WEBVTT Kind: captions Language: en 00:00:08.170 --> 00:00:12.090 Ashley Isham:  Good afternoon, or good morning from the U.S. Fish and Wildlife Service's 00:00:12.090 --> 00:00:15.290 National Conservation Training Center in Shepherdstown, West Virginia. 00:00:15.290 --> 00:00:17.830 My name is Ashley Fortune Isham. 00:00:17.830 --> 00:00:21.840 I would like to welcome you to our webinar series, held in partnership with the U.S. 00:00:21.840 --> 00:00:28.270 Geological Survey's National Climate Change and Wildlife Science Center in Reston, Virginia. 00:00:28.270 --> 00:00:33.030 The NCCWSC climate change science and management webinar series highlights their sponsored 00:00:33.030 --> 00:00:38.730 science projects related to climate change impact and adaptation, and aims to increase 00:00:38.730 --> 00:00:43.030 awareness and inform participants like you about potential and predicted climate change 00:00:43.030 --> 00:00:46.570 impact on fish and on wildlife. 00:00:46.570 --> 00:00:49.240 We appreciate you joining us today. 00:00:49.240 --> 00:00:51.420 I'd like to introduce Laurie Raymundo. 00:00:51.420 --> 00:00:56.420 She's at the University of Guam, and was one of the principal investigators with our speaker, 00:00:56.420 --> 00:00:57.540 Jeff Maynard. 00:00:57.540 --> 00:00:58.660 Laurie, welcome. 00:00:58.660 --> 00:01:01.460 Laurie Raymundo:  Good morning, Ashley. 00:01:01.460 --> 00:01:03.140 Ashley:  Good morning. 00:01:03.140 --> 00:01:10.770 Laurie:  [laughs] Yes, I have the honor of introducing a young man with whom I have enjoyed 00:01:10.770 --> 00:01:12.759 working, Dr. Jeff Maynard. 00:01:12.759 --> 00:01:15.450 He's an applied scientist. 00:01:15.450 --> 00:01:22.130 He works as a coral reef ecologist and he focuses on structured decisionmaking, risk 00:01:22.130 --> 00:01:23.689 analysis and climate change. 00:01:23.689 --> 00:01:31.479 He uses climate and ecological modeling to advance research into exploring and forecasting 00:01:31.479 --> 00:01:34.820 the impacts of climate change on coral reefs. 00:01:34.820 --> 00:01:39.810 He also applies these advances with coral reef managers to help address the threats 00:01:39.810 --> 00:01:42.999 posed to reefs by climate change. 00:01:42.999 --> 00:01:48.820 He's especially interested in assessing the relative resilience potential of coral reefs 00:01:48.820 --> 00:01:54.960 and using the results of these assessments to target different types of management action. 00:01:54.960 --> 00:02:00.799 This webinar is going to share the results of one of these ecological resilience assessments 00:02:00.799 --> 00:02:06.639 from a USGS PI CSC funded project that took place in the Commonwealth of the Northern 00:02:06.639 --> 00:02:10.990 Mariana Islands in the West Pacific last year. 00:02:10.990 --> 00:02:12.300 This is post bleaching. 00:02:12.300 --> 00:02:15.420 I'm very happy to welcome Jeff. 00:02:15.420 --> 00:02:16.860 Ashley:  Jeff. 00:02:16.860 --> 00:02:23.370 Jeff Maynard:  Good morning, afternoon, evening, and thank you, everyone, from me, for listening 00:02:23.370 --> 00:02:25.049 in. 00:02:25.049 --> 00:02:29.049 Laurie Raymundo, who you've just heard from, and I have had the great pleasure these last 00:02:29.049 --> 00:02:34.830 couple of years of coleading a team of scientists and managers that have been working in CNMI 00:02:34.830 --> 00:02:38.480 to better understand spatial variation and resilience potential. 00:02:38.480 --> 00:02:43.819 We have been applying what we've learned to the making of resiliencebased management suggestions 00:02:43.819 --> 00:02:46.200 that are aiding our manager partners with planning. 00:02:46.200 --> 00:02:51.230 This is a highly collaborative project that was funded by a grant at the University of 00:02:51.230 --> 00:02:55.540 Guam's marine laboratory from the Pacific Islands Climate Science Center, which is based 00:02:55.540 --> 00:02:59.530 in Hawaii and led by Dr. David Helweg. 00:02:59.530 --> 00:03:03.150 The PI CSC is one of the Climate Science Centers of the U.S. Geological Survey. 00:03:03.150 --> 00:03:06.640 We've enjoyed working with the PI CSC through the course of this project. 00:03:06.640 --> 00:03:11.590 PI CSC staff have helped with aspects of the presentation of our results and the project 00:03:11.590 --> 00:03:14.570 summaries we have prepared for the public. 00:03:14.570 --> 00:03:18.629 As is usual to these large projects, many have contributed their time, expertise and 00:03:18.629 --> 00:03:19.709 ideas. 00:03:19.709 --> 00:03:24.560 I'm speaking today on behalf of everyone who has contributed, especially the main contributors 00:03:24.560 --> 00:03:31.129 listed and the project coleaders, Laurie Raymundo of the University of Guam and Steven McKagan, 00:03:31.129 --> 00:03:38.700 who serves as the local NOAA Fisheries liaison in CNMI. 00:03:38.700 --> 00:03:40.810 We'll cover 10 topics during today's talk. 00:03:40.810 --> 00:03:45.629 I'll provide the background and history of resilience assessments in reef areas, our 00:03:45.629 --> 00:03:52.280 study objectives, the steps of the resilience assessment process, highlights of our methods, 00:03:52.280 --> 00:03:57.930 how we analyzed our data, the ways we assessed anthropogenic stressors, the ways our results 00:03:57.930 --> 00:04:03.939 can inform management, and how we used connectivity to interpret our results. 00:04:03.939 --> 00:04:09.129 I'll conclude by reviewing our main results, describing resources you can access and describing 00:04:09.129 --> 00:04:16.470 some of what we see as future directions for this research area. 00:04:16.470 --> 00:04:20.280 I want to first talk about how undertaking ecological resilience assessments got its 00:04:20.280 --> 00:04:26.410 start and how this idea and approach has evolved to what is being used and recommended today. 00:04:26.410 --> 00:04:30.510 Much resilience theory, as it pertains to coral reefs, started in the wake of the global 00:04:30.510 --> 00:04:37.140 scale bleaching event of 1998, associated with the El Nino that occurred that year. 00:04:37.140 --> 00:04:41.220 Prior to the early to mid1980s, bleaching tended to be rare and localized and corals 00:04:41.220 --> 00:04:42.720 generally recovered. 00:04:42.720 --> 00:04:46.000 There were even minor global scale events in 1987 and 1990. 00:04:46.000 --> 00:04:51.010 The 1998 event, however, was something altogether different. 00:04:51.010 --> 00:04:55.840 Coral reefs in 60 countries were affected by bleaching, and up to 70 percent mortality 00:04:55.840 --> 00:04:58.350 was documented in severely affected areas. 00:04:58.350 --> 00:05:02.470 Overall, the widely reported statistic about the '98 coral bleaching event is that as much 00:05:02.470 --> 00:05:05.830 as 16 percent of the world's coral may have died that year. 00:05:05.830 --> 00:05:10.910 The 1998 event raised awareness of the implications of global warming and climate change, at least 00:05:10.910 --> 00:05:13.280 among the coral reef community. 00:05:13.280 --> 00:05:19.780 The event also got people thinking since the impacts, so widespread, were clearly not spatially 00:05:19.780 --> 00:05:20.940 uniform. 00:05:20.940 --> 00:05:26.810 Jordan West of the US EPA and Rob Salm of the Nature Conservancy, who is shown here 00:05:26.810 --> 00:05:32.320 skin diving in the West Pacific, first proposed that spatial variation in factors that increase 00:05:32.320 --> 00:05:37.470 bleaching resistance and support recovery can be used as an assessment framework that 00:05:37.470 --> 00:05:40.080 can inform conservation. 00:05:40.080 --> 00:05:43.550 We refer to these factors as resilience indicators. 00:05:43.550 --> 00:05:49.350 Areas with characteristics that reduce stress or confer resistance or support recovery processes 00:05:49.350 --> 00:05:54.160 may be more robust in the face of continuing climate change, and thus, are priority areas 00:05:54.160 --> 00:06:01.400 of target management actions to reduce stressors related to human activities. 00:06:01.400 --> 00:06:05.660 The Nature Conservancy then included the concept of identifying areas with greater resilience 00:06:05.660 --> 00:06:10.130 potential, be it from resistance or recovery potential, in their conceptual resilience 00:06:10.130 --> 00:06:15.200 model, which was designed to assist with designing resilient networks of marine protected areas. 00:06:15.200 --> 00:06:20.650 Sites with greater relative resilience potential are critical areas, and preferentially investing 00:06:20.650 --> 00:06:25.220 management effort in these areas is one of the guiding principles that can help ensure 00:06:25.220 --> 00:06:29.400 we support the natural resilience of coral reef systems. 00:06:29.400 --> 00:06:32.740 This is a critical point I want to highlight as I work through this simple summary of why 00:06:32.740 --> 00:06:35.140 ecological resilience assessments are useful. 00:06:35.140 --> 00:06:40.190 The results can be used to target management actions that benefit site and system resilience, 00:06:40.190 --> 00:06:46.110 and thus, can help optimize application of our limited conservation and management resources. 00:06:46.110 --> 00:06:52.190 Importantly, up to 2009, none of these ideas had been formalized into guidance people could 00:06:52.190 --> 00:06:56.130 follow to undertake a resilience assessment. 00:06:56.130 --> 00:07:04.310 In 2009, scientists at the IUCN, TNC, and Great Barrier Reef Marine Park Authority published 00:07:04.310 --> 00:07:07.120 a guide for resilience assessment of coral reefs. 00:07:07.120 --> 00:07:11.861 Features of the guidance within this document include that it was recommended that 61 indicators 00:07:11.861 --> 00:07:16.990 be assessed or measured, which meant implementing the framework was highly resource intensive 00:07:16.990 --> 00:07:23.060 and included many subjective assessments. 00:07:23.060 --> 00:07:27.950 For our work, the most recent and most important step in the evolution of the methods for resilience 00:07:27.950 --> 00:07:32.940 assessment in reef areas happened in 2012 at the Marine Conservation Congress in Vancouver. 00:07:32.940 --> 00:07:38.720 A group of us designed a survey, 30 scientists and managers participated in, that examined 00:07:38.720 --> 00:07:45.810 what we considered to be the best subset of 30 of the previously proposed resilience indicators. 00:07:45.810 --> 00:07:50.500 Indicators were scored for perceived importance, scientific evidence and the feasibility of 00:07:50.500 --> 00:07:53.180 assessment and measurement. 00:07:53.180 --> 00:07:57.020 In the end, 11 indicators were recommended for resilience assessment. 00:07:57.020 --> 00:08:02.490 These were in either the top 10 for perceived importance or for scientific evidence and 00:08:02.490 --> 00:08:05.710 were considered feasible to assess or measure. 00:08:05.710 --> 00:08:10.040 The recommended indicators are: resistant coral species, coral diversity, coral recruitment, 00:08:10.040 --> 00:08:17.890 coral disease, macro algae cover, herbivore biomass and temperature variability and the 00:08:17.890 --> 00:08:23.900 anthropogenic stressors, nutrients, sediments, visible human impacts and fishing pressure. 00:08:23.900 --> 00:08:29.020 Our goal was to greatly reduce the number of indicators being assessed, as including 00:08:29.020 --> 00:08:33.839 weak indicators actually dilutes the importance of each indicator, and because evidence is 00:08:33.839 --> 00:08:38.890 increasing that, though complex, resilience processes in coral reefs are likely controlled 00:08:38.890 --> 00:08:41.750 by only a few factors. 00:08:41.750 --> 00:08:46.100 We found no relationship between results using our new method and results using the methods 00:08:46.100 --> 00:08:51.350 proposed with the IUCN 2009, and found that using 11 indicators resulted in much greater 00:08:51.350 --> 00:08:57.500 separation among sites in assessed resilience. 00:08:57.500 --> 00:09:01.709 The research our team has undertaken in these last few years in CNMI represents the first 00:09:01.709 --> 00:09:06.459 fieldbased implementation of the ideas presented within the paper on prioritizing indicators 00:09:06.459 --> 00:09:08.629 that I just described. 00:09:08.629 --> 00:09:14.480 Our collaborative work has three primary objectives to assess the resilience potential of areas 00:09:14.480 --> 00:09:18.800 where management activities have already been implemented, to identify priority conservation 00:09:18.800 --> 00:09:23.440 areas and better understand the primary drivers of resilience potential at the island, and 00:09:23.440 --> 00:09:26.329 CNMI wide scale. 00:09:26.329 --> 00:09:28.149 We also had a secondary objective. 00:09:28.149 --> 00:09:33.290 This was to support the coral reef conservation community by developing a detailed, adaptable 00:09:33.290 --> 00:09:39.210 process that guides the implementation of ecological resilience assessments. 00:09:39.210 --> 00:09:41.800 There are six steps in the process we used. 00:09:41.800 --> 00:09:48.040 These are: deciding whether to undertake an assessment, selecting indicators, collecting 00:09:48.040 --> 00:09:54.029 and compiling the data, analyzing the data, then identifying sites that warrant management 00:09:54.029 --> 00:09:57.319 attention and presenting and communicating the results. 00:09:57.319 --> 00:10:02.410 We're going to review these steps during this presentation, and I've listed the relevant 00:10:02.410 --> 00:10:04.350 steps on some of the slides. 00:10:04.350 --> 00:10:08.399 I'll rereview these once I've shared all the results, as I think it's easier to understand 00:10:08.399 --> 00:10:12.279 all the steps once you've seen our example. 00:10:12.279 --> 00:10:19.410 I'll start describing our research by providing some highlights of the methods we used. 00:10:19.410 --> 00:10:24.620 We measured or assessed all 11 of the indicators recommended within the McClanahan et al. 2012 00:10:24.620 --> 00:10:25.620 review. 00:10:25.620 --> 00:10:30.960 I want to be really clear here that the stressors related to human activity, listed at the end, 00:10:30.960 --> 00:10:35.540 are considered resilience indicators within the list of 11 recommended in the review. 00:10:35.540 --> 00:10:40.019 However, these challenge resilience, so are unlike the others, which are all indicators 00:10:40.019 --> 00:10:41.749 of resilience processes. 00:10:41.749 --> 00:10:45.779 Keep in mind through the coming slides that the anthropogenic stressors are assessed separately 00:10:45.779 --> 00:10:46.790 in our assessment. 00:10:46.790 --> 00:10:50.589 They're not included in the assessment of relative resilience potential. 00:10:50.589 --> 00:10:55.050 I'll review how they fit into our decision support framework a bit later in the presentation. 00:10:55.050 --> 00:11:00.230 Moving on to the indicators included in our resilience assessment and our field work. 00:11:00.230 --> 00:11:05.639 For the coral community, 12 to 16 quarter meter quadrants were used and all corals were 00:11:05.639 --> 00:11:10.410 identified to species, and the longest and perpendicular diameter were both estimated. 00:11:10.410 --> 00:11:15.380 In all, approximately 160 coral species were identified during our surveys. 00:11:15.380 --> 00:11:19.440 Stationary point counts were used to assess the fish community. 00:11:19.440 --> 00:11:24.670 One of our project coleaders, Steve McKagan, conducted a minimum of nine three minute long 00:11:24.670 --> 00:11:30.899 stationary point counts, identified all fish to species and estimated their lengths. 00:11:30.899 --> 00:11:35.759 In all, Steve estimated the lengths of tens of thousands of reef fish and identified 250 00:11:35.759 --> 00:11:36.759 species. 00:11:36.759 --> 00:11:41.501 You'll see, we put a small step two up, top right of this slide, as this is the step when 00:11:41.501 --> 00:11:45.089 indicators are selected and methods decided on. 00:11:45.089 --> 00:11:51.339 We surveyed 78 sites along the 30 foot contour of the four reefs of four islands of the CNMI, 00:11:51.339 --> 00:11:54.529 including Saipan, Tinian, Guguan and Rota. 00:11:54.529 --> 00:11:59.339 This map of our survey sites in Saipan shows that we had good spatial coverage around these 00:11:59.339 --> 00:12:06.730 islands, with our sites roughly a mile apart all the way around the island. 00:12:06.730 --> 00:12:10.720 This slide reviews the six indicators that were actually included in our assessment. 00:12:10.720 --> 00:12:15.410 Aside from the coral and fish communities, which I described on the previous slide, warm 00:12:15.410 --> 00:12:17.540 season temperature variability is also included. 00:12:17.540 --> 00:12:22.139 As sites where warm season temperatures are more variable, they'd be better acclimated 00:12:22.139 --> 00:12:25.269 to the temperature extremes that cause coral bleaching. 00:12:25.269 --> 00:12:29.699 The units are listed here, and as will be obvious to everyone, the units for all these 00:12:29.699 --> 00:12:31.579 indicators are necessarily very different. 00:12:31.579 --> 00:12:36.149 This is a key point as it speaks to the first required specimen data analysis, which I'll 00:12:36.149 --> 00:12:40.750 describe in an upcoming data analysis slide. 00:12:40.750 --> 00:12:44.490 One point, though, about our resilience indicators. 00:12:44.490 --> 00:12:49.019 We consulted colleagues working within the Nature Conservancy and NOAA's Coral Reef Ecosystems 00:12:49.019 --> 00:12:51.990 Division in developing our herbivore biomass metric. 00:12:51.990 --> 00:12:55.899 Our method is inclusive of three herbivore functional groups. 00:12:55.899 --> 00:13:00.540 We calculated that average biomass in kilograms per hectare of these three groups. 00:13:00.540 --> 00:13:05.300 Consequently, our herbivore biomass metric is inclusive of herbivore diversity, which 00:13:05.300 --> 00:13:08.980 much recent research suggests is just as important as herbivore biomass. 00:13:08.980 --> 00:13:14.610 This means that our average biomass values are not directly comparable with total herbivore 00:13:14.610 --> 00:13:16.680 biomass values from elsewhere. 00:13:16.680 --> 00:13:23.889 Now, over just a couple of minutes, I'll share a little of what represented many hundreds 00:13:23.889 --> 00:13:25.449 of person hours for our team. 00:13:25.449 --> 00:13:28.630 The reefs in CNMI are really, really beautiful. 00:13:28.630 --> 00:13:34.800 There are well over 400 reef fish species in CNMI, and at least 200 coral species, meaning 00:13:34.800 --> 00:13:39.100 CNMI definitely has among the greatest reef biodiversity among US coral reef locations. 00:13:39.100 --> 00:13:45.610 We learned, remarkably, the waters in CNMI are very clear. 00:13:45.610 --> 00:13:50.300 We set out three 50 meter transects, and people that were serving on snorkel safety support 00:13:50.300 --> 00:13:59.459 could frequently see our entire dive team in transects across a 100 plus meters of reefs. 00:13:59.459 --> 00:14:03.459 Here is Steve McKagan undertaking a fish species census to end his dive. 00:14:03.459 --> 00:14:06.930 He's diving in the coral gardens near Rota, which is in one of the established marine 00:14:06.930 --> 00:14:08.950 protected areas in CNMI. 00:14:08.950 --> 00:14:12.949 These photos will give you a bit of virtual tour. 00:14:12.949 --> 00:14:17.050 Another of our coleaders, Laurie Raymundo, is shown here assessing the coral community 00:14:17.050 --> 00:14:21.589 and coral disease prevalence at a site near Tinian Island. 00:14:21.589 --> 00:14:27.059 Steven Johnson is a reef ecologist with the marine monitoring team in CNMI. 00:14:27.059 --> 00:14:31.320 He's one of our two coral biologists and is a new Masters of Science student at the University 00:14:31.320 --> 00:14:32.320 of Guam's marine laboratory. 00:14:32.320 --> 00:14:36.540 Trust me, I would have liked to have shown him wearing a little more than he is here, 00:14:36.540 --> 00:14:38.459 but he only ever dives in board shorts. 00:14:38.459 --> 00:14:40.740 Here's Lyza Johnston. 00:14:40.740 --> 00:14:45.370 Liza is the science and team lead for the CNMI marine monitoring team. 00:14:45.370 --> 00:14:49.580 She is assessing the coral community at Bird Island, which is in northeast Saipan, and 00:14:49.580 --> 00:14:54.949 is another of the established marine protected areas in CNMI. 00:14:54.949 --> 00:15:05.059 Here are a few photos from other sites we surveyed to help you visualize what the coral 00:15:05.059 --> 00:15:17.149 reefs in CNMI are like. 00:15:17.149 --> 00:15:22.209 I'll now talk everyone through the basics of step four analyzing the data you collect 00:15:22.209 --> 00:15:24.899 and compile the resilient indicators. 00:15:24.899 --> 00:15:27.470 I'm calling this a look under the hood. 00:15:27.470 --> 00:15:30.880 You can see all of you in the audience depicted there in the top right. 00:15:30.880 --> 00:15:35.240 I thought if I showed a sideon view of this bloke working on a car, it would help to get 00:15:35.240 --> 00:15:38.559 your attention for the only slide I'll share that has a pretty detailed description of 00:15:38.559 --> 00:15:45.529 how the math for these analyses works. 00:15:45.529 --> 00:15:49.939 I mentioned before that each of the resilience indicators that we include in our assessment 00:15:49.939 --> 00:15:51.449 has different units. 00:15:51.449 --> 00:15:56.079 This means that all of the indicators have different scales. 00:15:56.079 --> 00:16:01.209 The data have to be normalized and converted to a unidirectional scale prior to calculating 00:16:01.209 --> 00:16:04.180 a composite score for resilience potential. 00:16:04.180 --> 00:16:09.300 To normalize the data, all values for each indicator are divided by the maximum value. 00:16:09.300 --> 00:16:15.350 This expresses all values as a decimal percentage of the site with the maximum value and ensures 00:16:15.350 --> 00:16:18.879 all indicators have a scale ranging from zero to one. 00:16:18.879 --> 00:16:23.209 The scale is inverted for macro algae covers, such that a high score always means higher 00:16:23.209 --> 00:16:26.980 relative resilience potential, which is why I call it a unidirectional scale. 00:16:26.980 --> 00:16:28.699 High score's always a good score. 00:16:28.699 --> 00:16:33.350 These normalized scores are then scaled or weighted. 00:16:33.350 --> 00:16:38.790 Part of Table Two from McClanahan et al. 2012, is reshown here. 00:16:38.790 --> 00:16:43.869 We compared the perceived importance scores by dividing these scores by the lowest important 00:16:43.869 --> 00:16:47.009 score for our indicators. 00:16:47.009 --> 00:16:50.430 This results in a multiplying factor you can see it on the right there, ranging from 1.36 00:16:50.430 --> 00:16:54.079 to one, up top. 00:16:54.079 --> 00:16:58.610 The normalized scores for the indicators are weighted using these multiplying factors because 00:16:58.610 --> 00:17:02.339 we intuitively know that some of the indicators are more important than others. 00:17:02.339 --> 00:17:07.000 The normalized scores are multiplied by the scaling factors we calculated. 00:17:07.000 --> 00:17:13.970 These converted scores are then averaged to produce the raw score for resilience potential. 00:17:13.970 --> 00:17:19.730 These values are then renormalized, which expresses resilience potential for each site 00:17:19.730 --> 00:17:23.140 as a decimal percentage of the site with the maximum score. 00:17:23.140 --> 00:17:25.610 We call it relative resilience potential. 00:17:25.610 --> 00:17:33.140 We then rank the sites from high to lowest score and use four relative classes based 00:17:33.140 --> 00:17:36.700 on where the final score fit into the distribution of scores. 00:17:36.700 --> 00:17:41.810 Sites with low relative resilience had scores less than the average minus one standard deviation. 00:17:41.810 --> 00:17:51.140 Sites with high scores had scores greater than the average plus one standard deviation. 00:17:51.140 --> 00:17:55.750 On this map, we show the results for our analysis that compared all sites against all other 00:17:55.750 --> 00:17:56.750 sites. 00:17:56.750 --> 00:18:01.860 On the top right, you can see the distribution of resilience scores with the average near 00:18:01.860 --> 00:18:03.860 0.8. 00:18:03.860 --> 00:18:09.300 The assessment results suggest the resilience of 17 of the sites is distinctly different 00:18:09.300 --> 00:18:14.190 and either greater or lower than the distribution defined by the average plus and minus one 00:18:14.190 --> 00:18:15.870 standard deviation. 00:18:15.870 --> 00:18:20.820 Seven of the sites have high relative resilience potential, and 10 have low relative resilience. 00:18:20.820 --> 00:18:26.380 37 of the sites have mediumhigh, and 24 of the sites have mediumlow relative resilience 00:18:26.380 --> 00:18:27.540 potential. 00:18:27.540 --> 00:18:33.170 All but one of the established MPAs has high or mediumhigh relative resilience. 00:18:33.170 --> 00:18:37.660 We had no preconceived notions as to where exactly the sites with highest and lowest 00:18:37.660 --> 00:18:43.040 relative resilience potential would be in CNMI, but suspected the sites most remote 00:18:43.040 --> 00:18:47.960 and least exposed to anthropogenic stressors would be among those with the highest resilience 00:18:47.960 --> 00:18:50.310 scores. 00:18:50.310 --> 00:18:52.250 We found the exact opposite to be the case. 00:18:52.250 --> 00:18:56.990 The majority of the high resilience locations among the surveyed islands are in Saipan, 00:18:56.990 --> 00:19:00.540 where greater than 90 percent of the 50,000 people residing in CNMI live. 00:19:00.540 --> 00:19:05.760 There are no high resilience sites in Rota, which is 50 kilometers south of Tinian and 00:19:05.760 --> 00:19:08.560 Aguijan, and roughly 50 kilometers north of Guam. 00:19:08.560 --> 00:19:10.880 That island has only 2,000 residents. 00:19:10.880 --> 00:19:14.900 Indeed, seven of the ten low resilience sites are in Rota. 00:19:14.900 --> 00:19:21.490 Our connectivity simulations help to explain this result, and I'll review those simulations 00:19:21.490 --> 00:19:25.680 in upcoming slides. 00:19:25.680 --> 00:19:30.240 Hopefully it's not too bad a memory, but I want to quickly show the looks under the hood 00:19:30.240 --> 00:19:32.920 and data analysis we'll have to distribute. 00:19:32.920 --> 00:19:37.980 This is just so that I can share that those steps I described can be undertaken for multiple 00:19:37.980 --> 00:19:38.980 spatial scales. 00:19:38.980 --> 00:19:44.050 On the slide I just presented, I mentioned that all of our survey sites were compared 00:19:44.050 --> 00:19:45.910 against all other survey sites. 00:19:45.910 --> 00:19:51.950 For the analysis shown on this slide, sites were only compared against sites surveyed 00:19:51.950 --> 00:19:57.090 on the same island, with Tinian and Aguijan combined. 00:19:57.090 --> 00:20:00.660 Conducted two analyses so that our results could inform decisionmaking, both at the region 00:20:00.660 --> 00:20:02.280 wide and island level scale. 00:20:02.280 --> 00:20:07.900 We found that there are at least two locations with low relative resilience potential and 00:20:07.900 --> 00:20:12.290 two sites with high relative resilience potential at each island. 00:20:12.290 --> 00:20:16.840 Generally, sites on more exposed sides of the island, east for Saipan and Tinian, and 00:20:16.840 --> 00:20:21.210 south for Rota have higher relative resilience potential. 00:20:21.210 --> 00:20:25.510 Understanding which variables most influenced differences in resilience potential is another 00:20:25.510 --> 00:20:27.620 valuable product of resilience investment. 00:20:27.620 --> 00:20:33.450 This is because the indicators most influencing rankings are the most important to include 00:20:33.450 --> 00:20:38.180 in monitoring programs, and they reveal the types of management actions that would benefit 00:20:38.180 --> 00:20:40.640 the greatest number of sites. 00:20:40.640 --> 00:20:44.990 We used two different analyses to examine which of the indicators are most driving differences 00:20:44.990 --> 00:20:50.370 in resilience potential among our survey sites, which was our project objective too. 00:20:50.370 --> 00:20:53.280 The scaling factors we used are pretty small. 00:20:53.280 --> 00:20:55.440 They're shown again here on the top right. 00:20:55.440 --> 00:21:00.640 Resulting in increases in the scores of greater than ten percent for only two of our indicators. 00:21:00.640 --> 00:21:05.280 Consequently, variation in the scores for the variables is indicative of which indicators 00:21:05.280 --> 00:21:08.370 are most driving rankings. 00:21:08.370 --> 00:21:13.270 Indicators with greater variability are most distinguishing sites from one another. 00:21:13.270 --> 00:21:18.100 You can clearly see for the interisland and all three intraisland analyses that coral 00:21:18.100 --> 00:21:22.090 recruitment and herbivore biomass are the most variable indicators and have the greatest 00:21:22.090 --> 00:21:23.830 range in value. 00:21:23.830 --> 00:21:28.840 We also used a canonical analysis of principle coordinates, which is a type of ordination 00:21:28.840 --> 00:21:33.700 analysis conducted in collaboration with our group by Gareth Williams, who works at Scripps 00:21:33.700 --> 00:21:36.390 Institution of Oceanography in San Diego. 00:21:36.390 --> 00:21:40.750 You can see that the relative classes we set are very different from one another, and clearly 00:21:40.750 --> 00:21:43.130 line up along the horizontal axis. 00:21:43.130 --> 00:21:48.040 The length of the line for each of the variables is indicative of the importance of the variable 00:21:48.040 --> 00:21:49.380 in distinguishing sites. 00:21:49.380 --> 00:21:54.890 Herbivore biomass, coral diversity, coral recruitment and macro algae cover are most 00:21:54.890 --> 00:21:57.480 driving differences among sites. 00:21:57.480 --> 00:22:03.970 We conducted the same analysis for the three islands and island groups. 00:22:03.970 --> 00:22:07.880 As is shown here for Rota, herbivore biomass and coral recruitment are driving differences 00:22:07.880 --> 00:22:11.900 in resilience potential as assessed here and this was the result for all of the surveyed 00:22:11.900 --> 00:22:15.720 islands. 00:22:15.720 --> 00:22:19.600 I mentioned earlier that the anthropogenic stressors were assessed separately to the 00:22:19.600 --> 00:22:20.600 resilience indicators. 00:22:20.600 --> 00:22:25.540 Anthropogenic physical impacts, such as from anchoring, were excluded as we observed almost 00:22:25.540 --> 00:22:27.590 none of these kinds of impacts during our surveys. 00:22:27.590 --> 00:22:32.530 However, we assessed landbased sources of pollution, which is inclusive of both nutrients 00:22:32.530 --> 00:22:39.520 and sediments as well as fishing access using GIS software and existing spatial data layers. 00:22:39.520 --> 00:22:45.880 For LBSP, we used land use spatial data layers from the forest service, and worked out which 00:22:45.880 --> 00:22:49.820 drainages affected each of the sites that we surveyed. 00:22:49.820 --> 00:22:54.690 Our LBSP metric included the proportion of the relevant drainages made up by urban and 00:22:54.690 --> 00:23:00.000 cleared land and the local human population density. 00:23:00.000 --> 00:23:03.700 The color scheme is the same here as is shown on the other maps in that green is good. 00:23:03.700 --> 00:23:05.150 So green scores would be low here. 00:23:05.150 --> 00:23:07.300 We're still using the relative scale. 00:23:07.300 --> 00:23:12.000 There were no sites with LBSP values in CNMI lower than the average minus one standard 00:23:12.000 --> 00:23:13.000 deviation. 00:23:13.000 --> 00:23:17.290 You can see, though, that there are sites with above average LBSP values and even sites 00:23:17.290 --> 00:23:21.440 with values greater than the average plus one standard deviation. 00:23:21.440 --> 00:23:28.290 LBSP values are, of course, highest near human populations and near cleared lands. 00:23:28.290 --> 00:23:36.330 For fishing access, our assumptions are that access to the fishery in these islands is 00:23:36.330 --> 00:23:42.370 primarily determined by the average wave height at a site, the distance between that site 00:23:42.370 --> 00:23:48.000 and an access point, such as a marina or boat ramp, and the human population density near 00:23:48.000 --> 00:23:49.510 the closest access point. 00:23:49.510 --> 00:23:54.030 There's good evidence that this is the case, given the exposed sides of these islands are 00:23:54.030 --> 00:23:59.742 difficult to impossible for small craft to access for much of the year. 00:23:59.742 --> 00:24:03.910 The wave symbols show prevailing wind exposure at the islands we surveyed. 00:24:03.910 --> 00:24:08.270 You can see access is low in these locations, which we assumed to be of benefit to the coral 00:24:08.270 --> 00:24:09.270 reef fish community. 00:24:09.270 --> 00:24:13.220 i.e., fishing pressure is probably lower in locations with high wave exposure and greater 00:24:13.220 --> 00:24:18.810 in locations with low wave exposure. 00:24:18.810 --> 00:24:24.670 We've now reviewed the first four of the six steps I described, and some of the six, given 00:24:24.670 --> 00:24:28.550 I've shown how we presented our main results in maps and tables. 00:24:28.550 --> 00:24:32.090 Step five is as or even more important than the others. 00:24:32.090 --> 00:24:34.660 It's where you could say "the rubber hits the road." 00:24:34.660 --> 00:24:39.400 This is where we maximize the value of the assessments and analyses for informing management 00:24:39.400 --> 00:24:40.750 decisionmaking. 00:24:40.750 --> 00:24:45.360 We set up a total of six custom queries of our data. 00:24:45.360 --> 00:24:49.980 And set criteria for these queries given there are different reasons sites may warrant management 00:24:49.980 --> 00:24:53.460 attention and actions to support resilience processes. 00:24:53.460 --> 00:25:01.060 Our queries identified targets for conservation, LBSP reduction, fishery regulations and enforcement, 00:25:01.060 --> 00:25:06.770 bleaching monitoring and supporting recovery, reef restoration and coral translocation, 00:25:06.770 --> 00:25:09.160 and tourism outreach and stewardship. 00:25:09.160 --> 00:25:14.290 Our first three queries are based on targeting actions to sites with greater relative resilience 00:25:14.290 --> 00:25:16.500 potential. 00:25:16.500 --> 00:25:21.090 This thinking is based on results presented within a "Conservation Biology" paper written 00:25:21.090 --> 00:25:27.400 in 2008 by Ed Game, who now works with TNC, and a few of his colleagues. 00:25:27.400 --> 00:25:32.240 The long and short of the findings from the modeling is that we should protect strong 00:25:32.240 --> 00:25:37.960 or high resilience sites if we are expecting sites to spend most of their time in a degraded 00:25:37.960 --> 00:25:38.960 state. 00:25:38.960 --> 00:25:43.080 The benefits of many types of management actions take a long time to manifest and disturbance 00:25:43.080 --> 00:25:46.400 frequencies are expected to increase in the coming decades as our climate changes. 00:25:46.400 --> 00:25:50.370 For these reasons, high resilience sites have greater conservation priorities. 00:25:50.370 --> 00:25:53.810 You may remember that I mentioned on one of the introductory slides that high resilience 00:25:53.810 --> 00:25:59.290 sites are among the critical areas we need to manage to support site and system resilience. 00:25:59.290 --> 00:26:03.290 A whole presentation could be prepared to explain that line of thinking. 00:26:03.290 --> 00:26:06.220 I'm sorry I had to review that so quickly for this webinar. 00:26:06.220 --> 00:26:10.210 I'll bring this up again really briefly when I review vulnerability assessments on one 00:26:10.210 --> 00:26:15.110 of the future direction slides. 00:26:15.110 --> 00:26:21.340 I'll show two examples of the results of the queries I just described. 00:26:21.340 --> 00:26:26.490 We identified high and low resilience sites that are currently outside established notake 00:26:26.490 --> 00:26:27.490 MPAs. 00:26:27.490 --> 00:26:32.110 As I was saying, the high resilience sites that aren't currently being protected can 00:26:32.110 --> 00:26:34.500 be considered conservation priorities. 00:26:34.500 --> 00:26:40.120 New MPAs or temporary closures or similar are not planned for CNMI right now, importantly. 00:26:40.120 --> 00:26:43.770 There are a range of other management initiatives that can be considered, though, including 00:26:43.770 --> 00:26:47.720 other types of fishing regulations along with increased enforcement and debris removal. 00:26:47.720 --> 00:26:52.010 This example is shared because many managers in coral reef areas will want to undertake 00:26:52.010 --> 00:26:56.730 an ecological resilience assessment to identify high resilience conservation priority sites. 00:26:56.730 --> 00:26:59.790 This is how we went about that. 00:26:59.790 --> 00:27:04.450 You can see the results, that there are high resilience sites not currently protected or 00:27:04.450 --> 00:27:11.900 rather not currently within the MPAtype of protection in both Saipan and Tinian. 00:27:11.900 --> 00:27:18.600 With this query, we show the locations that have high or mediumhigh relative resilience 00:27:18.600 --> 00:27:21.740 and above average scores for land based sources of pollution. 00:27:21.740 --> 00:27:23.082 These are targets for LBSP reduction. 00:27:23.082 --> 00:27:32.100 13 of the 78 sites meet the criteria set for this query. 00:27:32.100 --> 00:27:38.390 This summary graphic has the first letter of the query name within purple circles for 00:27:38.390 --> 00:27:44.040 all of the sites to which the criteria for at least one of the queries applied. 00:27:44.040 --> 00:27:49.680 In total, 55 of the 78 survey sites meet at least one of the six sets of query criteria. 00:27:49.680 --> 00:27:54.480 I want to make two important closing points about the queries we used to identify targets 00:27:54.480 --> 00:27:56.810 for different types of management actions. 00:27:56.810 --> 00:28:01.720 Firstly, the list of queries we set is not exhaustive of all the possible options. 00:28:01.720 --> 00:28:07.860 This is one of many reasons we always stress that the process we used in CNMI can be replicated 00:28:07.860 --> 00:28:09.280 or adapted. 00:28:09.280 --> 00:28:13.130 There are likely to be other kinds of queries that will make sense in other areas depending 00:28:13.130 --> 00:28:18.080 on the local context and the type of stressors related to human activity that are most likely 00:28:18.080 --> 00:28:21.630 to be challenging the resilience of local reefs. 00:28:21.630 --> 00:28:27.120 Secondly, we know that none of the management action options I've just described are new. 00:28:27.120 --> 00:28:31.710 The innovation is in using resilience explicitly as an information layer such that actions 00:28:31.710 --> 00:28:38.780 are targeted to maximize site and system resilience. 00:28:38.780 --> 00:28:43.030 Within our project, we also examined connectivity at the island scale. 00:28:43.030 --> 00:28:48.790 This part of the broader study involved collaboration with Matt Kendall, who works with NOAA's biogeography 00:28:48.790 --> 00:28:54.221 branch, and happened to be concurrently leading a project examining connectivity in CNMI while 00:28:54.221 --> 00:28:57.620 we were conducting our resilience assessments. 00:28:57.620 --> 00:29:04.230 Understanding connectivity, even at the wholeisland scale, can help us better understand the resilience 00:29:04.230 --> 00:29:08.140 assessment results and decide where to implement management actions. 00:29:08.140 --> 00:29:10.870 This second point has two parts. 00:29:10.870 --> 00:29:16.690 We can identify where actions are required to maintain larvae supply, and where actions 00:29:16.690 --> 00:29:21.250 may be ineffective, due to the larvae supply being really limited. 00:29:21.250 --> 00:29:25.760 The question we wanted to answer was, "What is the relative extent to which each of our 00:29:25.760 --> 00:29:35.130 survey islands is a larvae source and destination?" 00:29:35.130 --> 00:29:40.320 All I'm going to share about the methods for the connectivity simulations is that they're 00:29:40.320 --> 00:29:42.550 cool and really complicated. 00:29:42.550 --> 00:29:47.890 As you can see from this animation on the right, which shows a 4D hybrid coordinate 00:29:47.890 --> 00:29:53.340 ocean model with a one day timestep, which was used to examine connectivity by resolving 00:29:53.340 --> 00:29:55.480 island scale current patterns. 00:29:55.480 --> 00:29:57.960 We used two simulations. 00:29:57.960 --> 00:30:01.940 One that assumed larvae had no swimming ability, which is the case for coral larvae. 00:30:01.940 --> 00:30:04.940 And another that assumed larvae could swim with sensory capacity, which is often the 00:30:04.940 --> 00:30:07.330 case with reef fish larvae. 00:30:07.330 --> 00:30:11.860 We also included four pelagic larval durations to capture the range of days coral and fish 00:30:11.860 --> 00:30:18.030 larvae spend in the pelagic environment before settling. 00:30:18.030 --> 00:30:23.190 Our results took the form of eight matrices set out as you see here, with sources as columns 00:30:23.190 --> 00:30:26.210 and destinations as rows. 00:30:26.210 --> 00:30:28.900 Numbers in the table cells are virtual larvae. 00:30:28.900 --> 00:30:34.030 And we examined connectivity among our survey islands within the CNMI portion of the Marianas 00:30:34.030 --> 00:30:39.380 chain, Guam and other archipelagos. 00:30:39.380 --> 00:30:41.660 Here's the really simple summary. 00:30:41.660 --> 00:30:48.940 Considering both simulations and all four of the pelagic larval durations we used, Saipan 00:30:48.940 --> 00:30:54.850 is roughly twice the source as Tinian and Aguijan is and ten times the source that Rota 00:30:54.850 --> 00:30:56.260 is. 00:30:56.260 --> 00:31:02.680 Saipan and Tinian and Aguijan are comparable destinations and roughly twice the destination 00:31:02.680 --> 00:31:07.640 that Rota is. 00:31:07.640 --> 00:31:12.300 Here's what those results mean for the two reasons I described that summarize our interest 00:31:12.300 --> 00:31:14.260 in the connectivity information. 00:31:14.260 --> 00:31:19.930 Firstly, the lower connectivity between Rota and the other islands may be why seven of 00:31:19.930 --> 00:31:25.120 the ten sites with low relative resilience potential are in Rota. 00:31:25.120 --> 00:31:32.080 Secondly, management actions to reduce stress and support resilience in Saipan and Tinian/Aguijan 00:31:32.080 --> 00:31:34.410 can help to maintain larvae supply. 00:31:34.410 --> 00:31:40.500 Also, actions to support resilience in Rota may be insufficient to support recovery there, 00:31:40.500 --> 00:31:46.460 given the limited supply of larvae. 00:31:46.460 --> 00:31:50.310 We've covered a fair bit of ground, so I want to offer four highlights of our results that 00:31:50.310 --> 00:31:52.800 work as takehome messages. 00:31:52.800 --> 00:31:59.480 The first is that resilience potential varied greatly within and among islands for our analyses, 00:31:59.480 --> 00:32:04.580 and some sites have high and some have low relative resilience potential. 00:32:04.580 --> 00:32:10.590 Secondly, herbivore biomass and coral recruitment are key drivers in CNMI of differences in 00:32:10.590 --> 00:32:15.280 relative resilience potential as assessed here. 00:32:15.280 --> 00:32:19.660 The majority of sites were identified as warranting management attention for at least one reason 00:32:19.660 --> 00:32:22.930 we can relate to an action that will support resilience. 00:32:22.930 --> 00:32:28.570 Lastly, connectivity information really helps explain assessment results and prioritize 00:32:28.570 --> 00:32:34.280 from among the sites that warrant management attention. 00:32:34.280 --> 00:32:37.000 Here are our six steps again to review. 00:32:37.000 --> 00:32:41.480 First, was deciding whether to undertake an assessment. 00:32:41.480 --> 00:32:43.890 The second was selecting indicators. 00:32:43.890 --> 00:32:47.210 Third was collecting and compiling data. 00:32:47.210 --> 00:32:49.180 The fourth is analyzing the data. 00:32:49.180 --> 00:32:53.850 The fifth, identifying sites that warrant management attention. 00:32:53.850 --> 00:32:59.550 The sixth, presenting and communicating the results. 00:32:59.550 --> 00:33:03.800 I want to emphasize to you that our team considers scientist and manager collaboration to be 00:33:03.800 --> 00:33:05.740 essential for all of these steps. 00:33:05.740 --> 00:33:12.080 I actually had to remake this graphic because the first only had a sign on one side, which 00:33:12.080 --> 00:33:15.070 is actually indicative of the problem rather than the solution. 00:33:15.070 --> 00:33:19.180 The solutions we need and the building of stronger bridges between science and management 00:33:19.180 --> 00:33:23.890 requires scientists make suggestions to managers and viceversa. 00:33:23.890 --> 00:33:29.050 Our team believes our work to be a great example in the realm of operationalizing resilience, 00:33:29.050 --> 00:33:31.230 of scientists and managers collaborating. 00:33:31.230 --> 00:33:36.470 More collaboration like this are required both to undertake work like what we described, 00:33:36.470 --> 00:33:41.710 and so that the work can evolve and be refined and improved. 00:33:41.710 --> 00:33:47.170 As detailed as this presentation has been, this is really a highlightlike summary of 00:33:47.170 --> 00:33:51.560 what has been a really large body of work that has produced more results and local management 00:33:51.560 --> 00:33:56.320 suggestions than can be summarized here. 00:33:56.320 --> 00:33:59.930 The main aspect of our work and some important theoretical background hasn't been covered. 00:33:59.930 --> 00:34:04.690 However, we have produced a range of resources that share our process and our project results 00:34:04.690 --> 00:34:07.180 so that people can learn more about our work. 00:34:07.180 --> 00:34:14.310 These include our 2012 project report available on a NOAA CORIS website. 00:34:14.310 --> 00:34:19.309 A howto guide for undertaking resilience assessment is available on the TNC's reef resilience 00:34:19.309 --> 00:34:20.569 web page. 00:34:20.569 --> 00:34:26.019 Summaries of our guidance undertaking resilience assessments, which can also be found on TNC's 00:34:26.019 --> 00:34:28.249 reef resilience web page. 00:34:28.249 --> 00:34:32.740 A workshop report on resiliencebased management from a resiliencebased management workshop 00:34:32.740 --> 00:34:36.710 held in Honolulu late last year. 00:34:36.710 --> 00:34:42.440 Our USGS Pacific Islands Climate Science Center project report, which is available on a USGS 00:34:42.440 --> 00:34:46.250 web page that describes our project. 00:34:46.250 --> 00:34:50.970 And an 84page site summary appendix we are currently finishing to share results and management 00:34:50.970 --> 00:34:54.419 suggestion for each of the sites we surveyed. 00:34:54.419 --> 00:34:59.109 Lastly, we just submitted a manuscript for review that will be published open access 00:34:59.109 --> 00:35:00.690 later this year. 00:35:00.690 --> 00:35:05.680 All of these materials are either publicly accessible now or available upon request by 00:35:05.680 --> 00:35:12.720 sending me or one of the other project leaders an email. 00:35:12.720 --> 00:35:16.710 There are two different future directions for the applied research presented here that 00:35:16.710 --> 00:35:20.540 I want to quickly review before I conclude. 00:35:20.540 --> 00:35:25.500 Firstly, I want to make clear that the relative importance of resilience indicators will very 00:35:25.500 --> 00:35:28.829 spatially, especially among reef regions. 00:35:28.829 --> 00:35:35.779 For this reason, those interested in undertaking an assessment can start with recommended lists, 00:35:35.779 --> 00:35:41.660 and then include and exclude indicators as is appropriate for local context. 00:35:41.660 --> 00:35:45.059 We're going to need to develop recommended lists for the indicators for different reef 00:35:45.059 --> 00:35:46.059 regions. 00:35:46.059 --> 00:35:47.059 Those aren't available now. 00:35:47.059 --> 00:35:52.829 For example, we know the drivers of resilience processes are different in the Caribbean than 00:35:52.829 --> 00:35:54.480 they are in the Pacific. 00:35:54.480 --> 00:36:01.480 This is visually exemplified here using two photos from sites that were rated as having 00:36:01.480 --> 00:36:04.700 the greatest relative resilience potential from an assessment undertaking in the Cayman 00:36:04.700 --> 00:36:11.970 Islands in the Caribbean and for our study in CNMI. 00:36:11.970 --> 00:36:18.740 Secondly, we can undertake vulnerability assessments that combine resilience assessments with remote 00:36:18.740 --> 00:36:26.390 sensing and climate model based maps and projections of spatial variations and exposure to disturbances. 00:36:26.390 --> 00:36:32.019 In the IPCC’s framework for assessing vulnerability, exposure and sensitivity combined to produce 00:36:32.019 --> 00:36:36.950 potential impact which is moderated by adaptive capacity to yield vulnerability. 00:36:36.950 --> 00:36:41.789 The sensitivity and adaptive capacity terms can be seen as resilience, so by combining 00:36:41.789 --> 00:36:47.359 resilience assessments with exposure information, we can both assess vulnerability and target 00:36:47.359 --> 00:36:49.789 actions to the site with the lowest vulnerability. 00:36:49.789 --> 00:36:54.470 These are the high resilient sites with lower projected exposure. 00:36:54.470 --> 00:36:59.289 For example, we recently produced downscaled projections of coral bleaching conditions 00:36:59.289 --> 00:37:00.289 for the Caribbean. 00:37:00.289 --> 00:37:05.559 These projections are 4-km resolution and we identified countries where the variation 00:37:05.559 --> 00:37:09.640 in the projected timing of the onset of annual severe bleaching conditions is greater than 00:37:09.640 --> 00:37:10.830 10 years. 00:37:10.830 --> 00:37:14.799 In doing so, we're identifying locations that maybe temporarily refugia. 00:37:14.799 --> 00:37:19.720 It'll be interesting in coming years to identify locations that meet that criteria and have 00:37:19.720 --> 00:37:21.060 greater relative resilience. 00:37:21.060 --> 00:37:25.589 I’m just sort of scratching the surface of the kind of mapping our and other teams 00:37:25.589 --> 00:37:29.309 are doing in this working area, but, hopefully, you can see the potential. 00:37:29.309 --> 00:37:33.509 This and next year, Laurie Raymundo and I will lead another PI CSC project related to 00:37:33.509 --> 00:37:37.740 this modeling capability in collaboration with Ruben van Hooidonk. 00:37:37.740 --> 00:37:40.789 We will be producing downscale climate model projections from Micronesia. 00:37:40.789 --> 00:37:46.549 We'll be combining resilience assessment results with our downscale projections to collaboratively 00:37:46.549 --> 00:37:53.589 develop sustainability forecast with managers and reef stakeholders. 00:37:53.589 --> 00:37:57.359 I'm going to leave this slide up so that the recording shows the details of references 00:37:57.359 --> 00:38:00.410 cited in the presentation. 00:38:00.410 --> 00:38:09.720 [silence] Jeff:  I want to conclude the way I started, 00:38:09.720 --> 00:38:13.950 to reiterate that this project includes numerous contributors and has been made possible by 00:38:13.950 --> 00:38:18.519 funding provided by the USGS Pacific Island Climate Science Center along with grants to 00:38:18.519 --> 00:38:22.430 the project leaders from the other agencies listed here. 00:38:22.430 --> 00:38:24.869 Contact details of the project leaders are on the bottom right. 00:38:24.869 --> 00:38:29.519 While I'm likely to have enough time for all of the questions people have, I really encourage 00:38:29.519 --> 00:38:33.880 people to get in touch via email to provide comments or ask questions, even to set up 00:38:33.880 --> 00:38:39.829 the time to discuss the project results or assessment process. 00:38:39.829 --> 00:38:43.400 Thanks once again for everyone's attention and for your interest in our project. 00:38:43.400 --> 00:38:44.720 Ashley:  Excellent. 00:38:44.720 --> 00:38:48.029 Thank you very much, Jeff. 00:38:48.029 --> 00:38:49.349 All right. 00:38:49.349 --> 00:38:52.630 I see that some are coming in. 00:38:52.630 --> 00:38:59.089 I'd like to take the first question. 00:38:59.089 --> 00:39:03.869 It's going to come from Carl. 00:39:03.869 --> 00:39:11.000 It says, "Is there any concern relating to sea currents and ecological resiliencies of 00:39:11.000 --> 00:39:12.660 coral reefs?" 00:39:12.660 --> 00:39:22.190 Jeff:  I see that, I guess in the first instance, as a really broad question. 00:39:22.190 --> 00:39:26.609 If you write me, then we can put you in touch with Matt Kendall who was really the specialist 00:39:26.609 --> 00:39:30.769 that worked with us that did all the connectivity simulation that we summarized in the matrices 00:39:30.769 --> 00:39:35.380 that we used to make our various management recommendations and to interpret our results. 00:39:35.380 --> 00:39:39.549 The short answer, sort of broadly is that, yes, certainly there's uncertainty in that 00:39:39.549 --> 00:39:45.720 kind of modeling when we think about the future and how future changes in regional and global 00:39:45.720 --> 00:39:50.900 climate may affect currents because there's future uncertainty in that modeling. 00:39:50.900 --> 00:39:54.080 For us, it's still uncertain at the island scale. 00:39:54.080 --> 00:40:01.079 We saw it as being the best available information on a really important aspect of resilience 00:40:01.079 --> 00:40:03.589 at the best possible scale. 00:40:03.589 --> 00:40:07.250 Rather than ignore it, we build it in to the extent possible. 00:40:07.250 --> 00:40:11.220 I think it's a strength of what we've been able to do because it would have been confusing, 00:40:11.220 --> 00:40:16.630 I think, to a lot of people that worked in CNMI with us that suspected even more strongly 00:40:16.630 --> 00:40:22.579 than we did that the sites in Rota that are very far from where most of the people live 00:40:22.579 --> 00:40:25.059 didn't fare better in the assessment. 00:40:25.059 --> 00:40:29.730 Having the connectivity results helps us to explain that and, as you saw, really create 00:40:29.730 --> 00:40:34.619 a lens for us for how we can prioritize management actions among the island. 00:40:34.619 --> 00:40:40.880 There's definitely concerns about the uncertainty related to the work, but that's the best available 00:40:40.880 --> 00:40:43.489 information at the best available scale. 00:40:43.489 --> 00:40:50.410 As it's improved and refined, it can be continually included in these kinds of assessments and 00:40:50.410 --> 00:40:52.079 in future assessments. 00:40:52.079 --> 00:40:56.009 Hopefully, that touches on what you're asking. 00:40:56.009 --> 00:41:00.589 [silence] Ashley:  Thank you. 00:41:00.589 --> 00:41:04.369 The next question is from Bob Glazer. 00:41:04.369 --> 00:41:05.630 Hi, Bob. 00:41:05.630 --> 00:41:09.960 "Jeff, I'm particularly intrigue by the connectivity issues. 00:41:09.960 --> 00:41:14.440 You presented it well with respect to resilience and biodiversity conservation. 00:41:14.440 --> 00:41:20.589 I'm wondering if you would care to speculate on what it means for regulation, with respect 00:41:20.589 --> 00:41:23.710 to fisheries management and fisheries sustainability." 00:41:23.710 --> 00:41:30.670 Jeff:  Two questions on connectivity which really wasn't the part I was leading. 00:41:30.670 --> 00:41:34.039 This is particularly a tough one, so I don't want to necessarily just table it because 00:41:34.039 --> 00:41:39.210 I feel that question for the role that we had in this work needs to be answered by local 00:41:39.210 --> 00:41:42.150 managers that were working with us in CNMI. 00:41:42.150 --> 00:41:48.720 I can say though that the report that Matt Kendall and his colleagues produced is becoming 00:41:48.720 --> 00:41:51.319 available around the same time that we were developing this webinar. 00:41:51.319 --> 00:41:55.190 It's only in this last couple of months that people in Guam, where they're having Coral 00:41:55.190 --> 00:41:58.910 Reef Symposium this week actually, and in CNMI became exposed to it. 00:41:58.910 --> 00:42:04.319 It's definitely raising a lot of eyebrows, perking a lot of ears or whatever expression 00:42:04.319 --> 00:42:05.619 you want to use. 00:42:05.619 --> 00:42:06.721 They're looking into it. 00:42:06.721 --> 00:42:09.619 I think it will be built in the future fisheries management. 00:42:09.619 --> 00:42:12.960 How exactly, you'll need to follow up with us on a bit later. 00:42:12.960 --> 00:42:15.819 We could put you in contact with the managers that really are making those decisions. 00:42:15.819 --> 00:42:22.619 Ashley:  I'm not seeing any more hands or questions coming into the chat box. 00:42:22.619 --> 00:42:24.430 Holly, are you still on? 00:42:24.430 --> 00:42:26.540 Did you want to make any closing remarks? 00:42:26.540 --> 00:42:28.890 Holly:  I am on. 00:42:28.890 --> 00:42:34.430 This is Holly at the USGS and NCCWSC. 00:42:34.430 --> 00:42:36.890 We just like to say thank you to Jeff. 00:42:36.890 --> 00:42:38.230 That was excellent. 00:42:38.230 --> 00:42:43.260 It's always good to see what's going on out in the field. 00:42:43.260 --> 00:42:45.880 Thanks again. 00:42:45.880 --> 00:42:49.809 Ashley:  Thanks, Holly. 00:42:49.809 --> 00:42:56.420 I saw Dave on who was key in this as well in supporting it. 00:42:56.420 --> 00:43:00.059 I just want to give him the opportunity to make any remarks as well. 00:43:00.059 --> 00:43:07.339 Dave:  I'm very appreciative of both Laurie and Jeff and the team's hard work both in 00:43:07.339 --> 00:43:12.569 the field, the blitz they did on data collection, and they're windows to good weather, all of 00:43:12.569 --> 00:43:18.809 this is very sophisticated analytic work that went into this presentation. 00:43:18.809 --> 00:43:25.130 Thank you also to Ashley and Holly for helping us set this up. 00:43:25.130 --> 00:43:31.299 I hope this is just the first of a long series of collaborations between the Climate Science 00:43:31.299 --> 00:43:39.089 Center and the teams out in the Western Pacific. 00:43:39.089 --> 00:43:40.150 Ashley:  Thanks, Dave. 00:43:40.150 --> 00:43:41.150 All right. 00:43:41.150 --> 00:43:42.849 Well, I'd like to say one more time. 00:43:42.849 --> 00:43:44.319 Thank you very much, Jeff. 00:43:44.319 --> 00:43:46.239 That was a wonderful presentation.