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Land reclamation associated with natural gas development has become increasingly important to mitigate land surface disturbance in western North America. Since well pads occur on sites with multiple land use and ownership, the progress and outcomes of these efforts are of interest to multiple stakeholders including industry, practitioners and consultants, regulatory agents, private landowners and the scientific community. Reclamation success criteria often vary within, and among, government agencies and across land ownership type. Typically, reclamation success of a well pad is judged by comparing vegetation cover from a single transect on the pad to a single transect in an adjacent reference site and data are collected by a large number of technicians with various field monitoring skills. We utilized ‘SamplePoint’ image analysis software and a spatially balanced sampling design, called balanced acceptance sampling, to demonstrate how spatially‐explicit quantitative data can be used to determine if sites are meeting various reclamation success criteria and use chi‐square tests to show how sites in vegetation percent cover differ from a statistical standpoint. This method collects field data faster than traditional methods. We demonstrate how quantitative and spatially‐explicit data can be utilized by multiple stakeholders, how it can improve upon current reference site selection, how it can satisfy reclamation monitoring requirements for multiple regulatory agencies, how it may help improve future seed mix selection, and discuss how it may reduce costs for operations responsible for reclamation and how it may reduce observer bias. This article is protected by copyright. All rights reserved.
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Spatially balanced sampling and ground-level imagery
for vegetation monitoring on reclaimed well pads
Michael F. Curran1,2,3,4 , Samuel E. Cox5, Timothy J. Robinson6, Blair L. Robertson7,
Karen J. Rogers8, Zoe A. Sherman9, Todd A. Adams10, Calvin F. Strom1, Peter D. Stahl1,2,3
Land reclamation associated with natural gas development has become increasingly important to mitigate land surface
disturbance in western North America. Since well pads occur on sites with multiple land use and ownership, the progress
and outcomes of these efforts are of interest to multiple stakeholders including industry, practitioners and consultants,
regulatory agents, private landowners, and the scientic community. Reclamation success criteria often vary within, and
among, government agencies and across land ownership type. Typically, reclamation success of a well pad is judged by
comparing vegetation cover from a single transect on the pad to a single transect in an adjacent reference site and data are
collected by a large number of technicians with various eld monitoring skills. We utilized “SamplePoint” image analysis
software and a spatially balanced sampling design, called balanced acceptance sampling, to demonstrate how spatially explicit
quantitative data can be used to determine if sites are meeting various reclamation success criteria and used chi-square tests
to show how sites in vegetation percent cover differ from a statistical standpoint. This method collects eld data faster than
traditional methods. We demonstrate how quantitative and spatially explicit data can be utilized by multiple stakeholders,
how it can improve upon current reference site selection, how it can satisfy reclamation monitoring requirements for multiple
regulatory agencies, how it may help improve future seed mix selection, and discuss how it may reduce costs for operations
responsible for reclamation and how it may reduce observer bias.
Key words: balanced acceptance sampling, chi-square, multiple land use, reclamation success, reference site, SamplePoint,
Implications for Practice
Reclamation monitoring associated with natural resource
development involves many stakeholders and providing
standard monitoring protocol to satisfy a variety of needs,
such as delivering useful information to regulatory agen-
cies and data to improve future reclamation practices,
should be strived for.
Many technicians are necessary to conduct vegetation
monitoring of reclaimed sites associated with natural
resource development, providing techniques which are
rapid and which may reduce observer bias which is critical
to obtain meaningful data.
As GPS and camera technologies continue to advance
and become more accessible, incorporating them into
monitoring programs are likely to improve data reliability
and reduce costs for operators responsible for acquiring
eld data.
Natural gas development in western North America has resulted
in various forms of environmental degradation (Finn & Knick
2011). Land reclamation ensures land surface disturbances do
not have long-term negative impacts (Wortley et al. 2013).
Aside from assisting environmental recovery, reclamation may
have legal implications, and denitions of successful reclama-
tion may vary among a wide range of stakeholders (Zedler
2007). In Wyoming, reclaimed well pads are compared to
adjacent reference areas and subject to various regulatory
Author contributions: MFC, SEC, BLR, TAA, CFS, PDS conceived and designed
research; MFC, ZAS collected eld data; MFC, TJR analyzed data and statistics;
MFC, KJR analyzed data and policies; MFC wrote rst draft; all authors edited
subsequent drafts of manuscript.
1Wyoming Reclamation and Restoration Center, University of Wyoming, 1000 E.
University Avenue, Department 3354, Laramie, WY 82071, U.S.A.
2Department of Ecosystem Science and Management, University of Wyoming, 1000
E. University Avenue, Department 3354, Laramie, WY 82071, U.S.A.
3Program in Ecology, University of Wyoming, 1000 E. University Avenue, Berry
Center 231, Laramie, WY 82071, U.S.A.
4Address correspondence to M. F. Curran, email
5Bureau of Land Management, Wyoming State Ofce, 5353 Yellowstone Road,
Cheyenne, WY 82009, U.S.A.
6Department of Statistics, University of Wyoming, 1000 E. University Avenue, Depart-
ment 3332, Laramie, WY 82071, U.S.A.
7School of Mathematics and Statistics, University of Canterbury, Private Bag 4800,
Christchurch, 8140, New Zealand
8Wyoming Game and Fish Department, 5400 Bishop Boulevard, Cheyenne, WY
82006, U.S.A.
9School of Energy Resources, University of Wyoming, 1000 E. University Avenue,
Department 3012, Laramie, WY 82071, U.S.A.
10Environmental Field Technician Services, 85 Meadow Plains Road, Laramie, WY
82070, U.S.A.
© 2019 Society for Ecological Restoration
doi: 10.1111/rec.12956
Supporting information at:
Restoration Ecology 1
Vegetation monitoring on reclaimed well pads
criteria from Bureau of Land Management (BLM) local eld
ofce, inter-agency ofces or the Wyoming Department of
Environmental Quality’s (WYDEQ) Storm Water Pollution
Prevention Plan (SWPPP), and by the State of Wyoming’s
Sage-grouse Executive Order (SGEO) habitat suitability crite-
ria to evaluate management efforts for a species of concern such
as the Greater Sage-grouse (Centrocercus urophasianus). Moni-
toring plans are therefore often narrowly tailored to comply with
specic local or agency policies, and lack species-specic infor-
mation (Curran & Stahl 2015). This focus may limit advance-
ment of scientic knowledge, understanding of environmental
issues, and may result in operators investing money in unproven
management practices such as seeding reclamation areas with
poor seed mixes (Lovett et al. 2007). Developing an integrated
monitoring program, having distinct monitoring objectives and
improved decision-making capabilities for multiple stakehold-
ers, will likely increase the value of collected data (e.g. Toevs
et al. 2011).
Monitoring metrics often vary based on regulatory criteria.
Monitoring timing and methods can vary among eld tech-
nicians and are often inconsistent over time (Curran & Stahl
2015). Well pads undergoing reclamation have been monitored
using Daubenmire frames (Daubenmire 1959), ocular estimates,
and line point intercept (LPI) methods (Coulloudon et al. 1999)
to compare a reclaimed site area to an adjacent reference site.
Due to the large amount of natural resource development in
western United States, many technicians with various capa-
bilities are conducting vegetation monitoring. Both Dauben-
mire frame methods and ocular estimates are vulnerable to high
observer bias (Kennedy & Addison 1987; Bergstedt et al. 2009;
Morrison 2016). A typical quantitative method to measure veg-
etation cover on a reclaimed well pad versus a reference site is
to place a single transect in each area and conduct quantitative
analyses using the LPI technique (Curran & Stahl 2015). Several
pitfalls exist with a single transect comparison. First, transect
data spatial information may be suspect, even when transects are
permanently marked, because there is no location-verication
mechanism to ensure the data recorded on a page actually
came from the intended transect. We have seen many examples
of user-error resulting in mislabeled transect data, a mistake
impossible to rectify since there exists no independent spatial
information. Where temporal transect data change dramatically
and abruptly, a mislabeled transect is often suspected, leav-
ing managers wondering how to proceed. Second, LPI methods
are time and labor intensive, making them expensive for large
projects (West 1999). Due to LPI time requirements, pheno-
logical changes in some species may result in misidentica-
tion or underestimation (Cagney et al. 2011). Third, LPI may
overestimate standing cover in rangeland ecosystems (Cook &
Stubbendieck 1986). Fourth, since most reclaimed well pads are
drill seeded in rows, a linear primary sampling frame with sys-
tematic secondary samples (e.g. a point read every 50 cm along
a 100 m transect) inadequately estimates population variance
(Thompson 2002). Fifth, despite multiple observations along a
transect, it is still a single primary sampling unit from which
population variance cannot be estimated, thus limiting statis-
tical inference. Sixth, a single reference transect is unlikely
to capture variability of the reference ecosystem (Ruiz-Jaen &
Aide 2005) or the variability of the reclaimed area itself if spatial
heterogeneity exists (Stevens & Olsen 2004). Seventh, dramatic
temporal changes in vegetation may be due to user bias or vari-
ation in plant identication skill rather than actual changes in
vegetation, yet these biases cannot be detected or conrmed.
Finally, traditional techniques often rely on technician opinion
for transect placement, adding an additional source of observer
bias and eliminating a crucial stochastic component of sampling
Alternative methods, such as image-based sampling, have
been shown to reduce monitoring costs and time while increas-
ing statistical power and reducing observer bias (Cagney et al.
2011; Duniway et al. 2011). Additionally, since nearby units
associated with environmental surveys tend to be spatially
auto-correlated, a spatially balanced sample is likely to improve
monitoring design (Stevens & Olsen 2004). In addition to reduc-
ing costs compared to traditional LPI methods, Cagney et al.
(2011) highlighted that images provide a permanent record,
which can be reevaluated if data are questionable, if software
improves, or if management objectives change. Here, we add
a spatially balanced sampling design, called balanced accep-
tance sampling (BAS) (Robertson et al. 2013, 2017), along with
geo-tagged imagery, to sample reclaimed natural gas well pads
and reference sites. BAS is a representative sample of the pop-
ulation from which it is drawn (Robertson et al. 2013). In this
study, BAS was used to generate points to take spatially bal-
anced images across the study populations, reclaimed well pads
and reference sites. We demonstrate this method’s ability to pro-
vide valid statistical comparisons, to satisfy various regulatory
criteria, to evaluate species on reclaimed sites compared to their
seed mixes, and discuss its improved time efciency, and reduc-
tion of observer bias.
Study Areas
Jonah Infill. Four well pads undergoing interim reclamation
and their adjacent reference areas were monitored in the Jonah
Inll natural gas eld in Sublette County, WY, U.S.A. (Fig. 1).
This eld is comprised almost entirely of federal land reg-
ulated by the Jonah Interagency Ofce (JIO— consisting of
Pinedale BLM Field Ofce, Wyoming Department of Agricul-
ture, WYDEQ, and Wyoming Game and Fish Department). All
well pads were located in the Stud Horse Butte (SHB) section
of this gas eld. One well pad, SHB 32-10, was seeded with
“mix B” in fall 2008, while three other sites, SHB 68-11, SHB
80-11, and SHB 118-11, were seeded with “mix B1” in fall 2013
(Tables S1 and S2, Supporting Information). Well pads aver-
aged 5.3 acres in size.
Douglas. Two well pads undergoing interim reclamation
and adjacent reference areas were monitored on private land
near Douglas, WY, U.S.A. (Fig. 1). These sites are located on a
private ranch in an oil exploration area. One well pad, Trinity
3569-16-14, was seeded with “grass mix” in fall 2016 and
2Restoration Ecology
Vegetation monitoring on reclaimed well pads
Figure 1. A location map showing where the Jonah Inll and Douglas
natural gas elds lie within Wyoming, USA.
one well pad, Trinity 3468-17-44, was seeded with “grass and
alfalfa mix” in fall 2016 (Tables S3-S4). Well pads averaged
7.2 acres in size.
Reclamation Policies
Existing reclamation policies for all study well pads were iden-
tied. All sites are required to meet WYDEQ SWPPP, which
requires plant density or cover on the reclaimed area to be
greater than 70% of an adjacent reference site with no erosion
features present on the reclaimed area (WYDEQ 2016). Since
future development surrounding the Jonah Inll may fall within
Greater Sage-grouse core habitat, we examined how those sites
compared to the SGEO reclamation criteria, which requires a
reclaimed site to have two native forb species, two native grass
species (at least one bunchgrass), and a reference site no further
than 60 m away consisting of 5% or greater sagebrush cover.
Jonah Inll sites are also required to meet the following JIO
criteria (JIO 2007):
1. The site must be in stable condition as indicated by BLM’s
Erosion Control Classication System (BLM Tech Note 346),
the percentage of bare ground must be equal to or less than the
reference site;
2. The average density or frequency of forbs on the reclaimed
site must be a minimum of 75% of the reference site, with forb
richness on the reclaimed site being equal or greater than the
reference site;
3. The average density or frequency of shrubs on the
reclaimed site must be a minimum of 50% of the reference site,
with shrub richness on the reclaimed site being equal or greater
than the reference site;
4. The reclaimed site must have a minimum of three native
perennial grass species present, with at least two being native
5. Sites must be free from all species listed on WY or federal
noxious weed lists; and
6. Plants must be resilient as evidenced by well-developed
root systems, owers, and seed heads.
Qualitative analysis on site was recorded for erosion criteria
to determine if any rills, gullies, or other major erosion fea-
tures were present. Simple division was used to determine if
reclaimed sites passed various criteria which compare percent
cover against the reference area for WYDEQ and JIO require-
ments. Vegetation presence counts were used to determine if
species richness criteria were met. Flowers (forbs) and seed
heads (grasses) were observed in imagery, and if both existed it
was assumed that root systems were developing well, although
root development is not typically measured using traditional
techniques or on reclamation sites since redisturbance would
be required. Sage-grouse Executive Order criteria were eval-
uated rst by determining the amount of sagebrush cover in
the reference area (if >5%, the reclaimed area was evaluated)
and then using forb and grass richness information from the
reclaimed site.
Vegetation Sampling and Analysis
A two-stage sampling design was utilized in both study areas
(i.e. reclaimed and reference sites) where images served as the
primary sampling units, and pixels within images served as sec-
ondary sampling units to estimate vegetation cover. This data
structure is considered a product multinomial design, and dif-
ferences between reclaimed and reference areas were deter-
mined using chi-square tests. If the pixels used to classify
vegetation cover were equally distributed among functional
groups on reclaimed versus reference sites, sites would not be
considered statistically different, whereas if sites were signi-
cantly different the chi-square analyses show which categories
are responsible for the difference. Chi-square analyses were
conducted to compare reclamation and reference areas using
the following groups: bare ground, herbaceous litter, woody lit-
ter, native forb, native shrub, bunchgrass, rhizomatous grass,
and weeds.
Prior to eld work, aerial imagery (ESRI World Imagery,
Digital Globe) in ArcMap v10.3 (ESRI, Redlands, CA, U.S.A.)
was used to draw polygons around interim reclamation portions
of each well pad, and a buffer polygon was placed around the
outer perimeter of the well pad (Fig. 2). In Jonah Inll, a 30 m
wide undisturbed zone around each reclaimed well pad was used
as a reference area. Primary sampling locations were gener-
ated quasi-randomly by ArcMap so that the minimum distance
between two locations was greater than 10 m. Sample sizes of
40 were used on both reclaimed well pads and reference areas.
Reclaimed well pads in the Douglas area were surrounded by
60 m wide undisturbed zones (reference areas) and 30 primary
sampling locations (BAS points) were drawn from both the
reclaimed well pads and reference areas using package “SDraw”
(McDonald 2016) and transferred from Program R to ArcMap
using package “rgdal” (R Core Team 2016; Bivand et al. 2017).
All primary sampling locations (either ArcMap generated points
or BAS points) were transferred from ArcMap into ArcPad v.
10.2 and loaded into a Juno 5 handheld GPS unit (Trimble, Sun-
nyvale, CA, U.S.A.).
Study areas were sampled on the ground in the Jonah Inll on
16 July, 2016 and in Douglas on 1 August, 2017. At each site, the
Restoration Ecology 3
Vegetation monitoring on reclaimed well pads
Figure 2. Aerial view of well pad trinity 3468-17-44. A 60 m buffer was
placed around the well pad and 30 BAS points were selected on the interim
reclamation area and reference area. The long-term disturbance area of the
well pad and a pipeline leaving the well pad were not part of the sampling
Juno 5 GSP was used to locate preselected BAS points. At each
point, a ground-level image was acquired with a 12-megapixel
Ricoh G700SE camera with a GPS unit attached (Ricoh, Tokyo,
Japan). The camera was held over the point in a nadir position
1.3 m above ground level to acquire a 0.40 mm ground sam-
ple distance (GSD) image with a 0.5 m2footprint. This reso-
lution is similar to other studies using SamplePoint (e.g. Booth
et al. 2010). Images were acquired in sunny conditions during
daytime hours and shadowing was mitigated by the photog-
rapher adjusting body position. Image collection times were
recorded with a stopwatch.
Upon returning from the eld, images were associated with
their corresponding BAS point using GeoJot+Core v. 2.4.11, a
computer software package designed to extract metadata from
geo-tagged images (Geospatial Experts, Thornton, CO, U.S.A.).
The images were then evaluated in SamplePoint, a free software
that facilitates manual, pixel-based digital image classication
(Booth et al. 2006). The software selects a user-dened num-
ber of sample pixels from an image, either systematically or
randomly, and displays a crosshair around that pixel on-screen.
Using the surrounding pixels for context, an observer is able to
classify each sample pixel by clicking on 1 of 30 user-dened
buttons to certify the individual pixel classication. The soft-
ware records observer classications to a database with each
click. We used SamplePoint v 1.59 to classify 50 pixels in each
image as either bare ground, herbaceous litter, woody litter, or
plant (to species level; see tutorial on
Classied pixels were randomly chosen by the software with a
200-pixel exclusion buffer around each to avoid randomly clus-
tered sample pixels. Upon completion of image monitoring for
each area of interest automated summary reports are created
within seconds as comma separated value (.csv) les (Booth
et al. 2006). Time taken to analyze images was recorded with
a stopwatch. Upon completion of image analysis, species were
manually categorized into functional groups (see above) when
necessary for regulatory analysis and for chi-square tests, but
left as species-specic when analyzing species richness. Species
richness was used to determine seed mix establishment success,
as well as the presence of nonmix species.
Statistical Comparison Between Reclaimed Well Pads
and Reference Areas
Vegetation communities on reclaimed sites were different than
reference sites (p<0.0001), but categories driving differences
varied (Table 1). In Jonah Inll, all reclaimed sites had higher
bunchgrass and herbaceous litter percent cover than reference
areas, whereas all reference areas had higher shrub and woody
litter cover (Table 1). All reclaimed sites in Jonah Inll except
SHB118-11 had less bare ground than reference sites (Table 1).
Although all reclaimed sites in Jonah Inll had greater forb rich-
ness than reference sites, only SHB68-11 had higher forb cover.
Weed cover was no different between Jonah Inll reclaimed
and reference sites In Douglas, Trinity 3468-17-44 had less
bare ground and rhizomatous grass cover than its reference, and
higher herbaceous litter, shrub, and forb cover (Table 1). Trin-
ity 3569-16-14 had higher bare ground, rhizomatous grass, and
weed cover than its reference, while having less herbaceous lit-
ter and bunchgrass cover (Table 1).
Reclamation Policies
All sites, in Douglas and Jonah Inll, passed WYDEQ SWPPP
criteria (Table 2). In Jonah Inll, all four sites passed site
stability criteria, forb richness criteria, and forb density criteria,
but no site passed all JIO Regulatory Criteria (Table 3). In Jonah
Inll, three of four sites passed the SGEO Sage-grouse habitat
suitability criteria (Table 4).
Seed Mixes in Monitoring Data
In Jonah Inll, SHB 32-10 contained 8 of 15 species from
the seed mix, with 2 species present which were not included
in the seed mix (Table S1). All other sites had 12 of 21 species
from the seed mix present, 11 of which were common to all three
sites and 7 of which were absent from all three sites (Table S2).
All three sites contained three species which were not present
in the seed mix (Table S2). In Douglas, Trinity 3648-17-44
contained all seven species from the “grass and alfalfa mix” and
two species which were not in the seed mix, whereas Trinity
3569-16-14 contained four of ve species from the “grass mix”
and three species not in the seed mix (Tables S3 and S4). All
sites had at least one species on the site which was neither in
the intended seed mix nor in the reference area (Tables S1 S4).
We did not have the ability to conduct tests to determine if these
species were a result of a contaminated seed mix, encroachment
from the references area, or were preexisting in the replaced
stockpiled topsoil.
Image collection on reclaimed and reference sites in the Jonah
Inll averaged 16.2 and 17.7 minutes, respectively (n=40).
4Restoration Ecology
Vegetation monitoring on reclaimed well pads
Tabl e 1 . A table depicting which categories drove signicant differences between reclaimed sites and reference sites in chi-square tests. All sites were
signicantly different (p<0.0001), individual categories with a * are those which were responsible for signicance. Numbers in parentheses indicate the
proportion of the chi-square statistics accounted for by the given category.
Site Bare Ground Herbaceous Litter Woody Litter Shrub Forb Bunchgrass Rhizomatous Grass Weed
SHB32-10 *(28.6) *(27.4) *(8.7) *(20.1) (0.2) *(13.3) (1.4) (0.3)
SHB68-11 *(32) *(27.1) *(11.3) *(11) *(3.9) *(10.6) (2.6) (1.6)
SHB80-11 *(28) *(29) *(7.8) *(13.3) (0.6) *(6.6) *(12.6) (2)
SHB118-11 *(29.4) *(29.3) *(10.6) *(13) (2.3) *(9.25) (3.3) (2.9)
Trinity3468-17-44 *(38.9) *(40.7) (0.1) (3.6) *(5) (2.3) (6.4) (3)
Trinity3569-16-14 *(48.8) *(26.3) (0.1) (0) 2 *(10) *(8.7) *(4)
Tabl e 2 . Reclaimed well pads and from both Douglas and Jonah Inll com-
pared against Wyoming Department of Environmental Quality Stormwater
Pollution Prevention Plan. Passing criteria were considered binary (Y =yes,
N=no), and percent ground cover on the reclaimed area compared to ref-
erence area is shown in parentheses. *Denotes a site which has passed all
WYDEQ SWPPP criteria.
Site Name
Pass Erosion Control
Criteria (No Erosion
Control Features
Pass 70% Ground
Cover Compared to
Reference Criteria?
SHB32-10* Y Y (110.3%)
SHB68-11* Y Y (107.2%)
SHB80-11* Y Y (101.5%)
SHB118-11* Y Y (93.7%)
Trinity3648-17-44* Y Y (128.9%)
Trinity3569-16-14* Y Y (91.2%)
Reclaimed and reference sites near Douglas averaged 24 and
25.1 minutes, respectively (n=30). Image analysis averaged
1.3 minutes/image, with quantitative reports completed for
areas (i.e. reclaimed sites or reference sites) taking an average
of 51.2 minutes for Jonah Inll and 38.4 minutes in Douglas.
We attribute the increased time taken to record images in
Douglas to larger well pad size.
Since transportation is the most expensive cost of large-scale
vegetation sampling, the ability to rapidly collect data while
in the eld is critical to monitoring projects (Stohlgren et al.
1998). Traditional LPI methods have been timed to take a
two-person team 99 minutes/site (Cagney et al. 2011). The
method proposed in this study allows one individual to cap-
ture equivalent eld data in roughly one-fth that time, sug-
gesting a 10-fold increase in eld data collection efciency.
Even factoring in image analysis time, the photo-monitoring
method took less time than required for LPI eld data collec-
tion in Cagney et al.’s (2011) study. Since the proposed method
samples individual sites faster than LPI methods, fewer trips to
the study area may be required to achieve the desired sample
size, therefore reducing costs. Additionally, rapid methods to
capture data are critical in areas where phenologically sensi-
tive forb species are being increasingly recognized in conser-
vation efforts for the Greater Sage-grouse (Curran et al. 2015).
Providing a simple monitoring method which allows for data
to be collected once and utilized many times (e.g. to report to
varying regulatory agencies and to provide seed establishment
information) is likely to reduce operator costs.
Quantitative data obtained using this method are able to sat-
isfy multiple stakeholder groups and determine if reclamation
sites are meeting various regulatory criteria, while chi-square
analyses can assist in determining where signicant differences
between reclaimed sites and reference areas exist, regardless
of regulatory criteria. While the JIO has the most stringent
regulatory criteria associated with reclamation of oil and gas
disturbances in WY, data gathered from this technique can sat-
isfy other BLM eld ofce criteria, which are based on percent
ground cover and lack of noxious weeds (Curran et al. 2013).
Two metrics SamplePoint cannot currently capture, which may
have importance to wildlife species, include vegetation height
and canopy gap. Height can easily be measured with a meter
stick. Canopy gap has been measured from digital photos using
various simple techniques (Booth & Cox 2011; Karl et al. 2012).
Both height and canopy gap may be metrics which need only be
monitored when the reclaimed area is nearing bond release. It
has also been reported that image analysis may result in dif-
culties capturing vegetation under dense canopy cover (Hulvey
et al. 2018). Our study areas were not prone to this issue and
it is unlikely for reclaimed sites in semiarid sagebrush-steppe
ecosystems to have dense canopy cover during the interim recla-
mation phase.
Along with providing a rapid means of data collection, the
spatially balanced nature of this method coupled with more
primary and secondary sampling units increases the statistical
power of this method relative to the single primary sampling unit
associated with traditional LPI techniques. Quasi-random selec-
tion of sample points also reduces observer bias. Image-based
vegetation analysis has also shown to reduce inter-observer
bias compared to traditional techniques in previous studies and
allows for multiple individuals to reexamine the same image at
different times if necessary, and for images to be analyzed by
one expert regardless of how many individuals collected images
(Cagney et al. 2011), making it less time and cost intensive than
verifying observer bias along a transect. The images in this study
contain both temporal and geospatial metadata, allowing them
to be classied long after they are captured, providing bene-
t to regulatory agents who may be busy with permitting new
well pads while monitoring is being conducted and the ability
Restoration Ecology 5
Vegetation monitoring on reclaimed well pads
Tabl e 3 . Reclaimed well pads from Jonah Inll compared to Jonah Interagency Ofce Regulatory Criteria. Each category was binary (Y=yes, N =no) with
values in parentheses denoting percent (%) or richness (reclaimed site, reference site).
Percent Bare
Ground Cover
(100% of
Desirable Forb
Percent Forb
Cover (75% of
Shrub Richness
Percent Shrub
Cover (50%
of Reference)
Desirable Grass
(3 or >Tot a l
Grass Species,
Free o f All
Plants Show
Based on
Flowers and
Seed Heads
SHB32-10 Y Y (110.3%) Y (1, 0) Y N (1, 3) N Y Y Y
SHB68-11 Y Y (107.2%) Y (4, 1) Y Y (2, 2) N Y N Y
SHB80-11 Y Y (101.5%) Y (3, 0) Y N (2, 3) N Y N Y
SHB118-11 Y N (93.7%) Y (4, 0) Y Y (2, 2) N Y N Y
Tabl e 4 . Reclaimed well pads from Jonah Inll compared to Sage-grouse
Executive Order criteria for reclaimed sites. *Denotes a site which has
passed all SGEO criteria for sage-grouse habitat suitability.
Cover (5%)
Site Forb
Richness (2)
Reclaimed Site
Grass Richness
(2, At Least 1
SHB32-10 Y (24%) N Y
SHB68-11* Y (17%) Y Y
SHB80-11* Y (21.1%) Y Y
SHB118-11* Y (19.6%) Y Y
to ground-truth if data are questionable. The spatial precision
of the GPS units used in this study is within 3 m, though GPS
advances will result in better precision. While spatial precision
may be a drawback of this study, it has been documented that
permanent transect locations can be unreliable for repeatabil-
ity in some instances (Vittoz & Guisan 2007). Additionally, by
increasing the number of sample units, it is likely the accuracy
of our study design is greatly improved compared to a single
transect (Kowalewski et al. 2015). Species-level classication
allows for seed mixes to be evaluated on reclaimed sites. For
example, the 11 species which were present on all three Jonah
Inll sites which received seed mix “B1” are likely to be recom-
mended for future seeding, whereas the 7 species which were
absent from all sites may be dropped for future projects in the
area. Spatially explicit data can also inform decisions on weed
management and may help identify contaminated seed mixes.
This method is best suited for ecosystems where vegetation
is short enough to be captured by a hand-held camera. Using a
camera with a separate navigation unit does not optimize ef-
ciency or cost. We used two because neither unit excels at both
navigation and image acquisition, although it can be assumed a
single unit will arise. More studies should be conducted to deter-
mine the adequate or optimal sample size, which may change
over the lifecycle of a reclaimed well pad (e.g. a 1-year-old site
may be more homogeneous than a 5-year-old site and may need
less intensive sampling). Using a nonparametric bootstrap of our
representative BAS sample, we found that 40 photos resulted
in an ability to estimate the proportion of bare ground within
5% of its estimated value on the sites we studied. Additionally,
determining the optimal amount of pixels to sample within an
image may need further consideration. Here, we used 50 pix-
els, though recent studies suggest 20–30 pixels per image is
adequate to estimate vegetation at a landscape scale when multi-
ple images are acquired (Ancin-Murguzur et al. 2018). Finally,
although using BAS points in a buffer around a well pad as a
reference site improves spatial coverage and statistical analy-
ses compared to a single LPI transect, reclaimed areas in this
study are limited to being compared against their own unique
reference site, which may limit efciency.
The study was funded in majority by Wyoming Reclamation
and Restoration Center. Funding for the GPS unit was provided
by Warren Resources and Escalera Resources. David Legg pro-
vided suggestions to improve study design. We appreciate Jonah
Energy LLC and Anadarko Petroleum Company for access
to eld sites. Taylor Crow, Robert Kirkwood, and Nicholas Graf
provided support with gure creation. The authors declare no
conict of interest.
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Supporting Information
The following information may be found in the online version of this article:
Table S1. List of species from the seed mix and presence (P) or absence (A) as well as
list of species not in the seed mix which were present on site Stud Horse Butte 32-10.
Table S2. List of species from the seed mix and presence (P) or absence (A) as well as
list of species not in the seed mix which were present on sites Stud Horse Butte 68-11,
80-11, and 118-11.
Table S3. List of species from the seed mix and presence (P) or absence (A) as well
as list of species not in the seed mix which were present on site Trinity 3468-17-44.
Table S4. List of species from the seed mix and presence (P) or absence (A) as well
as list of species not in the seed mix which were present on site Trinity 3569-16-14.
Coordinating Editor: Purushothaman Abhilash Received: 25 March, 2018; Firstdecision: 25 June, 2018; Revised: 8 April, 2019;
Accepted: 9 April, 2019
Restoration Ecology 7
... These methods are often applied based on convenience rather than stochastically, with observers choosing where they collect data. Additionally, reported and actual sample locations frequently differ, causing confusion for land managers and other stakeholders reliant upon vegetation monitoring data 18 . Recent research has demonstrated that image-based vegetation monitoring is time-and cost-effective 6 , 19 , 20 . ...
... Differences in acquisition time between platforms was principally due to the UAS flying speed being 2-3x faster than the technician walking speed (Figure 4). Rapid field data collection is important not only for time-and cost-savings, but to ensure monitoring can be completed during short periods where plant phenology renders them readily identifiable (e.g., during blooming) 18 . While repeat photography has been utilized to study phenological trends over time 37 , 38 , the GPS capability of modern cameras and UAS systems can be used to further ensure image acquisition is occurring at the same location (or in very close proximity) over time, enhancing the ability to understand short-and longterm environmental changes. ...
... Sample sizes in this study were consistent with a previous study 18 , but more work is likely necessary to determine optimal sampling units in different sized areas as well as in different ecosystems. ...
Full-text available
Rangeland ecosystems cover 3.6 billion hectares globally with 239 million hectares located in the United States. These ecosystems are critical for maintaining global ecosystem services. Monitoring vegetation in these ecosystems is required to assess rangeland health, to gauge habitat suitability for wildlife and domestic livestock, to combat invasive weeds, and to elucidate temporal environmental changes. Although rangeland ecosystems cover vast areas, traditional monitoring techniques are often time-consuming and cost-inefficient, subject to high observer bias, and often lack adequate spatial information. Image-based vegetation monitoring is faster, produces permanent records (i.e., images), may result in reduced observer bias, and inherently includes adequate spatial information. Spatially balanced sampling designs are beneficial in monitoring natural resources. A protocol is presented for implementing a spatially balanced sampling design known as balanced acceptance sampling (BAS), with imagery acquired from ground-level cameras and unmanned aerial systems (UAS). A route optimization algorithm is used in addition to solve the ‘travelling salesperson problem’ (TSP) to increase time and cost efficiency. While UAS images can be acquired 2–3x faster than handheld images, both types of images are similar to each other in terms of accuracy and precision. Lastly, the pros and cons of each method are discussed and examples of potential applications for these methods in other ecosystems are provided.
... In Wyoming, natural gas well pads undergoing ecological restoration are typically judged by comparing recently disturbed sites which have been seeded with an approved seed mix to adjacent reference sites and by determining how these sites are progressing based upon existing regulatory frameworks [4,5]. These frameworks are often focused on land reclamation, a component of ecological restoration which emphasizes revegetation, regrading topography and erosion control [6][7][8]. In this sense, human-mediated reclamation efforts are often viewed as 'assisted succession' and focus on structural rather than functional endpoints [9]. ...
... A final reclamation process is implemented after the life of the well is complete, which includes plugging the well, removing equipment and seeding the remaining area of initial disturbance [19]. While policies in Wyoming associated with natural gas restoration often focus on erosion control, site stability, control of noxious and invasive weeds and vegetation comparisons to an adjacent reference site [6], selecting reference sites as measures of success has been debated by restoration ecologists [20,21]. In general, well pads undergoing reclamation can meet regulatory success criteria by establishing native plant species similar in composition to a reference site and controlling undesirable species (e.g., noxious weeds) [5,19]. ...
... The total number of pixel counts per cover type (a total of 2880 pixels) was used for each site type. Chi-square tests for equal distribution were conducted separately for each year by comparing the total number of pixel counts per vegetation classification group between reclaimed sites and their reference pairs in accordance with [6]. ...
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Natural resource extraction has been linked to habitat loss and declines in biodiversity. Insects, the most diverse and abundant animals on Earth, provide a wide array of critical ecosystem services, but are typically understudied in terrestrial restoration projects. Here, we examine how insects and other arthropods respond to reclamation efforts in the Pinedale Anticline natural gas field in semi-arid Wyoming, USA. Vegetation on two-year-old well pads seeded with native grass or one-year-old well pads seeded with a native annual forb, Rocky Mountain bee plant (Cleomeserrulata), was measured and compared to reference areas adjacent to the well pads with a free software program called SamplePoint. Reference areas in the Pinedale Anticline natural gas field consist primarily of decadent sagebrush stands with low floral diversity. Insect and arthropod communities were also collected and assessed for family richness and abundance on these well pads and reference areas over two years. Based on the mass flowering hypothesis, we expected higher insect abundance and diversity on well pads seeded with the Rocky Mountain bee plant compared to adjacent reference areas. Based on the plant vigor hypothesis, we expected higher insect abundance and diversity on well pads seeded with native grass than reference communities. In year one, 893 insects from 30 insect families with an additional 12 arthropods from 4 families were captured. In year two, 685 insects from 17 families were collected. Reclaimed well pads had significantly higher abundance in both years and vegetation types. In year one, we did not detect a significant difference in richness on native-grass-treated well pads vs. the reference site. We found a significant difference in richness on bee-plant-treated well pads vs. the reference in both years, as well as native-grass-treated well pads vs. the reference in year two. Implications of these findings are discussed in the manuscript.
... These studies are limited by image resolution and use various vegetation indices to measure changes in net primary productivity, rather than species-specific information. Recently, ground-level imagery has been shown to be an effective way to measure vegetation communities at the species-specific level on reclaimed well pads in the western US (Curran et al. 2019). Studies in rangeland environments have shown ground-level (handheld) digital imagery can be used to obtain species-specific data in a more timely fashion than traditional vegetation monitoring techniques, such as line point intercept (LPI) methods along vegetation transects (e.g. ...
... In a recent study, Curran et al. (2019) demonstrated that a single individual with a handheld camera utilising a BAS design could capture a statistically valid sample in a fraction of the time it takes two people to perform traditional LPI techniques to generate species-specific reports on reclaimed well pads. Seeking to further improve the efficiency demonstrated by that study, we designed the current study to test the hypothesis that an unmanned aerial system (UAS) could further reduce sample acquisition time without compromising data quality. ...
... Subsequently, package 'SDraw' (McDonald 2016) was used to generate 30 BAS points within each polygon. We used 30 BAS points as previous literature has shown this to be an adequate sample size on well pads of this size (Curran et al. 2019). Although BAS points provide adequate spatial coverage of our sites, the sample identification number associated with BAS points do not result in an optimised travel path. ...
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Biodiversity decline is widely considered a critical global environmental threat. In the western United States, land surface disturbance associated with oil and gas development is considered a top driver of habitat fragmentation and biodiversity decline. Land reclamation and ecosystem restoration activities help mitigate biodiversity loss, though monitoring practices to track these efforts are inconsistent, often lack measures of biodiversity response and are labour-intensive. Digital image analysis has been shown to reduce labour requirements and can provide robust, statistically valid reports on vegetation cover. We compare handheld image analysis to unmanned aerial system (UAS) image analysis to measure vegetation and ground cover on reclaimed oil and gas well pads. We utilise a spatially balanced sample design called balanced acceptance sampling along with a travelling salesperson algorithm to optimise walking and flight paths to obtain imagery in our study design. Images are then analysed with a free software program, ‘SamplePoint’, to classify vegetation on reclaimed well pads into functional groups. We conclude image acquisition is significantly faster with the UAS than with the handheld approach. We found that UAS image analysis and handheld analysis produced similar results in assessing vegetation and ground cover and we discuss pros and cons of each method. • Key policy insights • Rapid monitoring techniques which are statistically sound and provide robust datasets should help enhance knowledge of land reclamation practices in oil and gas fields. • Unmanned aerial systems can cover well pads significantly faster than a human walking with a camera, and images gathered by each have similar results when vegetation is analyzed at the functional group level. • Although slower, hand-held images may provide finer detail than UAS images flown 7.6 m above ground level, which may make hand-held images more useful for classifying vegetation to species-specific levels. • Utilizing GPS technology along with spatially balanced sampling, route optimization, and digitial images increases speed of data collection and spatial accuracy of data compared to traditional line point intercept techniques.
... In fact, new research in Wyoming oil and gas fields highlights the benefits of collecting sUAV data over traditional field inspections. This includes the time and money saved, the rich spatial datasets produced, and the ability for experts and stakeholders to review and interpret these data as needed (McKim 2020;Curran et al. 2019; University of Wyoming 2020). ...
MonitoringMonitoring efforts for remote high-latitude and high-altitude glacierized regions heavily rely on remote sensingRemote sensing. Rapid ongoing changes in polarPolar and cryosphericCryosphere environments owing to contemporary climate changeClimate change have attracted more attention towards these regions than ever before. Satellite Satellitesremote sensingRemote sensing has its own limitations related to low sun angles in high latitudes, high acquisition costs for high-resolution images, and persistent cloud cover over ice-dominated land and oceanOceans surfaces. As such, over the past several years, small unoccupied aerial systems (sUAS)Small unoccupied aerial systems (sUAS) have become a viable data collection tool to address the challenges related to spaceborne or expensive airborne remote sensingRemote sensing for monitoringMonitoring the cryosphereCryosphere and polarPolar regions. This chapter discusses sUASSmall unoccupied aerial systems (sUAS) adaptations for collecting data on snowSnow, glaciers, permafrostPermafrost, polarPolar biology, the oceanOceans, and atmosphereAtmosphere; the challenges of conducting sUASSmall unoccupied aerial systems (sUAS) operations in polarPolar latitudes; and the advantages and disadvantages of the technology. It also provides resources that can be used to guide future efforts in applying sUASSmall unoccupied aerial systems (sUAS) to polar and Polarcryospheric researchCryosphere.
... In this instance, the group of observers could potentially look at the video together and determine errors (e.g., why observer 1 always seemed to have higher counts than others and observers 3, 6 and 7 seemed to have lower counts than others). Other studies have shown that the use of cameras recording individuals collecting insects have been useful to correct observer bias [36] and that images provide permanent records which can be reviewed by multiple observers and stakeholder groups in vegetation surveys [37]. While our study was limited to insects, the technique presented could also be used as a non-lethal sampling strategy to study behavior in other animals (e.g., monitoring migratory bird behavior at stopover grounds). ...
Full-text available
Insects, the most diverse and abundant animal species on the planet, are critical in providing numerous ecosystem services which are significant to the United Nation's Sustainable Development Goals (UN-SDGs). In addition to the UN-SDGs, the UN has declared the period 2021-2030 as the "Decade on Ecosystem Restoration". Insects, because of the ecosystem services they provide, are critical indicators of restoration success. While the importance of insects in providing ecosystem services and their role in helping fulfil the UN-SDGs is recognized, traditional techniques to monitor insects may result in observer bias, high rates of type-I and type-II statistical error, and, perhaps most alarmingly, are often lethal. Since insects are critical in maintaining global food security, contribute to biological control and are a key food source for higher trophic levels, lethal sampling techniques which may harm insect populations are undesirable. In this study, we propose a method to visually sample insects which involves non-lethal 3-dimensional video cameras and virtual reality headsets. A total of eight observers viewed video captured insects visiting floral resources in a landscaped area on a university campus. While interobserver variability existed among individuals who partook in this study, the findings are similar to previous visual sampling studies. We demonstrate a combination of 3D video and virtual reality technology with a traditional insect count methodology, report monitoring results, and discuss benefits and future directions to improve insect sampling using these technologies. While improving quantitative monitoring techniques to study insects and other forms of life should always be strived for, it is a fitting time to introduce non-lethal sampling techniques as preservation and restoration of biodiversity are essential components of the UN-SDGs and the "Decade on Ecosystem Restoration".
... The log ratio difference and singular decomposition were combined using neighbor constraints. Finally, residual U-Net was applied to detect the changes [22,23]. ...
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The growth and development of particular region over time can be witnessed by remote sensing images. Although such raw images have less possibility to derive the insights, Serial Remote Sensing Images (SRSI) has the large potential to discover the patterns. The evolution of spatial patterns in various areas including urban development, expansion of vegetation cover and agriculture is the evidence for the utilization of SRSI accumulation. The application of conventional sequential pattern-mining algorithms on the SRSI images results in high computational complexity. This issue can be resolved by grouping the pixels and mining sequence patterns. A one-pass framework is introduced to compress and hide the data in the marked stream without any loss. In this paper, we proposed a Quantized ternary pattern based pixel grouping and Singular Value Decomposition—Run Length Coding based pattern mining. The algorithms are experimented using a dataset, namely, the Cropland data layer dataset. The proposed algorithm is efficient in terms of mining time and sequence pattern generation.
... Evaluation of plant communities via ecological imaging can minimize the possibility of false negatives (Type-II errors) by increasing sample size and reducing the timeframe of data collection relative to labor-intensive field methods. For example, Curran et al. (2019) found a 10-fold increase in field sampling efficiency for nadir photography when compared with LPI methods. Studies to compare field surveys and photographic data have found varying degrees of correspondence among methods, and difficulties can arise in measuring cover of lower canopy levels using digital images ( Cagney et al., 2011 ;Pilliod and Arkle, 2013 ;Hulvey et al., 2018 ). ...
Geomorphic reclamation creates variable topography and surface architecture, including rolling hillslopes and drainages. In contrast, traditional methods of reclamation result in landscapes susceptible to erosion due to steep, linear gradients. Geomorphic approaches to surface mine reclamation are relatively new, and hypotheses suggest the use of geomorphic principles in reclamation will improve vegetation outcomes relative to traditional methods. Topographic variability created by geomorphic reclamation likely results in more environmental heterogeneity, which should correlate with greater plant diversity. We examined revegetation outcomes of traditional and geomorphic reclamation on two reclaimed surface mines in Wyoming using nadir image sampling. Functional group diversity and measures of cover were compared between reclamation methods and undisturbed rangeland. Geomorphic reclamation supported greater total richness and greater native functional group richness relative to traditional reclamation. Native species cover on geomorphic reclamation, particularly for native perennial grasses, was either similar to undisturbed rangeland or greater than undisturbed rangeland and traditional reclamation. Reclamation shrub cover differed significantly from undisturbed sites, but was greater in geomorphic treatments. Results of nadir image analysis are compared to line-point intercept data from the same locations and outcomes are discussed in light of different reclamation techniques and sampling methods. Significant differences in cover categories were observed between nadir image and line-point intercept methods, however both methods revealed similar patterns between study sites.
This chapter highlights how small unoccupied aerial vehicles (sUAVs), or drones, and pole aerial photography (PAP) can provide actionable information for regulators and stakeholders on the state or condition of oil and gas wellpads on US federal grasslands. We believe that imagery-derived datasets such as orthomosaics, vegetation, elevation, and 3D models, as well as 360° drone video and very low-elevation pole aerial video, can help regulators such as the US Forest Service (USFS), as well as industry, identify major surface compliance issues from their office computers and therefore enhance the quantity and quality of site visits. Furthermore, we anticipated that these datasets would prove most useful when determining if remediation efforts met compliance targets during the 5-year reclamation phase, where abandoned wellpads are returned to a natural state. Findings suggest that 70% of the annual inspection can be conducted utilizing these datasets. For reclamation sites, they had broad applications. Though vegetation cover conditions could be detected, it was difficult to distinguish the grass seed mix, weeds, and invasive plants, as well as the condition of fences from visual analysis. Overall, access to and interpretation of these data can speed up inspections, increase efficiency, greatly enhance field visits, and target locations that indeed require additional field reviews and appropriate responses. We conclude that while these methods can improve current Forest Service field inspections, perhaps operators benefit more, since they can more readily adopt the latest aerial surveillance methods to monitor surface effects as they occur. This allows them to address areas of concern prior to and after inspections, thus better coordinating planning and actions with the USFS regulators throughout the life cycle of the well. Hence, operators can save time and money and reduce legal exposure while enhancing communication with regulators.
Full-text available
Insects are critical components of terrestrial ecosystems and are often considered ecosystem engineers. Due to the vast amount of ecosystem services they provide, because statistically valid samples can be captured in short durations, and because they respond rapidly to environmental change, insects have been used as indicators of restoration success and ecosystem functionality. In Wyoming (USA), thousands of acres of land surface has been disturbed to extract natural resources. While traditional reclamation practices of these lands focused on site stabilization and weed control, more recent efforts have been made to restore ecosystem services. It has been suggested that a spatial and temporal mosaic of flowering species will benefit insect populations. In this study, we compared early seral reclamation sites (i.e., well pads undergoing interim reclamation) to reference areas at two points within a growing season. We found reference ecosystems were devoid of forb species, while one year old reclaimed sites contained late-season blooming Rocky Mountain beeplant (Cleome serrulata) and three-four year old well pads contained early-season blooming perennial forb species, mainly western yarrow (Achillea millefolium). We compared insect abundance and family richness on 6 well pads with early season perennial forbs and 6 well pads with the late season annual forb, Rocky Mountain beeplant to insect communities on adjacent reference areas. A total of 237 insects were found on early season reclaimed sites compared to 84 on reference sites, while 858 insects were found on late season reclaimed sites compared to 40 on reference sites. Insect abundance and family richness was significantly higher on reclaimed well pads compared to reference areas at both points in the growing season. We also found interesting differences in abundance at family levels.
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• We used photography-based grid point intercept (GPI) analysis and Daubenmire to assess ecosystem services in high-shrub rangelands. • Cover estimates were higher for some functional groups when using Daubenmire, likely because Daubenmire frames were situated below the shrub canopy and thus included subcanopy cover, whereas GPI photographs taken above the canopy could not eliminate shrubs that obscured subcanopy attributes. • Choice of methods affected assessment of two ecosystem services: sage-grouse habitat quality and site biodiversity; each was higher when using Daubenmire. • Understanding cover-estimate differences that stem from using GPI photo plots versus Daubenmire will allow practitioners to decide if GPI methods address project objectives.
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Decision makers and stakeholders need high-quality data to manage ecosystem services (ES) efficiently. Landscape-level data on ES that are of sufficient quality to identify spatial tradeoffs, co-occurrence and hotspots of ES are costly to collect, and it is therefore important to increase the efficiency of sampling of primary data. We demonstrate how ES could be assessed more efficiently through image-based point intercept method and determine the tradeoff between the number of sample points (pins) used per image and the robustness of the measurements. We performed a permutation study to assess the reliability implications of reducing the number of pins per image. We present a flexible approach to optimize landscape-level assessments of ES that maximizes the information obtained from 1 m² digital images. Our results show that 30 pins are sufficient to measure ecosystem service indicators with a crown cover higher than 5% for landscape scale assessments. Reducing the number of pins from 100 to 30 reduces the processing time up to a 50% allowing to increase the number of sampled plots, resulting in more management-relevant ecosystem service maps. The three criteria presented here provide a flexible approach for optimal design of landscape-level assessments of ES.
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This paper will highlight the need for database creation and management associated with large-scale land reclamation and ecosystem restoration projects and suggests considerations for future improvements. Scientists at the University of Wyoming have created the Wyoming Reclamation and Restoration Center Oil and Gas Reclamation Database by collaborating with 20 oil and natural gas development companies as well as private environmental consulting firms, Petroleum Association of Wyoming, and various government and regulatory agencies. A commonly noted flaw in the practice of land reclamation and the field of restoration ecology is that they have been limited by lack of communication and collaboration among the scientific community, reclamation practitioners, and regulatory agencies. The Wyoming Reclamation and Restoration Center Oil and Gas Reclamation Database is the biggest collaboration to date between scientists, industry, practitioners, and regulatory agencies. The database has also been critical to assess reclamation and restoration efforts of ‘unprecedented’ conservation work and has been used by the U.S. Fish and Wildlife Service in their process of coming to a non-warranted Endangered Species Act listing decision of the Greater sage-grouse (Centrocercus urophasianus). While the framework of our database is sound, data quality has limited effectiveness of database analysis in many instances. Examples of database utility will be demonstrated and suggestions for improving data quality and monitoring plans will be made.
Full-text available
Aims Vegetation sampling employing observers is prone to both inter-observer and intra-observer error. Three types of errors are common: (i) overlooking error (i.e. not observing species actually present), (ii) misidentification error (i.e. not correctly identifying species) and (iii) estimation error (i.e. not accurately estimating abundance). I conducted a literature review of 59 articles that provided quantitative estimates or statistical inferences regarding observer error in vegetation studies.
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On the Ground: Greater sage-grouse are the species of concern in the largest conservation effort in US history and have populations spanning 11 western states. Restoration of sage-grouse habitat will assist these conservation efforts.It is known that forbs are critical to sage-grouse diets, but only isolated studies have measured forbs in the diet at a species- or genera-specific level and little is known about sage-grouse preference to forbs.Research has shown that local seed sources promote successful reestablishment of vegetation communities, although commercial seed sources for forb species used in sage-grouse diet often are lacking.We make suggestions for selecting forb species and improving seed sources for sage-grouse conservation.
This article presents a modification of balanced acceptance sampling (BAS) that causes inclusion probabilities to better approximate targeted inclusion probabilities. A new sample frame constructor for BAS is also introduced from which equi-probable spatially balanced samples are drawn.