tbep-tech / temp-manu

Materials for the manuscript describing temperature trends in Tampa Bay

temp-manu

Materials for the manuscript describing temperature trends in Tampa Bay

Draft: link

temp-manu's Issues

for consideration...include Tampa Bay Waterkeeper in acknowledgements for boat captain time?

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## Acknowledgments

Figure 5

1. Since surface and bottom temperature/salinity were not significantly different consider dropping surface measurements to streamline figure
2. Edit title in (a) to "Change in slope per year, 1975-2022"
3. The triangle that is not outlined (NS) is difficult to find

https://github.com/tbep-tech/temp-manu/blob/main/figs/kendall.png

Figure 4

Consider using more distinct colors for top and bottom measurements https://github.com/tbep-tech/temp-manu/blob/main/figs/meteowqraw.png

1975 rainfall

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Long-term meteorological data from Tampa International Airport showed significantly increasing trends for air temperature and precipitation ([@fig-meteowqraw]). Mean annual air temperature has increased by `r airtempslo` $^\circ$C per year (`r airtemppvl`, $R^2$ `r airtemprsq`). Mean annual air temperature in 1975 was `r airtempstr` $^\circ$C, whereas current mean annual air temperature in 2022 was `r airtempend` $^\circ$C, showing an overall increase in the period of record of `r airtempdif` $^\circ$C. Similarly, total precipitation has increased by `r prpslo` mm per year (`r prppvl`, $R^2$ `r prprsq`). Total precipitation in 1975 was `r prpstr` mm, whereas current total precipitation in 2022 was `r prpend` mm, showing an overall increase in the period of record of `r prpdif` mm. Trends in total annual hydrologic load from 1985 to present followed total annual precipitation, although the linear model was not significant likely due to a shorter period of record. The SPI showed notable anomalies in precipitation, with pronounced rainy periods in the early 1980s, late 1990s, 2005, and the last ten years.

avg annual rainfall hasn't really changed over the period of record tho, no? it is a bit misleading to reference 1975 as a baseline since it was a significant drought (see usgs records, https://pubs.usgs.gov/wri/1978/0029/report.pdf for example)

Seagrass GAM comments for the revision

• My first thought is to constrict the seagrass analyses to the FIM data since all data are collected at the same station and the depths are all suitable for seagrass growth; it will simplify the message, plus the inconclusive results of the EPC and Pinellas Co. models don't make a compelling reason to keep them. The SWFWMD seagrass cover and transect data would still be used to demonstrate seagrass change over time.

• The analyses for light attenuation address the reviewer's comments but don't really add anything to the story (especially for the FIM data), so I suggest leaving those as responses to comments rather than including them in the revised manuscript. The reviewers seemed to be most concerned about statements that light availability (as well as nitrogen, chlorophyll a) was relatively constant, Maybe simple graphs by year, dataset, and bay segment (without incorporating the seagrass data) to account for temporal differences in these factors would suffice?

• I see what you're getting at with the "heat map" graphs of partial effects by month and stressor, but it took me awhile to decipher it. Is there a simpler way to display these data? If kept, change the y axis labels to 2,5,7, etc. so that it's clear that it's by month.
  

depths of FIM samples

Another distinction of the FIM data/models are that the depths of the samples are compatible with seagrass growth.

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Our relatively simple modeling approach provided some evidence that climate-related stressors can explain the recent loss in seagrass in Tampa Bay. The models did not provide a consistent, nor statistically powerful, explanation that increasing temperature and decreasing salinity were key drivers. However, evaluating all models together does suggest a pattern that demonstrates the value of considering multiple datasets and models to explain noisy ecological patterns. Model results for the EPC and FIM datasets both suggested that increasing temperature and decreasing salinity were associated with potential seagrass loss post-2016, described primarily using separate interaction terms of temperature or salinity with time period. For the EPC model, the interaction term was not significant for temperature, whereas the interaction was marginally significant for the salinity metric such that a negative association was observed post-2016 as compared to pre-2016 where frequency occurrence of seagrass declined with the increasing number of days when salinity was below 25 ppt. Likewise, the FIM models had a significant interaction term for the association of the temperature with time period and a marginally significant interaction term for the association of salinity with time period, such that percent cover of seagrasses showed a decline with increasing temperature and decreasing salinity post-2016. An important distinction between the EPC and FIM models is that the former evaluated the number of days above/below thresholds each year to quantify increases in annual stress associated with temperature and salinity, whereas the latter evaluated observed temperature and salinity values at the time of seagrass sampling. As such, both models attempted to describe the role of these stressors on potential seagrass change, but use different independent variables given the different sampling designs of each monitoring programs. These differences highlight challenges describing noisy relationships in long-term ecological datasets, while also demonstrating the utility of our weight-of-evidence approach to describe these relationships.

Figure 7

Consider using a transformation on the FIM % cover data especially considering the high number of zeros. I've used log(x+1) in previous data analyses. https://github.com/tbep-tech/temp-manu/blob/main/figs/sgmods.png

Florida Bay hypersalinity

The hypersaline conditions in Florida Bay are likely not due to just drought; evapotranspiration and wave-driven circulation are major drivers in the hydrologically distinct basins of FB, and lack of effective restoration of freshwater sheet flow (as of yet) into the north central region of the bay complicate the issue. Suggest deleting the first part of that sentence - the point is still made without mentioning drought. Hypersalinity may continue to be a chronic issue there regardless of rainfall/freshwater flow.

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Lastly, our result showing that salinity has decreased in Tampa Bay is generally contrary to expectations for coastal systems consistent with sea-level rise projections [@alarcon2024]. Salinity changes with sea-level rise have caused numerous alterations of subtidal and nearshore habitats [@brinson1995; @white2017]. In southwest Florida, the most common ecological example is migration of mangroves upland as porewater salinity and water levels have gradually increased over the past few decades [@borchert2018]. Alteration of salinity regimes for surface and groundwater resources are also well documented. In Florida Bay, for example, widespread decline of *Thalassia testudinium* has been partially attributed to elevated salinity levels beyond the optimal range for the species [@hall2016]. Although drought has been implicated in the hypersaline conditions observed in Florida Bay, sea level rise is expected to further alter salinity dynamics in the region. @dessu2018 noted that sea level rise is expected to have the largest effect on salinity changes during periods of low freshwater outflow from the Florida Everglades, emphasizing that measured salinity represents the relative contributions of oceanic and freshwater surface waters. In Tampa Bay, the long-term trends of decreasing salinity suggest that the hydrologic load into the system has had a greater influence on salinity regimes than the effects of sea-level rise. This hypothesis is supported by our assessment of precipitation patterns over time, where the long-term increase is inversely correlated with the decrease in salinity.

hypothesis

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This paper describes a comprehensive assessment of long-term trends in water temperature and salinity in the Tampa Bay estuary over the last fifty years. Three datasets of varying sample design and temporal coverage were used to assess the primary hypothesis that Tampa Bay is trending towards hotter and fresher conditions that are likely pushing seagrasses beyond their optimal tolerance ranges. This analysis was supported by 30-year seagrass datasets describing approximate biennial coverage of all seagrasses, annual transect monitoring describing cover of individual species, and synoptic seagrass data collected with the water quality surveys. Specific focus was on the periods prior to and after 2016, when seagrasses recovered baywide and then declined despite water quality conditions remaining relatively stable. Our primary goal was to relate recent seagrass changes to climate stressors to provide a motivating example for the management community in the Tampa Bay region that a shifting ecological baseline presents new challenges beyond the known success story of long-term bay recovery. The results are also provided as a cautionary example of the subtle but increasing role of climate-related stressors on the resiliency of estuarine systems at the tropical-temperate boundary, prompting a reassessment of existing management paradigms to accommodate current and anticipated future conditions.

was our hypothesis really that tampa bay was getting fresher? or was that informed by preliminary analysis? it seems like the conventional wisdom of local managers is that the bay would be saltier and some lit reviews concur that a local expression of slr trends saltier, despite global salinity trending fresher (given ice melt, etc. ) see https://doi.org/10.1016/j.ocecoaman.2023.106490

i like that the conclusion notes that this finding is somewhat surprising and wonder if there might be a benefit from reframing the hypothesis here.

additional references to consider

1. Hall et al. 1999 - Florida Bay seagrass loss paper: https://link.springer.com/article/10.2307/1353210
2. Indian River paper you recently shared on macroalgae replacing seagrass: https://www.sciencedirect.com/science/article/pii/S1470160X23011779
3. Switzer et al. 2011, response of estuarine nekton to Bishop Harbor spill: https://aquadocs.org/handle/1834/41127

Title

Suggestion: Hot and fresh: evidence of climate-related suboptimal conditions for seagrass in a large Gulf coast estuary

Physical vs. physicochemical

Throughout the manuscript, changing "physical" conditions due to climate change are referenced. Since we're using temperature and salinity as metrics "physicochemical" conditions might be more appropriate.

Figure 6 and Stressor metrics

Reference dataset used for these figures in the figure legend - EPC, correct?
https://github.com/tbep-tech/temp-manu/blob/main/figs/mixeff.png

Also reference dataset used in text here to keep everything straight:

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### Stressor metrics

Figure 1 - map

Change the red points in panel a to black to avoid red/green issues
https://github.com/tbep-tech/temp-manu/blob/main/figs/map.png