The Importance of Small Fire Refugia in the Central Sierra Nevada, California, USA

Fire refugia – the unburned areas within fire perimeters – are important to the survival of many taxa through fire events and the revegetation of post-fire landscapes. Previous work has shown that species use and benefit from small-scale fire refugia (1 m2 to 1000 m2), but our understanding of where and how fire refugia form is largely limited to the scale of remotely sensed data (i.e., 900 m2 Landsat pixels). To examine the causes and consequences of small fire refugia, we field-mapped all unburned patches ≥1 m2 within a contiguous 25.6 ha forest plot that burned at generally low-to-moderate severity in the 2013 Yosemite Rim Fire, California, USA. Within the Yosemite Forest Dynamics Plot (YFDP), there were 685 unburned patches ≥1 m2, covering a total unburned area of 12,597 m2 (4.9%). Small refugia occurred in all fire severity classifications. Random forest models showed that the proportion of unburned area of 100 m2 grid cells corresponded to pre-fire density and basal area of trees, distance to the nearest stream, and immediate fire mortality, but the relationships were complex and model accuracy was variable. From a pre-fire population of 34,061 total trees ≥1 cm diameter at breast height (1.37 m; DBH) within the plot (1,330 trees ha-1), trees of all five of the most common species and those DBH \u3c30 cm had higher immediate survival rates if their boles were wholly or partially within an unburned patch (P ≤0.001). Trees 1 cm ≤ DBH \u3c10 that survived were located closer to the center of the unburned patch than the edge (mean 1.1 m versus 0.6 m; ANOVA; P ≤0.001). Four-year survival rates for trees 1 cm ≤ DBH \u3c10 cm were 58.8% within small refugia and 2.7% in burned areas (P ≤0.001). Species richness and the Shannon Diversity Index (SDI) were associated with unburned quadrats in NMDS ordinations 3 years post-fire. Burn heterogeneity in mixed-conifer forests likely exists at all scales and small refugia contribute to diversity of forest species and structures. Thus, managers may wish to consider scales from 1-m2 to the landscape when designing fuel reduction prescriptions. The partial predictability of refugia location suggests that further work may lead to predictive models of refugial presence that have considerable potential to preserve ecological function or human habitation in fire-frequent forests

Integrating snow science and wildlife ecology in Arctic-boreal North America

Snow covers Arctic and boreal regions (ABRs) for approximately 9 months of the year, thus snowscapes dominate the form and function of tundra and boreal ecosystems. In recent decades, Arctic warming has changed the snowcover\u27s spatial extent and distribution, as well as its seasonal timing and duration, while also altering the physical characteristics of the snowpack. Understanding the little studied effects of changing snowscapes on its wildlife communities is critical. The goal of this paper is to demonstrate the urgent need for, and suggest an approach for developing, an improved suite of temporally evolving, spatially distributed snow products to help understand how dynamics in snowscape properties impact wildlife, with a specific focus on Alaska and northwestern Canada. Via consideration of existing knowledge of wildlife-snow interactions, currently available snow products for focus region, and results of three case studies, we conclude that improving snow science in the ABR will be best achieved by focusing efforts on developing data-model fusion approaches to produce fit-for-purpose snow products that include, but are not limited to, wildlife ecology. The relative wealth of coordinated in situ measurements, airborne and satellite remote sensing data, and modeling tools being collected and developed as part of NASA\u27s Arctic Boreal Vulnerability Experiment and SnowEx campaigns, for example, provide a data rich environment for developing and testing new remote sensing algorithms and retrievals of snowscape properties

Mapping Multiple Insect Outbreaks across Large Regions Annually Using Landsat Time Series Data

Forest insect outbreaks have caused and will continue to cause extensive tree mortality worldwide, affecting ecosystem services provided by forests. Remote sensing is an effective tool for detecting and mapping tree mortality caused by forest insect outbreaks. In this study, we map insect-caused tree mortality across three coniferous forests in the Western United States for the years 1984 to 2018. First, we mapped mortality at the tree level using field observations and high-resolution multispectral imagery collected in 2010, 2011, and 2018. Using these high-resolution maps of tree mortality as reference images, we then classified moderate-resolution Landsat imagery as disturbed or undisturbed and for disturbed pixels, predicted percent tree mortality with random forest (RF) models. The classification approach and RF models were then applied to time series of Landsat imagery generated with Google Earth Engine (GEE) to create annual maps of percent tree mortality. We separated disturbed from undisturbed forest with overall accuracies of 74% to 80%. Cross-validated RF models explained 61% to 68% of the variation in percent tree mortality within disturbed 30-m pixels. Landsat-derived maps of tree mortality were comparable to vector aerial survey data for a variety of insect agents, in terms of spatial patterns of mortality and annual estimates of total mortality area. However, low-level tree mortality was not always detected. We conclude that our methodology has the potential to generate reasonable estimates of annual tree mortality across large extents

Detecting subtle change from dense Landsat time series: Case studies of mountain pine beetle and spruce beetle disturbance

In contrast to abrupt changes caused by land cover conversion, subtle changes driven by a shift in the condition, structure, or other biological attributes of land often lead to minimal and slower alterations of the terrestrial surface. Accurate mapping and monitoring of subtle change are crucial for an early warning of long-term gradual change that may eventually result in land cover conversion. Freely accessible moderate-resolution datasets such as the Landsat archive have great potential to characterize subtle change by capturing low-magnitude spectral changes in long-term observations. However, past studies have reported limited success in accurately extracting subtle changes from satellite-based time series analysis. In this study, we introduce a supervised framework named ‘PIDS’ to detect subtle forest disturbance from a comprehensive Landsat data archive by leveraging disturbance-based calibration sites. PIDS consists of four components: (1) Parameter optimization; (2) Index selection; (3) Dynamic stratified monitoring; and (4) Spatial consideration. PIDS was applied to map the early stage of bark beetle infestations (i.e., a lower per-pixel fraction of trees cover that show visual signs of infestation), which are a typical example of subtle change in conifer forests. Landsat Analysis Ready Data were used as the time series inputs for mapping mountain pine beetle and spruce beetle disturbance between 2001 and 2019 in Colorado, USA. PIDS-detection map assessment showed that the overall performance of PIDS (namely ‘F1 score’) was 0.86 for mountain pine beetle and 0.73 for spruce beetle, making a substantial improvement (\u3e 0.3) compared to other approaches/products including COntinuous monitoring of Land Disturbance, LandTrendr, and the National Land Cover Database forest disturbance product. A sub-pixel analysis of tree canopy mortality percentage was performed by linking classified high-resolution (0.3- and 1-m) aerial imagery and 30-m PIDS-detection maps. Results show that PIDS typically detects mountain pine beetle infestation when ≥56% of a Landsat pixel is occupied by red-stage canopy mortality (one year after initial infestation), and spruce beetle infestation when ≥55% is occupied by gray-stage mortality (two years after initial infestation). This study addresses an important methodological goal pertinent to the utility of event-based reference samples for detecting subtle forest change, which could be potentially applied to other types of subtle land change

Ecological insights from three decades of animal movement tracking across a changing Arctic

The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature

Ecological insights from three decades of animal movement tracking across a changing Arctic

The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.</p