Lindsey Peavey

Thank you Katie, Adam, Claire, CiCi, and Kita! Love you all. xo

Thanks so much, mom! My biggest supporter and fan :) Love you!

Thank you!! We made our goal! Hopefully we'll be in the running for the extra 2k grant, as well. Couldn't have done it without you!

Thank you so much, Josslyn! You pushed us to our fundraising goal, and we are ecstatic!

Marcia, the research team is extremely grateful for your generosity and support. Thank you!

Thanks for your support, Tara & Neal!

Hi again, Antonio :) Now, to answer your second question regarding how a marine resource manager could use this information: We see two main values of our research contributions. First, we are presenting just *one* potential way to quantify all of the simultaneous threats and stressors acting on a given marine mammal population --> drawing on experts to generate priors when none exist. We present a general, theoretical multiple impacts model that is transferable to any marine mammal population in any ocean. The general model can be adjusted as-needed (i.e., not all threats are present for all marine mammal populations), and there are also ways to complete just a fraction of our lengthy research process (surveying 16 researchers -- twice! -- regarding every single node and link in the full model) if time and resources are limited (which is the reality the majority of the time!). In our paper we will provide suggestions as to how to do that. Second, we carry the theoretical approach through for an important case study, endangered Southern Resident Killer Whales, and show how using our approach (which is one of perhaps several ways to quantify cumulative impacts) you can prioritize which threats require immediate action (to reduce the threat and increase the population's growth rate), and which threats require additional information before a management action is justified. I hope this helps clarify the significance of this work. Please follow-up with additional questions if you have them. Thank you for your support!

Hi Antonio, Thank you for your questions! I am going to answer them in two separate posts, in hopes they'll be easy to follow. We are not generating empirical data, necessarily. We are generating what you might refer to (in statistics) as "priors" based on expert knowledge. These priors (which can be continually updated over time) are produced by: 1) mathematically describing each expert's estimate as a range (density function) of potential values centered around their "best" estimate, and bounded by their stated confidence around that best estimate (essentially a confidence interval). 2) We draw (many times!) from the 16 expert distribution functions to produce one aggregate expert estimate for each node and link in our multiple impacts model. Keep in mind that in the best case, there will be both an expert-based estimate and an empirical-based estimate for a given node or link. In that case, we give more weight to the empirical-based estimate because it has previously been subject to a peer-review process, but both estimates are considered. In the worst case scenario, there is only an expert-based estimate for a given node or link, and in that case we use the aggregate expert-derived estimate as the prior. So, you are correct in that our estimates will be weighted, but not based on the expert's publication record -- instead the weighs come from the expert's self-defined confidence around their estimate(s), and whether or not we are able to also draw upon empirical data to anchor/validate the expert estimate(s). I hope that makes sense, and if anything is unclear I am happy to elaborate or try to describe the method another way! We appreciate your interest and support, we would like to hear what you think of our findings and our paper when it's complete.

Hi Richard, thank you very much for your support and insights. Both acute and chronic chemical pollution are among the 14 threats included in our model, as well as pathogens and harmful algal blooms. We link these threats to the various stresses they put on population vital rates, such as change in behavior (reproduction, migration, foraging), disease & immunosupression, and endocrine disruption. All of these are difficult to estimate by drawing from existing studies alone, which is why our approach combining empirical data with expert opinion is a critical first step in assessing all threats acting simultaneously -- particularly the threats you are concerned with. I hope you continue to follow this project, we will be sharing our progress and outcomes over the next several months, and finally in our paper. Thanks again!

Your time and energy is proving critical to the success of our crowdfunding campaign, and our project. We can't thank you enough, Philip!

Thank you, Famarama!

Many thanks, Jason. We greatly appreciate your support!