described in worksheet PointCounts)</p><p>Description: Repeated bird point counts at all sites</p><p>Number of fields: 89</p><p>Number of data rows: 72</p><p>Fields: </p><ul><li><b>Visit_Code</b>: Unique site x replicate code (Field type: id)</li><li><b>Plot</b>: SAFE Project plot ID (Field type: location)</li><li><b>Visit</b>: Visit number (Field type: replicate)</li><li><b>Date</b>: Date of point count (Field type: date)</li><li><b>Time_Start</b>: Time at start of point count (Field type: time)</li><li><b>Time_Finish</b>: Time at end of point count (Field type: time)</li><li><b>Weather</b>: Observations on weather conditions (Field type: comments)</li><li><b>Ashy.tailorbird</b>: Count of individuals (Field type: abundance)</li><li><b>Asian.fairy.bluebird</b>: Count of individuals (Field type: abundance)</li><li><b>Asian.paradise.flycatcher</b>: Count of individuals (Field type: abundance)</li><li><b>Asian.red.eyed.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Banded.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Banded.bay.cuckoo</b>: Count of individuals (Field type: abundance)</li><li><b>Black.and.red.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Black.and.yellow.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Black.capped.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Black.headed.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Black.headed.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Black.naped.monarch</b>: Count of individuals (Field type: abundance)</li><li><b>Blue.eared.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Blue.headed.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Bold.striped.tit.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Bornean.banded.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Bornean.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Bronzed.drongo</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.fulvetta</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.backed.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.throated.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Bushy.crested.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.backed.scimitar.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.munia</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.rumped.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.winged.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Collared.kingfisher</b>: Count of individuals (Field type: abundance)</li><li><b>Common.emerald.dove</b>: Count of individuals (Field type: abundance)</li><li><b>Cream.vented.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Crested.fireback</b>: Count of individuals (Field type: abundance)</li><li><b>Crimson.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Dark.necked.tailorbird</b>: Count of individuals (Field type: abundance)</li><li><b>Diards.trogon</b>: Count of individuals (Field type: abundance)</li><li><b>Dusky.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Fiery.minivet</b>: Count of individuals (Field type: abundance)</li><li><b>Fluffy.backed.tit.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Gold.whiskered.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Great.argus</b>: Count of individuals (Field type: abundance)</li><li><b>Greater.green.leafbird</b>: Count of individuals (Field type: abundance)</li><li><b>Greater.racket.tailed.drongo</b>: Count of individuals (Field type: abundance)</li><li><b>Green.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Grey.headed.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Helmeted.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Hooded.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Lesser.green.leafbird</b>: Count of individuals (Field type: abundance)</li><li><b>Little.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Long.billed.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Malaysian.blue.flycatcher</b>: Count of individuals (Field type: abundance)</li><li><b>Moustached.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Orange.bellied.flowerpecker</b>: Count of individuals (Field type: abundance)</li><li><b>Pied.fantail</b>: Count of individuals (Field type: abundance)</li><li><b>Plain.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Plaintive.cuckoo</b>: Count of individuals (Field type: abundance)</li><li><b>Puff.backed.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Purple.naped.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Raffless.malkoha</b>: Count of individuals (Field type: abundance)</li><li><b>Red.bearded.bee.eater</b>: Count of individuals (Field type: abundance)</li><li><b>Red.naped.trogon</b>: Count of individuals (Field type: abundance)</li><li><b>Red.throated.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Rhinoceros.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.collared.kingfisher</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.crowned.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.fronted.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.tailed.tailorbird</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.tailed.shama</b>: Count of individuals (Field type: abundance)</li><li><b>Scarlet.rumped.trogon</b>: Count of individuals (Field type: abundance)</li><li><b>Short.tailed.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Short.toed.coucal</b>: Count of individuals (Field type: abundance)</li><li><b>Slender.billed.crow</b>: Count of individuals (Field type: abundance)</li><li><b>Sooty.capped.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Spectacled.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Spectacled.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Violet.cuckoo</b>: Count of individuals (Field type: abundance)</li><li><b>White.crowned.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>White.crowned.shama</b>: Count of individuals (Field type: abundance)</li><li><b>Woodpecker.sp.</b>: Count of individuals (Field type: abundance)</li><li><b>Wreathed.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.breasted.flowerpecker</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.crowned.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.rumped.flowerpecker</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.vented.bulbul</b>: Count of individuals (Field type: abundance)</li></ul></li><li><p><b>Leaf herbivory</b> (described in worksheet LeafHerbivory)</p><p>Description: Within each treatment, I tagged and numbered seven leaves. I chose a variation of leaf ages within each treatment, as recommended by Coley and Barone (1996). I measured leaf area on all tagged leaves at monthly intervals, as recommended by Coley and Barone (1996) and detailed in Harrison and Banks-Leite (2019), between March and May 2019. I calculated arthropod herbivory rate using ImageJ software (Schindelin et al. 2012) to determine the percentage leaf area lost (LAL) over time.</p><p>Number of fields: 9</p><p>Number of data rows: 336</p><p>Fields: </p><ul><li><b>Site</b>: SAFE Project plot ID (Field type: location)</li><li><b>Treatment</b>: Experimental treatment: inside or outside exclusion cage? (Field type: categorical)</li><li><b>Leaf</b>: ID number for each leaf (Field type: replicate)</li><li><b>DateFirstObs</b>: Date of first leaf observation (Field type: date)</li><li><b>LeafArea</b>: Leaf area at first observation (Field type: numeric)</li><li><b>DateFinalObs</b>: Date of final leaf observation (Field type: date)</li><li><b>FinalLeafArea</b>: Leaf area at last observation (Field type: numeric)</li><li><b>LostArea</b>: Area of leaf lost to herbivory (Field type: numeric)</li><li><b>PercentLostArea</b>: Percent of leaf area lost to herbivory (Field type: numeric)</li></ul></li><li><p><b>Insect predation data</b> (described in worksheet PredationData)</p><p>Description: I assessed predation rates on invertebrates by placing five plasticine dummy caterpillars within each treatment, at each sampling location. The methods were based on those described in Howe, Lövei and Nachman (2009) Roslin et al. (2017) and Roels, Porter and Lindell (2018). I placed five fresh plasticine caterpillars at least one metre apart from each other within the treatment and recovered the caterpillars after 14 days. I quantified predation attempts on each set of caterpillars within each treatment, following guidance on visual predator identification as per Low et al. (2014).</p><p>Number of fields: 9</p><p>Number of data rows: 144</p><p>Fields: </p><ul><li><b>Visit_Code</b>: Unique site x replicate code (Field type: id)</li><li><b>Plot</b>: SAFE Project plot ID (Field type: location)</li><li><b>Visit</b>: Visit number (Field type: replicate)</li><li><b>Date</b>: Date of point count (Field type: date)</li><li><b>Treatment</b>: Experimental treatment: inside or outside exclusion cage? (Field type: categorical)</li><li><b>Invertebrate</b>: Number of plasticine invertebrate mimics attacked by invertebrate predator (Field type: numeric)</li><li><b>Mammal</b>: Number of plasticine invertebrate mimics attacked by mammalian predator (Field type: numeric)</li><li><b>Bird</b>: Number of plasticine invertebrate mimics attacked by avian predator (Field type: numeric)</li><li><b>Other</b>: Number of plasticine invertebrate mimics attacked by predator that couldn't be identified (Field type: numeric)</li></ul></li></ol><p><b>FraserAdam_TFE_2019_SAFE_AudioFiles.zip</b></p><p>Description: Audio files recorded during points counts</p><p><b>Date range: </b>2019-03-04 to 2019-05-10</p><p><b>Latitudinal extent: </b>4.6815 to 4.7435</p><p><b>Longitudinal extent: </b>117.5396 to 117.5971</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Chordata <br> -  -  -  Aves <br> -  -  -  -  Piciformes <br> -  -  -  -  -  Picidae <br> -  -  -  -  -  Ramphastidae <br> -  -  -  -  -  -  <i>Psilopogon</i> <br> -  -  -  -  -  -  -  <i>Psilopogon duvaucelii</i> <br> -  -  -  -  -  -  -  <i>Psilopogon chrysopogon</i> <br> -  -  -  -  -  -  -  <i>Psilopogon mystacophanos</i> <br> -  -  -  -  -  -  -  <i>Psilopogon henricii</i> <br> -  -  -  -  -  -  <i>Caloramphus</i> <br> -  -  -  -  -  -  -  <i>Caloramphus fuliginosus</i> <br> -  -  -  -  Coraciiformes <br> -  -  -  -  -  Alcedinidae <br> -  -  -  -  -  -  <i>Todiramphus</i> <br> -  -  -  -  -  -  -  <i>Todiramphus chloris</i> <br> -  -  -  -  -  -  <i>Actenoides</i> <br> -  -  -  -  -  -  -  <i>Actenoides concretus</i> <br> -  -  -  -  -  Meropidae <br> -  -  -  -  -  -  <i>Nyctyornis</i> <br> -  -  -  -  -  -  -  <i>Nyctyornis amictus</i> <br> -  -  -  -  Galliformes <br> -  -  -  -  -  Phasianidae <br> -  -  -  -  -  -  <i>Argusianus</i> <br> -  -  -  -  -  -  -  <i>Argusianus argus</i> <br> -  -  -  -  -  -  <i>Lophura</i> <br> -  -  -  -  -  -  -  <i>Lophura ignita</i> <br> -  -  -  -  Columbiformes <br> -  -  -  -  -  Columbidae <br> -  -  -  -  -  -  <i>Chalcophaps</i> <br> -  -  -  -  -  -  -  <i>Chalcophaps indica</i> <br> -  -  -  -  Passeriformes <br> -  -  -  -  -  Corvidae <br> -  -  -  -  -  -  <i>Corvus</i> <br> -  -  -  -  -  -  -  <i>Corvus enca</i> <br> -  -  -  -  -  Pellorneidae <br> -  -  -  -  -  -  <i>Pellorneum</i> <br> -  -  -  -  -  -  -  <i>Pellorneum capistratum</i> <br> -  -  -  -  -  -  <i>Alcippe</i> <br> -  -  -  -  -  -  -  <i>Alcippe brunneicauda</i> <br> -  -  -  -  -  -  <i>Trichastoma</i> <br> -  -  -  -  -  -  -  <i>Trichastoma malaccense</i> <br> -  -  -  -  -  -  <i>Malacopteron</i> <br> -  -  -  -  -  -  -  <i>Malacopteron magnirostre</i> <br> -  -  -  -  -  -  -  <i>Malacopteron magnum</i> <br> -  -  -  -  -  -  -  <i>Malacopteron affine</i> <br> -  -  -  -  -  Cisticolidae <br> -  -  -  -  -  -  <i>Orthotomus</i> <br> -  -  -  -  -  -  -  <i>Orthotomus ruficeps</i> <br> -  -  -  -  -  -  -  <i>Orthotomus atrogularis</i> <br> -  -  -  -  -  -  -  <i>Orthotomus sericeus</i> <br> -  -  -  -  -  Rhipiduridae <br> -  -  -  -  -  -  <i>Rhipidura</i> <br> -  -  -  -  -  -  -  <i>Rhipidura javanica</i> <br> -  -  -  -  -  Muscicapidae <br> -  -  -  -  -  -  <i>Trichixos</i> <br> -  -  -  -  -  -  -  <i>Trichixos pyrropygus</i> <br> -  -  -  -  -  -  <i>Cyornis</i> <br> -  -  -  -  -  -  -  <i>Cyornis turcosus</i> <br> -  -  -  -  -  -  <i>Copsychus</i> <br> -  -  -  -  -  -  -  <i>Copsychus stricklandii</i> <br> -  -  -  -  -  Dicaeidae <br> -  -  -  -  -  -  <i>Dicaeum</i> <br> -  -  -  -  -  -  -  <i>Dicaeum everetti</i> <br> -  -  -  -  -  -  -  <i>Dicaeum trigonostigma</i> <br> -  -  -  -  -  -  <i>Prionochilus</i> <br> -  -  -  -  -  -  -  <i>Prionochilus maculatus</i> <br> -  -  -  -  -  -  -  <i>Prionochilus xanthopygius</i> <br> -  -  -  -  -  Campephagidae <br> -  -  -  -  -  -  <i>Pericrocotus</i> <br> -  -  -  -  -  -  -  <i>Pericrocotus igneus</i> <br> -  -  -  -  -  Timaliidae <br> -  -  -  -  -  -  <i>Pomatorhinus</i> <br> -  -  -  -  -  -  -  <i>Pomatorhinus montanus</i> <br> -  -  -  -  -  -  <i>Cyanoderma</i> <br> -  -  -  -  -  -  -  <i>Cyanoderma erythropterum</i> <br> -  -  -  -  -  -  -  <i>Cyanoderma rufifrons</i> <br> -  -  -  -  -  -  <i>Stachyris</i> <br> -  -  -  -  -  -  -  <i>Stachyris maculata</i> <br> -  -  -  -  -  -  -  <i>Stachyris poliocephala</i> <br> -  -  -  -  -  -  <i>Macronus</i> <br> -  -  -  -  -  -  -  <i>Macronus ptilosus</i> <br> -  -  -  -  -  -  <i>Mixornis</i> <br> -  -  -  -  -  -  -  <i>Mixornis bornensis</i> <br> -  -  -  -  -  Eurylaimidae <br> -  -  -  -  -  -  <i>Eurylaimus</i> <br> -  -  -  -  -  -  -  <i>Eurylaimus javanicus</i> <br> -  -  -  -  -  -  -  <i>Eurylaimus ochromalus</i> <br> -  -  -  -  -  -  <i>Calyptomena</i> <br> -  -  -  -  -  -  -  <i>Calyptomena viridis</i> <br> -  -  -  -  -  -  <i>Cymbirhynchus</i> <br> -  -  -  -  -  -  -  <i>Cymbirhynchus macrorhynchos</i> <br> -  -  -  -  -  -  <i>Corydon</i> <br> -  -  -  -  -  -  -  <i>Corydon sumatranus</i> <br> -  -  -  -  -  Dicruridae <br> -  -  -  -  -  -  <i>Dicrurus</i> <br> -  -  -  -  -  -  -  <i>Dicrurus aeneus</i> <br> -  -  -  -  -  -  -  <i>Dicrurus paradiseus</i> <br> -  -  -  -  -  Estrildidae <br> -  -  -  -  -  -  <i>Lonchura</i> <br> -  -  -  -  -  -  -  <i>Lonchura atricapilla</i> <br> -  -  -  -  -  Pycnonotidae <br> -  -  -  -  -  -  <i>Pycnonotus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus brunneus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus atriceps</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus simplex</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus eutilotus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus erythropthalmos</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus goiavier</i> <br> -  -  -  -  -  Chloropseidae <br> -  -  -  -  -  -  <i>Chloropsis</i> <br> -  -  -  -  -  -  -  <i>Chloropsis sonnerati</i> <br> -  -  -  -  -  -  -  <i>Chloropsis cyanopogon</i> <br> -  -  -  -  -  Nectariniidae <br> -  -  -  -  -  -  <i>Aethopyga</i> <br> -  -  -  -  -  -  -  <i>Aethopyga siparaja</i> <br> -  -  -  -  -  -  <i>Anthreptes</i> <br> -  -  -  -  -  -  -  <i>Anthreptes malacensis</i> <br> -  -  -  -  -  -  -  <i>Anthreptes simplex</i> <br> -  -  -  -  -  -  <i>Arachnothera</i> <br> -  -  -  -  -  -  -  <i>Arachnothera everetti</i> <br> -  -  -  -  -  -  -  <i>Arachnothera longirostra</i> <br> -  -  -  -  -  -  -  <i>Arachnothera robusta</i> <br> -  -  -  -  -  -  -  <i>Arachnothera flavigaster</i> <br> -  -  -  -  -  -  <i>Kurochkinegramma</i> <br> -  -  -  -  -  -  -  <i>Kurochkinegramma hypogrammicum</i> <br> -  -  -  -  -  Irenidae <br> -  -  -  -  -  -  <i>Irena</i> <br> -  -  -  -  -  -  -  <i>Irena puella</i> <br> -  -  -  -  -  Pittidae <br> -  -  -  -  -  -  <i>Erythropitta</i> <br> -  -  -  -  -  -  -  <i>Erythropitta ussheri</i> <br> -  -  -  -  -  -  <i>Pitta</i> <br> -  -  -  -  -  -  -  <i>Pitta sordida</i> <br> -  -  -  -  -  Monarchidae <br> -  -  -  -  -  -  <i>Hypothymis</i> <br> -  -  -  -  -  -  -  <i>Hypothymis azurea</i> <br> -  -  -  -  -  -  <i>Terpsiphone</i> <br> -  -  -  -  -  -  -  <i>Terpsiphone paradisi</i> <br> -  -  -  -  Trogoniformes <br> -  -  -  -  -  Trogonidae <br> -  -  -  -  -  -  <i>Harpactes</i> <br> -  -  -  -  -  -  -  <i>Harpactes diardii</i> <br> -  -  -  -  -  -  -  <i>Harpactes kasumba</i> <br> -  -  -  -  -  -  -  <i>Harpactes duvaucelii</i> <br> -  -  -  -  Cuculiformes <br> -  -  -  -  -  Cuculidae <br> -  -  -  -  -  -  <i>Chrysococcyx</i> <br> -  -  -  -  -  -  -  <i>Chrysococcyx xanthorhynchus</i> <br> -  -  -  -  -  -  <i>Centropus</i> <br> -  -  -  -  -  -  -  <i>Centropus rectunguis</i> <br> -  -  -  -  -  -  <i>Cacomantis</i> <br> -  -  -  -  -  -  -  <i>Cacomantis sonneratii</i> <br> -  -  -  -  -  -  -  <i>Cacomantis merulinus</i> <br> -  -  -  -  -  -  <i>Rhinortha</i> <br> -  -  -  -  -  -  -  <i>Rhinortha chlorophaea</i> <br> -  -  -  -  Bucerotiformes <br> -  -  -  -  -  Bucerotidae <br> -  -  -  -  -  -  <i>Berenicornis</i> <br> -  -  -  -  -  -  -  <i>Berenicornis comatus</i> <br> -  -  -  -  -  -  <i>Anorrhinus</i> <br> -  -  -  -  -  -  -  <i>Anorrhinus galeritus</i> <br> -  -  -  -  -  -  <i>Rhyticeros</i> <br> -  -  -  -  -  -  -  <i>Rhyticeros undulatus</i> <br> -  -  -  -  -  -  <i>Buceros</i> <br> -  -  -  -  -  -  -  <i>Buceros rhinoceros</i> <br> -  -  -  -  -  -  <i>Rhinoplax</i> <br> -  -  -  -  -  -  -  <i>Rhinoplax vigil</i> <br> -  -  -  -  <i>Hydrornis</i> <br> -  -  -  -  -  <i>Hydrornis baudii</i> <br> -  -  -  -  -  <i>Hydrornis schwaneri</i> <br></div><p></p>
Destabilizing effects on a classic tri-trophic oyster-reef cascade
<p>How interactions among multiple predators affect the stability of trophic cascades is a topic of special ecological interest. To examine factors affecting the stability of the classic tri-trophic oyster reef cascade within a different context, configurations of three predators, including the Gulf toadfish, Gulf stone crab, and oystershell mud crab, were manipulated together with either oyster shell or limestone gravel substrate within a multiple predator effects (MPE) experiment. Additionally, a complimentary set of trait-mediated-indirect interaction (TMII) experiments examined the inhibition of oyster consumption relative to mud-crab size and top predator identity in the absence of other cues and factors. The classic tri-trophic cascade formed by the toadfish-mud crab-oyster configuration was potentially weakened by several interactions within the MPE experiment. Consumption of oysters and mud crabs by the intraguild stone crab was undeterred by the presence of toadfish. Although mud crab feeding was inhibited in the presence of both toadfish and stone crabs, estimated non-consumptive effects (NCEs) were weaker for stone crabs in the MPE experiment. Consequently, the total effect was destabilizing when all three predator species were together. Inhibition of mud crab feeding was inversely related to direct predation on mud crabs within the MPE experiment. Complimentary TMII experiments revealed greater inhibition of mud crab feeding in response to stone crabs under sparse conditions. TMII experiments also implied that inhibition of mud crab feeding could have largely accounted for NCEs relative to oysters within the MPE experiment, as opposed to interference by other mud crabs or top predators. An inverse relationship between mud crab size and NCE strength in the TMII experiment disclosed another potentially destabilizing influence on the tri-trophic-cascade. Finally, although habitat complexity generally dampened the consumption of oysters across MPE treatments, complex habitat promoted mud crab feeding in the presence of toadfish alone. This study underscores how ecological interactions can mediate trophic cascades and provides some additional insights into the trophic dynamics of oyster reefs for further testing under natural conditions.</p>
Cascading effects of climate change on plankton community structure
<p><span><span><span><span><span><span><span><span><span><span><span>Plankton communities account for at least half of global primary production and play a key role in the global carbon cycle. Warming and acidification may alter the interaction chains in these communities from the bottom and top of the food web. Yet, the relative importance of these potentially complex interactions has not yet been quantified. Here we examine the isolated and combined effects of warming, acidification, and reductions in phytoplankton and predator abundances in a series of factorial experiments. We find that warming directly impacts the top of the food web, but that the intermediate trophic groups are more strongly influenced by indirect effects mediated by altered top-down interactions. Direct manipulations of predator and phytoplankton abundance reveal similar strong top-down interactions following top predator decline. A meta-analysis of published experiments further support the conclusion that warming has stronger direct impacts on the top and bottom of the food web rather than the intermediate trophic groups, with important differences between freshwater and marine plankton communities. Our results reveal that the trophic effect of warming cascading down from the top of the plankton food web is a powerful agent of global change.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Cascading effects of a top predator on intraspecific competition at intermediate and basal trophic levels
1. Predators can impact competition among prey by altering prey density via consumption or by causing prey to modify their traits or foraging behavior. Yet, differences between these two mechanisms may lead to different cascading impacts on lower trophic levels. 2. Using a crab-snail-barnacle rocky intertidal food chain, we tested the effects of predation risk from crabs (top predators) on intraspecific competition among snails (intermediate consumers) and emergent indirect effects on the density of and competition between barnacles (basal resources). 3. The per capita foraging and growth rates of snails declined with high conspecific density. Predation risk from crabs, which caused even larger reductions in snail foraging and growth, weakened competition among snails, whereas a 45% increase in barnacle density had no detectable effect on snail competition. 4. Intraspecific competition between barnacles, however, depended on the interactive effects of barnacle density, snail density, and crab predation risk. Barnacles developed hummocking morphologies as they grew and competed for space. Hummock formation (a proxy for competition) increased as a result of either greater initial barnacle density or reduced snail foraging pressure, but these effects depended on predation risk. 5. The effects of crab predation risk on snail foraging behavior weakened an otherwise strong relationship between barnacle density and hummock development: hummocking increased with barnacle density in the absence of crabs but remained relatively high when crabs were present. In communities with similar final barnacle densities, hummocking was more common in those with crabs than those without crabs. 6. The extent to which predators can drive trophic cascades by suppressing the foraging rates of their prey is highly context-dependent: the positive trait-mediated indirect effect of predators on basal resource abundance is stronger when many prey respond simultaneously to the threat of predation. However, our results demonstrate that top predators can also enhance competition among basal resources even when their indirect effect on resource abundance is relatively weak. Hence, the cascading effects of predators on competition within lower trophic levels may play an important but underappreciated role in the dynamics of basal resource populations and the communities they support.
Data from: Contrasting complexity of adjacent habitats influences the strength of cascading predatory effects
Although cascading effects of top predators can help structure communities, their influence may vary across habitats that differentially protect prey. Therefore, to understand how and to what degree habitat complexity can affect trophic interactions in adjacent habitats, we used a combination of a broad regional-scale survey, manipulative field trials, and an outdoor mesocosm experiment to quantify predator–prey interaction strengths across four trophic levels. Within estuaries of the southeastern USA, bonnethead sharks (Sphyrna tiburo) hunt blue crabs on mudflats and adjacent oyster reefs, two habitats with vastly different aboveground structure. Using 12-h tethering trials of blue crabs we quantified habitat-dependent loss rates of 37% on reefs and 78% on mudflats. We hypothesized that the sharks' predatory effects on blue crabs would cascade down to release a lower-level mud crab predator, which subsequently would increase juvenile oyster mortality, but that the cascade strength would be habitat-dependent. We experimentally manipulated predator combinations in split-plot mesocosms containing reef and mudflat habitats, and quantified oyster mortality. Bonnetheads exerted strong consumptive and non-consumptive effects on blue crabs, which ceased eating oysters in the sharks' presence. However, mud crabs, regardless of shark and blue crab presence, continued to consume oysters, especially within the structural refuge of the reef where they kept oyster mortality high. Thus, bonnetheads indirectly boosted oyster survival, but only on the mudflat where mud crabs were less active. Our work demonstrates how structural differences in adjacent habitats can moderate trophic cascades, particularly when mesopredators exhibit differential use of structure and different sensitivities to top predators.
Data from: Effects of a trophic cascade on a multi-level facilitation cascade
<p>1. The role of cascades in natural communities has been extensively studied, but interactions between trophic and facilitation cascades are unexplored. In the White Sea (65° N) shallow subtidal bivalve primary facilitators provide hard substrate for secondary facilitator barnacles, that in turn provide substrate for conspecifics, ascidians, red algae, and multiple associated organisms, composing a multi-level facilitation cascade. Previous research revealed that predation by the whelk (Boreotrophon clathratus) accounts for ~7% of adult barnacle mortality. Low whelk abundance limits their effect, with barnacles living on conspecifics several times more vulnerable to predation than those living on primary substrate.</p> <p>2. Trophic cascades can selectively shield foundation species from consumers, and hence may affect the structure and length of facilitation cascades. We tested the hypothesis that low abundance of the whelks results from mesopredator predation on their juveniles. Depending on the magnitude of the effect, this would mean that a trophic cascade controls the abundance of barnacles on all substrates or only barnacles living on conspecifics. We also suggested that barnacles on primary substrates and conspecifics facilitate different dependent assemblages.</p> <p>3. We manipulated the presence of crab and shrimp mesopredators in field caging experiments to assess their effect on whelk recruitment. In a field survey we compared the assemblages of sessile macrobenthic organisms associated with barnacles living on different substrates.</p> <p>4. Caging experiments evidenced that crab and shrimp mesopredators reduce whelk recruitment by 4.6 times. Field data showed that barnacles on primary substrate and on conspecifics promote different dependent assemblages including secondary facilitator ascidians.</p> <p>5. Although mesopredators do not shield barnacles from elimination, their absence would restrict them from living on conspecifics. Barnacles on conspecifics are functially different from barnacles on primary substrate, and can be concidered a separate level of the facilitation cascade. Trophic cascades thus can generate community-wide effects on facilitation cascades by affecting their structure and possibly length.</p>
Data from: Cascading effects of earthworm invasion in tundra increase graminoid density and rodent grazing intensities
<p>Earthworms are being introduced to numerous ecosystems through human activities. Some non-native earthworm species have the potential to 'geoengineer' soils and increase plant nitrogen (N) uptake, but if the increased plant N concentrations can cause increased rodent grazing is not well known. In this study, we present findings from a common garden experiment with two tundra communities, meadow (forb dominated) and heath (shrub dominated), half of them subjected to four years of earthworm presence (<em>Lumbricus</em> spp. and <em>Aporrectodea</em> spp.). Within four summers, our earthworm treatment changed plant community composition by increasing graminoid density by on average 94 % in the heath vegetation and by 49 % in the meadow. Rodent winter grazing were more intense on plants growing in soils with earthworms, an effect that coincided with higher nitrogen concentrations in plants indicating a higher palatability. Moreover, although the earthworms decreased soil moisture, our proxy for plant community photosynthesis (greenness) was not negatively affected. We conclude that earthworm-induced changes in plant composition and trophic interactions may radically alter the functioning of tundra ecosystems.</p>
Dataset for "Cascading effects of mammal host community composition on tick vector occurrence at the urban human-wildlife interface"
<p>Dataset for the following paper:</p> <p><strong>Cascading effects of mammal host community composition on tick vector occurrence at the urban human-wildlife interface</strong></p> <p>Jonathan Bastard *, Nichar Gregory *, Maria Pilar Fernandez, Michaela Mincone, Olivia Card, Sara Kross, Maria Diuk-Wasser</p> <p>* These authors contributed equally.</p>
Data from: Cascading effects of a disease outbreak in a remote protected area
<p>Disease outbreaks induced by humans increasingly threaten wildlife communities worldwide. Like predators, pathogens can be key top-down forces in ecosystems, initiating trophic cascades that may alter food webs. An outbreak of mange in a remote Andean protected area caused a dramatic population decline in a mammalian herbivore (the vicuña), creating conditions to test the cascading effects of disease on the ecological community. By comparing a suite of ecological measurements to pre-disease baseline records, we demonstrate that mange restructured tightly-linked trophic interactions previously driven by a mammalian predator (the puma). Following the mange outbreak, scavenger (Andean condor) occurrence in the ecosystem declined sharply and plant biomass and cover increased dramatically in predation refuges where herbivory was historically concentrated. The evidence shows that a disease-induced trophic cascade, mediated by vicuña density, could supplant the predator-induced trophic cascade, mediated by vicuña behavior, thereby transforming the Andean ecosystem. </p>
Data from: Parasite-driven cascades or hydra effects: susceptibility and foraging depression shape parasite-host-resource interactions
<p>This contains data for the manuscript listed in the title.<br><br>We measured the foraging rates of individual zooplankton hosts, <em>Daphnia dentifera</em>, on phytoplankton resources, <em>Ankistrodesmus falcatus</em>, in the presence of fungal parasites of zooplankton, <em>Metschnikowia bicuspidata</em>. Some of these data are previously published (Genotypes12_foraging.csv by Strauss, Alexander T., et al. "Genotypic variation in parasite avoidance behaviour and other mechanistic, nonlinear components of transmission." <em>Proceedings of the Royal Society B</em> 286.1915 (2019): 20192164.) and some are published now for the first time (Genotype3_foraging.csv).<br><br>In addition, we present novel evidence from a mesocosm experiment (Mesocosm_data1.csv-Mesocosm_data20.csv) of populations of each genotype or each pair of genotypes with phytoplankton resources and fungal parasites present or absent; our last treatment was low or high nutrient supply for the phytoplankton. With data on infection prevalence, host density, and phytoplankton density, we show how host traits and nutrients control outcomes for prevalence, host density, and phytoplankton density.<br><br>These data may be reused with appropriate citation.</p>
Prey naiveté alters the balance of consumptive and non-consumptive predator effects and shapes trophic cascades in freshwater plankton
<p><span>Predators drive trophic cascades by reducing prey biomass and altering prey traits, selecting for prey that exhibit constitutive and induced anti-predator defenses that decrease susceptibility to consumption. These defense traits are often costly, generating a tradeoff between consumptive (CEs) and non-consumptive predator effects (NCEs). The ecological and evolutionary experience that prey share with a given predator may determine their position along this tradeoff curve, affecting the nature and strength of top-down control of ecosystems. Conceptual models predict that predator-experienced prey suffer greater NCEs than predator-naive prey, which suffer stronger CEs and total predator effects (CEs + NCEs), but this has not been tested in diverse prey communities. We tested these predictions by comparing the effects of predation (CEs + NCEs) and predation risk (NCEs only) of planktivorous fish on food web structure in pond mesocosms with diverse natural communities of either predator-naive or predator-experienced zooplankton. Contrary to expectations, top-down control of zooplankton and phytoplankton biomass was strengthened by prey community experience: in systems with experienced relative to naive zooplankton communities both predation risk (NCEs only) and predation (CEs + NCEs) had stronger effects on zooplankton prey biomass and trophic cascades were twice as strong. These results show that the ecological and evolutionary experience of diverse prey communities alters the balance of consumptive and non-consumptive predator effects and influences trophic cascade strength.</span></p>
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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.