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This semester I am having my students in my graduate seminar in conservation biology debate the following question: Are species or ecosystems the appropriate scale for conservation. While I suspect ahead of time the answer is going to be “yes” I’m curious to see what students come up with. As part of their assignment I had students choose a paper to help them think about the topic. I am creating this page as a way to help curate this literature.
To the students of Coastal & Estuarine Ecology
We will be holding class today, and I will get to the reasons why in a little bit. If however, you for whatever reason do not feel that you can go to class today. If you are sick, if you are tired, if you need to check in with the communities that you hold dear, I fully support your decision to not attend.
Last night we saw a refutation of the values that this, and many other, universities hold dear – equality, thoughtfulness, scholarship, and a belief that sound decision making will triumph over the noise and clamor of demagoguery. Unfortunately we also saw that the historical legacies of racism, sexism, and ignorance, still run deep within large swaths of our country.
It is ok to feel hurt and surprised. It is ok to question the future of our country, and our country’s role in global policies and phenomena that we study here in class. In addition to electing a man who claims that climate change is a myth perpetuated by China for economic advantage, the citizens of Florida also reelected Marco Rubio who does not think that human activities can influence the climate. It is tempting to fall back on cynicism or sarcasm in times like this. To think that if Florida keeps electing individuals that do not believe in climate change that eventually the problem will take care of itself. However if I’ve taught you anything this semester it is that the ocean is interconnected and that changes in one place ripple throughout the rest of the system. Much like the ocean our nation is interconnected and we cannot look at the bastion of blue where our university is located and say “this is someone else’s problem”.
This is not someone else’s problem, and saying that belies a level of privilege. For our poor communities, for our communities of color, for our LGTBQ communities, for our immigrant communities, for our disabled communities and for our Muslim brothers and sisters, this is not someone else’s problem. We are judged on how we treat those who have less power in our society, and my students, now is the time where we must redouble our personal efforts to reach out with kindness.
Why are we having class today? Because the administration that was just elected is demonstrably anti-science, anti-climate, and by extension anti-ocean. As students who are majoring in ecology and evolutionary biology you are facing a unique suite of challenges. To the seniors in the class, you are going to graduate within Trump’s first 100 days, to a time where the Republicans hold the house, the senate, and most likely the Supreme Court. To the juniors you are going to graduate within his first two years, and before any potentially ameliorating midterm elections. Thus, you are going to be graduating into a challenging time. A time when your science needs to be better, your arguments more convincing, and your commitment to protecting our natural environment fiercer.
We are holding class today because what I teach you is now even more important. You are going to have to up your game to operate in a culture that does not value the beliefs you hold dear. I am honored to teach you, to give you the tools and skills you will need to be a bulkhead against ignorance, and to help you find ways to intelligently speak from a position of authority.
We face real and honestly scary challenges ahead, but we are also a community. We take care of each other and we succeed or fail together. I think we will succeed, I think you will graduate and become leaders for the ocean, beacons of sanity to which people can steer their ships. So yes, we are having class, and yes we are going to learn, and yes we will be able to use this information to the betterment of our oceans and our country.
As always it is an honor.
(UPDATE 11/30/16: One of the students, Dev Harrington, did such a nice job with this assignment that I want to post it as an example. Well done Dev.)
One of the major questions facing ecologists and resource managers is understanding the amount of diversity in a particular area. This is important not only for describing macro ecological trends such as species gradients, but for allowing for the more precise application of limited conservation resources. Additionally, careful analysis of how species are distributed can even help identify some of the process underlying that pattern.
This raises the question, how do we measure the diversity within a particular area? Ecologists measure diversity using a variety of techniques but two important ones are Species Richness and Species Evenness. Species richness refers to the total number of species in a particular area, while Species Evenness refers to the distribution of those species within the total species pool. Figure 1, and 2 were tboth contain the same number of individuals (N= 12) however Fig. 1 only contains 1 species while Fig. 2 contains 10. We would say that the community represented by Figure 2 would have a greater species richness.
Now look at Fig 3 and 4. Again, both contain 12 individuals and five species but look at how those are distributed. Fig. 3 has 5 species with the distribution being Bellsprout (N=4) Beedrill (N=3) Abra (N=2) Bulbasaur (N=2) Butterfree (N=1) so 4,3,2,2,1. Figure 4 has again 12 individuals in 5 species but the distribution is as follows Eakans (N=6) Sandshrew (N=2) Nidoran (N=2) Nidoreina (N=1) and Nidoqueen (N=1) so 6,2,2,1,1. We can see from these distributions that the community represented in Figure 3 has a greater species eveneness.
When ecologists do field work one of the most common activities they do is to compile some measure of species diversity. This is often done by looking at the number of species encountered per fixed measure of effort or time. In practice this can mean running a 50m transect tape and seeing how many species are encountered, or sitting and listening for birds for a fixed period of time. When scientists accumulate these inventory data they can then do a number of statistical analyses to investigate the kinds of diversity present and if there are any patterns within that diversity. This is exactly what we are going to do today.
To investigate these ideas of community diversity and similarity we are going to need to collect data. To do that we are going to play Pokemon Go. For real. Working in pairs, I want you to time yourself for 30 min. During that time I want you and your partner to attempt to catch every pokemon you encounter. For each capture attempt record the following data: Species, Observed or Caught (i.e. did it run away before you could catch it) Combat Points, Number of poke pokeballs needed to capture the Pokemon, the kind of catch (nice/great/excellent) and the time that you caught it. I have made a data sheet available here. If you are playing along outside of class, please email me your sheets! We’d love to incorporate your data.
Additionally, I want you to record the following data. The level of the player and the approximate locality that you were sampling in. Since we want to replicate effort across all of our data please do not use incense and try to avoid pokestops that have lures and don’t use incense since those will artificially inflate your encounter rates.
Since our working hypothesis is that there will be a geographic signal in the kinds of species we encounter I want you to remain in one general area. In other words don’t walk from a grassy area down to a riverbank as that linear transect will likely cross multiple ecosystems. For this one, I would rather we have more students sample in different individual ecosystems than those crossing multiple ecosystems. You can sample wherever you want, however I would love if at least two pairs of students sampled:
- In Harlem along 125th between Lexington and Morningside, including the Apollo Theatre.
- Central Park’s lower east side (near the Central Park Zoo, apx. 59th to 65th St.).
- Within the American Museum of Natural History (suggested donation, you need not pay for this).
- Riverside Park near Grant’s Tomb (the corner of Riverside and Seminar Row).
- The Upper West Side (apx. 72nd St to 79th St. between Broadway and Columbus).
- Chinatown (between Worth and Canal St. and Bowry and Centre St).
- Little Italy (between Canal St. and Kenmore St, and Bowry and Centre St).
- Chelsea along the High Line
- Midtown. 40 and 49th St. Between Broadway and Lexington
This should give us 18 different transects to look at geographic patterns within New York City. I will also add two from the northern suburbs to see if there are differences there. Additionally if anyone else wants to join in we will make our data sets publicly available so we can compare pokecommuniites from different areas.
As always, remember to be safe. Work in paris so at least one of you is not focusing on the screen and, as I tell my son, “When you cross on the green, take your eyes off the screen.”
For those of you playing along at home we will post our data set here once it is completed
We will be using these data to explore three aspects of community ecology: species accumulation curves, species diversity indices and community similarity.
Species accumulation curves: How do we know when we’ve sampled enough? By looking at species accumulation curves ecologists get an idea as to how much of the total diversity they’ve captured. A species accumulation curve graphs the number of novel species captured per sampling event. Since, by definition, all species captured during the first sampling event are going to be novel the species richness of site 1 will be the Y value of the site one on the species accumulation curve. For each additional site added we add all newly encountered species to the total. Eventually the curve will asymptote along the true number of species present. If the curve appears to be steadily increasing at the end of your sampling then it typically means more sampling is required to estimate the total number of species. If, however the curve has passed the inflection point and appears to be flattening you have a rough estimate of how much diversity is present
For example in site 1 we capture 5 pokemon species, by definition all will be new, and our Y value for site 1 would be 5. In site two we capture 2 additional species, the Y value for site two would be 7 (e.g. 5 from site 1, plus 2 from site 2). For site 3 we capture no newly encountered species so the Y value for site 3 would remain at 7.
Now as a class let’s compile our data to create a species accumulation curve, add the stations from south to north (so the the Chinatown samples are first and the Westchester County samples are last):
- At the end of the sampling period was the curve increasing or flat? What does that mean for our sampling effort?
- Did you notice the curve being smooth or were there certain stations which created? What might cause a sudden jump in the rate of species accumulation?
Species Diversity Indices:
There are many methods that ecologists use to help quantify both richness and evenness. One of the most common ways to measure species richness is the Shannon-Weiner Index:
Where pi is the proportion of individuals in the ith species in the data set. Thus the summation of i1, i2,….iR includes all the species in the dataset. The Shannon-Weiner index also can be used to calculate an evenness
The evenness ranges from 1-0 with higher numbers being more even and lower numbers reflecting communities that are more skewed. Like all diversity indices, these measures is subject to sampling effort.
An additional measure of diversity is the Simpson’s index, which calculates the probability that two individuals drawn at random will be of the same category. It can be calculated thusly.
Where Lambda ranks from 0-1 with, confusingly, 0 being the most diverse. Therefore the index is usually reported as 1-Lambda.
These two indices are used to calculate the richness of an area, to calculate the evenness we use a formula derived by Evelyn Pielou:
Which ranges from 1-0 with higher numbers representing more even communities.
Lastly we have Jaccard’s coefficient, which is a way to calculate diversity based on presence/absence data.
Where J = Jaccards similarity index
a = number of species common to (shared by) quadrats,
b = number of species unique to the first quadrat, and
c = number of species unique to the second quadrat
Note, that this is a pairwise calculation.
- Calculate the Simpsons, Shannon-Weiner (diversity and evenness) and Pielou’s indices for each of the sites in our dataset. Which site was most diverse, which site was most even? You can do this by hand, using this website, or if you know R using the VEGAN package
- Why do we have different measures of diversity? What does it tell you when one site is more diverse by one measure while a second site is most diverse by a different?
- Are there any geographic patterns in diversity? What would this tell us about the distribution of Pokemon in NYC
- If you were approached by a tourist who only had a limited amount of time to play Pokemon Go about where to play, what neighborhood would you say was the best place to go? Why?
We can take the table of pairwise comparisons to generate a community similarity tree. Briefly this will be a graphical representation where neighborhoods that share more species in common will be connected to each other on nodes. Each clade represents a group of communities that are more like each other than they are to any other community. This method of thinking has been extensively used in phylogenetic where species that are more closely related to each other are on the same clade, while those less closely related are found further out on the tree:
If we look at the above example as a community ecologist and not a phylogeneticist (although, it is possible to be both, don’t let artificial dichotomies keep you from following interesting questions) we would say that communities A and B are more similar to each other than either of them is to community C. Similarly the distance between C and A is equal to the distance between C and B. We can use this “tree thinking” to visualize geographic patterns within our data.
In order to calculate Jacquard’s coefficient you had to create a matrix with rows being sample locations and columns being species. If you know R you can calculate a community similarity tree using that input format and the function ‘hclust’ in the R package VEGAN and you can assign significance using the function ‘simprof’ in the R package CLUSTSIG.
If you do not yet know how to use R, you can use the this website to build a tree, and use the “bootstrap” option to assign a level of significance to each node in your community tree. To use this site however you are going to have to format your data in a FASTA format.
For each site start with a “>” sign, then choose a four letter abbreviation and a number (representing the first or second sample from that neighborhood). Then press return. On the next line you will input the data which will be a string of 1’s and 0’s representing the presence or absence of every species in our data matrix. The last part is to hit return. Then on the next line press “>” again and put in the second site.
For those playing at home we will compile our data in R and FASTA and post them accordingly.
- Did sites taken from within the same neighborhood cluster together?
- Was there a geographic pattern present? If so, what was it?
- Did you see a habitat influence (e.g. sites in parks clustered together while sites in urban blocks cluttered together)?
- What communities were the most dissimilar? Why do you think these communities were most different?
While this lab obviously focus on fake biodiversity the skills and analytical methods here are broadly applicable to a variety of actual biodiveristy. I hope you had fun playing Pokemon but I also encourage you to go outside with a pair of binoculars or a mask and snorkel* and enjoy the real world diversity that is around us.
*don’t go swimming in the Hudson or East River near NYC. Just sayin’
Writing grants is one of the most critical skills you will acquire as a scientist, regardless of whether you end up in academia or not. However like all skills it must be developed through practice and with feedback. As part of Thesis Development we will be spending time helping you grow your grant writing skills so that you may successfully obtain funding to support your thesis.
There are several blog posts out there that will provide useful tips and pointers. In particular I found this and this to be of great value. Several helpful hints keep reappearing so I want to emphasize them here:
- Read the request for proposal all the way through. These documents contain useful information like when the grant is due and to whom you should send it. They also have fine print, like if research in particular areas is or is not covered. No sense wasting your time writing a grant if that funder is not going to cover your research
- Look at what other projects the funder has supported. This will give you an idea of what their funding philosophies are, what kinds of projects resonate with the funders, and if there are funding trends that may or may not hurt you. It is worth seeing if you can talk to a program officer or a past winner to get a better idea of what helps makes a successful application.
- Sell yourself and you team. Funders tend to be risk adverse and they want to make sure that if they give a team money to do a project, that the project will get done. As a new student you probably have not yet developed a track record to ensure funding confidence. You can circumvent that problem by building a good team. Make the case that ever person on your team fills a role and that together you are more than the sum of your parts.
- State your hypotheses! You want to be very clear about the quality of your science and if you do not have clearly stated hypothses, and methods that will generate data to sufficiently test those hypotheses, your grant will be dead in the water.
- Quantify your output. One of the biggest red flags for reviewers is a proposal becoming very vague about what the researchers are going to do once the experiment has been run. You can help this by being specific about where data will be archived, what conferences you will present at, and how exactly you are going to quantify your outreach and broader impacts.
To help the students focus on the art of writing a grant I asked them to formulate proposals based around deforestation of Truffula trees and the impacts on endangered Lorax and other populations in that ecosystem. Based on the criteria of the American Philosophical Society’s Lewis and Clark grants, I gave the students 40 min to prepare a short grant and then 7 min to present that idea and field questions. The three grant proposals were:
1) Loraxes derailed? An exploration of the effects of Thneedsville commuter rail development on truffula forest habitat and its endemic Lorax population
Brief Summary: In 2010, the City of Thneedville approved plans to build a commuter rail that transects surrounding Truffula tree forest (Figure 1; Thneedsville Mayor’s Office press release 2010). We seek to examine the impact of this development on Truffula forest habitat and of its endemic Lorax population
2) The effect of noise pollution of the super axe-hacker on the Song of the Swomee Swan
Brief Summary: The Swomee Swan, which lives in the Truffula forest, is known for its song. The logging of the Truffula tree is not thought to affect the Swomee Swan. We hypothesize noise pollution influences the song of the Swomee Swan, that may be related to the decreasing trend in Swomee Swan populations.
3) The effect of deforestation on Lorax reproduction during breeding season (May-July) in the Trufffula forest.
Brief Summary: The endemic Lorax population has been found to exhibit breeding site fidelity in dense truffula forests far from edge habitat (Seuss et al. 1971). Their breeding season occurs in early summer May-July (Seuss et al. 1971). Our study aims to determine the potential impacts of deforestation of truffula trees on Lorax reproduction. We hypothesize that the loss of important breeding sites and increase in noise pollution due to deforestation will negatively impact Lorax populations. We predict that loss of breeding sites will increase population fragmentation and make finding a mate more difficult, thereby leading to reduction of offspring.
Overall I found this a very enjoyable exercise to do in class. My 30 minute lecture helped frame the topic and provide useful information. The group work got students thinking about the topic as a cohort and gave them some ownership of the information, and the presentation allowed us to have some fun while practicing talking about our proposals to audiences.
The Nitrogen cycle is a beautifully complex part of our natural world that has direct impacts on the productivity of the oceans, and by extension, the amount of carbon in the Atmosphere. It has been suggested that if the N cycle were to break down the amount of global CO2 would increase by nearly 50% (Gruber 2008).
Because of the importance of the N cycle we are going to spend some time looking at it in detail in class. It is important to note that although N is the most common element in the atmosphere (N2 making up ~78% of air) it is largely biologically unavailable. Plants are literally bathing in fertilizer but it is inaccessible to them until the process of Nitrogen fixation. This process, carried out by a polyphyletic assemblage of microbial species, splits gaseous N2 into biologically available N molecules.
This N is usually available in Ammonium NH4+ or Nitrate NO3-. From these forms N can be used by a variety of phytoplankton, which in turn, are used by zooplankton and bacteria. Nitrogen tends to bounce around among these forms and is highly sought after. But remember, because the phytoplankton are photosynthetic this can only take place in the photic zone. Once the biologically available N sinks below the photic zone (in the form of Dissolved or Particulate Organic Material) it becomes sequestered from the phytoplankton. This is why deeper waters tend to be nutrient rich and why upwelling areas tend to be productive.
To complete the N cycle gaseous N2 must be returned to the atmosphere. This takes place through two microbial processes Denitrification and Anammox. In addition to completing the N cycle these process are important in reducing nutrient loads in eutrophic coastal waters (Smith et al. 2015)
To gain a better understanding of N flux we carried out a (very) active learning module in class today: We start with labeling ping pong balls as Nitrogen
First I taped two balls together to represent N2 gas. Then we N-4 students stand in a circle, with three students in the middle and one with a bag of N2 gas ping pong balls. The student with the bag splits the ping pong balls apart and throws them at the students in the circle. The students in the circle represent phytoplankton, zooplankton and bacteria and catch the balls, quickly passing them to other students in the circle. The students in the middle catch the fallen balls and tape them back together, handing them to the student with the N2 bag.
Questions for students:
1) What did the person playing the N fixing bacteria do?
2) How did we model the flow of N among phytoplankton, zooplankton and bacteria?
3) What did the balls falling to the floor represent?
4) The various forms of N differ in their residency time in the water column. NO3– gets turned over in the water column every 400 years, while NH4+ gets turned over every two weeks. Which form of these forms of N do you think is most biologically preferred? Why?
One of the predicted impacts of climate change is a increased stratification of the ocean (Wang et al. 2015). With this decreased mixing of waters…
5) What do you predict will happen to phytoplankton populations and what impacts will that have to water chemistry/nutrient availability?
6) If the upper layer of warm water grows thicker, what do you think will happen to the productivity of coastal upwelling?
One controversial approach to ameliorating climate change is ocean fertilization where large quantities of reaction limiting elements (N, P, Fe) are dumped into the open ocean to stimulate phytoplankton blooms.
7) Critique the science behind this and talk about whether you think this is a viable climate change mitigation scheme. Why or why not and use two peer-reviewed sources to help support your arguments.
8) Lastly, given that in winter large storms break down stratification and create a more well mixed ocean, while in summer warm temperatures help increase stratification, graph out how populations of phytoplankton, nutrients and the thermocline vary over one year in the high latitude northwest Atlantic (say in Halifax, NS).
9) For each season describe what is the most limiting resource.
Gruber, Nicolas. “The marine nitrogen cycle: overview and challenges.” Nitrogen in the marine environment (2008): 1-50.
Smith, Richard L., et al. “Role of Anaerobic ammonium oxidation (anammox) in nitrogen removal from a freshwater aquifer.” Environmental Science & Technology 49.20 (2015): 12169-12177.
Wang, Daiwei, et al. “Intensification and spatial homogenization of coastal upwelling under climate change.” Nature 518.7539 (2015): 390-394.
Over Compensation Schemes in Mitigating Human-Carnivore Conflicts
by Adam Pekor, MA student
Around the world, fostering the coexistence of people and large carnivores is a major challenge. From wolves in the U.S. to tigers in India, carnivores impose substantial costs on human communities through livestock depredation. As a result, they are often killed in retaliation for attacking cattle and other domestic animals. This human-carnivore conflict creates a lose-lose situation for people and wildlife: people lose critical income from carnivore attacks, and carnivore populations suffer from retaliatory killings. The decline or loss of carnivores can also have negative consequences for local ecosystems, in which carnivores play an important role, and for local economies, since carnivores are an important driver of wildlife tourism.
In East Africa, human-carnivore conflict is the primary driver of the decline of lion numbers. In light of the rapid expansion of people in the region, viable lion populations are not expected to survive outside large protected areas such as Serengeti National Park or the Selous Game Reserve beyond the next few decades. Accordingly, mitigating the conflict between people and lions is critical to both the conservation of lions outside of parks and the well-being of the people with whom they share the landscape. Since the financial burden that lions impose lies at the core of the problem, figuring out how to eliminate that burden without eliminating lions is essential.
In East and Southern Africa, the dominant approach to minimizing the financial impact of carnivores has been to compensate people for the livestock losses they suffer as a result of carnivore attacks. Although some compensation schemes have yielded positive results, many have suffered from a variety of problems that have rendered them largely ineffective. As explained below, conservation incentive payment (CIP) programs—in which people are paid directly for helping to conserve carnivores—are a promising alternative approach to mitigating the intense human-carnivore conflicts that persist in Africa.
The Problems with Compensation Schemes
Among the many problems that have plagued livestock compensation schemes in Africa, perhaps the most serious is the fact that reimbursement is often grossly inadequate. Because compensation generally requires proof that a livestock loss was caused by a carnivore, many losses (i.e., those that cannot be proved) go uncompensated. In one program in Botswana, for example, net compensation amounted to only 42% of the value of depredated livestock once uncompensated claims were considered. Thus, because such schemes do not make people whole for the losses they suffer, they are unlikely to increase local tolerance of carnivores.
Compounding this problem are the significant time lags and transaction costs associated with many compensation schemes. Because compensation claims can take many months to be paid, livestock owners are often forced to deal with unpredictable and extended financial disruptions. In addition, obtaining compensation can be a lengthy and time-consuming process, requiring a livestock owner to discover and report a kill, meet with scouts and claims officers, potentially appeal the denial of a claim, and show up at a designated time and place to receive payment. All of these steps take valuable time and energy that could be spent on other activities.
Even when compensation schemes do provide adequate levels of payment, they aren’t likely to minimize carnivore-livestock attacks. If full compensation is paid for a loss, livestock owners lose much of their incentive to minimize attacks since the financial costs of such attacks will be borne by the compensating entity (e.g., the government or an NGO). Further, this “moral hazard” perversely incentivizes livestock owners to let undesirable animals (e.g., sick or old cattle) be attacked in order to obtain compensation. In Kenya, at least one compensation scheme has been discontinued due to fraudulent claims being filed.
As a result of these problems, many compensation schemes in East and Southern Africa have failed to deliver satisfactory results for people or for carnivores.
The Advantages of Conservation Incentive Payment Programs
Conservation incentive payments (CIPs) address the costs of conservation in a fundamentally different way. Under a CIP program, communities are paid a predetermined amount specifically for helping to achieve a conservation goal. The key feature of a CIP program is that payment is contingent upon a community taking agreed-upon conservation actions and/or achieving agreed-upon results. If the agreed upon actions or results are not taken or achieved, no payment is made.
Most commonly, CIPs have been used in the payments-for-ecosystem services context (e.g., paying communities to maintain forests for carbon sequestration). However, in a handful of cases, CIPs have been used to mitigate human-carnivore conflicts. In those cases, payments have been conditioned on, for example, the utilization of enhanced livestock guarding methods (an action-based CIP scheme) or an increase in carnivore numbers (a results-based CIP scheme). In either case, the key to establishing an effective CIP program has been setting the payment level to meet or exceed the costs carnivores are expected to impose. By making carnivore conservation more attractive than carnivore eradication, these programs are able to align a community’s financial interests with conservation goals in a way that compensation schemes cannot.
In addition to the strong incentives they create, CIP programs offer a number of key advantages over compensation schemes. Most importantly, by rewarding communities for conserving wildlife, CIP programs treat local stakeholders as essential partners in conservation. By recognizing the role of local people in achieving conservation goals, CIPs encourage their participation in and commitment to conservation efforts. By contrast, under a compensation scheme, payments are divorced from conservation outcomes—that is, the actions of local people are treated as external to the conservation endeavor. As a result, local stakeholders are unlikely to exhibit the same support for conservation efforts.
Another key advantage of CIP programs is that they allow local people to profit from conservation. As noted above, the amounts payable under a CIP program are generally set to equal or exceed the community’s anticipated losses from carnivore attacks. So, as long as the community fulfills its obligations (upon which payments are conditioned), a CIP program can pay as much or more than a compensation scheme would. But, unlike in a compensation scheme, under a CIP program, people get paid for taking pro-conservation actions and/or achieving pro-conservation results, even if they suffer no livestock losses. Accordingly, under a CIP program, the more people can minimize carnivore attacks, the more they can profit off the program. That is, if they can minimize attacks, their payments stay the same but their losses go down. Under a compensation scheme, by contrast, there is no opportunity for profit; the most people can hope for is to recoup their losses from carnivore attacks. This incentivize to minimize losses is critical. With an initial goodwill payment made under a CIP program, communities can invest in resources to help limit carnivore attacks. Fewer attacks means more profit, thus creating a positive cycle for people and wildlife.
Of course, there are serious challenges associated with the use of CIPs, including determining how to set ecologically meaningful and achievable targets, how to measure a community’s performance, how to ensure that payments are equitably distributed, and how to resolve disputes under such a program, among others. And, even if these challenges can be met, CIPs should not be expected to be stand-alone, silver-bullet solutions to conservation problems that are often complex and motivated by more than just financial concerns.
However, given the potential of CIPs to deliver significant benefits for both people and wildlife, they are likely to be an important conservation tool going forward. Recognizing that local communities should not unfairly bear the costs of conserving carnivores is a critical development in mitigating human-carnivore conflicts. Implementing programs that effectively incentivize and reward community efforts is the next step.
This is another in my series of student guest blogs. This one by Grace Musser
Two weekends ago I attended and presented a poster at the First Annual Women In Science at Columbia (WISC) Graduate Research Symposium. The Symposium included speakers from many different disciplines within STEM fields and included speakers that focused on professional development and conflict resolution in the lab. These latter speakers were particularly valuable as they focused on these topics in a way that was particularly geared towards women.
The keynote speaker, Dr. Chloë Bulinski, was especially inspiring. From the start it was clear that Chloë was all around what many women in science aspire to be: a highly lauded professor at Columbia University, a pioneer in her field, and a loving mother. It was so aspiring to hear from a woman who successfully wears so many hats, and especially empowering when she emphasized one of the most important aspects of choosing a program: making sure that the place you choose will place as little stress as possible on you outside of school and research so that you can do your best work.
As a women in the STEM sciences and a daughter a mother in the STEM sciences, I have often been told of and shown the disqualifiers and difficulties plaguing women in STEM and indeed almost any field today. The admonishments from my and others’ advisors, professors and even fellow graduate students themselves often ring to the tune of “you have to choose between your children and your career,” “you have to choose between your relationship and your career,” “you have to go to x school no matter what the financial or emotional cost,” “you need to devote your time to research and publish no matter what else is going on,” “there are many times when your laptop should be your only friend.” This coupled with watching my mother’s difficulty in finding even a high school biology teaching job due to her focus on raising her children even after winning a National Science Foundation Graduate Research Fellowship and a Fulbright, earning her Ph.D. from Berkeley, and conducting research internationally, provided me with a bleak outlook on the choices I will “need” to face in the future of my career.
Despite this, Chloë’s statement gave me an incredible amount of hope. Here was a renowned Columbia professor telling us that we didn’t need to strain our relationships or our pocketbooks to go to “the best” program as what matters most was how those programs could be best for us, and essentially shattering the mythic notion that the best research comes from being trapped in the lab with little to no social life—a romantic notion that is limiting to anyone, but especially to women. While I feel that there is still a huge stigma against becoming a stay-at-home mom during part of your career and focusing on anything other than research, Chloë’s statement made me hopeful: as more women become involved in STEM and show that we can be all-star scientists while still being doting wives and partners or super moms if we wish, maybe we can truly start creating a world where it is admitted that good science often is catalyzed by and can certainly include a full life, and where women are not looked down upon or punished for choosing to interface more with the world outside of academia or the lab.
I face this issue as a visual artist as well, and see many parallels between the two romantic figures; like the mad scientist mythos, the romanticized “starving artist” is expected to live in the streets, starve, neglect themselves and basically do anything to just be able to continue making their work as it is their “calling.” The reality is that, once again, even making art largely requires art supplies, a safe shelter, storage space, food, and money for all of the above—not to mention that subsequent depression, starvation, and the resulting fatigue stymies inspiration more often than not.
What I find most disturbing about both of these myths is that they encourage one to live only for their work, essentially limiting one to a very narrow aspect of life—and seem to be born of a paternalistic ideal. This is especially strange to me as both science and art are creative fields, and creativity requires new ideas, communication, and building off of the work of others. Thus both of these myths not only limit one’s life but the quality of the work itself—and in Chloë’s words, “that is no way to live.”