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Natural environments provide many important ecosystem services, however, the use of these services often leads to environmental degradation (Watson et al., 2014). Early detection of signs of damage and degradation is critical in developing effective science-based management plans and policymaking, especially before irreversible changes have occurred (Wang et al., 2018). The protection and safeguarding of these environments through effective early detection will ensure the sustainability of ecosystem services that these areas provide (Watson et al., 2014). Experimental ecology has previously been utilized to monitor ecosystems, however recently citizen science and community monitoring have gained increasing attention (Teleki, 2012).
Experimental ecology is the use of scientific studies to manipulate or monitor environments to understand the mechanisms and factors involved in environmental disruption, whilst citizen science is generally defined as the voluntary involvement of the public in research (Silvertown, 2009). Citizen science has provided several enhancements in environmental monitoring research, including increasing the temporal and spatial scale of research, cost advantages and increasing community understanding and awareness, however, it is not without its limitations (Sauermann & Franzoni, 2015).
Whilst citizen science is a relatively new term, public involvement in research, especially environmental monitoring has been utilized for almost 2000 years (Tian et al., 2011). Over the past decade the term has increased in popularity, across many disciplines, providing large sources of information for scientists (Teleki, 2012). A high proportion of the data describing changing bird migrations, flowering times and insect activities is from citizen scientists (Chandler et al., 2017 Theobald et al., 2015). Recent technological advancements have increased the visibility and reach to engage the public in projects, and increased the value of community monitoring and citizen science in the eye of the scientific community (Schröter et al.
, 2017 Silvertown, 2009).
Some of the most critical environments to observe and manage are challenging to monitor for degradation due to limited resources, and data collection being cost and resource-intensive due to their isolated location such as subtropical reefs. This often leads to large gaps in data despite their ecological importance (Goffredo et al., 2010 Roelfsema et al., 2016). Citizen science aids in the expansion of the temporal and spatial coverage of data allowing ecologists to understand ecosystems at large geographic scales especially in landscape ecology where dominating processes may not be detectable on small scales (Dickinson et al., 2010 Lottig et al., 2014). Roelfsema et al. (2016) demonstrated that expansion of the spatial scale of studies allowed for the identification of discrete exposure regimes at very small spatial scales, which has previously not been identified by experimental ecological studies which are often restricted to much smaller spatial scales (Sommer et al., 2014). This is a key limitation of experimental studies, as demonstrated by impact assessment studies where the short temporal scale reduced the ability to understand anthropogenic impacts on animal behavioural responses. This results in the misinterpretation of the findings and thus inappropriate conclusions of the current state of the ecosystem and the future management strategies (Bejder et al., 2009). Community monitoring has proven effective in the quantification of the effect of environmental degradation through fragmentation and habitat loss on wildlife populations due to the increase in the spatial scale of the research (Boulinier et al., 1998). In addition to tracking changing distributions of invasive species and infectious diseases that are causing significant environmental change and damage (Crowl et al., 2008).
Environmental monitoring especially of remote and potentially isolated environments such as coral reef ecosystems is often very cost-intensive. Citizen science projects can, therefore, provide a significant cost advantage in particular in labour costs (Sauermann & Franzoni, 2015). The value of volunteer contributions can exceed $200,000 depending on the study (Sauermann & Franzoni, 2015). Theobald et al. (2015) demonstrated the significance of the cost advantage, indicating that volunteers participating in biodiversity projects alone contribute over $2.5 billion in-kind labour annually. Therefore community monitoring through divers and fishermen that naturally frequent these sites may provide critical information as to the state of the environment over large time scales to detect potential degradation in the environment with minimal cost constraints (Roelfsema et al., 2016).
Furthermore, citizen science and community monitoring engage the public and stakeholders in the management of their local environments (Pollock & Whitelaw, 2005). In doing so increasing the public’s awareness and ability to recognize anthropogenic impacts, for example, physical coral damage caused by boat anchors, divers or discarded fishing material (Roelfsema et al., 2016). In addition to providing the public with a sense of ownership and stewardship, and learning opportunities to aid in monitoring and conserving our environments especially from anthropogenic pressures (Roelfsema et al., 2016). This increased awareness and scientific literacy may prompt the public to change habits that may adversely impact the environment whilst triggering discussions, to help disseminate information to continue to inform other areas of the community and potentially provide opportunities to inform policymakers. Moreover, due to the generally greater spatial and temporal scale of community monitoring, the ability to monitor and observe changes in a range of environments and thus potentially detect early signs environmental degradation is increased (Schröter et al., 2017 Teleki, 2012).
There are several experimental approaches and protocols to identify environmental degradation especially those caused by humans (Wang et al., 2018). Recently Wang et al. (2018) developed a novel approach through in situ experiments and intensive sampling of sensitive biological indicators to detect early signs of degradation and distinguish the mechanisms of human disturbances to cause damage in particular in protected areas. Thus, providing robust results to inform science-based policy and appropriate management strategies, in comparison to citizen science projects, where data quality is often a common concern. Data collected from the public is generally simple proxies that are indirectly related to the topic in question (Schröter et al., 2017). Several studies demonstrate that data from volunteers to be more variable compared to reference data collected by scientists (Harvey et al., 2002 Moyer‐Horner et al., 2012 Roelfsema et al., 2016). This can lead to and enhance the scientific and governmental mistrust in the credibility of the data and it not being taken into account by policymakers (Gouveia et al., 2004).
Many studies require advanced knowledge and skills to properly assess the condition of an environment or aid in the identification of species (Schröter et al., 2017). Potentially leading to observer bias from a lack of objectivity, non-reliable identification of species, inaccurate results or fragmentation of data of untrained volunteers. This can result in an over or underestimation of the abundance or diversity of various species. The implementation of the wrong management strategies will potentially result in devasting impacts on that ecosystem and further perpetuate the mistrust in citizen science (Gouveia et al., 2004 Nicosia et al., 2014 Taylor & Gerrodette, 1993). Roelfsema et al. (2016) demonstrated that using a large number of volunteers can lead to inconsistency in data collection and recording despite volunteer training and robust experimental design. This contributes to variability in the data that couldn’t be explained by other factors investigated such as seasonality, in addition to errors in the data that couldn’t be validated in the post-survey data entry (Roelfsema et al., 2016). The quality of the data can be significantly affected by the age of the participants, as demonstrated by Delaney et al. (2008) who illustrated the difference in the quality of data provided by students in year 7 and university students. This indicates that age and experience of the participants in citizen science projects should be taken into account relative the quality of observations being made to observe signs for environmental degradation (Delaney et al., 2008). Furthermore, some complex environments such as marine ecosystems are difficult for volunteers to monitor effectively as fish are transient species, giving volunteers limited time to correctly identify the species (Roelfsema et al., 2016). However, this challenge isn’t limited to volunteers, with Harvey et al. (2002) demonstrating the difficulty of monitoring marine environment’s, with experienced scientists having a low precision of measurements (mean standard deviation =5:29 cm) and therefore low statistical power in detecting changes in mean length of fish.
Another challenge associated with the utilization of citizen science in detecting environmental degradation is that some environments are preferentially favoured for monitoring and surveillance by the public (Schröter et al., 2017). Previous studies have demonstrated that aesthetically pleasing, recreational or culturally important ecosystems such as coral reefs have a large base of volunteers willing to participate in the research, allowing for the ecosystem to be regularly monitored (Hobbs & White, 2012 Schröter et al., 2017). If reliance is placed on citizen science this can lead to the unbalanced monitoring of different environments and therefore critical signs of environment degradation could go unnoticed in especially in marginal environments.
Data collection and project design have been identified as a key constraint of citizen science rather than who the research is being conducted by. Therefore, to combat some of the mistrust associated with citizen science, the scientific design of these community monitoring projects needs to be improved to ensure reliable, robust and measurable data. As demonstrated by Hoyer et al. (2012) in which the robust study design in conjunction with standard operating procedures for both field and laboratory activities resulted in functionally equal results in the concentrations phosphorus, nitrogen and chlorophyll in a lake between volunteers and professional biologists. Similarly, Hames et al. (2002) highlighted the effectiveness of citizen science to aid in the collection of data used in the quantification of calcium-rich invertebrates, used to demonstrate the effect of bio-contaminates on bird breeding. This indicates the potentially important role that the public can have in environmental monitoring with the correct training, skills, support and structure and experimental procedures to collect credible data which can be used to inform regulatory decision making (Hoyer et al., 2012). It has therefore been suggested that citizen science is most suited to research that is designed around defined questions and hypothesis, with simple protocols allowing for participation and replication (Brown & Williams, 2019 Nichols et al., 2012). In comparison to observation-based studies which lack the ability to make strong inferences from the data (Brown & Williams, 2019 Nichols et al., 2012). However, observation-based studies are effective at informing ecologists on potential future projects through the early detection of changes in the environment.
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