General description of Experiment and Projects: Hurricanes are important drivers of periodic disturbances on tropical forests of the Luquillo Mountauns. The immediate impact of this disturbance is on the canopy biomass which is redistributed from the canopy compartments to the detrital pool of the forest floor hence creating a wide opened canopy. The Canopy Trimming Experiment (CTE) is a long-term experiment designed for two purposes: 1) to decouple the effect of canopy disturbance (e.g., increasing light levels, temperature, moisture, etc.) from those of increased detrital inputs on rates of germination, growth, survival, detritus processing, nutrient cycling, soil conditions, and trophic structure, and 2) to increase the frequency of simulated hurricane effects above background levels to once every six to ten years. Climate change models predict increased frequency and intensity of Caribbean hurricanes (Emmanuel 1987, Goldenberg et al. 2001), and the goal is to evaluate predictions regarding the effects of an increased rate of hurricane disturbance on tabonuco forest (Sanford et al. 1991). The interaction of biotic and abiotic processes, all modified by the disturbance, are key in determining ecosystem responses because they regulate critical ecosystem fluxes and storage associated with detritus decomposition. These processes define detrital dynamics and play a central role in the recovery of forest structure and function after disturbance. Therefore, a third component of this experiment was to implement a series of short-term biotic manipulations nested within the large-scale CTE design, consisting on faunal manipulations to measure the strength of interactions between autotrophic and detrital food webs in the context of hurricane-associated disturbance, which allowed to asses the important components of the foodwebs. The overall hypothesis is as follow: Short-term dynamics of key response variables after disturbance will be a function of the interaction between microclimate and detrital inputs, whereas long-term dynamics (particularly of SOM and NPP) will be a function of detrital inputs.
Canopy Trimming experiment, Litterfall, DNA, DBH, Depth Breast Height, Soil Trace gases, Litter decomposition
XML is in ISO-19115 geographic metadata format, compatible with ESRI Geoportal Server.
Citation for This Dataset
Cantrell, Sharon; Gonzalez, Grizelle; Lodge, D. Jean; McDowell, William H.; Richardson, Barbara A.; Sharpe, Joanne M.; Shiels, Aaron; Schowalter, Timothy D.; Silver, Whendee; Willig, Michael R. Canopy Trimming Experiment (CTE) 2015.
Citation for This Webpage
Cantrell, Sharon; Gonzalez, Grizelle; Lodge, D. Jean; McDowell, William H.; Richardson, Barbara A.; Sharpe, Joanne M.; Shiels, Aaron; Schowalter, Timothy D.; Silver, Whendee; Willig, Michael R. (2016). "CZO Dataset: Quebrada Prieta, El Verde - Vegetation, Soil Gas, Soil Moisture (2003-2016) - Canopy Trimming Experiment." Retrieved 06 Dec 2019, from http://criticalzone.org/national/data/dataset/5751/
Data Use Policy
1. Use our data freely. All CZO Data Products* except those labelled Private** are released to the public and may be freely copied, distributed, edited, remixed, and built upon under the condition that you give acknowledgement as described below. Non-CZO data products — like those produced by USGS or NOAA — have their own use policies, which should be followed.
2. Give proper citation and acknowledgement. Publications, models and data products that make use of these datasets must include proper citation and acknowledgement. Most importantly, provide a citation in a similar way as a journal article (i.e. author, title, year of publication, name of CZO “publisher”, edition or version, and URL or DOI access information. See http://www.datacite.org/whycitedata). Also include at least a brief acknowledgement such as: “Data were provided by the NSF-supported Southern Sierra Critical Zone Observatory” (replace with the appropriate observatory name).
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**Private. Most private data will be released to the public within 1-2 years, with some exceptionally challenging datasets up to 4 years. To inquire about potential earlier use, please contact us.
Data Sharing Policy
All CZO investigators and collaborators who receive material or logistical support from a CZO agree to:
1. Share data privately within 1 year. CZO investigators and collaborators agree to provide CZO Data Products* — including data files and metadata for raw, quality controlled and/or derived data — to CZO data managers within one year of collection of samples, in situ or experimental data. By default, data values will be held in a Private CZO Repository**, but metadata will be made public and will provide full attribution to the Dataset Creators†.
2. Release data to public within 2 years. CZO Dataset Creators will be encouraged after one year to release data for public access. Dataset Creators may chose to publish or release data sooner.
3. Request, in writing, data privacy up to 4 years. CZO PIs will review short written applications to extend data privacy beyond 2 years and up to 4 years from time of collection. Extensions beyond 3 years should not be the norm, and will be granted only for compelling cases.
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* CZO Data Products. Defined as data collected with any monetary or logistical support from a CZO. Logistical support includes the use of any CZO sensors, sampling infrastructure, equipment, vehicles, or labor from a supported investigator, student or staff person. CZO Data Products can acknowledge multiple additional sources of support.
** Private CZO Repository. Defined as a password-protected directory on each CZO’s data server. Files will be accessible by all investigators and collaborators within the given CZO and logins will be maintained by that local CZO’s data managers. Although data values will not be accessible by the public or ingested into any central data system (i.e. CUAHSI HIS), metadata will be fully discoverable by the public. This provides the dual benefit of giving attribution and credit to dataset creators and the CZO in general, while maintaining protection of intellectual property while publications are pending.
† Dataset Creators. Defined as the people who are responsible for designing, collecting, analyzing and providing quality assurance for a dataset. The creators of a dataset are analogous to the authors of a publication, and datasets should be cited in an analogous manner following the emerging international guidelines described at http://www.datacite.org/whycitedata.