Conceptions of Long-Term Data Among Marine Conservation Biologists and What Conservation Paleobiologists Need to Know

Abstract

Marine conservation biologists increasingly recognize the value of long-term data and the temporal context they can provide for modern ecosystems. Such data are also available from conservation paleobiology, but the enormous potential for integration of geohistorical data in marine conservation biology remains unrealized. The lack of a common language for data integration and a tendency in each field to measure different variables, at scales that may differ by orders of magnitude, make integration difficult. To better understand how conservation paleobiology can maximize its potential, we conducted a survey of marine conservation biologists working in the United States.

The respondent population included 90 marine conservation biologists from a variety of workplaces (e.g., governmental, academic) and experience levels (<5 years to >25 years). Survey responses indicated that our fields share common conservation goals (e.g., conservation of biodiversity and ecosystem services) and use long-term data in similar ways (e.g., to establish baselines and elucidate trends and patterns). Respondents, however, mostly considered “long term” to refer to decadal timescales and rarely mentioned geohistorical data.

Overall, the survey results suggest conservation paleobiologists have much work to do before geohistorical data are regularly accepted and applied in marine conservation biology. We highlight four takeaways from the results of our survey that can help conservation paleobiologists integrate their data into marine conservation practice. (1) Conservation paleobiologists must improve their communication with marine conservation biologists inside and outside of academia. (2) One of the most promising areas for integration is investigating climate change and its ecological implications. (3) The types of long-term data that marine conservation biologists want and need are deliverables conservation paleobiologists can provide. (4) Conservation paleobiologists must be proactive in addressing the barriers that hinder the application of long-term data in conservation practice.

Appendices

Appendix 1: Survey Questions

Demographics and Professional Information

• 1. With which race/ethnicity do you identify?

• White

• Black

• Asian

• Hispanic

• Other: _____________

• 2. With which gender do you identify?

• Male

• Female

• Other: _____________

• 3. Please list up to three fields (e.g., fisheries biology, historical ecology, etc.) with which you identify.

• 4. Which of the following best describes your workplace?

• Government

• Nongovernmental organization

• Academia

• Other:___________

• 5. Which of the following best describes your highest completed level of education?

• a. Doctorate

• b. Master’s

• c. Bachelor’s

• d. Other: _____________

• 6. How many years of experience do you have in marine conservation?

• <5

• 5–10

• 10–15

• 15–20

• 20–25

• >25

• 7. Please describe your work as it relates to marine conservation in one sentence or less.

• 8. At what level of biological organization does your work primarily focus?

• Population

• Species

• Community

• Ecosystem

• Biome

• Other: _____________

Goals and Approaches

• 9. Please list up to three primary goals of the field of marine conservation (e.g., preservation of biodiversity) in your opinion.

• 10. What are the cutting-edge approaches currently being practiced in marine conservation to achieve the goals you mentioned in the previous question?

Long-term Data: Definitions and Sources

• 11. In your opinion, to what timescales does the phrase “long-term data” typically refer in the conservation community?

• Days

• Weeks

• Months

• Years

• Decades

• Centuries

• Thousands of years

• Tens of thousands of years

• Hundreds of thousands of years

• Millions of years

• Unsure

• 12. In your opinion, what is the importance of long-term data for achieving the goals of marine conservation?

• 13. If you use long-term data, how do you use it and why do you use it? Or, if long-term data are not considered in your work, why not?

• 14. Please list five sources of long-term data and indicate whether you have used each one in your own research.

• 15. Considering the sources of long-term data you listed previously, at what time scale(s) are data from these sources most useful?

	Days	Weeks	Months	Years	Decades	Centuries	Millennia	104 years	105 years	106 + years	Unsure
Source A	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]
Source B	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]
Source C	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]
Source D	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]
Source E	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]

Long-term Data and Ecological Stressors

• 16. The Millennium Ecosystem Assessment (2005) identified the following five most-important stressors in ecosystems. Please rate each stressor’s importance in marine conservation biology (one being highest importance and five being lowest importance).

	Importance
	1	2	3	4	5	Unsure
Pollution	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]
Habitat change	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]
Climate change	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]
Overexploitation	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]
Invasive species	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]

• 17. Given that these stressors interact in complex ways, please identify and briefly describe the interaction that is most pressing to understand in marine conservation, in your opinion (e.g., the additive interaction between invasive species and climate change).

• 18. Which of the long-term data sources that you identified previously do you believe can be used to address the five stressors or their interactions?

	A	B	C	D	E
Pollution	[ ]	[ ]	[ ]	[ ]	[ ]
Habitat change	[ ]	[ ]	[ ]	[ ]	[ ]
Climate change	[ ]	[ ]	[ ]	[ ]	[ ]
Overexploitation	[ ]	[ ]	[ ]	[ ]	[ ]
Invasive species	[ ]	[ ]	[ ]	[ ]	[ ]
Unsure	[ ]	[ ]	[ ]	[ ]	[ ]

• 19. Please select one or more timescales of data that would be needed to best address each stressor, in your opinion.

	Days	Weeks	Months	Years	Decades	Centuries	Millennia	104years	105years	106+years	Unsure
Pollution	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]
Habitat change	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]
Climate change	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]
Over-exploi-tation	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]
Invasive species	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]	[ ]

Temporal vs. Spatial Data

One important reason for using long-term temporal data is to produce baselines against which current conditions in ecosystems can be compared, but spatial data also are frequently used as references against which to judge current conditions at a specific location. The following two questions are intended to help us understand the balance between use of temporal and spatial data to produce baselines and reference conditions in marine conservation.

• 20. If you use reference conditions or baselines in your research/conservation work, please list three types of data sources that you use to produce them (e.g., reference sites, monitoring records, etc.).

• 21. In your opinion, are spatial and temporal data of equal value in establishing reference conditions and baselines? Please explain briefly.

Problems and Challenges with Applying Long-term Data

• 22. Are there types of long-term data that would be useful, but that aren’t currently available or of which you would want more? If so, please give an example.

• 23. What barriers (e.g., communication, funding, data availability, etc.) have you experienced (or do you perceive to exist) in applying long-term data to marine conservation?

Appendix 2: Survey Population Selection

First Solicitation

In order to establish our survey population, we searched the internet for organizations conducting research or management in marine systems. All institutions, agencies, laboratories, etc. were based in the United States and included National Estuarine Research Reserves (e.g., Chesapeake Bay NERR), Sea Grant programs (e.g., Alaska Sea Grant), governmental departments (e.g., Alaska Department of Fish and Game) and their divisions (Division of Habitat), and academic marine laboratories (e.g., Darling Marine Center, University of Maine). A full list of all organizations contacted for the survey can be downloaded at http://doi.org/10.7298/X4VM4965.

For each organization, we contacted the director, president, or positional equivalent via email prior to the activation of the survey (n = 202). If we received a positive response (agreement to distribute the survey) from an organization (n = 54), we sent a solicitation to the contact upon activation of the survey. If we did not receive an initial response (n = 136), we sent a second email to the contact with a solicitation at the time of survey activation to encourage participation. We did not contact those who responded negatively (n = 12) to the initial solicitation. The survey was open September–November 2015.

Second Solicitation

We opened the survey a second time during January 2016. In this period, we sent a solicitation to the Ecological Society of America listserv, ECOLOG-L, in an attempt to reach marine conservation biologists who may not have been reached by our first solicitation. ECOLOG-L is distributed internationally, however the solicitation explicitly requested participation from researchers and managers working in the United States of America.

Third Solicitation

During April 2016, we opened the survey for a third time, with a goal of increasing participation from the academic demographic. We sent a solicitation to the President of the National Association of Marine Laboratories (NAML) who kindly agreed to distribute the survey to the directors of the member laboratories. NAML includes governmental laboratories but its more than 50 members are primarily associated with academia. A full list of all organizations contacted for the survey can be downloaded at http://doi.org/10.7298/X4VM4965. Visit http://www.naml.org/index.php for more information on NAML.

Appendix 3: Categorization of Responses

We categorized the survey responses for all free response and short answer questions prior to analysis. For each question, all three authors reviewed each of the categories to which responses were assigned and when disagreements occurred the categories were discussed until a consensus was reached. Similarly, responses to free response and short answer questions were reviewed collectively and placed within categories after the authors reached agreement. Responses were categorized for the following 11 questions: 3, 7, 9, 10, 12, 14, 17, and 20–23.

Question 3: Please list up to three fields/scientific disciplines (e.g., fisheries biology, historical ecology) with which you identify. Fields and disciplines listed by respondents were grouped into five categories: Fisheries science, Marine biology, Conservation and environmental sciences, Earth and atmospheric sciences, and Other. The use of keywords by respondents facilitated this categorization. For instance, any response including “fishery” (e.g., fisheries biology, fishery management) was categorized as Fisheries science and any inclusion of “conservation” or “restoration” (e.g., conservation biology, ecological restoration) was considered Conservation and environmental sciences. Marine biology was applied generally and was inclusive of responses such as “marine ecology” and “estuarine ecology”. The Earth and atmospheric sciences category included responses such as “Geography” and “Geology”. Responses grouped as Other included “biogeochemistry,” “genetics,” and “molecular biology.”

Question 7: Please describe your work as it relates to marine conservation in one sentence or less. Responses to this question were grouped into six categories—Research, Education, Management (conservation), Management (resources), Administration, and Other—and were not mutually exclusive. Many respondents indicated that they conducted Research (e.g., “I am a marine ecologist studying…”) and also filled Education (e.g., “Educating bay stewards”) or Management roles. Keywords were particularly useful when distinguishing between Management (conservation) and Management (resources). Responses were grouped under Management (conservation) when the emphasis was on the preservation or restoration of biodiversity or ecosystems (e.g., “Assess status and trends of ecosystem health in our local estuaries”) whereas responses in the Management (resources) category focused on ecosystem services and fisheries activities (e.g., “...implement resource management actions…”). Administration was differentiated from these categories based on the level at which the respondent was working. For example, “Chair of several science or technical advisory committees to coastal policy groups” was considered Administration and “…developing strategies to protect and restore salmon habitat” was considered Management (resources). Responses categorized as Other were generally too vague to fit any of the aforementioned categories (e.g., “Working hard today to ensure a better future tomorrow”).

Question 9: Please list up to three primary goals in the field of marine conservation (e.g., preservation of biodiversity). Responses were grouped into six categories: Maintenance of biodiversity, Maintenance of ecosystem services, Maintenance of ecosystem structure and function, Habitat protection, Sustainability, and Other. These groupings were not mutually exclusive, as responses such as “Conservation of ecosystem function and services” were considered both Maintenance of ecosystem services and Maintenance of ecosystem structure and function. Maintenance of biodiversity, which was taken to be inclusive of all types of diversity (e.g., genetic, species, ecosystem), ecosystem services, and structure and function were distinguished based on phrasing and keywords used by respondents—most prominently the category names themselves. Habitat protection was applied in a general sense (i.e., not necessarily implying human exclusion from nature). The Sustainability category included responses mentioning management practices in a general sense (e.g., “smart management”) as well as responses that explicitly mentioned sustainability (e.g., “long-term sustainability”). We acknowledge that the concept of sustainability can be complicated (Callicott and Mumford 1997), but use it here in a broad sense to mean the current and continued coexistence of humans and the ecosystems in which they are embedded. Several respondents also included educational goals (e.g., “education”), focused on research (e.g., “To study the impact we have had…”), or gave vague responses (e.g., “Understand marine ecosystems”); these were considered Other.

Question 10: What are the cutting-edge approaches currently being practiced in marine conservation to achieve the goals you mentioned in question 9? List no more than three. Responses to this question were variable and ranged from data collection tools (e.g., “drones”) to practices (e.g., “adaptive management”) and management actions (e.g., “marine protected areas”). Thus, responses were grouped into the broad categories of Management, Technology, Mathematics, Research, and Other. Many of the responses included multiple types of approaches and others described approaches that spanned more than one of the approach categories (e.g., the response, “…statistical and modeling approaches combined with field data from long term studies…”, was categorized as Mathematics and Research). Responses in the Management category included decision making (e.g., “utilization of diverse data sets to make management decisions”) and management actions (e.g., “Marine Protected Areas”) as well as policy changes (e.g., “use laws and politics to control the human activities”). Technology approaches referred to improving (e.g., “greater computing power”) as well as adapting existing technology to conservation practice (e.g., “use of drones”). Mathematics approaches were most commonly related to improved modeling (e.g., “Modeling approaches combined with community-based monitoring…”) and analysis (e.g., “spatial analysis”). The Research category primarily included descriptions of applying data to conservation practice (e.g., “interdisciplinary collaborative research…studying how major river freshwater plumes effect [sic] early life stage survival in marine environments”), some more theoretical considerations (e.g., “ecosystem processes understanding”), and citizen science (e.g., “Developing crowd-sources data [sic] and information products”). The Other approaches included responses that were too broad to fit other categories (e.g., “genetics”) or did not fit the previous categories (e.g., “education”).

Question 12: In your opinion, what is the importance of long-term temporal data for achieving the goals of marine conservation? Responses to this question were classified into one of three commonly described categories (Strayer et al. 1986; Lindenmayer et al. 2012; Dietl et al. 2015)—Baselines, Trends and patterns, Range of variability—and a fourth category, Other, for miscellaneous responses. In many cases responses included components of multiple categories and were tallied in each of those categories. Responses in the Baseline category typically referred to using LTD to inform decision making in the future (e.g., “To combine with known conditions to be able to model and predict future outcomes”). Responses classified as Trends and patterns implied that LTD are important for determining trajectories and removing short-term variation (e.g., “identifies long-term trends in populations or water quality. Eliminates the noise of year-to-year variation…”). Range of variability most commonly included responses that highlighted the dynamic nature of populations and ecosystems (e.g., “critical for detecting natural dynamics of ecosystems…”). The vast majority of responses fell in one of these three categories and two remaining responses were grouped as Other (e.g., “Convincing policy makers…”).

Question 14: Please list five sources of long-term data and indicate whether you have used each one in your own research. The respondent-provided sources of long-term data were grouped into four categories, Modern observational, Historical, Geohistorical, and Other, related to those described for sources of data in marine historical ecology (Lotze and McClenachan 2014; Jackson and McClenachan 2017). In marine historical ecology, “archaeological” is given equivalent status as a data source, however, here it was subsumed under Geohistorical due to similarities in timescales and the small number of responses including these data. Modern observational included monitoring data and any contemporaneously collected data such as “seabird productivity data,” “Weather station data,” and “fishery catch data.” Historical (e.g., “historical documents”) was distinguished from Geohistorical (e.g., “Paleontological”) by its association with records kept by people (e.g., “historical documents”), as opposed to records in nature (e.g., “sediment cores”). The Other category included various responses including organizations (e.g., “NOAA”) and variables (e.g., “pH”) that were too broad to categorize otherwise.

Question 17: Given that these stressors interact in complex ways, please identify and describe the interaction that is most pressing to understand in marine conservation, in your opinion (e.g., the additive interaction between invasive species and climate change)? In 2005, the Millennium Ecosystem Assessment identified five stressors—pollution, habitat change, climate change, overexploitation, and invasive species—as the most important threats to ecosystems and it has subsequently been noted that these stressors often interact in complex ways (Crain et al. 2008; Darling and Côté 2008). Many respondents identified multiple interactions or interactions between three or more stressors they found to be important. Consequently, responses to this question were assessed in two ways. First, the total number of mentions for each stressor was tallied. Second, interactions between stressors were tallied. When three or more stressors were mentioned, each unique pairing was tallied (e.g., a respondent mentioning climate change, habitat change, and pollution resulted in tallies for climate change-habitat change, climate change-pollution, and habitat change-pollution).

Question 20: If you use reference conditions or baselines in your research/conservation work, please list three types of data sources that you use to produce them (e.g., references sites, monitoring records, etc.)? Responses were categorized into five groups: Modern observational, Reference sites, Historical, Geohistorical, and Other. These categories were chosen to reflect those used in Question 14. Responses classified as Modern observational commonly included mentions of monitoring (e.g., “monitoring records”). “Reference sites” was also a frequently given response and formed the basis for the Reference sites category; such responses were not considered Modern observational because they implied a spatial component rather than continued observation at one or a few sites. Similarly, responses in the Reference sites category were distinguished from responses in the Historical and Geohistorical categories by the mention or implication of spatial rather than temporal data. Historical included baselines from human-produced sources including “Literature,” “historical data,” and “historical accounts.” Responses in the Geohistorical category often included mentions of paleontological data (e.g., “paleobiology”) and geological sources (e.g., “sediment cores”). The Other category included responses giving methods (e.g., “Hindcast Circulation and Climate Models”) or variables (e.g., “ocean conditions”) that could not be linked unequivocally to one of the aforementioned categories.

Question 21: In your opinion, are spatial and temporal data of equal value in establishing reference conditions and baselines? Please explain briefly. Responses to this question were categorized at two levels. First, responses were split into three groups—Yes, No, and It depends—with respect to whether respondents found spatial and temporal data to be of equal value. Second, the No category was also subdivided into two groups based on whether respondents found Temporal or Spatial data to be of greater value for establishing baselines.

Question 22: Are there types of long-term data that would be useful, but that aren’t currently available or you would want more of? If so, please give an example. Responses to this question were assessed at three levels. First, responses were divided into those saying Yes, No, or Unsure to the initial question. Second, Yes responses were categorized into Abiotic, Biotic, or Other (e.g., “rate or process data”) groups. Third, the Abiotic and Biotic groups were further subdivided into the specific types of data identified by respondents. For the Abiotic subgroup, data types included Temperature (e.g., “Deep-ocean temperatures.”), Water chemistry (e.g., “Nutrient concentration of seawater.”), and Other (e.g., “seismic”). For the Biotic subgroup, data types included Species abundance (e.g., “abundance of key species”), Species distribution (e.g., “species distribution data …”), Interactions (e.g., “predator-prey relationships”), and Other (e.g., “species extinction rates”).

Question 23: What barriers (e.g., communication, funding, data availability, etc.) have you experienced (or do you perceive to exist) in applying long-term data to marine conservation? Responses to this question were grouped into four categories—Funding, Data availability, Communication, and Institutional—similar to those identified by conservation biologists (e.g., Strayer et al. 1986; Lindenmayer et al. 2012) and a fifth category, Other, for miscellaneous responses. Many respondents identified multiple barriers and each was tallied under the appropriate category (e.g., “Funding and agency interest” was categorized as Funding and Institutional). Responses categorized as Data availability discussed barriers related to data accessibility or lack of data (e.g., “lack of data availability”, “True long-term data is often not available”). The Communication category encompassed responses at the level of disciplines (e.g., “…communication may be one barrier, with researchers not recognizing how certain other disciplines might value their contributions”) as well as general challenges such as “Communicating long term data can also be difficult if the data is collected on timescales not easily processed by human minds.” Responses classified as Other included such impediments as education (e.g., “educational barriers”) and politics (e.g., “Playing political small ball…”).