How Reef Shark Connectivity Can Inform Conservation Writing Sample

As the apex predators of coral reef ecosystems, reef sharks are crucial to the health and equilibrium of these delicate ecosystems. Overfishing and habitat loss, on the other hand, have led to a decline in many reef shark populations over the past few years. By studying their connectivity, conservation efforts for reef sharks can be informed. The movement of individuals between distinct populations or habitats is referred to as connectivity (Osgood & Baum, 2015). By understanding how various populations of reef sharks are associated, scientists can recognize key regions for preservation and the board. Hence, this essay looks to show how the connectivity in Reef Shark connectivity can be used to inform the conservation of this marine biology.

For conservation to occur, according to Dwyer et al. (2020), the marine protected areas (MPAs) have to be a large area of about more than 50km and a minimum of about 10km. With this, it can be conducive for the sharks to move around. It is because one of the most important factors in determining whether MPAs will be able to achieve conservation goals is the relationship between the scale of a species’ movements and the size of the MPA locally (Martín et al., 2020). Therefore, to reduce the unsustainable levels of fishing pressure and other anthropogenic stressors placed on coral reef sharks, particularly in areas where traditional fisheries management is either inadequate or has not been successful in restoring them. It is also affected by the rate of transition.

Another way to look at the other ways reef sharks can be improved. With involves making decisions using the local conservations and the trans-pacific breaks using genomes. The genome-wide genetic data that can answer difficult ecological and evolutionary questions have emerged due to the shift from conservation genetics to conservation genomics (Pazmiño et al., 2018). It is difficult to document genetic differences in marine environments because there are few obvious barriers to gene flow, especially for species that migrate a lot, like sharks. Population structure in marine organisms can be attributed to barriers like ocean currents, geographical distance, habitat discontinuity, or differential dispersal ability.

Due to their inherent susceptibility to overfishing, sharks are among the most endangered marine fish. Utilizing behavioural methods to identify biological hotspots remains both a challenge and an opportunity, particularly for species whose meat or fins are highly prized and whose political will to conserve is weak (Jacoby et al., 2022). Identifying areas and associated environmental correlates where animals’ movements bring them back to the same location semi-regularly is an important first step toward conserving these animals, even for species that spend months in pelagic and high-seas habitats. According to Lara-Lizardi et al. (2022), for studies of open ocean and pelagic shark movements and habitat use, the Northwestern Pacific region needs more data. However, commercial fishing places a significant strain on this region. As a result, shark movement data from this region has significant implications for management and conservation, particularly for endangered species (Lédée et al., 2021). Here, people give the principal information on occasional residency and developments of scalloped hammerhead, the concerns about the endangered and exploited reef shark species.

Managing exploited species effectively and addressing conservation concerns for threatened species is crucial. Fish migration and the movements that accompany it are important determinants of population structure because they are key ways separate populations mix together (McCauley et al., 2012). This can be accomplished by learning about the large predators, who frequently possess high levels of mobility and can use multiple habitats. Surprisingly little is known about how important ecosystem connectivity processes are influenced by predator mobility. For instance, if researchers discover that a particular population of reef sharks is connected to several other populations, they might prioritize conserving that area to safeguard multiple populations. In contrast, conservation efforts may focus on enhancing connectivity with other populations if a population is isolated (Jacoby et al., 2022). Additionally, connectivity studies can assist in identifying areas of high fishing pressure or habitat destruction as potential threats to reef shark populations. By comprehending their movement patterns, researchers can identify areas where reef sharks are most vulnerable to these threats and target conservation efforts accordingly.

To conclude, in some species of reef sharks, network analysis revealed previously unknown connections between populations. In others, it supported stock discrimination by identifying important nodes and routes for connectivity; as a result, the important implications for understanding how ecosystems work, managing large populations of predators, and designing conservation measures to protect entire ecosystems. Resource managers, policymakers, and ecologists must work to understand how large mobile predators create connectivity and how their depletion may affect the integrity of these linkages in the face of widespread declines. In general, examining the connectivity of reef sharks can aid conservation efforts and ensure the long-term survival of these significant apex predators and the coral reef ecosystems in which they live.

References

Dwyer, R. G., Krueck, N. C., Udyawer, V., Heupel, M. R., Chapman, D., Pratt, H. L., Jr, Garla, R., & Simpfendorfer, C. A. (2020). Individual and population benefits of marine reserves for reef sharks. Current Biology: CB, 30(3), 480-489.e5. https://doi.org/10.1016/j.cub.2019.12.005

Jacoby, D. M. P., Watanabe, Y. Y., Packard, T., Healey, M., Papastamatiou, Y. P., & Gallagher, A. J. (2022). First descriptions of the seasonal habitat use and residency of scalloped hammerhead (Sphyrna lewini) and Galapagos sharks (Carcharhinus galapagensis) at a coastal seamount off Japan. Animal Biotelemetry, 10(1). https://doi.org/10.1186/s40317-022-00293-z

Lara-Lizardi, F., Hoyos-Padilla, E. M., Klimley, A. P., Grau, M., & Ketchum, J. T. (2022). Movement patterns and residency of bull sharks, Carcharhinus leucas, in a marine protected area of the Gulf of California. Environmental Biology of Fishes, 105(12), 1765–1779. https://doi.org/10.1007/s10641-022-01223-x

Lédée, E. J. I., Heupel, M. R., Taylor, M. D., Harcourt, R. G., Jaine, F. R. A., Huveneers, C., Udyawer, V., Campbell, H. A., Babcock, R. C., Hoenner, X., Barnett, A., Braccini, M., Brodie, S., Butcher, P. A., Cadiou, G., Dwyer, R. G., Espinoza, M., Ferreira, L. C., Fetterplace, L., … Simpfendorfer, C. A. (2021). Continental‐scale acoustic telemetry and network analysis reveal new insights into stock structure. Fish and Fisheries (Oxford, England), 22(5), 987–1005. https://doi.org/10.1111/faf.12565

Martín, G., Espinoza, M., Heupel, M., & Simpfendorfer, C. A. (2020). Estimating marine protected area network benefits for reef sharks. The Journal of Applied Ecology, 57(10), 1969–1980. https://doi.org/10.1111/1365-2664.13706

McCauley, D. J., Young, H. S., Dunbar, R. B., Estes, J. A., Semmens, B. X., & Micheli, F. (2012). Assessing the effects of large mobile predators on ecosystem connectivity. Ecological Applications: A Publication of the Ecological Society of America, 22(6), 1711–1717. https://doi.org/10.1890/11-1653.1

Osgood, G. J., & Baum, J. K. (2015). Reef sharks: recent advances in ecological understanding to inform conservation: Sharks on coral reefs. Journal of Fish Biology, 87(6), 1489–1523. https://doi.org/10.1111/jfb.12839

Pazmiño, D. A., Maes, G. E., Green, M. E., Simpfendorfer, C. A., Hoyos-Padilla, E. M., Duffy, C. J. A., Meyer, C. G., Kerwath, S. E., Salinas-de-León, P., & van Herwerden, L. (2018). Strong trans-Pacific break and local conservation units in the Galapagos shark (Carcharhinus galapagensis) revealed by genome-wide cytonuclear markers. Heredity, 120(5), 407–421. https://doi.org/10.1038/s41437-017-0025-2

Effect Of Change In Temperature On The Spring Constant Of A Metallic Steel Spring Free Sample

Aim

This physics investigation aims to examine the effect of temperature change on the spring constant of a metallic steel spring.

Introduction

This investigation is linked to my long interest in and participation in Bungee jumping. In this game, I am particularly interested in how people are able to jump from great heights on elastic cords. This investigation is linked to my long interest in and participation in Bungee jumping. In this game, I am particularly interested in how people are able to jump from great heights on elastic cords. I realized that a person’s weight on the spring is similar to a mass hanging on a spring, and the extension of this spring could be a subject weight or force that acts on it.

The spring constant is the force ratio of a spring to its displacement (Dwivedi 1). The spring constant is calculated through the following general formula;

Figure 1: A Representation of Loaded Spring

Different factors could influence the constant of the spring represented in Figure 1 above. According to Garrett (2), the spring’s length, geometry, and material properties could directly influence the spring constant. Additionally, temperature could affect the spring constant due to changes in thermal expansion when the spring is heated or cooled. The interest of this investigation is to increase the temperature and examine the impact of this increase on the spring constant of a steel spring while controlling the spring’s length, geometry, and material properties.

Hypothesis

It is hypothesized that the spring constant of the steel spring will decrease with an increase in temperature. This hypothesis is supported by the study of Werner et al. (2), which supposes that when the temperature in an elastic body is increased, the metallic lattice’s atoms tend to vibrate with increased energy, making the atoms occupy more space. As a result, the spring’s length increase, leading to a reduction of stiffness.

Variables

Independent Variable

The Independent variable in this scientific investigation is temperature. The temperature will be varied from 25⁰C to 50⁰C increments of 5⁰C using the hot water and measured by mercury thermometer (± 0.1⁰C).

Dependent Variable

The spring constant of the steel spring will be the dependent variable. The calculation of this variable will be based on the mass of a 100 g mass and the change in the length of the spring.

Control Variable

The major control variables in this scientific investigation are presented in table 1.

Table 1: Main Control Variables, their Impact, and Control Mechanism

Control Variable	Impact of the Variable	Mechanism of the Control
Mass	The size of the mass attached to the steel spring will directly affect the extension. Thus, the use of different masses will lead to inconsistent extensions across the trials.	One 100 g mass will be used in all the trials.
Steel spring	Variations of springs will vary the spring constants since different springs could have different properties.	A single spring will be used across all the trials of this investigation.
Experimental technique	Changing the techniques of conducting the experiment could lead to inconsistent results; for instance, heating the spring while hanging on the clamp stand in some steps and heating the spring in water before suspending on the spring.	A unified technique for performing the experiment will be ensured and maintained across all the trials.
Environmental temperature	Fluctuations in environmental temperature can lead to compressions and tensions of the spring leading to inconsistent extensions across the trials.	The entire experiment will be conducted in a single room to ensure maximum control in environmental temperature conditions.

Apparatus

A stopwatch

A clamp stand

An electronic beam balance

A steel spring

A wire to suspend the spring

A meter ruler

A 100 g mass

A hot plate

A beaker

Distilled water

A mercury thermometer

Method

The spring was then suspended vertically on the clamp stand, as depicted in Figure 1, ensuring that it did not touch any surface.

The 100 g mass was then placed onto the lower part of the spring, and its initial extension was measured using the ruler.

The steel spring was then placed into the water, placed in a beaker, and heated on a hot plate to a temperature of 25⁰C with the help of the mercury thermometer.

The spring was then suspended on the clamp stand as in step 1, and the extension of the spring was measured.

Steps 3-4 were repeated for four more trials.

Steps 3-5 were repeated at temperatures of 30⁰C, 35⁰C, 40⁰C, 45⁰C, and 50⁰C, recording the results for each trial in the raw data table.

Set-up

Risk Assessment

The steel spring and the rest of the equipment were handled with prime care to prevent unprecedented injuries or damages.

The hot steel spring and beaker were handled with pliers and a beaker holder to prevent accidental burns.

Protective gear, including safety goggles and hand gloves, was worn during the entire experiment to reduce the chances of injuries.

Raw Data

Initial extension of the spring, e₁ = 3.9 cm

Table 2: Extension of the Metallic Steel Spring at different Temperatures

Temperature, T	Extension of the Metallic Steel Spring, e₂
Temperature, T	Trial 1	Trial 2	Trial 3	Trial 4	Trial 5
50.0	5.5	5.4	5.4	5.3	5.5
45.0	5.3	5.2	5.1	5.2	5.3
40.0	5.0	5.1	5.0	4.9	5.2
35.0	4.7	4.8	4.7	4.6	4.7
30.0	4.5	4.6	4.5	4.7	4.5
25.0	4.0	4.2	4.1	4.2	4.1

Data Processing

Calculations of Change in Length, x

The change in length of the steel spring corresponding to the various conditions of temperature was first determined as the difference between the initial and final extensions of the spring when loaded by the 100 g mass.

The measurement corresponding to the first trial of 50.0⁰C was used in a sample calculation;

Table 3: Change in Lengths of the spring at different Temperatures

Temperature, T	Change in lengths of the Metallic Steel Spring, x
Temperature, T	Trial 1	Trial 2	Trial 3	Trial 4	Trial 5
50.0	0.016	0.015	0.015	0.014	0.016
45.0	0.014	0.013	0.012	0.013	0.014
40.0	0.011	0.012	0.011	0.01	0.013
35.0	0.008	0.009	0.008	0.007	0.008
30.0	0.006	0.007	0.006	0.008	0.006
25.0	0.001	0.003	0.002	0.003	0.002

Calculations of Average Change in Lengths and Corresponding Uncertainty

The average change in length at the different temperatures and the corresponding uncertainties were then calculated using the following general formulas;

Table 4: Average Change in Lengths and Corresponding Uncertainty at Different Temperatures

Temperature, T	Average Change in Length, (m)	Uncertainty,
50.0	0.0152	0.0010
45.0	0.0132	0.0010
40.0	0.0114	0.0015
35.0	0.0080	0.0010
30.0	0.0066	0.0010
25.0	0.0022	0.0010

Determination of Spring Constant, k

The spring constant was calculated as a function of force due to the mass suspended onto the spring and the average change in length;

The corresponding uncertainty of the spring constant was then calculated as a function of the uncertainty of the mass and the uncertainty of the change in length of the steel spring;

Table 5: Spring Constant of the Steel Spring and Uncertainties at Different Temperatures

Temperature, T	Spring Constant of the Steel Spring, k (N/m)	Uncertainty, ∆k (N/m)
50.0	64.54	0.067
45.0	74.32	0.077
40.0	86.05	0.133
35.0	122.63	0.126
30.0	148.64	0.153
25.0	445.91	0.456

Graph of Spring Constant against Temperature

The data in table 4 was used to create a linear graphical plot of spring constant against the temperature. The uncertainties of the spring constant were used on the linear plot as the error bars. This graph was created in Microsoft Excel.

Figure 3: Linear Plot of Spring Constant of Steel Spring against Temperature

The linear graph in Figure 3 above shows a downward trend in the spring constant of the steel spring as the temperature is increased, defined by a slope of -12.379. The square regression constant (0.6377) was greater than 0.5, indicative a strong negative relationship between the spring constant and temperature. Additionally, the error bars on the linear plot were very small in size, indicative of high reliability and accuracy both in the method used and results collected and processed in this scientific investigation.

Conclusion

This investigation was purposed to examine the effect of temperature change on the spring constant of a metallic steel spring. It had been hypothesized that the spring constant of the steel spring would decrease. A lab-based investigation was designed using a single steel spring, heated at different temperatures, hanged on a clamp stand, and loaded with a 100 g mass. The resulting changes in the lengths of the springs were used to calculate the spring constants at different temperatures. The processed results revealed that spring constants of the steel spring decrease with a rise in temperature. Ideally, the spring constant was 445.91 N/m at 25°C and 64.54 N/m at a temperature of 50°C. The decrease in spring constant on increasing temperature was associated with thermal expansion as the temperature increased. The thermal expansion weakened the atomic bonds of the spring, making the atoms occupy more space and increasing cross-sectional area, which reduced the spring’s stiffness, hence the reduction in spring constant. The investigation provided a better understanding of the basic relationship between temperature changes and a metallic spring’s spring constant. These results could be used in different fields, including the design of mechanical devices that are temperature sensitive.

Evaluation

The experiment of this investigation was performed under several controlled conditions, a factor that favored increased the accuracy of final results. Additionally, experimental data of extensions of the spring were collected at five different temperatures providing a comprehensive and valid evaluation of the effect of temperature on the spring constant. However, there were some limitations, which may have affected the results, as depicted below.

Table 6: Main Limitations, their Impact, and Proposed Improvements

Limitation	Significance	Proposed Improvement
Systematic errors	The apparatus used to measure the length of the spring had a high uncertainty, leading to possible measurement errors.	Apparatus with higher precision could be used, such as the vernier callipers in place of the meter ruler, for more accurate results.
Limitation of type of spring	Only one type of metallic steel spring was used, limiting the validity of the investigation.	The experimental process could be repeated with different types of steel springs for a more comprehensive and valid investigation.

Proposed Extension

This scientific investigation could be extended further in different ways. For instance, the experimental process could be repeated with a higher range of temperatures to find out whether there exists any threshold beyond which an increase in temperature will not reduce the spring constant’s magnitude. In addition, the effect of temperature on the spring constant could be evaluated with other types of springs, such as rubber springs.

Works Cited

Dwivedi, Kamal. Spring Constant: Definition, Formula, Unit, Calculation. 7 Jan. 2023, www.mechical.com/2022/07/spring-constant.html.

Garrett, Steven L. “Elasticity of Solids.” Understanding Acoustics, 2020, pp. 179–233, https://doi.org/10.1007/978-3-030-44787-8_4.

Werner, Brian T., Bonnie R. Antoun, and George B. Sartor. “Thermal Degradation of Extension Springs.” Challenges in Mechanics of Time-Dependent Materials, Volume 2: Proceedings of the 2015 Annual Conference on Experimental and Applied Mechanics. Springer International Publishing, 2016.

Effects Of Asthma On Covid-19 Patients Essay Example

Annotated Bibliography

Broadhurst, R., Peterson, R., Wisnivesky, J. P., Federman, A., Zimmer, S. M., Sharma, S., … & Holguin, F. (2020). Asthma in COVID-19 hospitalizations: an overestimated risk factor? Annals of the American Thoracic Society, 17(12), 1645-1648.

https://www.atsjournals.org/doi/full/10.1513/AnnalsATS.202006-613RL

Broadhurst et al. (2020) sought to establish whether asthma is a risk factor to covid 19 patients and whether it increases hospitalization. The researchers conducted a thorough analysis of various literature review materials. The results of the study indicated that the likelihood of hospitalization among covid 19 patients who have asthma was actually lower compared to those who had influenza. These findings denote that Asthma does not increase the likelihood of hospitalization among covid 19 patients. This study is particularly important to my research topic since it provides a unique perspective on the effects of asthma on covid 19 patients, particularly on hospitalization rate.

Choi, Y. J., Park, J. Y., Lee, H. S., Suh, J., Song, J. Y., Byun, M. K., … & Park, H. J. (2021). Effect of asthma and asthma medication on the prognosis of patients with COVID-19. European Respiratory Journal, 57(3).

https://pubmed.ncbi.nlm.nih.gov/32978309/

Choi et al. (2021) showcases the research finding of a study conducted on 7950 covid 19 patients. Out of these 218 of them had an underlying asthmatic condition. The results of the study further revealed that Asthma was not the sole risk factor for hospitalization among Covid 19 patients. Also, the results revealed that covid 19 patients who had asthmatic conditions had a larger hospital bill compared to those who didn’t have asthma due to the constant oral short-acting agonists that the patient is given. This article is an important resource since it displays the effect of Asthma on Covid 19 hospital bills and will greatly aid in my research.

Liu, S., Cao, Y., Du, T., & Zhi, Y. (2021). Prevalence of comorbid asthma and related outcomes in COVID-19: a systematic review and meta-analysis. The Journal of Allergy and Clinical Immunology: In Practice, 9(2), 693-701.

https://pubmed.ncbi.nlm.nih.gov/33309934/

Liu et al. (2021) investigated the effects of asthma on Covid 19 patients. The research used a systematic review to analyze 131 studies. The findings of the research indicated that most patients who have Covid 19 also have asthma according to the studies done. The studies presented information from different countries across the globe. Further the results of the study revealed that Covid 19 patients who had asthma were less likely to die compared to Covid 19 patients who did not have asthma. I find this source material to be quite useful in my research since it highlights the effects of asthma on the mortality rate of Covid 19 patients.

Murphy, R. C., Lai, Y., Barrow, K. A., Hamerman, J. A., Lacy-Hulbert, A., Piliponsky, A. M., … & Hallstrand, T. S. (2020). Effects of asthma and human rhinovirus A16 on the expression of SARS-CoV-2 entry factors in human airway epithelium. American Journal of respiratory cell and molecular biology, 63(6), 859-863.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790138/

Murphy et al. (2020) paper examines how the human rhinovirus A16 (HRV-A16) and asthma affect the expression of SARS-CoV-2 entrance factors in the human airway epithelium. Asthma or HRV-A16 infection had no effect on the expression of the SARS-CoV-2 entrance factors ACE2 and TMPRSS2. Nevertheless, compared to non-asthmatic donors, airway epithelial cells from asthmatic donors expressed more neuropilin-1 (NRP1) which is another SARS-CoV-2 entrance factor. Both donors with asthma and those without it had higher NRP1 expression as a result of HRV-A16 infection. According to the study, NRP1 may be a possible target for the creation of fresh treatments aimed at lessening the harshness of COVID-19 results in asthmatic patients. This source material is important in providing a deeper understanding of Covid 19 and asthma.

Song, J., Zeng, M., Wang, H., Qin, C., Hou, H. Y., Sun, Z. Y., … & Liu, Z. (2021). Distinct effects of asthma and COPD comorbidity on disease expression and outcome in patients with COVID‐19. Allergy, 76(2), 483-496.

https://pubmed.ncbi.nlm.nih.gov/32716553/

Song et al. (2021) is a research article that discusses the effects of asthma and COPD on Covid 19 patients. The results of the study revealed that asthma was not a risk factor for Covid 19 patients whereas COPD posed a greater risk factor. Further, the researchers examined various underlying processes that would explain the observed variations between the two groups, such as variations in lung function and inflammatory response. The results emphasized the necessity of managing individuals with COVID-19 and pre-existing respiratory diseases including asthma and COPD on an individual basis. This source is good reference material since it is detailed and informative.

References

https://www.atsjournals.org/doi/full/10.1513/AnnalsATS.202006-613RL

https://pubmed.ncbi.nlm.nih.gov/32978309/

https://pubmed.ncbi.nlm.nih.gov/33309934/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790138/

https://pubmed.ncbi.nlm.nih.gov/32716553/