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Frank W. Davis

Publications and source records attributed to Frank W. Davis.

At least 19 recordsLinked to original sources
USGS2025

Unlocking ecological insights from sub-seasonal visible-to-shortwave infrared imaging spectroscopy: The SHIFT campaign

We stand at the threshold of a transformative era in Earth observation, marked by space-borne visible-to-shortwave infrared (VSWIR) imaging spectrometers that promise consistent global observations of ecosystem function, phenology, and inter- and intra-annual change. However, the full value of repeat spectroscopy, the information embedded within different temporal scales, and the reliability of existing algorithms across diverse ecosystem types and vegetation phenophases have remained elusive due to the absence of suitable sub-seasonal spectroscopy data. In response, the Surface Biology and Geology (SBG) High-Frequency Time Series (SHIFT) campaign was initiated during late February 2022 in Santa Barbara County, California. SHIFT, designed to support NASA's SBG mission, addressed mission scoping, scientific advancement, applications development, and community building. This ambitious endeavor included weekly Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) imagery acquisitions for 13 weeks (spanning February 24 to May 29, 2022), accompanied by coordinated terrestrial vegetation and coastal aquatic data collection. We describe the rich datasets collected and illustrate how the complex sub-seasonal patterns of change can be linked to biological science and applications, surpassing insights from multispectral observations. Leveraging open-source processing methods and cloud-based analysis tools, the SHIFT campaign showcases the readiness of the scientific community to harness ecological insights from remotely sensed hyperspectral time series. We provide an overview of SHIFT's goals, data collections, preliminary results, and the collaborative efforts of early career scientists committed to unlocking the transformative potential of high-frequency time series data from space-borne VSWIR imaging spectrometers.

Ecosphere↗
USGS2017

Synthesis centers as critical research infrastructure

Demand for the opportunity to participate in a synthesis-center activity has increased in the years since the US National Science Foundation (NSF)–funded National Center for Ecological Analysis and Synthesis (NCEAS) opened its doors in 1995 and as more scientists across a diversity of scientific disciplines have become aware of what synthesis centers provide. The NSF has funded four synthesis centers, and more than a dozen new synthesis centers have been established around the world, some following the NSF model and others following different models suited to their national funding environment ( http://synthesis-consortium.org ). Scientific synthesis integrates diverse data and knowledge to increase the scope and applicability of results and yield novel insights or explanations within and across disciplines (Pickett et al. 2007 , Carpenter et al. 2009 ). The demand for synthesis comes from the pressing societal need to address grand challenges related to global change and other issues that cut across multiple societal sectors and disciplines and from recognition that substantial added scientific value can be achieved through the synthesis-based analysis of existing data. Demand also comes from groups of scientists who see exciting opportunities to generate new knowledge from interdisciplinary and transdisciplinary collaboration, often capitalizing on the increasingly large volume and variety of available data (Kelling et al. 2009 , Bishop et al. 2014 , Specht et al. 2015b ). The ever-changing nature of societal challenges and the availability of data with which to address them suggest there will be an expanding need for synthesis. However, we are now entering a phase in which government support for some existing synthesis centers has ended or will be ending soon, forcing those centers to close or develop new operational models, approaches, and funding streams. We argue here that synthesis centers play such a unique role in science that continued long-term public investment to maximize benefits to science and society is justified. In particular, we argue that synthesis centers represent community infrastructure more akin to research vessels than to term-funded centers of science and technology (e.g., NSF Science and Technology Centers). Through our experience running synthesis centers and, in some cases, developing postfederal funding models, we offer our perspective on the purpose and value of synthesis centers. We present case studies of different outcomes of transition plans and argue for a fundamental shift in the conception of synthesis science and the strategic funding of these centers by government funding agencies.

BioScience↗
USGS2017

Developing a translational ecology workforce

We define a translational ecologist as a professional ecologist with diverse disciplinary expertise and skill sets, as well as a suitable personal disposition, who engages across social, professional, and disciplinary boundaries to partner with decision makers to achieve practical environmental solutions. Becoming a translational ecologist requires specific attention to obtaining critical non‐scientific disciplinary breadth and skills that are not typically gained through graduate‐level education. Here, we outline a need for individuals with broad training in interdisciplinary skills, use our personal experiences as a basis for assessing the types of interdisciplinary skills that would benefit potential translational ecologists, and present steps that interested ecologists may take toward becoming translational. Skills relevant to translational ecologists may be garnered through personal experiences, informal training, short courses, fellowships, and graduate programs, among others. We argue that a translational ecology workforce is needed to bridge the gap between science and natural resource decisions. Furthermore, we argue that this task is a cooperative responsibility of individuals interested in pursuing these careers, educational institutions interested in training scientists for professional roles outside of academia, and employers seeking to hire skilled workers who can foster stakeholder‐engaged decision making.

Frontiers in Ecology and the Environment↗
USGS2017

Foundations of translational ecology

Ecologists who specialize in translational ecology (TE) seek to link ecological knowledge to decision making by integrating ecological science with the full complement of social dimensions that underlie today's complex environmental issues. TE is motivated by a search for outcomes that directly serve the needs of natural resource managers and decision makers. This objective distinguishes it from both basic and applied ecological research and, as a practice, it deliberately extends research beyond theory or opportunistic applications. TE is uniquely positioned to address complex issues through interdisciplinary team approaches and integrated scientist–practitioner partnerships. The creativity and context‐specific knowledge of resource managers, practitioners, and decision makers inform and enrich the scientific process and help shape use‐driven, actionable science. Moreover, addressing research questions that arise from on‐the‐ground management issues – as opposed to the top‐down or expert‐oriented perspectives of traditional science – can foster the high levels of trust and commitment that are critical for long‐term, sustained engagement between partners.

Frontiers in Ecology and the Environment↗
USGS2016

Shrinking windows of opportunity for oak seedling establishment in southern California mountains

Seedling establishment is a critical step that may ultimately govern tree species’ distribution shifts under environmental change. Annual variation in the location of seed rain and microclimates results in transient “windows of opportunity” for tree seedling establishment across the landscape. These establishment windows vary at fine spatiotemporal scales that are not considered in most assessments of climate change impacts on tree species range dynamics and habitat displacement. We integrate field seedling establishment trials conducted in the southern Sierra Nevada and western Tehachapi Mountains of southern California with spatially downscaled grids of modeled water-year climatic water deficit (CWD wy ) and mean August maximum daily temperature ( T max ) to map historical and projected future microclimates suitable for establishment windows of opportunity for Quercus douglasii , a dominant tree species of warm, dry foothill woodlands, and Q. kelloggii , a dominant of cooler, more mesic montane woodlands and forests. Based on quasi-binomial regression models, Q. douglasii seedling establishment is significantly associated with modeled CWD wy and to a lesser degree with modeled T max . Q. kelloggii seedling establishment is most strongly associated with T max and best predicted by a two-factor model including CWD wy and T max . Establishment niche models are applied to explore recruitment window dynamics in the western Tehachapi Mountains, where these species are currently widespread canopy dominants. Establishment windows are projected to decrease by 50–95%, shrinking locally to higher elevations and north-facing slopes by the end of this century depending on the species and climate scenario. These decreases in establishment windows suggest the potential for longer-term regional population declines of the species. While many additional processes regulate seedling establishment and growth, this study highlights the need to account for topoclimatic controls and interannual climatic variation when assessing how seedling establishment and colonization processes could be affected by climate change.

California↗
USGS2015

High and dry: high elevations disproportionately exposed to regional climate change in Mediterranean-climate landscapes

Context Predicting climate-driven species’ range shifts depends substantially on species’ exposure to climate change. Mountain landscapes contain a wide range of topoclimates and soil characteristics that are thought to mediate range shifts and buffer species’ exposure. Quantifying fine-scale patterns of exposure across mountainous terrain is a key step in understanding vulnerability of species to regional climate change. Objectives We demonstrated a transferable, flexible approach for mapping climate change exposure in a moisture-limited, mountainous California landscape across 4 climate change projections under phase 5 of the Coupled Model Intercomparison Project (CMIP5) for mid-(2040–2069) and end-of-century (2070–2099). Methods We produced a 149-year dataset (1951–2099) of modeled climatic water deficit (CWD), which is strongly associated with plant distributions, at 30-m resolution to map climate change exposure in the Tehachapi Mountains, California, USA. We defined climate change exposure in terms of departure from the 1951–1980 mean and historical range of variability in CWD in individual years and 3-year moving windows. Results Climate change exposure was generally greatest at high elevations across all future projections, though we encountered moderate topographic buffering on poleward-facing slopes. Historically dry lowlands demonstrated the least exposure to climate change. Conclusions In moisture-limited, Mediterranean-climate landscapes, high elevations may experience the greatest exposure to climate change in the 21st century. High elevation species may thus be especially vulnerable to continued climate change as habitats shrink and historically energy-limited locations become increasingly moisture-limited in the future.

Landscape Ecology↗
USGS2015

Conservation planning for offsetting the impacts of development: a case study of biodiversity and renewable energy in the Mojave Desert

Balancing society’s competing needs of development and conservation requires careful consideration of tradeoffs. Renewable energy development and biodiversity conservation are often considered beneficial environmental goals. The direct footprint and disturbance of renewable energy, however, can displace species’ habitat and negatively impact populations and natural communities if sited without ecological consideration. Offsets have emerged as a potentially useful tool to mitigate residual impacts after trying to avoid, minimize, or restore affected sites. Yet the problem of efficiently designing a set of offset sites becomes increasingly complex where many species or many sites are involved. Spatial conservation prioritization tools are designed to handle this problem, but have seen little application to offset siting and analysis. To address this need we designed an offset siting support tool for the Desert Renewable Energy Conservation Plan (DRECP) of California, and present a case study of hypothetical impacts from solar development in the Western Mojave subsection. We compare two offset scenarios designed to mitigate a hypothetical 15,331 ha derived from proposed utility-scale solar energy development (USSED) projects. The first scenario prioritizes offsets based precisely on impacted features, while the second scenario offsets impacts to maximize biodiversity conservation gains in the region. The two methods only agree on 28% of their prioritized sites and differ in meeting species-specific offset goals. Differences between the two scenarios highlight the importance of clearly specifying choices and priorities for offset siting and mitigation in general. Similarly, the effects of background climate and land use change may lessen the durability or effectiveness of offsets if not considered. Our offset siting support tool was designed specifically for the DRECP area, but with minor code modification could work well in other offset analyses, and could provide continuing support for a potentially innovative mitigation solution to environmental impacts.

California↗
USGS2015

Tree mortality predicted from drought-induced vascular damage

The projected responses of forest ecosystems to warming and drying associated with twenty-first-century climate change vary widely from resiliency to widespread tree mortality 1 , 2 , 3 . Current vegetation models lack the ability to account for mortality of overstorey trees during extreme drought owing to uncertainties in mechanisms and thresholds causing mortality 4 , 5 . Here we assess the causes of tree mortality, using field measurements of branch hydraulic conductivity during ongoing mortality in Populus tremuloides in the southwestern United States and a detailed plant hydraulics model. We identify a lethal plant water stress threshold that corresponds with a loss of vascular transport capacity from air entry into the xylem. We then use this hydraulic-based threshold to simulate forest dieback during historical drought, and compare predictions against three independent mortality data sets. The hydraulic threshold predicted with 75% accuracy regional patterns of tree mortality as found in field plots and mortality maps derived from Landsat imagery. In a high-emissions scenario, climate models project that drought stress will exceed the observed mortality threshold in the southwestern United States by the 2050s. Our approach provides a powerful and tractable way of incorporating tree mortality into vegetation models to resolve uncertainty over the fate of forest ecosystems in a changing climate.

Nature Geoscience↗
USGS2015

Adapting California’s ecosystems to a changing climate

Significant efforts are underway to translate improved understanding of how climate change is altering ecosystems into practical actions for sustaining ecosystem functions and benefits. We explore this transition in California, where adaptation and mitigation are advancing relatively rapidly, through four case studies that span large spatial domains and encompass diverse ecological systems, institutions, ownerships, and policies. The case studies demonstrate the context specificity of societal efforts to adapt ecosystems to climate change and involve applications of diverse scientific tools (e.g., scenario analyses, downscaled climate projections, ecological and connectivity models) tailored to specific planning and management situations (alternative energy siting, wetland management, rangeland management, open space planning). They illustrate how existing institutional and policy frameworks provide numerous opportunities to advance adaptation related to ecosystems and suggest that progress is likely to be greatest when scientific knowledge is integrated into collective planning and when supportive policies and financing enable action.

BioScience↗
USGS2015

Can orchards help connect Mediterranean ecosystems? Animal movement data alter conservation priorities

As natural habitats become fragmented by human activities, animals must increasingly move through human-dominated systems, particularly agricultural landscapes. Mapping areas important for animal movement has therefore become a key part of conservation planning. Models of landscape connectivity are often parameterized using expert opinion and seldom distinguish between the risks and barriers presented by different crop types. Recent research, however, suggests different crop types, such as row crops and orchards, differ in the degree to which they facilitate or impede species movements. Like many mammalian carnivores, bobcats ( Lynx rufus ) are sensitive to fragmentation and loss of connectivity between habitat patches. We investigated how distinguishing between different agricultural land covers might change conclusions about the relative conservation importance of different land uses in a Mediterranean ecosystem. Bobcats moved relatively quickly in row crops but relatively slowly in orchards, at rates similar to those in natural habitats of woodlands and scrub. We found that parameterizing a connectivity model using empirical data on bobcat movements in agricultural lands and other land covers, instead of parameterizing the model using habitat suitability indices based on expert opinion, altered locations of predicted animal movement routes. These results emphasize that differentiating between types of agriculture can alter conservation planning outcomes.

California↗
USGS2014

Optimization in the utility maximization framework for conservation planning: a comparison of solution procedures in a study of multifunctional agriculture

Quantitative methods of spatial conservation prioritization have traditionally been applied to issues in conservation biology and reserve design, though their use in other types of natural resource management is growing. The utility maximization problem is one form of a covering problem where multiple criteria can represent the expected social benefits of conservation action. This approach allows flexibility with a problem formulation that is more general than typical reserve design problems, though the solution methods are very similar. However, few studies have addressed optimization in utility maximization problems for conservation planning, and the effect of solution procedure is largely unquantified. Therefore, this study mapped five criteria describing elements of multifunctional agriculture to determine a hypothetical conservation resource allocation plan for agricultural land conservation in the Central Valley of CA, USA. We compared solution procedures within the utility maximization framework to determine the difference between an open source integer programming approach and a greedy heuristic, and find gains from optimization of up to 12%. We also model land availability for conservation action as a stochastic process and determine the decline in total utility compared to the globally optimal set using both solution algorithms. Our results are comparable to other studies illustrating the benefits of optimization for different conservation planning problems, and highlight the importance of maximizing the effectiveness of limited funding for conservation and natural resource management.

California↗
USGS2013

Cross-scale modeling of surface temperature and tree seedling establishment inmountain landscapes

Abstract: Introduction: Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment, processes which occur at heights of only several centimeters. Currently, future climate models predict temperature at 2 m above ground, leaving ground-surface microclimate not well characterized. Methods: Using a network of field temperature sensors and climate models, a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature. Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution. Results: The surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing, south-facing, valley, and ridgeline topographic settings, and when compared to measured temperatures yielded an R2 of 0.88, 0.80, 0.88, and 0.80, respectively. Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures, resulting in R2 values of 0.86, 0.77, 0.72, and 0.79 for north-facing, south-facing, valley, and ridgeline topographic settings. Quasi-Poisson regressions predicting recruitment of Quercus kelloggii (black oak) seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m. Conclusion: Predicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment. Such methods could be applied to improve projections of species’ range shifts under climate change. Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes.

Ecological Processes↗
USGS2013

Carnivore use of avocado orchards across an agricultural-wildland gradient

Wide-ranging species cannot persist in reserves alone. Consequently, there is growing interest in the conservation value of agricultural lands that separate or buffer natural areas. The value of agricultural lands for wildlife habitat and connectivity varies as a function of the crop type and landscape context, and quantifying these differences will improve our ability to manage these lands more effectively for animals. In southern California, many species are present in avocado orchards, including mammalian carnivores. We examined occupancy of avocado orchards by mammalian carnivores across agricultural-wildland gradients in southern California with motion-activated cameras. More carnivore species were detected with cameras in orchards than in wildland sites, and for bobcats and gray foxes, orchards were associated with higher occupancy rates. Our results demonstrate that agricultural lands have potential to contribute to conservation by providing habitat or facilitating landscape connectivity.

California↗
USGS2013

Cumulative biological impacts framework for solar energy projects in the California Desert

This project developed analytical approaches, tools and geospatial data to support conservation planning for renewable energy development in the California deserts. Research focused on geographical analysis to avoid, minimize and mitigate the cumulative biological effects of utility-scale solar energy development. A hierarchical logic model was created to map the compatibility of new solar energy projects with current biological conservation values. The research indicated that the extent of compatible areas is much greater than the estimated land area required to achieve 2040 greenhouse gas reduction goals. Species distribution models were produced for 65 animal and plant species that were of potential conservation significance to the Desert Renewable Energy Conservation Plan process. These models mapped historical and projected future habitat suitability using 270 meter resolution climate grids. The results were integrated into analytical frameworks to locate potential sites for offsetting project impacts and evaluating the cumulative effects of multiple solar energy projects. Examples applying these frameworks in the Western Mojave Desert ecoregion show the potential of these publicly-available tools to assist regional planning efforts. Results also highlight the necessity to explicitly consider projected land use change and climate change when prioritizing areas for conservation and mitigation offsets. Project data, software and model results are all available online.

California↗
USGS2012

Modeling plant species distributions under future climates: how fine scale do climate projections need to be?

Recent studies suggest that species distribution models (SDMs) based on fine‐scale climate data may provide markedly different estimates of climate‐change impacts than coarse‐scale models. However, these studies disagree in their conclusions of how scale influences projected species distributions. In rugged terrain, coarse‐scale climate grids may not capture topographically controlled climate variation at the scale that constitutes microhabitat or refugia for some species. Although finer scale data are therefore considered to better reflect climatic conditions experienced by species, there have been few formal analyses of how modeled distributions differ with scale. We modeled distributions for 52 plant species endemic to the California Floristic Province of different life forms and range sizes under recent and future climate across a 2000‐fold range of spatial scales (0.008–16 km 2 ). We produced unique current and future climate datasets by separately downscaling 4 km climate models to three finer resolutions based on 800, 270, and 90 m digital elevation models and deriving bioclimatic predictors from them. As climate‐data resolution became coarser, SDMs predicted larger habitat area with diminishing spatial congruence between fine‐ and coarse‐scale predictions. These trends were most pronounced at the coarsest resolutions and depended on climate scenario and species' range size. On average, SDMs projected onto 4 km climate data predicted 42% more stable habitat (the amount of spatial overlap between predicted current and future climatically suitable habitat) compared with 800 m data. We found only modest agreement between areas predicted to be stable by 90 m models generalized to 4 km grids compared with areas classified as stable based on 4 km models, suggesting that some climate refugia captured at finer scales may be missed using coarser scale data. These differences in projected locations of habitat change may have more serious implications than net habitat area when predictive maps form the basis of conservation decision making.

California↗
USGS2012

A state-based national network for effective wildlife conservation

State wildlife conservation programs provide a strong foundation for biodiversity conservation in the United States, building on state wildlife action plans. However, states may miss the species that are at the most risk at rangewide scales, and threats such as novel diseases and climate change increasingly act at regional and national levels. Regional collaborations among states and their partners have had impressive successes, and several federal programs now incorporate state priorities. However, regional collaborations are uneven across the country, and no national counterpart exists to support efforts at that scale. A national conservation-support program could fill this gap and could work across the conservation community to identify large-scale conservation needs and support efforts to meet them. By providing important information-sharing and capacity-building services, such a program would advance collaborative conservation among the states and their partners, thus increasing both the effectiveness and the efficiency of conservation in the United States.

BioScience↗
USGS2010

Gene movement and genetic association with regional climate gradients in California valley oak ( Quercus lobata Née) in the face of climate change

Rapid climate change jeopardizes tree populations by shifting current climate zones. To avoid extinction, tree populations must tolerate, adapt, or migrate. Here we investigate geographic patterns of genetic variation in valley oak, Quercus lobata Née, to assess how underlying genetic structure of populations might influence this species’ ability to survive climate change. First, to understand how genetic lineages shape spatial genetic patterns, we examine historical patterns of colonization. Second, we examine the correlation between multivariate nuclear genetic variation and climatic variation. Third, to illustrate how geographic genetic variation could interact with regional patterns of 21st Century climate change, we produce region‐specific bioclimatic distributions of valley oak using Maximum Entropy (MAXENT) models based on downscaled historical (1971–2000) and future (2070–2100) climate grids. Future climatologies are based on a moderate‐high (A2) carbon emission scenario and two different global climate models. Chloroplast markers indicate historical range‐wide connectivity via colonization, especially in the north. Multivariate nuclear genotypes show a strong association with climate variation that provides opportunity for local adaptation to the conditions within their climatic envelope. Comparison of regional current and projected patterns of climate suitability indicates that valley oaks grow in distinctly different climate conditions in different parts of their range. Our models predict widely different regional outcomes from local displacement of a few kilometres to hundreds of kilometres. We conclude that the relative importance of migration, adaptation, and tolerance are likely to vary widely for populations among regions, and that late 21st Century conditions could lead to regional extinctions.

California↗