http://lod.bco-dmo.org/id/dataset/891670
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2023-03-09
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Landscape parameters of seagrass, fish and macroinvertebrate communities within Artificial Seagrass Units (ASU) in Back Sound, NC from July to September 2018
2023-03-27
publication
2023-03-27
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2023-03-28
publication
https://doi.org/10.26008/1912/bco-dmo.891670.1
F. Joel Fodrie
University of North Carolina at Chapel Hill
principalInvestigator
Lauren Yeager
University of Texas - Marine Science Institute
principalInvestigator
Cori Lopazanski
University of North Carolina at Chapel Hill
principalInvestigator
Abigail K. Poray
University of North Carolina at Chapel Hill
principalInvestigator
Amy Yarnall
University of North Carolina at Chapel Hill
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Yarnall, A., Fodrie, F. J., Lopazanski, C., Poray, A. K., Yeager, L. (2023) Landscape parameters of seagrass, fish and macroinvertebrate communities within Artificial Seagrass Units (ASU) in Back Sound, NC from July to September 2018. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2023-03-27 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.891670.1 [access date]
Methods and Sampling: <p><span style="font-size:14px"><span style="font-family:arial,helvetica,sans-serif">To examine fragmentation components independently and interactively, we conducted this study on Oscar Shoal and an adjacent unnamed shoal in Back Sound, NC, USA (34°42′20" N to 34°41′60" N, 76°36′ 15" W to 76°35′17" W) during the summer of 2018. Both shoals were shallow (less than 0.5-meter depth at low tide) and historically supported expansive, ephemeral seagrass meadows (Peterson et al., 2001) that have been absent over the last decade. During 2018, these shoals had large expanses of sandy area speckled with small patches of seagrass (which were avoided during landscape siting) composed of a mixture of eelgrass, <em>Zostera marina </em>(Linnaeus 1753), and shoal grass, <em>Halodule wrightii</em> (Ascherson 1868) (Yeager et al., 2016). Both shoals were adjacent to deep boating channels between two large salt marsh complexes to the north (North River Marsh) and south (Middle Marsh).<br />
<br />
We generated 25 unique 18-meters × 13-meters (234 square meter) landscapes along orthogonal axes of percent cover of seagrass within the landscape footprint (10 percent, 22.5 percent, 35 percent, 47.5 percent, and 60 percent) and fragmentation <em>per se</em> (i.e., percolation probability: 0.1, 0.225, 0.35, 0.475, 0.59). Blueprints for landscape construction in the field were generated by a modified random cluster (MRC) method (Saura and Martinez-Millan, 2000) using the <em>randomHabitat</em> function in the <em>secr</em> package in R (Efford, 2016). In using the MRC method, landscapes of low percolation probability exhibit low connectivity from one ASU to the next (i.e., are highly fragmented), which approaches a lower limit of realistic landscape fragmentation at percolation probability = 0.1 (Saura and Martinez-Millan, 2000). Additionally, patch cohesion is maximized (i.e., landscapes are contiguous) when percent cover reaches approximately 60 percent and percolation probability approaches approximately 0.59 (Saura and Martinez-Millan, 2000). Therefore, we chose 60 percent cover and percolation probability <em>= </em>0.59 as the upper limits of our landscape parameters, and 10 percent cover and percolation probability <em>= </em>0.1 as the lower limits. We also note that the generated landscapes fell within the range of the number of patches (approximately 1-15 patches) observed within natural, low seagrass area landscapes (approximately 250-375 square meters) in our system (Yeager et al., 2016). For simplicity, landscape parameters will be hereafter described in the context of percent cover and fragmentation <em>per se</em> (i.e., low percolation probability is high fragmentation <em>per se</em>). Landscapes were constrained to fall within 2 percent of the area input parameter and maintain consistent edge-to-area ratios within individual fragmentation <em>per se</em> treatment levels (<em>secr</em> package in R; Efford, 2016). Within an individual landscape defined by more than 1 seagrass patch, discrete patches of artificial seagrass were separated from one another by a minimum of 0.86-meter (short-side length of an ASU) of sandy matrix in all directions.</span></span></p>
<p><span style="font-size:14px"><span style="font-family:arial,helvetica,sans-serif">Each landscape contained 22 to 135 ASUs (total ASUs constructed = 2059) constructed to mimic shoot density, shoot width, and canopy height of <em>Zostera marina </em>meadows in this system (Yeager et al., 2016). For each ASU, 30-centimeter (cm) lengths of green splendorette curling ribbon (0.5-cm width) were tied to approximately 1-square meter bases of rigid black plastic VEXAR (0.86-meter x 1.2-meter, 2.5-centimeter) mesh so that each ASU had uniformly spaced "shoots" (450 square meters) with two 15-centimeter length "leaves". Each ASU required approximately 3 hours to construct, with the entire manufacturing effort requiring the equivalent of three full-time person work years (with work divided among a number of technicians and community volunteers).&nbsp;</span></span></p>
<p><span style="font-size:14px"><span style="font-family:arial,helvetica,sans-serif">Twenty-five ASU landscapes were deployed over the course of 10 days (21-May to 31-May 2018) in haphazard order and placement: 19 were located on Oscar Shoal and the remaining 6 were located on the adjacent, unnamed shoal. All landscapes were more than 50 meters apart from each other and greater than 30 meters from natural seagrass patches. Individual ASUs were secured to the sediment surface and each other with lawn staples (16 per ASU) and zip ties (0-4 per ASU, based on the presence/absence of adjacent ASUs), respectively. The site with 60 percent cover and 0.59 percolation probability (i.e., "60 percent-0.59"; hereafter sites will be named by this convention), was replicated (on 8-Jun 2018) as a 26<sup>th</sup> landscape to evaluate potential differences in ecological response metrics influenced by the identity of the two shoal environments.</span></span></p>
<p><span style="font-size:14px"><span style="font-family:arial,helvetica,sans-serif"><em>Hurricane Florence</em><br />
The study area and artificial landscapes were directly impacted by Hurricane Florence during 13-16 Sept 2018. Despite ASU re-enforcements made prior to Florence's landfall (i.e., additional lawn staples and cable ties), our landscapes experienced substantial disturbance akin to natural seagrasses in the vicinity, in many cases completely removing or burying ASUs which altered the landscape percent cover and fragmentation <em>per se</em> parameters. Because of this substantial disturbance, we opportunistically examined how our landscapes were altered by Hurricane Florence as a proxy for how extreme storm events may alter natural seagrass meadows. We recalculated landscape parameters based on ASU-by-ASU checks made after Hurricane Florence. Post-Florence landscape percent cover and percolation probabilities were recalculated both including and excluding ASUs that were fully buried under sediment. Within natural habitats, depending on sedimentation intensity, seagrass burial may represent temporary or permanent habitat loss (Cabaço et al., 2008). Holding the original landscape 234-square meter footprint constant, the percent cover of each landscape was recalculated from the remaining number of ASUs (including and excluding buried ASUs). Percolation probability is a fragmentation <em>per se</em> input parameter for landscape generation (Saura and Martinez-Millan, 2000) but is not generally used to describe existing or natural landscapes. Therefore, to determine how landscape fragmentation <em>per se</em> was altered, we first determined the linear relationship between the initial number of seagrass patches and our percolation probability treatments (<em>y </em>= 0.61 – 0.06<em>x</em>, <em>r<sup>2</sup></em> = 0.912). We then used this relationship to predict post-Florence landscape percolation probabilities from the remaining number of patches in each landscape (including and excluding buried ASUs).</span></span></p>
<p><span style="font-size:14px"><span style="font-family:arial,helvetica,sans-serif"><strong>Known Issues:</strong><br />
See Hurricane Florence section in methods. Some landscapes were completely removed or buried and landscape parameters are denoted with 0 or NA.</span></span></p>
<p>&nbsp;</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1635950 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1635950
completed
F. Joel Fodrie
University of North Carolina at Chapel Hill
252-726-6841
Institute of Marine Sciences & Department of Marine Sciences 3431 Arendell Street
Morehead City
NC
28557
USA
jfodrie@unc.edu
pointOfContact
Lauren Yeager
University of Texas - Marine Science Institute
750 Channel View Dr
Port Aransas
TX
78373
US
laurenayeager@gmail.com
pointOfContact
Cori Lopazanski
University of North Carolina at Chapel Hill
Bren School of Environmental Science & Management, University of California Santa Barbara
Santa Barbara
CA
USA
cori.lopazanski@gmail.com
pointOfContact
Abigail K. Poray
University of North Carolina at Chapel Hill
Institute of Marine Sciences & Department of Marine Sciences 3431 Arendell Street
Morehead City
NC
28557
USA
ab.poray@gmail.com
pointOfContact
Amy Yarnall
University of North Carolina at Chapel Hill
(601) 634-3772
Engineer Research Development Center, USACE 3909 Halls Ferry Rd.
Vicksburg
MS
39180
USA
amyhyarnall@gmail.com
pointOfContact
asNeeded
Dataset Version: 1
Unknown
Site_ID
Latitude
Longitude
Per_cov
Frag
Landscape_timeperiod
Buried_ASUs
Actual_cover
Actual_Frag
Total_area
N_patches
landscape.shape.index
largest.patch.index
perim.area.ratio
frac.dim.index
patch.cohesion.index
Ohaus H-5276
theme
None, User defined
Site_ID
latitude
longitude
percent coverage
site description
comments
surface_area
count
area_measured
No BCO-DMO term
featureType
BCO-DMO Standard Parameters
scale or balance
instrument
BCO-DMO Standard Instruments
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
Collaborative Research: Habitat fragmentation effects on fish diversity at landscape scales: experimental tests of multiple mechanisms
https://osprey.bco-dmo.org/project/714026
Collaborative Research: Habitat fragmentation effects on fish diversity at landscape scales: experimental tests of multiple mechanisms
<p>Amount and quality of habitat is thought to be of fundamental importance to maintaining coastal marine ecosystems. This research will use large-scale field experiments to help understand how and why fish populations respond to fragmentation of seagrass habitats. The question is complex because increased fragmentation in seagrass beds decreases the amount and also the configuration of the habitat (one patch splits into many, patches become further apart, the amount of edge increases, etc). Previous work by the investigators in natural seagrass meadows provided evidence that fragmentation interacts with amount of habitat to influence the community dynamics of fishes in coastal marine landscapes. Specifically, fragmentation had no effect when the habitat was large, but had a negative effect when habitat was smaller. In this study, the investigators will build artificial seagrass habitat to use in a series of manipulative field experiments at an ambitious scale. The results will provide new, more specific information about how coastal fish community dynamics are affected by changes in overall amount and fragmentation of seagrass habitat, in concert with factors such as disturbance, larval dispersal, and wave energy. The project will support two early-career investigators, inform habitat conservation strategies for coastal management, and provide training opportunities for graduate and undergraduate students. The investigators plan to target students from underrepresented groups for the research opportunities.</p>
<p>Building on previous research in seagrass environments, this research will conduct a series of field experiments approach at novel, yet relevant scales, to test how habitat area and fragmentation affect fish diversity and productivity. Specifically, 15 by 15-m seagrass beds will be created using artificial seagrass units (ASUs) that control for within-patch-level (~1-10 m2) factors such as shoot density and length. The investigators will employ ASUs to manipulate total habitat area and the degree of fragmentation within seagrass beds in a temperate estuary in North Carolina. In year one, response of the fishes that colonize these landscapes will be measured as abundance, biomass, community structure, as well as taxonomic and functional diversity. Targeted ASU removals will then follow to determine species-specific responses to habitat disturbance. In year two, the landscape array and sampling regime will be doubled, and half of the landscapes will be seeded with post-larval fish of low dispersal ability to test whether pre- or post-recruitment processes drive landscape-scale patterns. In year three, the role of wave exposure (a natural driver of seagrass fragmentation) in mediating fish community response to landscape configuration will be tested by deploying ASU meadows across low and high energy environments.</p>
Habitat Fragmentation
largerWorkCitation
project
eng; USA
biota
oceans
-76.603
-76.589
34.701
34.707
2018-07-03
2018-09-03
North Carolina
0
BCO-DMO catalogue of parameters from Landscape parameters of seagrass, fish and macroinvertebrate communities within Artificial Seagrass Units (ASU) in Back Sound, NC from July to September 2018
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/892043.rdf
Name: Site_ID
Units: unitless
Description: <p>Artificial seagrass unit (ASU) landscape name (Percent cover value-Percolation probability value)</p>
http://lod.bco-dmo.org/id/dataset-parameter/892044.rdf
Name: Latitude
Units: decimal degrees
Description: <p>Latitude North (South is negative) of sampling site</p>
http://lod.bco-dmo.org/id/dataset-parameter/892045.rdf
Name: Longitude
Units: decimal degrees
Description: <p>Longitude East (West is negative) of sampling site</p>
http://lod.bco-dmo.org/id/dataset-parameter/892046.rdf
Name: Per_cov
Units: percent (%)
Description: <p>Percent cover treatment of ASUs in 234 square meter landscape footprint (10, 22.5, 35, 47.5, 60)</p>
http://lod.bco-dmo.org/id/dataset-parameter/892047.rdf
Name: Frag
Units: unitless
Description: <p>ASU landscape fragmentation per se treatment indexed by percolation probability (0.1, 0.225, 0.35, 0.475, 0.59)</p>
http://lod.bco-dmo.org/id/dataset-parameter/892048.rdf
Name: Landscape_timeperiod
Units: unitless
Description: <p>Original landscape design parameters or Post-Hurricane Florence re-calculated landscape parameters?</p>
http://lod.bco-dmo.org/id/dataset-parameter/892049.rdf
Name: Buried_ASUs
Units: unitless
Description: <p>Are buried ASUs included or excluded from post-Florence landscape parameter calculations?</p>
http://lod.bco-dmo.org/id/dataset-parameter/892050.rdf
Name: Actual_cover
Units: percent (%)
Description: <p>True percent cover of landscape (may not exactly match the treatment level)</p>
http://lod.bco-dmo.org/id/dataset-parameter/892051.rdf
Name: Actual_Frag
Units: unitless
Description: <p>True percolation probability of landscape (may not exactly match the treatment level)</p>
http://lod.bco-dmo.org/id/dataset-parameter/892052.rdf
Name: Total_area
Units: square meters (m^2)
Description: <p>Total area of ASUs</p>
http://lod.bco-dmo.org/id/dataset-parameter/892053.rdf
Name: N_patches
Units: unitless
Description: <p>Number of ASU patches</p>
http://lod.bco-dmo.org/id/dataset-parameter/892054.rdf
Name: landscape.shape.index
Units: unitless
Description: <p>Total landscape perimeter (meters), divided by the square root of the total landscape area (square meters), adjusted by a constant for a circular standard (vector) or square standard (raster)</p>
http://lod.bco-dmo.org/id/dataset-parameter/892055.rdf
Name: largest.patch.index
Units: percent (%)
Description: <p>The percentage of the landscape comprised by the largest patch</p>
http://lod.bco-dmo.org/id/dataset-parameter/892056.rdf
Name: perim.area.ratio
Units: (m^-1)
Description: <p>Total landscape perimeter (meters) divided by the total landscape area (square meters)</p>
http://lod.bco-dmo.org/id/dataset-parameter/892057.rdf
Name: frac.dim.index
Units: unitless
Description: <p>The sum of 2 times the logarithm of patch perimeter (meters) divided by the logarithm of patch area (square meters) for each patch in the landscape, divided by the number of patches; the raster formula is adjusted to correct for the bias in perimeter</p>
http://lod.bco-dmo.org/id/dataset-parameter/892058.rdf
Name: patch.cohesion.index
Units: unitless
Description: <p>Characterises the connectedness of patches. It can be used to asses if patches are located aggregated or rather isolated</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
8247
https://darchive.mblwhoilibrary.org/server/api/core/bitstreams/20384094-06cf-49c9-86ff-5d126f4fd45c/content
download
https://doi.org/10.26008/1912/bco-dmo.891670.1
download
onLine
dataset
<p><span style="font-size:14px"><span style="font-family:arial,helvetica,sans-serif">To examine fragmentation components independently and interactively, we conducted this study on Oscar Shoal and an adjacent unnamed shoal in Back Sound, NC, USA (34°42′20" N to 34°41′60" N, 76°36′ 15" W to 76°35′17" W) during the summer of 2018. Both shoals were shallow (less than 0.5-meter depth at low tide) and historically supported expansive, ephemeral seagrass meadows (Peterson et al., 2001) that have been absent over the last decade. During 2018, these shoals had large expanses of sandy area speckled with small patches of seagrass (which were avoided during landscape siting) composed of a mixture of eelgrass, <em>Zostera marina </em>(Linnaeus 1753), and shoal grass, <em>Halodule wrightii</em> (Ascherson 1868) (Yeager et al., 2016). Both shoals were adjacent to deep boating channels between two large salt marsh complexes to the north (North River Marsh) and south (Middle Marsh).<br />
<br />
We generated 25 unique 18-meters × 13-meters (234 square meter) landscapes along orthogonal axes of percent cover of seagrass within the landscape footprint (10 percent, 22.5 percent, 35 percent, 47.5 percent, and 60 percent) and fragmentation <em>per se</em> (i.e., percolation probability: 0.1, 0.225, 0.35, 0.475, 0.59). Blueprints for landscape construction in the field were generated by a modified random cluster (MRC) method (Saura and Martinez-Millan, 2000) using the <em>randomHabitat</em> function in the <em>secr</em> package in R (Efford, 2016). In using the MRC method, landscapes of low percolation probability exhibit low connectivity from one ASU to the next (i.e., are highly fragmented), which approaches a lower limit of realistic landscape fragmentation at percolation probability = 0.1 (Saura and Martinez-Millan, 2000). Additionally, patch cohesion is maximized (i.e., landscapes are contiguous) when percent cover reaches approximately 60 percent and percolation probability approaches approximately 0.59 (Saura and Martinez-Millan, 2000). Therefore, we chose 60 percent cover and percolation probability <em>= </em>0.59 as the upper limits of our landscape parameters, and 10 percent cover and percolation probability <em>= </em>0.1 as the lower limits. We also note that the generated landscapes fell within the range of the number of patches (approximately 1-15 patches) observed within natural, low seagrass area landscapes (approximately 250-375 square meters) in our system (Yeager et al., 2016). For simplicity, landscape parameters will be hereafter described in the context of percent cover and fragmentation <em>per se</em> (i.e., low percolation probability is high fragmentation <em>per se</em>). Landscapes were constrained to fall within 2 percent of the area input parameter and maintain consistent edge-to-area ratios within individual fragmentation <em>per se</em> treatment levels (<em>secr</em> package in R; Efford, 2016). Within an individual landscape defined by more than 1 seagrass patch, discrete patches of artificial seagrass were separated from one another by a minimum of 0.86-meter (short-side length of an ASU) of sandy matrix in all directions.</span></span></p>
<p><span style="font-size:14px"><span style="font-family:arial,helvetica,sans-serif">Each landscape contained 22 to 135 ASUs (total ASUs constructed = 2059) constructed to mimic shoot density, shoot width, and canopy height of <em>Zostera marina </em>meadows in this system (Yeager et al., 2016). For each ASU, 30-centimeter (cm) lengths of green splendorette curling ribbon (0.5-cm width) were tied to approximately 1-square meter bases of rigid black plastic VEXAR (0.86-meter x 1.2-meter, 2.5-centimeter) mesh so that each ASU had uniformly spaced "shoots" (450 square meters) with two 15-centimeter length "leaves". Each ASU required approximately 3 hours to construct, with the entire manufacturing effort requiring the equivalent of three full-time person work years (with work divided among a number of technicians and community volunteers).&nbsp;</span></span></p>
<p><span style="font-size:14px"><span style="font-family:arial,helvetica,sans-serif">Twenty-five ASU landscapes were deployed over the course of 10 days (21-May to 31-May 2018) in haphazard order and placement: 19 were located on Oscar Shoal and the remaining 6 were located on the adjacent, unnamed shoal. All landscapes were more than 50 meters apart from each other and greater than 30 meters from natural seagrass patches. Individual ASUs were secured to the sediment surface and each other with lawn staples (16 per ASU) and zip ties (0-4 per ASU, based on the presence/absence of adjacent ASUs), respectively. The site with 60 percent cover and 0.59 percolation probability (i.e., "60 percent-0.59"; hereafter sites will be named by this convention), was replicated (on 8-Jun 2018) as a 26<sup>th</sup> landscape to evaluate potential differences in ecological response metrics influenced by the identity of the two shoal environments.</span></span></p>
<p><span style="font-size:14px"><span style="font-family:arial,helvetica,sans-serif"><em>Hurricane Florence</em><br />
The study area and artificial landscapes were directly impacted by Hurricane Florence during 13-16 Sept 2018. Despite ASU re-enforcements made prior to Florence's landfall (i.e., additional lawn staples and cable ties), our landscapes experienced substantial disturbance akin to natural seagrasses in the vicinity, in many cases completely removing or burying ASUs which altered the landscape percent cover and fragmentation <em>per se</em> parameters. Because of this substantial disturbance, we opportunistically examined how our landscapes were altered by Hurricane Florence as a proxy for how extreme storm events may alter natural seagrass meadows. We recalculated landscape parameters based on ASU-by-ASU checks made after Hurricane Florence. Post-Florence landscape percent cover and percolation probabilities were recalculated both including and excluding ASUs that were fully buried under sediment. Within natural habitats, depending on sedimentation intensity, seagrass burial may represent temporary or permanent habitat loss (Cabaço et al., 2008). Holding the original landscape 234-square meter footprint constant, the percent cover of each landscape was recalculated from the remaining number of ASUs (including and excluding buried ASUs). Percolation probability is a fragmentation <em>per se</em> input parameter for landscape generation (Saura and Martinez-Millan, 2000) but is not generally used to describe existing or natural landscapes. Therefore, to determine how landscape fragmentation <em>per se</em> was altered, we first determined the linear relationship between the initial number of seagrass patches and our percolation probability treatments (<em>y </em>= 0.61 – 0.06<em>x</em>, <em>r<sup>2</sup></em> = 0.912). We then used this relationship to predict post-Florence landscape percolation probabilities from the remaining number of patches in each landscape (including and excluding buried ASUs).</span></span></p>
<p><span style="font-size:14px"><span style="font-family:arial,helvetica,sans-serif"><strong>Known Issues:</strong><br />
See Hurricane Florence section in methods. Some landscapes were completely removed or buried and landscape parameters are denoted with 0 or NA.</span></span></p>
<p>&nbsp;</p>
Specified by the Principal Investigator(s)
<p>Blueprints for landscape construction in the field were generated by a modified random cluster (MRC) method (Saura and Martinez-Millan, 2000) using the <em>randomHabitat</em> function in the <em>secr</em> package in R (Efford, 2016) and landscapes were constrained to fall within 2 percent of the area input parameter and maintain consistent edge-to-area ratios within individual fragmentation <em>per se</em> treatment levels (<em>secr</em> package in R; Efford, 2016).</p>
<p>All data were entered electronically into an Excel spreadsheet.</p>
<p><strong>BCO-DMO Processing Description:</strong><br />
- Missing data identifier ‘NA’ replaced with blank (BCO-DMO's default missing data identifier)<br />
<span style="background-color:transparent; color:rgb(0, 0, 0)">- Added "Latitude" and "Longitude" columns and rounded to three decimal places<br />
- Rounded columns "Actual_cover", "landscape_shape_index", "largest_patch_index", "perim_area_ratio", "frac_dim_index", "patch_cohexion_index" to 3 decimal places<br />
- Removed "%" symbol in data cells</span></p>
Specified by the Principal Investigator(s)
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
Ohaus H-5276
Ohaus H-5276
PI Supplied Instrument Name: Ohaus H-5276 Instrument Name: scale or balance Instrument Short Name: Instrument Description: Devices that determine the mass or weight of a sample. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/LAB13/