patrickbdevaney/mia9 · Datasets at Hugging Face

text stringlengths 0 6.44k
Date Correct Total Accuracy
11/26/2017 13 15 86.6%
2/14/2018 10 13 76.9%
2/17/2019 11 13 84.6%
6/25/2019 11 13 84.6%
2/4/2020 9 13 69.2%
Total 54 67 80.6%
significantly affected the size of the plume, explaining 63% of
the deviance, and found no evidence of variation as a function
of season (e.g., fall vs. spring satellite images; Figure 4 and
Table 2). We detected a breakpoint in the sediment plume
coverage of the region in November 2016 (95% CI: September
2015–February 2018; Table 3). This date straddled the Fall 2015
seagrass die-off and the Fall 2017 hurricane Irma. The average
size of the sediment plume before the breakpoint was 163.5 km2
(±26.8 km2
), which increased to 223.5 km2
(±19.9 km2
) postbreakpoint–a 37% increase in area.
Basin Specific Responses to
Disturbances and Sediment Plume
Coverage
When considering our focal basins, Johnson and Rankin, we
found differences in the magnitude, timing and duration of effects
of the sediment plume. Both basins exhibited breakpoints, but
the breakpoint was earlier, and resulted in more severe and
longer lasting effects in the western basin, Johnson (Figure 5). An
ANOVA conducted on the proportion of the basins covered by
the plume, showed a significant basin and breakpoint interaction,
with both Johnson and Rankin having a significantly higher
proportion of basin covered by the plume after the change
point compared to before (Tukey’s HSD < 0.05; Figure 6A
and Table 4). In Johnson, there was a breakpoint in March
2015 (95% CI: October 2014–September 2015; Figure 5 and
Table 3), and sustained high sediment coverage through the last
data point in the time series. Before the breakpoint, an average
of 11.6% (±10.8%) of Johnson was covered by the sediment
plume while 78.6% (±13.4%) of Johnson was covered by the
plume after the breakpoint (Figure 6A). In contrast, for Rankin,
there were two breakpoints. The first breakpoint was February
2017 (95% CI September 2015–November 2017), and the second
was November 2018 (95% CI February 2018–February 2020;
Figure 5 and Table 4). Here, 0% of Rankin was covered by
the plume before the first breakpoint, while 22% (±21%) was
covered by the plume after the first breakpoint (Figure 6A). The
second breakpoint in Rankin represents a sediment contraction,
indicating the short term effects in this basin, and thus, was not
considered in further analyses.
Interaction Between Sediment Plume
Coverage and Changes in Seagrass
Cover
Along with differences in the extent of the sediment plume,
we also found differences in seagrass cover between basins, and
a basin-specific interaction between plume extent and seagrass
cover. For seagrass cover, the interaction between basin and
before and after the change point was significant (Table 4).
Seagrass cover in Johnson basin decreased significantly after its
March 2015 breakpoint (Tukey’s HSD < 0.05; Figure 6B and
Table 4). The average BB score in Johnson dropped from 3.6
(±0.34; approximately 60% cover) to 2.5 (±0.38; approximately
35% cover) after the breakpoint. In contrast, we found no
change in seagrass cover as a function of its February 2017
breakpoint in Rankin. The average BB score of Rankin before
Frontiers in Marine Science \| www.frontiersin.org 6 July 2021 \| Volume 8 \| Article 633240
Rodemann et al. Sediment Plume and Seagrass Resilience
FIGURE 4 \| Temporal trend in the sediment plume size in Florida Bay between 2008 and 2020. The black line shows the fitted GAM model and 95% confidence
interval (gray shaded area). The vertical red line shows the breakpoint in sediment plume size, with its 95% confidence interval (red shaded area). The vertical green
line represents the 2015 seagrass die-off and the vertical blue line represents Hurricane Irma.
the breakpoint was 2.7 (±0.61; approximately 40% cover) and
was 2.8 (±0.05; approximately 45% cover) after the breakpoint.
Further, in Johnson, there was a negative correlation between the
proportion of basin covered by the sediment plume and seagrass
cover (r = −0.75, p = 0.005; Figure 6C). There was no correlation
between the proportion of basin covered by the sediment plume
and seagrass cover in Rankin (r = 0.05, p = 0.88; Figure 6C).
DISCUSSION
Anthropogenic and natural disturbances have jointly contributed
to the degradation of seagrass habitats worldwide, including
in Florida Bay, which have resulted in two drought-induced
seagrass die-offs (Fourqurean and Robblee, 1999; Hall et al.,
TABLE 2 \| Generalized additive models (GAM) used for the temporal assessment
of sediment plume size.
Term edf Ref.df F p Deviance
explained
AIC
(a) Date Date 4.3 5.3 5.8 0.002* 62.8 229.8
(b) Date and
Season
DateFall 2.2 2.8 7.3 0.002 59.5 230.5
DateSpring 1.4 1.7 3.5 0.04
Two models were fitted: (a) without seasonality and (b) with seasonality. Models
were based on a log link function. Shown are the smooth term effective degrees
of freedom (edf), the test statistic of the model smooth terms (F), and the p-values
for the null hypotheses that each smooth term is zero (p). Percentage deviance
explained and Akaike information criterion (AIC) of the GAMS were used to
determine the best model.
Significant values are denoted with *.
2016). The most recent seagrass die-off occurred in 2015, causing
a potential localized regime shift from a densely vegetated
state to a turbid, non-vegetated state (Hall et al., 2016; Hall

Date Correct Total Accuracy

11/26/2017 13 15 86.6%

2/14/2018 10 13 76.9%

2/17/2019 11 13 84.6%

6/25/2019 11 13 84.6%

2/4/2020 9 13 69.2%

Total 54 67 80.6%

significantly affected the size of the plume, explaining 63% of

the deviance, and found no evidence of variation as a function

of season (e.g., fall vs. spring satellite images; Figure 4 and

Table 2). We detected a breakpoint in the sediment plume

coverage of the region in November 2016 (95% CI: September

2015–February 2018; Table 3). This date straddled the Fall 2015

seagrass die-off and the Fall 2017 hurricane Irma. The average

size of the sediment plume before the breakpoint was 163.5 km2

(±26.8 km2

), which increased to 223.5 km2

(±19.9 km2

) postbreakpoint–a 37% increase in area.

Basin Specific Responses to

Disturbances and Sediment Plume

Coverage

When considering our focal basins, Johnson and Rankin, we

found differences in the magnitude, timing and duration of effects

of the sediment plume. Both basins exhibited breakpoints, but

the breakpoint was earlier, and resulted in more severe and

longer lasting effects in the western basin, Johnson (Figure 5). An

ANOVA conducted on the proportion of the basins covered by

the plume, showed a significant basin and breakpoint interaction,

with both Johnson and Rankin having a significantly higher

proportion of basin covered by the plume after the change

point compared to before (Tukey’s HSD < 0.05; Figure 6A

and Table 4). In Johnson, there was a breakpoint in March

2015 (95% CI: October 2014–September 2015; Figure 5 and

Table 3), and sustained high sediment coverage through the last

data point in the time series. Before the breakpoint, an average

of 11.6% (±10.8%) of Johnson was covered by the sediment

plume while 78.6% (±13.4%) of Johnson was covered by the

plume after the breakpoint (Figure 6A). In contrast, for Rankin,

there were two breakpoints. The first breakpoint was February

2017 (95% CI September 2015–November 2017), and the second

was November 2018 (95% CI February 2018–February 2020;

Figure 5 and Table 4). Here, 0% of Rankin was covered by

the plume before the first breakpoint, while 22% (±21%) was

covered by the plume after the first breakpoint (Figure 6A). The

second breakpoint in Rankin represents a sediment contraction,

indicating the short term effects in this basin, and thus, was not

considered in further analyses.

Interaction Between Sediment Plume

Coverage and Changes in Seagrass

Cover

Along with differences in the extent of the sediment plume,

we also found differences in seagrass cover between basins, and

a basin-specific interaction between plume extent and seagrass

cover. For seagrass cover, the interaction between basin and

before and after the change point was significant (Table 4).

Seagrass cover in Johnson basin decreased significantly after its

March 2015 breakpoint (Tukey’s HSD < 0.05; Figure 6B and

Table 4). The average BB score in Johnson dropped from 3.6

(±0.34; approximately 60% cover) to 2.5 (±0.38; approximately

35% cover) after the breakpoint. In contrast, we found no

change in seagrass cover as a function of its February 2017

breakpoint in Rankin. The average BB score of Rankin before

Frontiers in Marine Science | www.frontiersin.org 6 July 2021 | Volume 8 | Article 633240

Rodemann et al. Sediment Plume and Seagrass Resilience

FIGURE 4 | Temporal trend in the sediment plume size in Florida Bay between 2008 and 2020. The black line shows the fitted GAM model and 95% confidence

interval (gray shaded area). The vertical red line shows the breakpoint in sediment plume size, with its 95% confidence interval (red shaded area). The vertical green

line represents the 2015 seagrass die-off and the vertical blue line represents Hurricane Irma.

the breakpoint was 2.7 (±0.61; approximately 40% cover) and

was 2.8 (±0.05; approximately 45% cover) after the breakpoint.

Further, in Johnson, there was a negative correlation between the

proportion of basin covered by the sediment plume and seagrass

cover (r = −0.75, p = 0.005; Figure 6C). There was no correlation

between the proportion of basin covered by the sediment plume

and seagrass cover in Rankin (r = 0.05, p = 0.88; Figure 6C).

DISCUSSION

Anthropogenic and natural disturbances have jointly contributed

to the degradation of seagrass habitats worldwide, including

in Florida Bay, which have resulted in two drought-induced

seagrass die-offs (Fourqurean and Robblee, 1999; Hall et al.,

TABLE 2 | Generalized additive models (GAM) used for the temporal assessment

of sediment plume size.

Term edf Ref.df F p Deviance

explained

AIC

(a) Date Date 4.3 5.3 5.8 0.002* 62.8 229.8

(b) Date and

Season

Date*Fall 2.2 2.8 7.3 0.002* 59.5 230.5

Date*Spring 1.4 1.7 3.5 0.04*

Two models were fitted: (a) without seasonality and (b) with seasonality. Models

were based on a log link function. Shown are the smooth term effective degrees

of freedom (edf), the test statistic of the model smooth terms (F), and the p-values

for the null hypotheses that each smooth term is zero (p). Percentage deviance

explained and Akaike information criterion (AIC) of the GAMS were used to

determine the best model.

Significant values are denoted with *.

2016). The most recent seagrass die-off occurred in 2015, causing

a potential localized regime shift from a densely vegetated

state to a turbid, non-vegetated state (Hall et al., 2016; Hall