Prescribed burning by Indigenous people was once ubiquitous throughout California. Settler colonialism brought immense investments in fire suppression by the United States Forest Service and the California Department of Forestry and Fire Prevention (CAL FIRE) to protect timber and structures, effectively limiting prescribed burning in California. Despite this, fire-dependent American Indian communities such as the Karuk and Yurok peoples, stalwartly advocate for expanding prescribed burning as a part of their efforts to revitalize their culture and sovereignty. To examine the political ecology of prescribed burning in Northern California, we coupled participant observation of prescribed burning in Karuk and Yurok territories (2015–2019) with 75 surveys and 18 interviews with Indigenous and non-Indigenous fire managers to identify political structures and material conditions that facilitate and constrain prescribed fire expansion. Managers report that interagency partnerships have provided supplemental funding and personnel to enable burning, and that decentralized prescribed burn associations facilitate prescribed fire. However, land dispossession and centralized state regulations undermine Indigenous and local fire governance. Excessive investment in suppression and the underfunding of prescribed fire produces a scarcity of personnel to implement and plan burns. Where Tribes and local communities have established burning infrastructure, authorities should consider the devolution of decision-making and land repatriation to accelerate prescribed fire expansion.
Recent developments to spatial-capture recapture models have allowed their use on species whose members are not uniquely identifiable from photographs by including individual identity as a latent, unobserved variable in the model. These ‘unmarked’ spatial capture recapture (uSCR) models have also been extended to presence-absence data and modified to allow categorical environmental covariates on density, but a uSCR model, which allows fitting continuous environmental covariates to density, has yet to be formulated. In this paper, we fill this gap and present an extension to the uSCR modeling framework by modeling animal density on a discrete state space as a function of continuous environmental covariates and investigate a form of Bayesian variable selection to improve inference. We used an elk population in their winter range within Karuk Indigenous Territory in Northern California as a case study and found a positive credible effect of increasing forb/grass cover on elk density and a negative credible effect of increasing tree cover on elk density. We posit that our extensions to uSCR modeling increase its utility in a wide range of ecological and management applications in which spatial counts of wildlife can be derived and environmental heterogeneity acts as a control on animal density.
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