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In mountain landscapes, surface temperatures vary over short distances due to interacting influences of topography and overstory vegetation on local energy and water balances. At two study landscapes in the Sierra Nevada of California, characterized by foothill oak savanna at 276–481 m elevation and montane conifer forest at 1977–2135 m, we deployed 288 near-surface (5 cm above the surface) temperature sensors to sample site-scale (30 m) temperature variation related to hillslope orientation and vegetation structure and microsite-scale (2–10 m) variation related to microtopography and tree overstory. Daily near-surface maximum and minimum temperatures for the 2013 calendar year were related to topographic factors and vegetation overstory characterized using small footprint LiDAR imagery acquired by the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). At both landscapes we recorded large site and microsite spatial variation in daily maximum temperatures, and less absolute variation in daily minimum temperatures. Generalized boosted regression trees were estimated to measure the influence of tree canopy density, understory solar radiation, cold-air drainage and pooling, ground cover and microtopography on daily maximum and minimum temperatures at site and microsite scales. Site-scale models based on indices of understory solar radiation and landscape position explained an average of 61–65% of daily variation in maximum temperature; site-scale models based on tree canopy density and landscape position explained 65–83% of variation in minimum temperatures. Models explained

Wildfire activity is increasing globally. The resulting smoke plumes can travel hundreds to thousands of kilometers, reflecting or scattering sunlight and depositing particles within ecosystems. Several key physical, chemical, and biological processes in lakes are controlled by factors affected by smoke. The spatial and temporal scales of lake exposure to smoke are extensive and under‐recognized. We introduce the concept of the lake smoke‐day, or the number of days any given lake is exposed to smoke in any given fire season, and quantify the total lake smoke‐day exposure in North America from 2019 to 2021. Because smoke can be transported at continental to intercontinental scales, even regions that may not typically experience direct burning of landscapes by wildfire are at risk of smoke exposure. We found that 99.3% of North America was covered by smoke, affecting a total of 1,333,687 lakes ≥10 ha. An incredible 98.9% of lakes experienced at least 10 smoke‐days a year, with 89.6% of lakes receiving over 30 lake smoke‐days, and lakes in some regions experiencing up to 4 months of cumulative smoke‐days. Herein we review the mechanisms through which smoke and ash can affect lakes by altering the amount and spectral composition of incoming solar radiation and depositing carbon, nutrients, or toxic compounds that could alter chemical conditions and impact biota. We develop a conceptual framework that synthesizes known and theoretical impacts of smoke on lakes to guide future research. Finally, we identify emerging research priorities that can help us better understand how lakes will be affected by smoke as wildfire activity increases due to climate change and other anthropogenic activities. [ABSTRACT FROM AUTHOR]

Climate change has emerged as a major threat to biodiversity, but there have been few assessments of variability in sensitivity to climate across species’ ranges. We examined the sensitivity of ponderosa pine (Pinus ponderosa), a common, commercially important tree species found throughout the western United States, to climate variability using tree rings mostly from the International Tree Ring Data Bank (161 chronologies) and multiple climate products for 1930–1979. We compared interannual tree ring variation to water-year precipitation (wy ppt), May-July vapor pressure deficit (MJJ VPD), April-July precipitation (AMJJ ppt) and average winter (Dec-Feb) minimum temperature (winter tmn). We mapped growth-climate correlations for each variable and applied hierarchical agglomerative cluster analysis to identify five main groups of climate sensitivities, one of which contained mostly climate-insensitive populations. Ponderosa pine growth was positively correlated with wy ppt and AMJJ ppt and negatively correlated with MJJ VPD throughout its range, but sensitivities were greater in the Southern Rockies and Northern Great Plains than in Pacific and Southwestern populations. Sensitivities to winter tmn were weaker than responses to other climate variables, but Pacific and interior populations mostly demonstrated positive and negative responses, respectively. In summary, our analyses revealed the general pattern that interior populations of ponderosa pine were more climate-sensitive than Pacific populations, but there is considerable heterogeneity in sensitivity throughout the species’ range. Sensitivities to climate variables were related to position along corresponding climate gradients for all variables except MJJ VPD, but the unevenness of these relationships suggests a role of local adaptation. Our results illustrate the variation in climate response for a uniquely wide-ranging species and suggest that “leading” and “trailing” range edge concepts can oversimplify patterns of species exposure to climate change.

Climate adaptation corridors are widely recognized as important for promoting biodiversity resilience under climate change. Central America is part of the Mesoamerican biodiversity hotspot, but there have been no regional-scale analyses of potential climate adaptation corridors in Central America. We identified 2375 potential corridors throughout Central America that link lowland protected areas (≤ 500 m) with intact, high-elevation forests (≥ 1500 m) that represent potential climate change refugia. Whereas we found potential corridors in all Central American countries, potential corridors in Panama, Belize, and Honduras were most protected (medians = 64%, 49%, and 47%, respectively) and potential corridors in El Salvador were least protected (median = 10%). We also developed a corridor priority index based on the ecological characteristics and protected status of potential corridors and their associated start and end points. Compared to low- and medium-priority corridors, high-priority corridors (n = 160; top 7% of all corridors) were generally more protected, forested, and distributed across wider elevational gradients and more Key Biodiversity Areas, but also generally linked larger lowland protected areas to target areas that were larger, more protected, and spanned wider elevational gradients. For example, based on median values, high-priority corridors were 9% more protected and overlapped with 2–3 more Key Biodiversity Areas than low- and medium-priority corridors. Although high-elevation targets spanned considerably wider elevational gradients than lowland protected areas (medians = 695 vs. 142 m, respectively) and thus may be more likely to support refugia, they were considerably smaller than lowland protected areas (medians = 11 vs. 50 km2 respectively) and mostly unprotected (median = 4% protection). This initial, regional assessment can help prioritize locations for finer-scale research, conservation, and restoration activities in support of climate adaptation corridors throughout Central America and highlights the need for greater conservation of potential high-elevation refugia. [ABSTRACT FROM AUTHOR]

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.

Monitoring is essential to ensure that environmental goals are being achieved, including those of sustainable agriculture. Growing interest in environmental monitoring provides an opportunity to improve monitoring practices. Approaches that directly monitor land cover change and biodiversity annually by coupling the wall-to-wall coverage from remote sensing and the site-specific community composition from environmental DNA (eDNA) can provide timely, relevant results for parties interested in the success of sustainable agricultural practices. To ensure that the measured impacts are due to the environmental projects and not exogenous factors, sites where projects have been implemented should be benchmarked against counterfactuals (no project) and control (natural habitat) sites. Results can then be used to calculate diverse sets of indicators customized to monitor different projects. Here, we report on our experience developing and applying one such approach to assess the impact of shaded cocoa projects implemented by the Instituto de Manejo e Certificação Florestal e Agrícola (IMAFLORA) near São Félix do Xingu, in Pará, Brazil. We used the Continuous Degradation Detection (CODED) and LandTrendr algorithms to create a remote sensing-based assessment of forest disturbance and regeneration, estimate carbon sequestration, and changes in essential habitats. We coupled these remote sensing methods with eDNA analyses using arthropod-targeted primers by collecting soil samples from intervention and counterfactual pasture field sites and a control secondary forest. We used a custom set of indicators from the pilot application of a coupled monitoring framework called TerraBio. Our results suggest that, due to IMAFLORA's shaded cocoa projects, over 400 acres were restored in the intervention area and the community composition of arthropods in shaded cocoa is closer to second-growth forests than that of pastures. In reviewing the coupled approach, we found multiple aspects worked well, and we conclude by presenting multiple lessons learned. [ABSTRACT FROM AUTHOR]

A variety of classification approaches are used to facilitate understanding, prediction, monitoring, and the management of lakes. However, broad‐scale applicability of current approaches is limited by either the need for in situ lake data, incompatibilities among approaches, or a lack of empirical testing of approaches based on ex situ data. We developed a new geographic classification approach for 476,697 lakes ≥ 1 ha in the conterminous U.S. based on lake archetypes representing end members along gradients of multiple geographic features. We identified seven lake archetypes with distinct combinations of climate, hydrologic, geologic, topographic, and morphometric properties. Individual lakes were assigned weights for each of the seven archetypes such that groups of lakes with similar combinations of archetype weights tended to cluster spatially (although not strictly contiguous) and to have similar limnological properties (e.g., concentrations of nutrients, chlorophyll a (Chl a), and dissolved organic carbon). Further, archetype lake classification improved commonly measured limnological relationships (e.g., between nutrients and Chl a) compared to a global model; a discrete archetype classification slightly outperformed an ecoregion classification; and considering lakes as continuous mixtures of archetypes in a more complex model further improved fit. Overall, archetype classification of US lakes as continuous mixtures of geographic features improved understanding and prediction of lake responses to limnological drivers and should help researchers and managers better characterize and forecast lake states and responses to environmental change. [ABSTRACT FROM AUTHOR]

Despite increasing wildfires, few studies have investigated seasonal water quality responses to wildfire characteristics (e.g., burn severity) across a large number of lakes. We monitored 30 total lakes (15 burned, 15 control) monthly following the Greenwood Fire in Minnesota, USA, a lake‐rich region with historically prevalent wildfire. We found increases in median concentrations of total nitrogen (68%), total phosphorus (70%), dissolved organic carbon (127%), total suspended solids (71%), and reduced water clarity (48%) and pH (0.45) in burned lakes. Post‐wildfire responses in drainage lakes were often persistent or cumulative throughout the open‐water season, compared to isolated lakes. Total phosphorus (TP) increased linearly with watershed high‐severity burns, and shoreline high‐severity burns explained more variation in TP than lake morphometry and watershed variables. Post‐wildfire chlorophyll‐a responses were nonsignificant and inconsistent, possibly due to light limitation. Our results suggest that increasing wildfires have significant potential to affect water quality of inland lakes. Plain Language Summary: Despite increasing wildfire activity, there has been limited research on wildfire effects on lakes. We monitored lake water quality throughout summer 2022 following the 2021 Greenwood Fire in Minnesota, USA, a lake‐rich region where wildfire was historically common. We found that lakes with burned watersheds were more nutrient‐ and carbon‐rich and more acidic and murky. Responses often increased throughout the summer, particularly for lakes with tributaries from burned areas. However, murkier water may have prevented increased nutrients from increasing algae abundance. Water quality responses were greater following burns near lake shorelines and of greater severity, reflecting damage to vegetation and soil. Our results suggest that increasing wildfire under climate change may degrade lake water quality. Key Points: We observed post‐wildfire increases in nutrients, dissolved organic carbon, sediments, and acidity and reduced water clarity in lakesWater quality responses were often persistent or cumulative throughout the summer, especially for lakes with tributaries from burned areasHigh‐severity and shoreline burns resulted in a nearly two‐fold increase in total phosphorus concentration compared to control lakes [ABSTRACT FROM AUTHOR]

Maintaining regional‐scale freshwater connectivity is challenging due to the dendritic, easily fragmented structure of freshwater networks, but is essential for promoting ecological resilience under climate change. Although the importance of stream network connectivity has been recognized, lake‐stream network connectivity has largely been ignored. Furthermore, protected areas are generally not designed to maintain or encompass entire freshwater networks. We applied a coarse‐filter approach to identify potential freshwater corridors for diverse taxa by calculating connectivity scores for 385 lake‐stream networks across the conterminous United States based on network size, structure, resistance to fragmentation, and dam prevalence. We also identified 2080 disproportionately important lakes for maintaining intact networks (i.e., hubs; 2% of all network lakes) and analyzed the protection status of hubs and potential freshwater corridors. Just 3% of networks received high connectivity scores based on their large size and structure (medians of 1303 lakes, 498.6 km north–south stream distance), but these also contained a median of 454 dams. In contrast, undammed networks (17% of networks) were considerably smaller (medians of six lakes, 7.2 km north–south stream distance), indicating that the functional connectivity of the largest potential freshwater corridors in the conterminous United States currently may be diminished compared with smaller, undammed networks. Network lakes and hubs were protected at similar rates nationally across different levels of protection (8%–18% and 6%–20%, respectively), but were generally more protected in the western United States. Our results indicate that conterminous United States protection of major freshwater corridors and the hubs that maintain them generally fell short of the international conservation goal of protecting an ecologically representative, well‐connected set of fresh waters (≥17%) by 2020 (Aichi Target 11). Conservation planning efforts might consider focusing on restoring natural hydrologic connectivity at or near hubs, particularly in larger networks, less protected, or biodiverse regions, to support freshwater biodiversity conservation under climate change. [ABSTRACT FROM AUTHOR]

Clear Lake (Lake County, CA, USA) is hypereutrophic and used for drinking water, tribal use, and supports a significant fishing economy. The Mendocino Complex (2018), one of the largest wildfires in California's post‐settlement history, burned 40% of the Clear Lake watershed, providing a timely opportunity to study the impacts of historical and current wildfires on this valuable aquatic resource. Using long‐term monthly monitoring data from 1968 to 2019, paired with historical watershed fire data, we found that for the three largest fire years in the watershed's history, 3‐year postfire median July–October epilimnetic total phosphorus (TP) concentrations were below or equal to 3‐year prefire TP concentrations. However, both median TP epilimnetic concentrations and deepwater temperature across the lake have increased since the late 1960s. Long‐term TP increases were more strongly correlated with monthly maximum air temperatures than precipitation, suggesting a potential role of warming‐induced water column stratification, dissolved oxygen (DO) depletion, and high potential for internal phosphorus loading. Hypoxic occurrences were correlated with higher hypolimnetic soluble reactive phosphorus and TP concentrations, but additional high‐frequency monitoring of DO will help determine the duration of anoxia and its contribution to internal phosphorus loading. These long‐term data suggest that for this large, hypereutrophic lake, wildfires did not significantly alter in‐lake TP concentrations based on long‐term, monthly monitoring and that other internal or external sources of TP may mask any wildfire effects. Nonetheless, our study underscores the value of synthesizing decades of water quality, watershed wildfire, and climate data to build a more comprehensive, nuanced picture of multiple long‐term threats to aquatic ecosystems under global change. Moreover, monitoring and studying fire effects across a wide range of lake types beyond this study will help promote more effective lake management during changing climates and increasingly frequent large wildfires. [ABSTRACT FROM AUTHOR]

Near‐term ecological forecasts provide resource managers advance notice of changes in ecosystem services, such as fisheries stocks, timber yields, or water quality. Importantly, ecological forecasts can identify where there is uncertainty in the forecasting system, which is necessary to improve forecast skill and guide interpretation of forecast results. Uncertainty partitioning identifies the relative contributions to total forecast variance introduced by different sources, including specification of the model structure, errors in driver data, and estimation of current states (initial conditions). Uncertainty partitioning could be particularly useful in improving forecasts of highly variable cyanobacterial densities, which are difficult to predict and present a persistent challenge for lake managers. As cyanobacteria can produce toxic and unsightly surface scums, advance warning when cyanobacterial densities are increasing could help managers mitigate water quality issues. Here, we fit 13 Bayesian state‐space models to evaluate different hypotheses about cyanobacterial densities in a low nutrient lake that experiences sporadic surface scums of the toxin‐producing cyanobacterium, Gloeotrichia echinulata. We used data from several summers of weekly cyanobacteria samples to identify dominant sources of uncertainty for near‐term (1‐ to 4‐week) forecasts of G. echinulata densities. Water temperature was an important predictor of cyanobacterial densities during model fitting and at the 4‐week forecast horizon. However, no physical covariates improved model performance over a simple model including the previous week's densities in 1‐week‐ahead forecasts. Even the best fit models exhibited large variance in forecasted cyanobacterial densities and did not capture rare peak occurrences, indicating that significant explanatory variables when fitting models to historical data are not always effective for forecasting. Uncertainty partitioning revealed that model process specification and initial conditions dominated forecast uncertainty. These findings indicate that long‐term studies of different cyanobacterial life stages and movement in the water column as well as measurements of drivers relevant to different life stages could improve model process representation of cyanobacteria abundance. In addition, improved observation protocols could better define initial conditions and reduce spatial misalignment of environmental data and cyanobacteria observations. Our results emphasize the importance of ecological forecasting principles and uncertainty partitioning to refine and understand predictive capacity across ecosystems. [ABSTRACT FROM AUTHOR]

Despite wide recognition of the importance of anthropogenically driven changes in large herbivore communities—including both declines in wildlife and increases in livestock—there remain large gaps in our knowledge about the impacts of these changes on plant communities, particularly when combined with concurrent changes in climate. Considering these prominent forms of global change in tandem enables us to better understand controls on savanna vegetation structure and diversity under real‐world conditions.We conducted a field experiment using complete and semi‐permeable herbivore exclosures to explore the difference in plant communities among sites with wild herbivores only, with cattle in addition to wild herbivores, and with no large herbivores. To understand variation in effects across climatic contexts, the experiment was replicated at three locations along a topoclimatic gradient in California. Critically, this is the first such experiment to compare cattle and wildlife impacts along an environmental gradient within a single controlled experiment.Vegetation structure responded strongly to herbivore treatment regardless of climate. Relative to the isolated effects of wildlife, exclusion of all large herbivores generally increased structural components related to cover and above‐ground biomass while the addition of cattle led to reductions in vegetation cover, litter, shading and standing biomass. Furthermore, wildlife had a consistent neutral or positive effect on plant diversity, while the effect of livestock addition was context dependent. Cattle had a neutral to strongly negative effect at low aridity, but a positive effect at high aridity. These results suggest that (a) herbivore effects can override climate effects on vegetation structure, (b) cattle addition can drive different effects on diversity and (c) herbivore effects on diversity are modulated by climate.Synthesis. Our results illustrate very distinctive shifts in plant communities between two realistic forms of change in ungulate herbivore assemblages—livestock addition and large herbivore losses—particularly for plant diversity responses, and that these responses vary across climatic contexts. This finding has important implications for the management and protection of plant biodiversity given that over a quarter of the Earth's land area is managed for livestock and climate regimes are changing globally. [ABSTRACT FROM AUTHOR]

Depth is a fundamental property of lakes, essential for understanding and quantifying a range of biological, chemical, and physical processes of individual lakes as well as the collective functioning of the millions of lakes across the globe. Despite this importance, lake depth is rarely available for large numbers of lakes across the broad scales of regions and continents. We describe a new open‐access dataset, LAGOS‐US DEPTH, which contains 17,675 maximum depths and 6,137 mean depths for lakes in the conterminous United States. These data represent one of the largest compilations of lake depths in the world and are connected to other data products through the LAGOS‐US research platform. Here, we describe characteristics of lake maximum depth across the conterminous United States and identify gaps in data coverage that we encourage other researchers to fill by linking their own depth datasets for lakes within the LAGOS‐US spatial footprint. Extending this open‐access effort to include other regions and countries across the globe to build a more comprehensive and representative database of lake depth would better position scientists to quantify and articulate the critical roles that lakes play globally in biogeochemical cycling, maintaining biodiversity, and in maintaining the many ecosystem services that lakes provide. [ABSTRACT FROM AUTHOR]

Macroscale studies of aquatic ecosystems are needed to address many contemporary broad‐scale problems related to global change, particularly to inform national‐scale environmental policies. In this data paper, we fill two important gaps in data availability for lakes at the scale of the conterminous U.S., the lack of: (1) high‐resolution geographic representations of lakes and their watersheds and (2) an open data platform to connect disparate U.S. national‐scale lake datasets. We describe the LAGOS‐US LOCUS v1.0 data module that includes a detailed User Guide, which is part of the LAGOS‐US extensible research‐ready open data platform. This platform can be used to study the 479,950 lakes and reservoirs larger than or equal to 1 ha across the entire conterminous U.S. at multiple scales of space and time. The LOCUS module includes spatially‐explicit information on lakes and their watersheds, including location information, physical characteristics, and identifiers of other important national‐scale datasets. [ABSTRACT FROM AUTHOR]

The Convention on Biological Diversity (https://www.cbd.int/) recommends globally protecting ≥ 17% of ecologically representative freshwaters by 2020 to sustain critical ecosystem services and rapidly declining freshwater biodiversity. We examined whether current conservation efforts meet this target for lakes (≥ 1 ha) across the continental U.S. and Environmental Protection Agency ecoregions using the U.S. Protected Areas Database. How one defines lake protection matters: 17.8% of lakes fell within multiuse or strictly protected areas, but only 7.5% of lakes had ≥ 80% of their catchments in strictly protected areas. Protected lakes occurred disproportionately in the lake‐poor western U.S. and most lake‐rich regions fell short of the 17% target. Lakes connected to streams and other lakes were disproportionately protected relative to headwater and isolated lakes, which are important for ecosystem services and biodiversity. Meeting conservation targets requires protecting thousands of additional U.S. lakes and catchments across more diverse ecological settings and explicitly considering connectivity. [ABSTRACT FROM AUTHOR]

Biodiversity–ecosystem functioning (BEF) theory has largely focused on species richness, although studies have demonstrated that evenness may have stronger effects. While theory and numerous small‐scale studies support positive BEF relationships, regional studies have documented negative effects of evenness on ecosystem functioning. We analysed a lake dataset spanning the continental US to evaluate whether strong evenness effects are common at broad spatial scales and if BEF relationships are similar across diverse regions and trophic levels. At the continental scale, phytoplankton evenness explained more variance in phytoplankton and zooplankton resource use efficiency (RUE; ratio of biomass to resources) than richness. For individual regions, slopes of phytoplankton evenness–RUE relationships were consistently negative and positive for phytoplankton and zooplankton RUE, respectively, and most slopes did not significantly differ among regions. Findings suggest that negative evenness effects may be more common than previously documented and are not exceptions restricted to highly disturbed systems. [ABSTRACT FROM AUTHOR]

Wildfires are becoming larger and more frequent across much of the United States due to anthropogenic climate change. No studies, however, have assessed fire prevalence in lake watersheds at broad spatial and temporal scales, and thus it is unknown whether wildfires threaten lakes and reservoirs (hereafter, lakes) of the United States. We show that fire activity has increased in lake watersheds across the continental United States from 1984 to 2015, particularly since 2005. Lakes have experienced the greatest fire activity in the western United States, Southern Great Plains, and Florida. Despite over 30 years of increasing fire exposure, fire effects on fresh waters have not been well studied; previous research has generally focused on streams, and most of the limited lake‐fire research has been conducted in boreal landscapes. We therefore propose a conceptual model of how fire may influence the physical, chemical, and biological properties of lake ecosystems by synthesizing the best available science from terrestrial, aquatic, fire, and landscape ecology. This model also highlights emerging research priorities and provides a starting point to help land and lake managers anticipate potential effects of fire on ecosystem services provided by fresh waters and their watersheds. [ABSTRACT FROM AUTHOR]

Highlights • We developed a dynamic mass balance model for organic carbon in lake ecosystems. • Allochthonous loads dominated in four of five lakes. • The ratio of respiration to burial increased as water temperatures increased during summer. • Organic carbon fates were mediated by carbon source (allochthonous vs. autochthonous). • Future work should address dissolved organic carbon in tributaries and groundwater, particulate organic carbon, and burial. Abstract Lakes are active processors of organic carbon (OC) and play important roles in landscape and global carbon cycling. Allochthonous OC loads from the landscape, along with autochthonous OC loads from primary production, are mineralized in lakes, buried in lake sediments, and exported via surface or groundwater outflows. Although these processes provide a basis for a conceptual understanding of lake OC budgets, few studies have integrated these fluxes under a dynamic modeling framework to examine their interactions and relative magnitudes. We developed a simple, dynamic mass balance model for OC, and applied the model to a set of five lakes. We examined the relative magnitudes of OC fluxes and found that long-term (>10 year) lake OC dynamics were predominantly driven by allochthonous loads in four of the five lakes, underscoring the importance of terrestrially-derived OC in northern lake ecosystems. Our model highlighted seasonal patterns in lake OC budgets, with increasing water temperatures and lake productivity throughout the growing season corresponding to a transition from burial- to respiration-dominated OC fates. Ratios of respiration to burial, however, were also mediated by the source (autochthonous vs. allochthonous) of total OC loads. Autochthonous OC is more readily respired and may therefore proportionally reduce burial under a warming climate, but allochthonous OC may increase burial due to changes in precipitation. The ratios of autochthonous to allochthonous inputs and respiration to burial demonstrate the importance of dynamic models for examining both the seasonal and inter-annual roles of lakes in landscape and global carbon cycling, particularly in a global change context. Finally, we highlighted critical data needs, which include surface water DOC observations in paired tributary and lake systems, measurements of OC burial rates, groundwater input volume and DOC, and budgets of particulate OC. [ABSTRACT FROM AUTHOR]

Climate change has emerged as a major threat to biodiversity, but there have been few assessments of variability in sensitivity to climate across species’ ranges. We examined the sensitivity of ponderosa pine ( Pinus ponderosa ), a common, commercially important tree species found throughout the western United States, to climate variability using tree rings mostly from the International Tree Ring Data Bank (161 chronologies) and multiple climate products for 1930–1979. We compared interannual tree ring variation to water-year precipitation (wy ppt), May-July vapor pressure deficit (MJJ VPD), April-July precipitation (AMJJ ppt) and average winter (Dec-Feb) minimum temperature (winter tmn). We mapped growth-climate correlations for each variable and applied hierarchical agglomerative cluster analysis to identify five main groups of climate sensitivities, one of which contained mostly climate-insensitive populations. Ponderosa pine growth was positively correlated with wy ppt and AMJJ ppt and negatively correlated with MJJ VPD throughout its range, but sensitivities were greater in the Southern Rockies and Northern Great Plains than in Pacific and Southwestern populations. Sensitivities to winter tmn were weaker than responses to other climate variables, but Pacific and interior populations mostly demonstrated positive and negative responses, respectively. In summary, our analyses revealed the general pattern that interior populations of ponderosa pine were more climate-sensitive than Pacific populations, but there is considerable heterogeneity in sensitivity throughout the species’ range. Sensitivities to climate variables were related to position along corresponding climate gradients for all variables except MJJ VPD, but the unevenness of these relationships suggests a role of local adaptation. Our results illustrate the variation in climate response for a uniquely wide-ranging species and suggest that “leading” and “trailing” range edge concepts can oversimplify patterns of species exposure to climate change. [ABSTRACT FROM AUTHOR]

We evaluated use of MODIS 250 m imagery for remote lake monitoring in Maine. Despite limited spectral resolution (visible red and near infrared bands), the twice daily image capture has a potential advantage over conventionally used, often cloudy Landsat imagery (16 day interval) when short time windows are of interest. We analyzed 364 eligible (≥100 ha) Maine lakes during late summer (Aug–early Sep) 2000–2011. The red band was strongly correlated with natural log-transformed Secchi depth (SD), and the addition of ancillary lake and watershed variables explained some variability in ln(SD) (R2= 0.68–0.85; 9 models). Weak spectral resolution and variable lake conditions limited accurate lake monitoring to relatively productive periods in late summer, as indicated by inconsistent, sometimes weak regressions during June and July when lakes were clearer and less stable (R2= 0.19–0.74; 8 models). Additionally, SD estimates derived from 2 sets of concurrent MODIS and Landsat imagery generally did not agree unless Landsat imagery (30 m) was resampled to 250 m, likely owing to various factors related to scale. Average MODIS estimates exceeded those of Landsat by 0.35 and 0.49 m on the 2 dates. Overall, MODIS 250 m imagery are potentially useful for remote lake monitoring during productive periods when Landsat data are unavailable; however, analyses must occur when algal communities are stable and well-developed, are biased toward large lakes, may overestimate SD, and accuracy may be unreliable without non-spectral lake predictors. [ABSTRACT FROM AUTHOR]

Abstract: Water clarity is a reliable indicator of lake productivity and an ideal metric of regional water quality. Clarity is an indicator of other water quality variables including chlorophyll-a, total phosphorus and trophic status; however, unlike these metrics, clarity can be accurately and efficiently estimated remotely on a regional scale. Remote sensing is useful in regions containing a large number of lakes that are cost prohibitive to monitor regularly using traditional field methods. Field-assessed lakes generally are easily accessible and may represent a spatially irregular, non-random sample of a region. We developed a remote monitoring program for Maine lakes >8ha (1511 lakes) to supplement existing field monitoring programs. We combined Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) brightness values for TM bands 1 (blue) and 3 (red) to estimate water clarity (secchi disk depth) during 1990–2010. Although similar procedures have been applied to Minnesota and Wisconsin lakes, neither state incorporates physical lake variables or watershed characteristics that potentially affect clarity into their models. Average lake depth consistently improved model fitness, and the proportion of wetland area in lake watersheds also explained variability in clarity in some cases. Nine regression models predicted water clarity (R2 =0.69–0.90) during 1990–2010, with separate models for eastern (TM path 11; four models) and western Maine (TM path 12; five models that captured differences in topography and landscape disturbance. Average absolute difference between model-estimated and observed secchi depth ranged 0.65–1.03m. Eutrophic and mesotrophic lakes consistently were estimated more accurately than oligotrophic lakes. Our results show that TM bands 1 and 3 can be used to estimate regional lake water clarity outside the Great Lakes Region and that the accuracy of estimates is improved with additional model variables that reflect physical lake characteristics and watershed conditions. [Copyright &y& Elsevier]

Climate change is a well-recognized threat to lake ecosystems and, although there likely exists geographic variation in the sensitivity of lakes to climate, broad-scale, long-term studies are needed to understand this variation. Further, the potential mediating role of local to regional ecological context on these responses is not well documented. In this study, we examined relationships between climate and water clarity in 365 lakes from 1981 to 2010 in two distinct regions in the northeastern and midwestern United States. We asked (1) How do climate-water-clarity relationships vary across watersheds and between two geographic regions? and (2) Do certain characteristics make some lakes more climate sensitive than others? We found strong differences in climate-water-clarity relationships both within and across the two regions. For example, in the northeastern region, water clarity was often negatively correlated with summer precipitation (median correlation = -0.32, n = 160 lakes), but was not correlated with summer average maximum temperature (median correlation = 0.09, n = 205 lakes). In the midwestern region, water clarity was not related to summer precipitation (median correlation = -0.04), but was often negatively correlated with summer average maximum temperature (median correlation = -0.18). There were few strong relationships between local and sub-regional ecological context and a lake's sensitivity to climate. For example, ecological context variables explained just 16-18% of variation in summer precipitation sensitivity, which was most related to total phosphorus, chlorophyll a, lake depth, and hydrology in both regions. Sensitivity to summer maximum temperature was even less predictable in both regions, with 4% or less of variation explained using all ecological context variables. Overall, we identified differences in the climate sensitivity of lakes across regions and found that local and sub-regional ecological context weakly influences the sensitivity of lakes to climate. Our findings suggest that local to regional drivers may combine to influence the sensitivity of lake ecosystems to climate change, and that sensitivities among lakes are highly variable within and across regions. This variability suggests that lakes are sensitive to different aspects of climate change (temperature vs. precipitation) and that responses of lakes to climate are heterogeneous and complex., (© 2019 by the Ecological Society of America.)