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In this study, we automate tree species classification and mapping using field-based training data, high spatial resolution airborne hyperspectral imagery, and a convolutional neural network classifier (CNN). We tested our methods by identifying seven dominant trees species as well as dead standing trees in a mixed-conifer forest in the Southern Sierra Nevada Mountains, CA (USA) using training, validation, and testing datasets composed of spatially-explicit transects and plots sampled across a single strip of imaging spectroscopy. We also used a three-band 'Red-Green-Blue' pseudo true-color subset of the hyperspectral imagery strip to test the classification accuracy of a CNN model without the additional non-visible spectral data provided in the hyperspectral imagery. Our classifier is pixel-based rather than object based, although we use three-dimensional structural information from airborne Light Detection and Ranging (LiDAR) to identify trees (points > 5 m above the ground) and the classifier was applied to image pixels that were thus identified as tree crowns. By training a CNN classifier using field data and hyperspectral imagery, we were able to accurately identify tree species and predict their distribution, as well as the distribution of tree mortality, across the landscape. Using a window size of 15 pixels and eight hidden convolutional layers, a CNN model classified the correct species of 713 individual trees from hyperspectral imagery with an average F-score of 0.87 and F-scores ranging from 0.67-0.95 depending on species. The CNN classification model performance increased from a combined F-score of 0.64 for the Red-Green-Blue model to a combined F-score of 0.87 for the hyperspectral model. The hyperspectral CNN model captures the species composition changes across ~700 meters (1935 to 2630 m) of elevation from a lower-elevation mixed oak conifer forest to a higher-elevation fir-dominated coniferous forest. High resolution tree species maps can support forest ecosystem monitoring and management, and identifying dead trees aids landscape assessment of forest mortality resulting from drought, insects and pathogens. We publicly provide our code to apply deep learning classifiers to tree species identification from geospatial imagery and field training data.

The Endangered Species Act (ESA) has succeeded in shielding hundreds of species from extinction and improving species recovery over time. However, recovery for most species officially protected by the ESA - i.e., listed species-has been harder to achieve than initially envisioned. Threats to species are persistent and pervasive, funding has been insufficient, the distribution of money among listed species is highly uneven, and at least 10 times more species than are actually listed probably qualify for listing. Moreover, many listed species will require ongoing management for the foreseeable future to protect them from persistent threats. Climate change will exacerbate this problem and increase both species risk and management uncertainty, requiring more intensive and controversial management strategies to prevent species from going extinct.

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 (CWDwy) and mean August maximum daily temperature (Tmax) 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 CWDwy and to a lesser degree with modeled Tmax. Q. kelloggii seedling establishment is most strongly associated with Tmax and best predicted by a two-factor model including CWDwy and Tmax. 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.

In this study pollinators visiting highbush blueberry fields set in landscapes with differing land use pattern in south-central Chile were investigated. Effects of spatial buffers from 0.5 to 8 km around each blueberry field on the abundance of the main wild pollinator, Bombus terrestris queens, were tested. Wild B. terrestris abundances were positively affected by natural forest area and negatively affected by high-food resource area, and these effects were strongest at a buffer radius of 1 and 3.5 km, respectively. Possibly, continuous food resources provided by natural forest areas favor colony establishment and growth, and/or increase overwintering survival of bumblebee queens. Also, pollinator dependent crop area can generate a “transient dilution effect” by decreasing the density of bumblebees in simultaneously flowering crops. Management strategies might increase crop pollination services by considering the importance of nesting and overwintering habitat quality/amount and area of simultaneously flowering crops requiring insect pollination.

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.

Aim: Forest regeneration data provide an early signal of the persistence and migration of tree species, so we investigated whether species shifts due to climate change exhibit a common signal of response or whether changes vary by species. Location: California Floristic Province, United States; mediterranean biome. Methods: We related Forest Inventory and Analysis (FIA) data from 2000-07 for 13 tree species to high-resolution climate and geographical data. Using methods from invasion ecology, we derived indices of species-specific regeneration overlap and central tendency change (range-wide global indicators) based on kernel density estimation of presence and absence of regeneration. We then built regeneration surfaces to identify areas of occurrence of high regeneration (regeneration hotspots, local indicators) in both geographical and climate space for 13 common tree species. Results: Differences between presence and absence of regeneration in forests varied in magnitude across species, with little evidence that tree regeneration is shifting to higher latitudes and elevations, the expected geographical fingerprint of climate change. We also identified potential topographic mediators of regeneration dynamics. Multiple regeneration hotspots were found for many species, suggesting the influence of non-climatic factors on regeneration. Differences between the presence and absence of regeneration in geographic and climate spaces were not always congruent, suggesting that shifting climate space and range area are not entirely coupled. Main conclusions: The distributions of regeneration in Californian forests show diverse signals, not always tracking the higher latitudinal-elevation fingerprint of climate change. Local regeneration hotspots are common in our analysis, suggesting spatially varying persistence of forest linked to natural and anthropogenic disturbances. Our results emphasize that projections of tree range shifts in the context of climate change should consider the variation of regeneration drivers within species ranges, beyond the overall climate signal.

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. 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. 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.

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.

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.

Many aspects of the Californian approach to controlling the greenhouse gases that cause climate change now have a sufficient track record to provide potential models or lessons for national and even international action. In comparison, the state's efforts on climate change adaptation, although multifaceted, are less well developed and thus far have focused largely on information sharing, impact assessments, and planning. Still, adaptation could advance more quickly in California than in many other regions, given relatively high public awareness and concern, extensive scientific information, a strong tradition of local and regional planning, and some enabling policies and institutions. Much more political support and sufficient financing will have to be mustered at state and local levels to enable new projects and initiatives to cope with sea level rise, water management, and ecosystem adaptation, not to mention public health and other key areas of concern. Even so, California's initial efforts to adapt to unavoidable changes in climate may offer insights for other governments that will, inevitably, need to fashion their own adaptation strategies. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

After solar and other renewable energy developers select generally suitable sites for exploration, they frequently encounter conflict over biodiversity conservation values that were not factored into the initial suitability rating methods. This paper presents a spatial multicriteria analysis method for modeling risk of conflict with biological resources and applies the model in the California deserts where such conflicts are rapidly rising. The premise of the model is that the least conflict will occur on sites that are the most ecologically degraded with low conservation value and that would engender low off-site impacts when connecting to existing transmission infrastructure. Model results suggest sufficient compatible land exists in flat, non-urban areas to meet state solar energy targets of 8.7 GW of installed capacity in the California deserts for 2040. The model is a promising tool to fill the gap between site suitability analysis for renewable energy and regional biodiversity conservation planning to identify areas where rapid impact assessment and permitting will generate the least regrets. © 2013 Elsevier Ltd.

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. © 2012 by American Institute of Biological Sciences. All rights reserved.

Biofuels from agricultural sources are an important part of California's strategy to reduce greenhouse gas emissions and dependence on foreign oil. Land conversion for agricultural and urban uses has already imperiled many animal species in the state. This study investigated the potential impacts on wildlife of shifts in agricultural activity to increase biomass production for transportation fuels. We applied knowledge of the suitability of California's agricultural landscapes for wildlife species to evaluate wildlife effects associated with plausible scenarios of expanded production of three potential biofuel crops (sugar beets, bermudagrass, and canola). We also generated alternative, spatially explicit scenarios that minimized loss of habitat for the same level of biofuel production. We explored trade-offs to compare the marginal changes per unit of energy for transportation costs, wildlife, land and water-use, and total energy produced, and found that all five factors were influenced by crop choice. Sugar beet scenarios require the least land area: 3.5 times less land per liter of gasoline equivalent than bermudagrass and five times less than canola. Canola scenarios had the largest impacts on wildlife but the greatest reduction in water use. Bermudagrass scenarios resulted in a slight overall improvement for wildlife over the current situation. Relatively minor redistribution of lands converted to biofuel crops could produce the same energy yield with much less impact on wildlife and very small increases in transportation costs. This framework provides a means to systematically evaluate potential wildlife impacts of alternative production scenarios and could be a useful complement to other frameworks that assess impacts on ecosystem services and greenhouse gas emissions. © 2011 Blackwell Publishing Ltd.

For centuries humans have reduced and transformed Mediterranean-climate oak woodland and savanna ecosystems, making it difficult to establish credible baselines for ecosystem structure and composition that can guide ecological restoration efforts. We combined historical data sources, with particular attention to mid-1800s General Land Office witness tree records and maps and twentieth century air photos, to reconstruct 150 years of decline in extent and stand density of Valley oak (Quercus lobata Neé) woodlands and savannas in the Santa Clara Valley of central coastal California. Nineteenth century Valley oak woodlands here were far more extensive and densely stocked than early twentieth century air photos would suggest, although reconstructed basal areas (7.5 m2/ha) and densities (48.9 trees/ha) were not outside the modern range reported for this ecosystem type. Tree densities and size distribution varied across the landscape in relation to soil and topography, and trees in open savannas were systematically larger than those in denser woodlands. For the largest woodland stand, we estimated a 99% decline in population from the mid-1800s to the 1930s. Although most of the study area is now intensely developed, Valley oaks could be reintroduced in urban and residential areas as well as in surrounding rangelands at densities comparable to the native oak woodlands and savannas, thereby restoring aspects of ecologically and culturally significant ecosystems, including wildlife habitat and genetic connectivity within the landscape. © 2010 Society for Ecological Restoration International.

Decisions about which places to conserve are based upon the geographic heterogeneity of three types of information: public goods or benefits, their vulnerability to threats, and the costs to avert those threats. The choice of public goods depends on the mission of the conservation organization (e.g., biodiversity, open space, cultural values, or farmland). For spatial targeting of conservation at the regional scale, practitioners must estimate the values of these types of information. The quality of the estimations will vary by the primary data used, the assumptions made, and the practitioner's technical ability to analyze complex data. This paper contributes to the growing literature by presenting a systematic evaluation of effect of the quality of the estimation on the cost-effectiveness of the set of sites selected for conservation based upon those estimates. The specific case study targets farmland for preservation from urban development in California's Central Valley where a new land trust was recently established to purchase conservation easements. In one analysis, we compared the cost-effectiveness of farmland benefits using our most sophisticated estimation procedures to those that ignored costs and/or potential loss (i.e., assumed they were equal among sites). Excluding information about the potential loss of resources caused only a slight decrease in cost-effectiveness. On the other hand, ignoring cost information was extremely inefficient. The second analysis compared the performance of the sophisticated estimate to increasingly simpler estimates, such as those that are representative of the methods used by many American farmland preservation programs. The simplification of the estimates caused a 5- to 20-fold decline in the benefits that could be retained for a given budget. To make more cost-effective targeting strategies accessible to farmland preservation programs, we recommend that researchers develop new spatial targeting tools to overcome obstacles in data processing. © 2010 Elsevier Ltd.

Regrowth after fire is critical to the persistence of chaparral shrub communities in southern California, which has been subject to frequent fire events in recent decades. Fires that recur at short intervals of 10 years or less have been considered an inhibitor of recovery and the major cause of 'community type-conversion' in chaparral, primarily based on studies of small extents and limited time periods. However, recent sub-regional investigations based on remote sensing suggest that short-interval fire (SIF) does not have ubiquitous impact on postfire chaparral recovery. A region-wide analysis including a greater spatial extent and time period is needed to better understand SIF impact on chaparral. This study evaluates patterns of postfire recovery across southern California, based on temporal trajectories of Normalized Difference Vegetation Index (NDVI) derived from June-solstice Landsat image series covering the period 1984-2018. High spatial resolution aerial images were used to calibrate Landsat NDVI trajectory-based estimates of change in fractional shrub cover (dFSC) for 294 stands. The objectives of this study were (1) to assess effects of time between fires and number of burns on recovery, using stand-aggregate samples (n = 294) and paired single- and multiple-burn sample plots (n = 528), and (2) to explain recovery variations among predominant single-burn locations based on shrub community type, climate, soils, and terrain. Stand-aggregate samples showed a significant but weak effect of SIF on recovery (p < 0.001; R 2  = 0.003). Results from paired sample plots showed no significant effect of SIF on dFSC among twice-burned sites, although recovery was diminished due to SIF at sites that burned three times within 25 years. Multiple linear regression showed that annual precipitation and temperature, chaparral community type, and edaphic variables explain 28% of regional variation in recovery of once-burned sites. Many stands that exhibited poor recovery had burned only once and consist of xeric, desert-fringe chamise in soils of low clay content., Competing Interests: Declaration of competing interest No conflict of interest is reported by the authors., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Objective: To examine the proportion of skeletally immature anterior cruciate ligament reconstructed (ACLR) patients who achieve ≥90% of lower extremity recovery at 6-9 months post-operatively., Design: Cross-sectional study., Setting: Biomechanical laboratory., Participants: Skeletally immature ACLR patients., Main Outcome Measure(s): Muscular strength (quadriceps, hamstrings, hip abductors, and hip extensors), dynamic balance (anterior reach, posteromedial reach, and posterolateral reach), and functional hops tests (single hop, triple hops, cross-over hops, and 6 m timed hops) were examined. The primary outcome variable was the proportion of the study patients whose limb symmetry index (LSI) were ≥90% during return to sport (RTS) tests., Results: A total of 105 skeletally immature ACLR patients who are planning to return to sporting activities (age: 13.4 ± 1.4 years) were enrolled. The proportion of skeletally immature ACLR patients who achieved ≥90% of LSI in all four strength, three balance, and four hop tests were 20.0%, 65.4%, and 27.8%. In those who completed all test battery (72/105), only 4.2% of skeletally immature ACLR patients demonstrated ≥90% of LSI in all RTS tests., Conclusion: A small proportion of skeletally immature ACLR patients demonstrated ≥90% of lower extremity recovery approximately at 7 months following ACLR., Competing Interests: Declaration of competing interest All authors have no conflict of interest to disclose., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Chaparral shrubs in southern California may be vulnerable to frequent fire and severe drought. Drought may diminish postfire recovery or worsen impact of short-interval fires. Field-based studies have not shown the extent and magnitude of drought effects on recovery, which may vary among chaparral types and climatic zones. We tracked regional patterns of shrub cover based on June-solstice Landsat Normalized Difference Vegetation Index series, compared between the periods 1984-1989 and 2014-2018. High spatial resolution ortho-imagery was used to map shrub cover in distributed sample plots, to empirically constrain the Landsat-based estimates of mature-stage lateral canopy recovery. We evaluated precipitation, climatic water deficit (CWD), and Palmer Drought Severity Index in summer and wet seasons preceding and following fire, as regional predictors of recovery in 982 locations between the Pacific Coast and inland deserts. Wet-season CWD was the strongest drought-metric predictor of recovery, contributing 34-43 % of explanatory power in multivariate regressions ( R 2 =0.16-0.42). Limited recovery linked to drought was most prevalent in transmontane chamise chaparral; impacts were minor in montane areas, and in mixed and montane chaparral types. Elevation was correlated negatively to recovery of transmontane chamise; this may imply acute drought sensitivity in resprouts which predominate seedlings at higher elevations. Landsat Visible Atmospherically Resistant Index (sensitive to live-fuel moisture) was evaluated as a landscape-scale predictor of recovery and explained the greatest amount of variance in a multivariate regression ( R 2 = 0.53). We find that drought severity was more closely related to recovery differences among twice-burned sites than was fire-return interval. Summarily, drought has a major role in long-term shrub cover reduction within xeric chaparral ecotones bounding the Mojave Desert and Colorado Desert, likely in tandem with other global change stressors., Competing Interests: Conflict of interest The authors declare that they have no conflict of interest.

The field of systematic conservation planning has grown substantially, with hundreds of publications in the peer-reviewed literature and numerous applications to regional conservation planning globally. However, the extent to which systematic conservation plans have influenced management is unclear. This paper analyses factors that facilitate the transition from assessment to implementation in conservation planning, in order to help integrate assessment and implementation into a seamless process. We propose a framework for designing implementation strategies, taking into account three critical planning aspects: processes, inputs, and context. Our review identified sixteen processes, which we broadly grouped into four themes and eight inputs. We illustrate how the framework can be used to inform context-dependent implementation strategies, using the process of 'engagement' as an example. The example application includes both lessons learned from successfully implemented plans across the engagement spectrum, and highlights key barriers that can hinder attempts to bridge the assessment-implementation gap.

The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite-based sensors can repeatedly record the visible and near-infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100-m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short-wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14-bit digitization, absolute radiometric calibration <2%, relative calibration of 0.2%, polarization sensitivity <1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3-d repeat low-Earth orbit could sample 30-km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications., (© 2018 The Authors Ecological Applications published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.)

We synthesize insights from current understanding of drought impacts at stand-to-biogeographic scales, including management options, and we identify challenges to be addressed with new research. Large stand-level shifts underway in western forests already are showing the importance of interactions involving drought, insects, and fire. Diebacks, changes in composition and structure, and shifting range limits are widely observed. In the eastern US, the effects of increasing drought are becoming better understood at the level of individual trees, but this knowledge cannot yet be confidently translated to predictions of changing structure and diversity of forest stands. While eastern forests have not experienced the types of changes seen in western forests in recent decades, they too are vulnerable to drought and could experience significant changes with increased severity, frequency, or duration in drought. Throughout the continental United States, the combination of projected large climate-induced shifts in suitable habitat from modeling studies and limited potential for the rapid migration of tree populations suggests that changing tree and forest biogeography could substantially lag habitat shifts already underway. Forest management practices can partially ameliorate drought impacts through reductions in stand density, selection of drought-tolerant species and genotypes, artificial regeneration, and the development of multistructured stands. However, silvicultural treatments also could exacerbate drought impacts unless implemented with careful attention to site and stand characteristics. Gaps in our understanding should motivate new research on the effects of interactions involving climate and other species at the stand scale and how interactions and multiple responses are represented in models. This assessment indicates that, without a stronger empirical basis for drought impacts at the stand scale, more complex models may provide limited guidance., (© 2016 John Wiley & Sons Ltd.)

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.

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.

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.

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., (© 2012 Blackwell Publishing Ltd.)

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 valley oak (Quercus lobata Née) is a seriously threatened endemic oak species in California and a keystone species for foothill oak ecosystems. Urban and agricultural development affects a significant fraction of the species' range and predicted climate change is likely to dislocate many current populations. Here, we explore spatial patterns of multivariate genotypes and genetic diversity throughout the range of valley oak to determine whether ongoing and future patterns of habitat loss could threaten the evolutionary potential of the species by eradicating populations of distinctive genetic composition. This manuscript will address three specific questions: (i) What is the spatial genetic structure of the chloroplast and nuclear genetic markers? (ii) What are the geographical trends in the distribution of chloroplast and nuclear genotypes? (iii) Is there any part of the species' range where allelic diversity in either the chloroplast or nuclear genomes is particularly high? We analysed six chloroplast and seven nuclear microsatellite genetic markers of individuals widespread across the valley oak range. We then used a multivariate approach correlating genetic markers and geographical variables through a canonical trend surface analysis, followed by GIS mapping of the significant axes. We visualized population allelic richness spatially with GIS tools to identify regions of high diversity. Our findings, based on the distribution of multivariate genotypes and allelic richness, identify areas with distinctive histories and genetic composition that should be given priority in reserve network design, especially because these areas also overlap with landscape change and little degree of protection. Thus, without a careful preservation plan, valuable evolutionary information will be lost for valley oak.

We analyzed recent survey data and mapped environmental variables integrated over a home range scale of 10 km2 to model the distribution of fisher (Martes pennanti) habitat in California, USA. Our goal was to identify habitat factors associated with the current distribution of fishers in California, and to test whether those factors differ for widely disjunct northern and southern populations. Our analyses were designed to probe whether poor habitat quality can explain the current absence of fishers in the historically occupied central and northern Sierra Nevada region that separates these two populations. Fishers were detected at 64/433 (14.8%) sample units, including 35/111 (32%) of sample units in the Klamath/Shasta region and 28/88 (32%) of sample units in the southern Sierra Nevada. Generalized additive models (GAM) that included mean annual precipitation, topographic relief, forest structure, and a spatial autocovariate term best predicted fisher detections over the species' recent historical range in California. Models derived using forest structure data from ground plots were comparable to models derived from Landsat Thematic Mapper imagery. Models for the disjunct Klamath/Cascades and southern Sierra Nevada populations selected different environmental factors and showed low agreement in the spatial pattern of model predictions. Including a spatial autocovariate term significantly improved model fits for all models except the southern Sierra Nevada. We cannot rule out dispersal or habitat in explaining the absence of fishers in the northern and central Sierra Nevada, but mapped habitat quality is low over much of the region. Landscapes with good fisher habitat may exist in rugged forested canyons of the currently unoccupied northern Sierra Nevada, but these areas are fragmented and at least 60 km from the nearest recent fisher detections.

We review published studies on the demography and recruitment of California oak trees and focus on the widespread dominant species of the foothill woodlands, Quercus douglasii, Q. lobata, and Q. agrifolia, to ascertain the nature and strength of evidence for a decline in populations of these species. The vast majority of studies have been of short duration (less than three years), focused on the acorn and seedling life stages, and conducted at few locations within each species geographic range. We summarize the extensive body of research that has been conducted on the biological and physical factors that limit natural seedling recruitment of oaks. The oak "regeneration problem" has largely been inferred from current stand structure rather than by demographic analyses, which in part reflects the short-term nature of most oak research. When viewed over longer periods of time usingfield surveys or historical photos, the evidence for a regeneration problem in foothill oaks is mixed. Q. douglasii shows very limited seedling or sapling recruitment at present, but longer term studies do not suggest a decline in tree density, presumably because rare recruitment is sufficient to offset low rates of mortality of overstory individuals. Q. agrifolia appears to be stable or increasing in some areas, but decreasing in areas recently impacted by the disease Phytophthora ramorum. Evidence from the few available studies is more consistent in suggesting long-term declines in foothill populations of Q. lobata. Long-term monitoring, age structure analysis, and population models are needed to resolve the current uncertainty over the sustainability of oak woodlands in California.

California Valley oak (Quercus lobata), one of the state's most distinctive oak species, has experienced serious demographic attrition since the 19th century, due to human activities. Recent estimates of pollen dispersal suggest a small reproductive neighborhood. Whether small neighborhood size is a recent phenomenon, a consequence of reduced gene flow caused by demographic changes, or whether it has been historically restricted, remains unclear. To examine this question, we have characterized the spatial genetic structure of N = 191 Q. lobata individuals, spread over an area of 230 ha, using eight microsatellite loci. The observed autocorrelogram suggests an historical standard deviation of gene flow distance of about 350 m per generation, higher than contemporary pollen dispersal estimates. To determine whether our estimates were affected by strong prevailing winds from the west-northwest, we developed and utilized a novel anisotropic autocorrelation analysis. We detected no more than a hint of anisotropy, and we concluded that adult spatial structure is indicative of strong historical signature of "isolation by distance." This historical estimate provides a useful reference value against which to gauge the future gene flow consequences of ongoing anthropogenic disturbance.

The fragmented populations and reduced population densities that result from human disturbance are issues of growing importance in evolutionary and conservation biology. A key issue is whether remnant individuals become reproductively isolated. California Valley oak (Quercus lobata) is a widely distributed, endemic species in California, increasingly jeopardized by anthropogenic changes in biota and land use. We studied pollen movement in a savannah population of Valley oak at Sedgwick Reserve, Santa Barbara County, to estimate effective number of pollen donors (Nep) and average distance of effective pollen movement (delta). Using twogener, our recently developed hybrid model of paternity and genetic structure treatments that analyses maternal and progeny multilocus genotypes, we found that current Nep = 3.68 individuals. Based on an average adult density of d= 1.19 stems/ha, we assumed a bivariate normal distribution to model current average pollen dispersal distance (delta) and estimated delta= 64.8 m. We then deployed our parameter estimates in spatially explicit models of the Sedgwick population to evaluate the extent to which Nep may have changed, as a consequence of progressive stand thinning between 1944 and 1999. Assuming that pollen dispersal distance has not changed, we estimate Nep was 4.57 individuals in 1944, when stand density was 1.48. Both estimates indicate fewer effective fathers than one might expect for wind-pollinated species and fewer than observed elsewhere. The results presented here provide a basis for further refinements on modelling pollen movement. If the trends continue, then ongoing demographic attrition could further reduce neighbourhood size in Valley oak resulting in increased risk of reproductive failure and genetic isolation.

Evaluating the characteristics of a set of sites as potential scientific research reserves is an example of land suitability assessment. Suitability in this case is based upon multiple criteria, many of which can be linguistically imprecise and often incompatible. Fuzzy logic is a useful method for characterizing imprecise suitability criteria and for combining criteria into an overall suitability rating. The Ecosystem Management Decision Support software combined a fuzzy logic knowledge base we developed to represent the assessment problem with a GIS database providing site-specific data for the assessment. Assessment of sites as a potential natural reserve for the new University of California campus at Merced demonstrates the benefits of fuzzy suitability assessment. The study was conducted in three stages of successively smaller assessment regions with increasingly fine spatial resolution and specificity of criteria. Several sites were identified that best satisfy the suitability criteria for a reserve to represent vernal pool habitat.

The effectiveness and cost of three techniques for obtaining client ratings of their own levels of functioning were assessed in a private, outpatient, mental health clinic. Seventy-five clients were asked to rate the adequacy of their own functioning on vocational, family, social, personal, and overall dimensions. Clients were randomly assigned to (a) mail, (b) telephone, or (c) mail followed (if necessary) by telephone administration of the ratings questionnaire. Mail followed if necessary by phone administration was found to be more cost effective than either mail alone or telephone alone.