Arboriculture & Urban Forestry 44(6): November 2018 challenges, PHS and Forest Service personnel have stressed during training that crews should record tree stewardship variables as observed when they found the tree, and should always mark yes/no for binary variables (i.e., never leave a data field blank). Train- ings in future years will also emphasize thresholds for stewardship variables with real-world examples, for instance, using photos from prior years to illus- trate how much weeds and trash need to be pres- ent in a planting pit to warrant a "yes" finding. Notably, Tree Checkers volunteers did not need to identify species of the planted trees, as this infor- mation was pre-populated into the mobile data col- lection system and printed data collection sheet. Prior studies about urban tree species identifica- tion accuracy by volunteers have suggested that volunteers perform fairly well for common genera (consistency ~86%–91%), with results varying across species (Roman et al. 2013; Bancks et al. 2018; Crown et al. 2018). Indeed, monitoring recently planted trees for survival may be partic- ularly well-suited to amateur volunteers because species identification skills are not necessary. Importantly, volunteers noted two trees as mortal- ity status "not planted." These trees were improperly included in the planting records. One tree was not actually delivered to a neighborhood Tree Tenders group on planting day, and the other was given to a Tree Tenders group but could not be planted. These trees were included in both the volunteer and intern samples, but only the volunteers correctly categorized the two trees because they had situational knowl- edge about planting events. These two trees repre- sent 0.3% of the trees observed by volunteers, and 1.0% of the trees observed by interns. While these are low overall proportions, every percent (or even tenth of a percent) matters for mortality rate calcula- tions, particularly for studies such as Widney et al. (2016) that model tree population growth over time using mortality rates calculated from establishment phase monitoring. Therefore, when such errors in the baseline planting data are not caught, they can lead to inflated mortality rates, and the inappropri- ate mortality rate can be compound in projection models. This phenomena speaks to the importance of high-quality baseline data that lists only trees that have been confirmed planted (Vogt et al. 2015). Ultimately, in the mortality rates reported in this study, the authors excluded these two trees from 261 the calculations. It is possible that similar circum- stances arose in previous monitoring studies of PHS trees (Table 2), but external researchers (and their field interns) may not have been able to catch the issue. The concern of tree distribution records that include trees never planted has been discussed for yard tree giveaway programs (Roman et al. 2014b), yet the extent of the failure to plant phenomenon is not well understood for street tree program records. While PHS staff and Forest Service researchers cannot be certain of the underlying causes of every data quality issue discussed above, they have identi- fied a few changes moving forward that will hope- fully improve baseline and monitoring needs. First, PHS staff will pay close attention to trees not planted, ensuring that the baseline data given to Tree Check- ers does not contain such trees. Second, steward- ship variables will have their definitions adjusted and training improved to promote clarity and con- sistency. Third, when PHS staff present findings of stewardship variables, the outcomes will be framed with a grain of salt because of the subjective and ephemeral nature of evaluating maintenance. Fur- thermore, it must be reiterated that the Tree Checkers stewardship variables were not originally intended to be used for data analysis, per se. Finally, regard- ing sampling, if Tree Checkers continue to report data on the vast majority of trees, PHS may consider recruiting additional volunteers (e.g., local college students) to monitor the remaining trees each August or September. Such a hybrid system would retain the original resident-to-resident focus of Tree Check- ers, while also producing data on all planted trees. LESSONS LEARNED In reviewing the evolution of the Tree Checkers pro- gram at PHS, staff and researchers have identified the following lessons learned that may be helpful to others involved with citizen science in urban forestry. Citizen science programs are not static. These pro- grams evolve to address changing priorities, improve workflows, adapt to new technologies, and enhance engagement opportunities. With outcomes moni- toring as part of adaptive management, the adap- tive component is sometimes taken to refer to shiſts in management strategies in response to outcomes observed (McKinley et al. 2015). Yet the monitor- ing program itself can and should also adapt to meet new needs and opportunities (Lindenmayer ©2018 International Society of Arboriculture
November 2018
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