As I write this, while sitting in my 82-degree New Haven apartment, I cannot help but feel some nostalgia for the two summers I have now spent in Pinedale, WY doing research for my Master’s degree. I have spent the vast majority of my life in New England. Prior to the past two field seasons, I had never spent any substantial time in the drylands of the West. I distinctly remember thinking to myself after first arriving in Pinedale how vastly different the landscape was than anywhere else I had lived. While I was accustomed to ecosystems dominated by mixed forest types, I now found myself seeing one main species, big sagebrush, for miles on end.
Even though the basis of my masters research is running a computer model, which could have been done from anywhere, it was instantly clear that it was vital for me to do field work in the environment that would be the area of consideration in the model. If I tried running this model based on my experience of ecosystems I had spent the most time in, I would not be able to represent any part of the system actually in question. In every environment I had been in prior to June of 2021, water was abundant and decreased precipitation in any given year would not have any extraordinary impact on the overall composition of the species in the area. However, in my first field season in Wyoming, which ended up being a particularly hot and dry summer, it was clear this same expectation was not the case in this region. Due to the dry conditions, flowering plants were few and far between, and the entire landscape looked overall brown; starkly different from the lush green forests I grew up in. Contrarily, my second field season had a wetter spring which drastically altered the local vegetation in the opposite direction. This summer flowering plants were abundant and many plants appeared to reach their reproductive stage later in the summer. Seeing this first-hand comparison of the impacts of climatic conditions was extremely valuable when trying to understand how these factors might be incorporated in a computer model of vegetation responses to climate. The extent to which vegetation responds to precipitation levels became instantly obvious in my two field seasons in Wyoming. I may never have completely understood this if I had not made it into the field. Even though it would have been much easier to run the model from the confines of my New Haven apartment, without having a solid understanding of what impacts environmental factors can have on the landscape, the model results would have been nearly meaningless.
My desire to do research that will influence management decisions has also created a necessity to get out to the field. Naturally, with the vastly different landscapes of my home on the east coast and my study site in Wyoming comes vastly different lifestyles and livelihoods. A large number of the people living in and around Pinedale make their living as cattle ranchers or natural gas workers, jobs I have never encountered in my 25+ years in New England. With these differences in landscapes and lifestyles also comes tremendous differences in land use practices. While on the east coast the majority of land is privately owned and public parks or conserved areas are typically clearly delineated, the opposite is true near Pinedale, Wyoming. Much of the open area land around Pinedale is publicly owned and managed by the Bureau of Land Management (BLM) and then private operations, such as natural gas developments and cattle grazing, are allowed to occur on this public land via a lease. Without living in the region for the roughly six months I have, I’m not sure I would have been able to understand the nuances of land management that cover the area. I could have run the model and tried to make some semblance of a management recommendation, but this recommendation would have been woefully misinformed if it came from the past version of me who had not spent any time in the West. Even still, I am aware that my understanding of the complexities of conservation and land management are lacking. However, simply through completing two seasons of field work in the area where my model results could influence management decisions, I believe my recommendations have much more credibility than they would without the field work.
Models can be a fantastic tool to better understand environmental processes, and to project possible and likely outcomes of conditions over large temporal and spatial scales. The model that I am currently working to create will assess plant community change over the next century of climate change, but just in the small area surrounding Pinedale. Models at this spatial scale can be very helpful, especially when the person running them has a sense of what the region looks like at the ground level. Once the spatial scale increases, though, which frequently can occur as scientists hope to make their models widely applicable, it becomes increasingly difficult to understand on-the-ground processes.
At the time of writing this, I am working as part of a team to help welcome the new cohort of students to the Yale School of the Environment and New Haven. Through this three week orientation, my team is working closely with community members from around the city who have spent a great deal of time to improve and maintain the parks of the area. One of the main points we hope students take home is that, even in a program where we are constantly thinking about big ideas at the global scale, real change happens on the local level with efforts put in by the community that lives there. I see this idea as a microcosm of the importance of doing field work in the context of a model-based project. If we do not put ourselves in a position where we can better understand the environmental and social factors that contribute to how communities function, making meaningful management contributions will be more difficult and less effective. Models can increase our ability to make inferences about the natural world, but even just a few months of work on-the-ground in the areas of interest can substantially improve the quality of our science and the recommendations that result.