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Measuring greenhouse gas (GHG) fluxes and pools in ecosystems are becoming increasingly common in ecological studies due to their relevance to climate change. With it, the need for analytical platforms adaptable to measuring different pools and fluxes within research groups also grows. This study aims to develop a procedure to use portable optical spectroscopy-based gas analyzers, originally designed and marketed for gas flux measurements, to measure GHG concentrations in aqueous samples. The protocol involves the traditional headspace equilibration technique followed by the injection of a headspace gas subsample into a chamber connected through a closed loop to the inlet and outlet ports of the gas analyzer. The chamber is fabricated from a generic mason jar and simple laboratory supplies, and it is an ideal solution for samples that may require pre-injection dilution. Methane concentrations measured with the chamber are tightly correlated (r 2 > 0.98) with concentrations determined separately through gas chromatography-flame ionization detection (GC-FID) on subsamples from the same vials. The procedure is particularly relevant for field studies in remote areas where chromatography equipment and supplies are not readily available, offering a practical, cheaper, and more efficient solution for measuring methane and other dissolved greenhouse gas concentrations in aquatic systems.

Wetlands cycle carbon by being net sinks for carbon dioxide (CO 2 ) and net sources of methane (CH 4 ). Daily and seasonal temporal patterns, dissolved oxygen (DO) availability, inundation status (flooded or dry/partially flooded), water depth, and vegetation can affect the magnitude of carbon uptake or emissions, but the extent and interactive effects of these variables on carbon gas fluxes are poorly understood. We characterized the linkages between carbon fluxes and these environmental and temporal drivers at the Old Woman Creek National Estuarine Research Reserve (OWC), OH. We measured diurnal gas flux patterns in an upstream side channel (called the cove) using chamber measurements at six sites (three vegetated and three non-vegetated). We sampled hourly from 7 AM to 7 PM and monthly from July to October 2022. DO concentrations and water levels were measured monthly. Water inundation status had the most influential effect on carbon fluxes with flooded conditions supporting higher CH 4 fluxes (0.39 μmol CH 4 m -2  s -1 ; -1.23 μmol CO 2 m -2  s -1 ) and drier conditions supporting higher CO 2 fluxes (0.03 μmol CH 4 m -2  s -1 ; 0.86 μmol CO 2 m -2  s -1 ). When flooded, the wetland was a net CO 2 sink; however, it became a source for both CH 4 and CO 2 when water levels were low. We compared chamber-based gas fluxes from the cove in flooded (July) and dry (August) months to fluxes measured with an eddy covariance tower whose footprint covers flooded portions of the wetland. The diurnal pattern of carbon fluxes at the tower did not vary with changing water levels but remained a CO 2 sink and a CH 4 source even when the cove where we performed the chamber measurements dried out. These results emphasize the role of inundation status on wetland carbon cycling and highlight the importance of fluctuating hydrologic patterns, especially hydrologic drawdowns, under changing climatic conditions., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Lauren Kinsman-Costello reports financial support was provided by US Department of Energy. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The wetland at Old Woman Creek National Estuarine Research Reserve, with flux tower US-OWC, which is characterized by high methane fluxes, high spatial heterogeneity, dynamic hydrology and water level fluctuations, and high lateral transport of dissolved organic carbon and nutrients, embodies many of the challenges in modeling methane fluxes., (© 2023 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

CH 4 emissions from inland waters are highly uncertain in the current global CH 4 budget, especially for streams, rivers, and other lotic systems. Previous studies have attributed the strong spatiotemporal heterogeneity of riverine CH 4 to environmental factors such as sediment type, water level, temperature, or particulate organic carbon abundance through correlation analysis. However, a mechanistic understanding of the basis for such heterogeneity is lacking. Here, we combine sediment CH 4 data from the Hanford reach of the Columbia River with a biogeochemical-transport model to show that vertical hydrologic exchange flows (VHEFs), driven by the difference between river stage and groundwater level, determine CH 4 flux at the sediment-water interface. CH 4 fluxes show a nonlinear relationship with the magnitude of VHEFs, where high VHEFs introduce O 2 into riverbed sediments, which inhibit CH 4 production and induce CH 4 oxidation, and low VHEFs cause transient reduction in CH 4 flux (relative to production) due to reduced advective CH 4 transport. In addition, VHEFs lead to the hysteresis of temperature rise and CH 4 emissions because high river discharge caused by snowmelt in spring leads to strong downwelling flow that offsets increasing CH 4 production with temperature rise. Our findings reveal how the interplay between in-stream hydrologic flux besides fluvial-wetland connectivity and microbial metabolic pathways that compete with methanogenic pathways can produce complex patterns in CH 4 production and emission in riverbed alluvial sediments.

Wetland water depth influences microbial and plant communities, which can alter the above- and below-ground carbon cycling of a wetland. Wetland water depths are likely to change due to shifting precipitation patterns, which will affect projections of greenhouse gas emissions; however, these effects are rarely incorporated into wetland greenhouse gas models. Seeking to address this gap, we used a mechanistic model, ecosys, to simulate a range of water depth scenarios in a temperate wetland, and analyzed simulated predictions of carbon dioxide (CO 2 ) and methane (CH 4 ) fluxes over the 21st century. We tested our model using eddy covariance measurements of CO 2 and CH 4 fluxes collected at the Old Woman Creek National Estuarine Research Reserve (OWC) during 2015 and 2016. OWC is a lacustrine, estuarine, freshwater, mineral-soil marsh. An empirical model found that the wetland water depth is highly dependent on the water depth of the nearby Lake Erie. Future wetland surface water depths were modeled based on projection of Lake Erie's water depth using four separate NOAA projections, resulting in four wetland water-depth scenarios. Two of the four 21st century projections for Lake Erie water depths used in this study indicated that the water depth of the wetland would remain nearly steady; however, the other two indicated decreases in the wetland water depth. In our scenario where the wetland dries out, we project the wetland's climatological warming effect will decrease due to smaller CH 4 fluxes to the atmosphere and larger CO 2 uptake by the wetland. We also found that increased water level can lower emissions by shifting the site towards more open water areas, which have lower CH 4 emissions. We found that decreased water depths would cause more widespread colonization of the wetland by macrophyte vegetation. Using an empirical relationship, we also found that further drying could result in other, non-wetland vegetation to emerge, dramatically altering soil carbon cycling. In three of our four projections, we found that in general the magnitude of CO 2 and CH 4 fluxes steadily increase over the next 100 years in response to higher temperatures. However, in our driest simulations, we projected a different response due to increased oxidation of soil carbon, with CH 4 emissions decreasing substantially from an annual cumulative peak of 224.6 to a minimum of 104.7 gC m -2 year -1 . In that same simulation, net cumulative flux of CO 2 changed from being a sink of 56.5 gC m -2 year -1 to a source of 369.6 gC m -2 year -1 over the same period, despite a temperature increase from 13.7 °C to 14.2 °C. This temperature shift in our other three cases with greater water depths increased the source strength of CH 4 and the sink strength of CO 2 . We conclude that the magnitude of wetland greenhouse-gas fluxes depended on the water depth primarily as it affected the areal percentage of the wetland available for plant colonization, but dramatic decreases in water depths could cause significant reductions in the wetland CH 4 fluxes, while simultaneously altering the wetland vegetation., Competing Interests: Declaration of competing interest The authors declare that they have no known financial personal relationships that could have appeared to influence the outcomes of the work reported. The material we present is new and was not published in any other journal. All co-authors saw the final version of this manuscript and agreed with its submission., (Copyright © 2022. Published by Elsevier B.V.)

Permafrost thaw is a major potential feedback source to climate change as it can drive the increased release of greenhouse gases carbon dioxide (CO 2 ) and methane (CH 4 ). This carbon release from the decomposition of thawing soil organic material can be mitigated by increased net primary productivity (NPP) caused by warming, increasing atmospheric CO 2 , and plant community transition. However, the net effect on C storage also depends on how these plant community changes alter plant litter quantity, quality, and decomposition rates. Predicting decomposition rates based on litter quality remains challenging, but a promising new way forward is to incorporate measures of the energetic favorability to soil microbes of plant biomass decomposition. We asked how the variation in one such measure, the nominal oxidation state of carbon (NOSC), interacts with changing quantities of plant material inputs to influence the net C balance of a thawing permafrost peatland. We found: (1) Plant productivity (NPP) increased post-thaw, but instead of contributing to increased standing biomass, it increased plant biomass turnover via increased litter inputs to soil; (2) Plant litter thermodynamic favorability (NOSC) and decomposition rate both increased post-thaw, despite limited changes in bulk C:N ratios; (3) these increases caused the higher NPP to cycle more rapidly through both plants and soil, contributing to higher CO 2 and CH 4  fluxes from decomposition. Thus, the increased C-storage expected from higher productivity was limited and the high global warming potential of CH 4 contributed a net positive warming effect. Although post-thaw peatlands are currently C sinks due to high NPP offsetting high CO 2 release, this status is very sensitive to the plant community's litter input rate and quality. Integration of novel bioavailability metrics based on litter chemistry, including NOSC, into studies of ecosystem dynamics, is needed to improve the understanding of controls on arctic C stocks under continued ecosystem transition., (© 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Forest disturbances alter land biophysics. Their impacts on local climate and land surface temperature (LST) cannot be directly measured by comparing pre- and post-disturbance observations of the same site over time (e.g., due to confounding such as background climate fluctuations); a common remedy is to compare spatially-adjacent undisturbed sites instead. This space-for-time substitution ignores the inherent biases in vegetation between two paired sites, interannual variations, and temporal dynamics of forest recovery. Besides, there is a lack of observation-based analyses at fine spatial resolutions capable of capturing spatial heterogeneity of small-scale forest disturbances. To address these limitations, here we report new satellite analyses on local climate impacts of forest loss at 30 m resolution. Our analyses combined multiple long-term satellite products (e.g., albedo and evapotranspiration [ET]) at 700 sites across major climate zones in the conterminous United States, using time-series trend and changepoint detection methods. Our method helped isolate the biophysical changes attributed to disturbances from those attributed to climate backgrounds and natural growth. On average, forest loss increased surface albedo, decreased ET, and reduced leaf area index (LAI). Net annual warming-an increase in LST-was observed after forest loss in the arid/semiarid, northern, tropical, and temperate regions, dominated by the warming from decreased ET and attenuated by the cooling from increased albedo. The magnitude of post-disturbance warming was related to precipitation; climate zones with greater precipitation showed stronger and longer warming. Reduction in leaf or LAI was larger in evergreen than deciduous forests, but the recovery in LAI did not always synchronize with those of albedo and ET. Overall, this study presents new evidence of biophysical effects of forest loss on LST at finer spatial resolutions; our time-series method can be further leveraged to derive local policy-relevant ecosystem climate regulation metrics or support model-based climate-biosphere studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

As human and automated sensor networks collect increasingly massive volumes of animal observations, new opportunities have arisen to use these data to infer or track species movements. Sources of broad scale occurrence datasets include crowdsourced databases, such as eBird and iNaturalist, weather surveillance radars, and passive automated sensors including acoustic monitoring units and camera trap networks. Such data resources represent static observations, typically at the species level, at a given location. Nonetheless, by combining multiple observations across many locations and times it is possible to infer spatially continuous population-level movements. Population-level movement characterizes the aggregated movement of individuals comprising a population, such as range contractions, expansions, climate tracking, or migration, that can result from physical, behavioral, or demographic processes. A desire to model population movements from such forms of occurrence data has led to an evolving field that has created new analytical and statistical approaches that can account for spatial and temporal sampling bias in the observations. The insights generated from the growth of population-level movement research can complement the insights from focal tracking studies, and elucidate mechanisms driving changes in population distributions at potentially larger spatial and temporal scales. This review will summarize current broad-scale occurrence datasets, discuss the latest approaches for utilizing them in population-level movement analyses, and highlight studies where such analyses have provided ecological insights. We outline the conceptual approaches and common methodological steps to infer movements from spatially distributed occurrence data that currently exist for terrestrial animals, though similar approaches may be applicable to plants, freshwater, or marine organisms., (© 2021. The Author(s).)

Many secondary deciduous forests of eastern North America are approaching a transition in which mature early-successional trees are declining, resulting in an uncertain future for this century-long carbon (C) sink. We initiated the Forest Accelerated Succession Experiment (FASET) at the University of Michigan Biological Station to examine the patterns and mechanisms underlying forest C cycling following the stem girdling-induced mortality of >6,700 early-successional Populus spp. (aspen) and Betula papyrifera (paper birch). Meteorological flux tower-based C cycling observations from the 33-ha treatment forest have been paired with those from a nearby unmanipulated forest since 2008. Following over a decade of observations, we revisit our core hypothesis: that net ecosystem production (NEP) would increase following the transition to mid-late-successional species dominance due to increased canopy structural complexity. Supporting our hypothesis, NEP was stable, briefly declined, and then increased relative to the control in the decade following disturbance; however, increasing NEP was not associated with rising structural complexity but rather with a rapid 1-yr recovery of total leaf area index as mid-late-successional Acer, Quercus, and Pinus assumed canopy dominance. The transition to mid-late-successional species dominance improved carbon-use efficiency (CUE = NEP/gross primary production) as ecosystem respiration declined. Similar soil respiration rates in control and treatment forests, along with species differences in leaf physiology and the rising relative growth rates of mid-late-successional species in the treatment forest, suggest changes in aboveground plant respiration and growth were primarily responsible for increases in NEP. We conclude that deciduous forests transitioning from early to middle succession are capable of sustained or increased NEP, even when experiencing extensive tree mortality. This adds to mounting evidence that aging deciduous forests in the region will function as C sinks for decades to come., (© 2021 by the Ecological Society of America.)

Flying over the open sea is energetically costly for terrestrial birds. Despite this, over-water journeys of many birds, sometimes hundreds of kilometres long, are uncovered by bio-logging technology. To understand how these birds afford their flights over the open sea, we investigated the role of atmospheric conditions, specifically wind and uplift, in subsidizing over-water flight at a global scale. We first established that Δ T , the temperature difference between sea surface and air, is a meaningful proxy for uplift over water. Using this proxy, we showed that the spatio-temporal patterns of sea-crossing in terrestrial migratory birds are associated with favourable uplift conditions. We then analysed route selection over the open sea for five facultative soaring species, representative of all major migratory flyways. The birds maximized wind support when selecting their sea-crossing routes and selected greater uplift when suitable wind support was available. They also preferred routes with low long-term uncertainty in wind conditions. Our findings suggest that, in addition to wind, uplift may play a key role in the energy seascape for bird migration that in turn determines strategies and associated costs for birds crossing ecological barriers such as the open sea.

While wetlands are the largest natural source of methane (CH 4 ) to the atmosphere, they represent a large source of uncertainty in the global CH 4 budget due to the complex biogeochemical controls on CH 4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH 4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH 4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH 4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH 4 emissions., (© 2021 John Wiley & Sons Ltd.)

Measurements of the spatial heterogeneity of methane fluxes in wetlands are critical to better understand and predict methane emissions at the ecosystem scale. However, the within-wetland spatial heterogeneity of fluxes is rarely assessed. Here, we use a spatially balanced rapid chamber-based survey of methane at different ecohydrological patches within a temperate freshwater marsh. We measured fluxes exclusively from the water surface without including vegetation. We further used the data from chamber measurements to partition diffusive and ebullitive fluxes. Three ecohydrological patches were distinguishable in the marsh, defined by the type and presence/absence of vegetation. These patches were emergent vegetation, floating-leaved, and open water. Net methane fluxes from the water surface (diffusion plus ebullition) in emergent vegetation patches were larger than in the floating-leaved vegetation and open water patches (p < 0.05). Diffusive fluxes, representing a sizable smaller fraction of net fluxes, were larger in vegetated than in unvegetated patches (p < 0.05), while ebullitive fluxes mirrored the magnitude and differences observed in the net fluxes. Moreover, pooled net and ebullitive fluxes across patches (but not diffusive fluxes) were negatively correlated with water levels, the primary variable affecting patch distribution. Altogether, our results indicate that the differences among ecohydrological patches are driven by ebullition, ultimately highlighting challenges faced by scientists and practitioners in the field and modelers seeking to improve the predictability and resolution of wetland biogeochemical models., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Wetland methane (CH 4 ) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH 4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH 4 production are thus needed to improve global CH 4 budget assessments.

Warming-induced carbon loss through terrestrial ecosystem respiration ( Re ) is likely getting stronger in high latitudes and cold regions because of the more rapid warming and higher temperature sensitivity of Re ( Q 10 ). However, it is not known whether the spatial relationship between Q 10 and temperature also holds temporally under a future warmer climate. Here, we analyzed apparent Q 10 values derived from multiyear observations at 74 FLUXNET sites spanning diverse climates and biomes. We found warming-induced decline in Q 10 is stronger at colder regions than other locations, which is consistent with a meta-analysis of 54 field warming experiments across the globe. We predict future warming will shrink the global variability of Q 10 values to an average of 1.44 across the globe under a high emission trajectory (RCP 8.5) by the end of the century. Therefore, warming-induced carbon loss may be less than previously assumed because of Q 10 homogenization in a warming world., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Greenhouse gas (GHG) emissions from rivers are a critical missing component of current global GHG models. Their exclusion is mainly due to a lack of in-situ measurements and a poor understanding of the spatiotemporal dynamics of GHG production and emissions, which prevents optimal model parametrization. We combined simultaneous observations of porewater concentrations along different beach positions and depths, and surface fluxes of methane and nitrous oxide at a plot scale in a large regulated river during three water stages: rising, falling, and low. Our goal was to gain insights into the interactions between hydrological exchanges and GHG emissions and elucidate possible hypotheses that could guide future research on the mechanisms of GHG production, consumption, and transport in the hyporheic zone (HZ). Results indicate that the site functioned as a net source of methane. Surface fluxes of methane during river water stages at three beach positions (shallow, intermediate and deep) correlated with porewater concentrations of methane. However, fluxes were significantly higher in the intermediate position during the low water stage, suggesting that low residence time increased methane emissions. Vertical profiles of methane peaked at different depths, indicating an influence of the magnitude and direction of the hyporheic mixing during the different river water stages on methane production and consumption. The site acted as either a sink or a source of nitrous oxide depending on the elevation of the water column. Nitrous oxide porewater concentrations peaked at the upper layers of the sediment throughout the different water stages. River hydrological stages significantly influenced porewater concentrations and fluxes of GHG, probably by influencing heterotrophic respiration (production and consumption processes) and transport to and from the HZ. Our results highlight the importance of including dynamic hydrological exchanges when studying and modeling GHG production and consumption in the HZ of large rivers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020. Published by Elsevier B.V.)

Wetland soils are one of the largest natural contributors to the emission of methane, a potent greenhouse gas. Currently, microbial contributions to methane emissions from these systems emphasize the roles of acetoclastic and hydrogenotrophic methanogens, while less frequently considering methyl-group substrates (e.g., methanol and methylamines). Here, we integrated laboratory and field experiments to explore the potential for methylotrophic methanogenesis in Old Woman Creek (OWC), a temperate freshwater wetland located in Ohio, USA. We first demonstrated the capacity for methylotrophic methanogenesis in these soils using laboratory soil microcosms amended with trimethylamine. However, subsequent field porewater nuclear magnetic resonance (NMR) analyses to identify methanogenic substrates failed to detect evidence for methylamine compounds in soil porewaters, instead noting the presence of the methylotrophic substrate methanol. Accordingly, our wetland soil-derived metatranscriptomic data indicated that methanol utilization by the Methanomassiliicoccaceae was the likely source of methylotrophic methanogenesis. Methanomassiliicoccaceae relative contributions to mcrA transcripts nearly doubled with depth, accounting for up to 8% of the mcrA transcripts in 25-cm-deep soils. Longitudinal 16S rRNA amplicon and mcrA gene surveys demonstrated that Methanomassiliicoccaceae were stably present over 2 years across lateral and depth gradients in this wetland. Meta-analysis of 16S rRNA sequences similar (>99%) to OWC Methanomassiliicoccaceae in public databases revealed a global distribution, with a high representation in terrestrial soils and sediments. Together, our results demonstrate that methylotrophic methanogenesis likely contributes to methane flux from climatically relevant wetland soils. IMPORTANCE Understanding the sources and controls on microbial methane production from wetland soils is critical to global methane emission predictions, particularly in light of changing climatic conditions. Current biogeochemical models of methanogenesis consider only acetoclastic and hydrogenotrophic sources and exclude methylotrophic methanogenesis, potentially underestimating microbial contributions to methane flux. Our multi-omic results demonstrated that methylotrophic methanogens of the family Methanomassiliicoccaceae were present and active in a freshwater wetland, with metatranscripts indicating that methanol, not methylamines, was the likely substrate under the conditions measured here. However, laboratory experiments indicated the potential for other methanogens to become enriched in response to trimethylamine, revealing the reservoir of methylotrophic methanogenesis potential residing in these soils. Collectively, our approach used coupled field and laboratory investigations to illuminate metabolisms influencing the terrestrial microbial methane cycle, thereby offering direction for increased realism in predictive process-oriented models of methane flux in wetland soils., (Copyright © 2019 Narrowe et al.)

Tropical alpine peatlands are among the least studied wetlands types on earth. Their important ecosystem services at local and regional scope are currently threatened by climate and land use changes. Recent studies in these ecosystems suggest their importance to the provision of climate regulation services, prompting a better understanding of the underlying functions and their variability at ecosystem scales. The objective of this study is to determine the variability of methane (CH 4 ) fluxes and carbon (C) sequestration within a tropical alpine peatland in three locations along a microtopographic gradient and its associated plant diversity. These locations accounted for: 1) hummocks, found mostly near the edge of the peat with a water table below the soil surface, 2) lawns, in the transition zone, with a water-table near the soil surface, and 3) hollows, permanently flooded with a water table above the soil surface, composed of small patches of open water intermingled with unconsolidated hummocks that surface the water level. Results indicate that CH 4 flux is lowest in the lawns, while C sequestration is highest. Conversely, the hummock and hollow have higher CH 4 flux and lower C sequestration. In addition, plant diversity in the lawns is higher than in the hummock and hollow location. Dryer conditions brought by current climate change in the northern Andes are expected to lower the water tables in the peatland. This change is expected to drive a change in CH 4 flux and C sequestration at the lawns, currently dominating the peatland, towards values more similar to those measured in the hummocks. This decrease may also represent a change towards the lower plant diversity that characterized the hummock. Such changes will reduce the ratio of C sequestration:CH 4 flux signifying the reduction of resilience and increment of vulnerability of the climate-regulating service to further perturbations., (Copyright © 2018 Elsevier B.V. All rights reserved.)

There is long-standing scientific interest in understanding purposeful movement by animals and humans. Traditionally, collecting data on individual moving entities was difficult and time-consuming, limiting scientific progress. The growth of location-aware and other geospatial technologies for capturing, managing and analyzing moving objects data are shattering these limitations, leading to revolutions in animal movement ecology and human mobility science. Despite parallel transitions towards massive individual-level data collected automatically via sensors, there is little scientific cross-fertilization across the animal and human divide. There are potential synergies from converging these separate domains towards an integrated science of movement. This paper discusses the data-driven revolutions in the animal movement ecology and human mobility science, their contrasting worldviews and, as examples of complementarity, transdisciplinary questions that span both fields. We also identify research challenges that should be met to develop an integrated science of movement trajectories.

Water stress has been identified as a key mechanism of the contemporary increase in tree mortality rates in northwestern North America. However, a detailed analysis of boreal tree hydrodynamics and their interspecific differences is still lacking. Here we examine the hydraulic behaviour of co-occurring larch (Larix laricina) and black spruce (Picea mariana), two characteristic boreal tree species, near the southern limit of the boreal ecozone in central Canada. Sap flux density (Js), concurrently recorded stem radius fluctuations and meteorological conditions are used to quantify tree hydraulic functioning and to scrutinize tree water-use strategies. Our analysis revealed asynchrony in the diel hydrodynamics of the two species with the initial rise in Js occurring 2 h earlier in larch than in black spruce. Interspecific differences in larch and black spruce crown architecture explained the observed asynchrony in their hydraulic functioning. Furthermore, the two species exhibited diverging stomatal regulation strategies with larch and black spruce employing relatively isohydric and anisohydric behaviour, respectively. Such asynchronous and diverging tree-level hydrodynamics provide new insights into the ecosystem-level complementarity in tree form and function, with implications for understanding boreal forests' water and carbon dynamics and their resilience to environmental stress.

Water transport and storage through the soil-plant-atmosphere continuum is critical to the terrestrial water cycle, and has become a major research focus area. Biomass capacitance plays an integral role in the avoidance of hydraulic impairment to transpiration. However, high temporal resolution measurements of dynamic changes in the hydraulic capacitance of large trees are rare. Here, we present procedures for the calibration and use of capacitance sensors, typically used to monitor soil water content, to measure the volumetric water content in trees in the field. Frequency domain reflectometry-style observations are sensitive to the density of the media being studied. Therefore, it is necessary to perform species-specific calibrations to convert from the sensor-reported values of dielectric permittivity to volumetric water content. Calibration is performed on a harvested branch or stem cut into segments that are dried or re-hydrated to produce a full range of water contents used to generate a best-fit regression with sensor observations. Sensors are inserted into calibration segments or installed in trees after pre-drilling holes to a tolerance fit using a fabricated template to ensure proper drill alignment. Special care is taken to ensure that sensor tines make good contact with the surrounding media, while allowing them to be inserted without excessive force. Volumetric water content dynamics observed via the presented methodology align with sap flow measurements recorded using thermal dissipation techniques and environmental forcing data. Biomass water content data can be used to observe the onset of water stress, drought response and recovery, and has the potential to be applied to the calibration and evaluation of new plant-level hydrodynamics models, as well as to the partitioning of remotely sensed moisture products into above- and belowground components.

The current paradigm, widely incorporated in soil biogeochemical models, is that microbial methanogenesis can only occur in anoxic habitats. In contrast, here we show clear geochemical and biological evidence for methane production in well-oxygenated soils of a freshwater wetland. A comparison of oxic to anoxic soils reveal up to ten times greater methane production and nine times more methanogenesis activity in oxygenated soils. Metagenomic and metatranscriptomic sequencing recover the first near-complete genomes for a novel methanogen species, and show acetoclastic production from this organism was the dominant methanogenesis pathway in oxygenated soils. This organism, Candidatus Methanothrix paradoxum, is prevalent across methane emitting ecosystems, suggesting a global significance. Moreover, in this wetland, we estimate that up to 80% of methane fluxes could be attributed to methanogenesis in oxygenated soils. Together, our findings challenge a widely held assumption about methanogenesis, with significant ramifications for global methane estimates and Earth system modeling.

Lianas are an important component of tropical forests, where they reduce tree growth, fecundity, and survival. Competition for light from lianas may be intense; however, the amount of light that lianas intercept is poorly understood. We used a large-scale liana-removal experiment to quantify light interception by lianas in a Panamanian secondary forest. We measured the change in plant area index (PAI) and forest structure before and after cutting lianas (for 4 yr) in eight 80 m × 80 m plots and eight control plots (16 plots total). We used ground-based LiDAR to measure the 3-dimensional canopy structure before cutting lianas, and then annually for 2 yr afterwards. Six weeks after cutting lianas, mean plot PAI was 20% higher in control vs. liana removal plots. One yr after cutting lianas, mean plot PAI was ~17% higher in control plots. The differences between treatments diminished significantly 2 yr after liana cutting and, after 4 yr, trees had fully compensated for liana removal. Ground-based LiDAR revealed that lianas attenuated light in the upper- and middle-forest canopy layers, and not only in the upper canopy as was previously suspected. Thus, lianas compete with trees by intercepting light in the upper- and mid-canopy of this forest., (© 2016 by the Ecological Society of America.)

Land surface models and dynamic global vegetation models typically represent vegetation through coarse plant functional type groupings based on leaf form, phenology, and bioclimatic limits. Although these groupings were both feasible and functional for early model generations, in light of the pace at which our knowledge of functional ecology, ecosystem demographics, and vegetation-climate feedbacks has advanced and the ever growing demand for enhanced model performance, these groupings have become antiquated and are identified as a key source of model uncertainty. The newest wave of model development is centered on shifting the vegetation paradigm away from plant functional types (PFTs) and towards flexible trait-based representations. These models seek to improve errors in ecosystem fluxes that result from information loss due to over-aggregation of dissimilar species into the same functional class. We advocate the importance of the inclusion of plant hydraulic trait representation within the new paradigm through a framework of the whole-plant hydraulic strategy. Plant hydraulic strategy is known to play a critical role in the regulation of stomatal conductance and thus transpiration and latent heat flux. It is typical that coexisting plants employ opposing hydraulic strategies, and therefore have disparate patterns of water acquisition and use. Hydraulic traits are deterministic of drought resilience, response to disturbance, and other demographic processes. The addition of plant hydraulic properties in models may not only improve the simulation of carbon and water fluxes but also vegetation population distributions.

The flight performance of birds is strongly affected by the dynamic state of the atmosphere at the birds' locations. Studies of flight and its impact on the movement ecology of birds must consider the wind to help us understand aerodynamics and bird flight strategies. Here, we introduce a systematic approach to evaluate wind speed and direction from the high-frequency GPS recordings from bird-borne tags during thermalling flight. Our method assumes that a fixed horizontal mean wind speed during a short (18 seconds, 19 GPS fixes) flight segment with a constant turn angle along a closed loop, characteristic of thermalling flight, will generate a fixed drift for each consequent location. We use a maximum-likelihood approach to estimate that drift and to determine the wind and airspeeds at the birds' flight locations. We also provide error estimates for these GPS-derived wind speed estimates. We validate our approach by comparing its wind estimates with the mid-resolution weather reanalysis data from ECMWF, and by examining independent wind estimates from pairs of birds in a large dataset of GPS-tagged migrating storks that were flying in close proximity. Our approach provides accurate and unbiased observations of wind speed and additional detailed information on vertical winds and uplift structure. These precise measurements are otherwise rare and hard to obtain and will broaden our understanding of atmospheric conditions, flight aerodynamics, and bird flight strategies. With an increasing number of GPS-tracked animals, we may soon be able to use birds to inform us about the atmosphere they are flying through and thus improve future ecological and environmental studies.

Ecologically-similar species were found to develop specific strategies to partition their resources, leading to niche differentiation and divergence, in order to avoid interspecific competition. Our study determines multi-dimensional differentiation of two sympatric top-predators, long-legged buzzards (LLB) and short-toed eagles (STE), which recently became sympatric during their breeding season in the Judean Foothills, Israel. By combining information from comprehensive diet and movement analyses we found four dimensions of differentiation: (1) Geographic foraging area: LLB tended to forage relatively close to their nests (2.35 ± 0.62 km), while STE forage far from their nest (13.03 ± 2.20 km); (2) Foraging-habitat type: LLBs forage at low natural vegetation, avoiding cultivated fields, whereas STEs forage in cultivated fields, avoiding low natural vegetation; (3) Diurnal dynamics of foraging: LLBs are uniformly active during daytime, whereas STEs activity peaks in the early afternoon; and (4) Food-niche: while both species largely rely on reptiles (47.8% and 76.3% for LLB and STE, respectively), LLB had a more diverse diet and consumed significantly higher percentages of lizards, while STE consumed significantly higher percentages of snakes. Our results suggest that this multidimensional differentiation allows the spatial coexistence of these two dense populations in the study area.

Soaring raptors can fly at high altitudes of up to 9000 m. The behavioural adjustments to high-altitude flights are largely unknown. We studied thermalling flights of Himalayan vultures (Gyps himalayensis) from 50 to 6500 m above sea level, a twofold range of air densities. To create the necessary lift to support the same weight and maintain soaring flight in thin air birds might modify lift coefficient by biophysical changes, such as wing posture and increasing the power expenditure. Alternatively, they can change their flight characteristics. We show that vultures use the latter and increase circle radius by 35% and airspeed by 21% over their flight altitude range. These simple behavioural adjustments enable vultures to move seamlessly during their annual migrations over the Himalaya without increasing energy output for flight at high elevations., (© 2016 The Authors.)

Ecosystem models often perform poorly in reproducing interannual variability in carbon and water fluxes, resulting in considerable uncertainty when estimating the land-carbon sink. While many aggregated variables (growing season length, seasonal precipitation, or temperature) have been suggested as predictors for interannual variability in carbon fluxes, their explanatory power is limited and uncertainties remain as to their relative contributions. Recent results show that the annual count of hours where evapotranspiration (ET) is larger than its 95th percentile is strongly correlated with the annual variability of ET and gross primary production (GPP) in an ecosystem model. This suggests that the occurrence of favorable conditions has a strong influence on the annual carbon budget. Here we analyzed data from eight forest sites of the AmeriFlux network with at least 7 years of continuous measurements. We show that for ET and the carbon fluxes GPP, ecosystem respiration (RE), and net ecosystem production, counting the "most active hours/days" (i.e., hours/days when the flux exceeds a high percentile) correlates well with the respective annual sums, with correlation coefficients generally larger than 0.8. Phenological transitions have much weaker explanatory power. By exploiting the relationship between most active hours and interannual variability, we classify hours as most active or less active and largely explain interannual variability in ecosystem fluxes, particularly for GPP and RE. Our results suggest that a better understanding and modeling of the occurrence of large values in high-frequency ecosystem fluxes will result in a better understanding of interannual variability of these fluxes.

Approximately two thirds of migratory songbirds in eastern North America negotiate the Gulf of Mexico (GOM), where inclement weather coupled with no refueling or resting opportunities can be lethal. However, decisions made when navigating such features and their consequences remain largely unknown due to technological limitations of tracking small animals over large areas. We used automated radio telemetry to track three songbird species (Red-eyed Vireo, Swainson's Thrush, Wood Thrush) from coastal Alabama to the northern Yucatan Peninsula (YP) during fall migration. Detecting songbirds after crossing ∼1,000 km of open water allowed us to examine intrinsic (age, wing length, fat) and extrinsic (weather, date) variables shaping departure decisions, arrival at the YP, and crossing times. Large fat reserves and low humidity, indicative of beneficial synoptic weather patterns, favored southward departure across the Gulf. Individuals detected in the YP departed with large fat reserves and later in the fall with profitable winds, and flight durations (mean = 22.4 h) were positively related to wind profit. Age was not related to departure behavior, arrival, or travel time. However, vireos negotiated the GOM differently than thrushes, including different departure decisions, lower probability of detection in the YP, and longer crossing times. Defense of winter territories by thrushes but not vireos and species-specific foraging habits may explain the divergent migratory behaviors. Fat reserves appear extremely important to departure decisions and arrival in the YP. As habitat along the GOM is degraded, birds may be limited in their ability to acquire fat to cross the Gulf.

The proliferation of digital cameras co-located with eddy covariance instrumentation provides new opportunities to better understand the relationship between canopy phenology and the seasonality of canopy photosynthesis. In this paper we analyze the abilities and limitations of canopy color metrics measured by digital repeat photography to track seasonal canopy development and photosynthesis, determine phenological transition dates, and estimate intra-annual and interannual variability in canopy photosynthesis. We used 59 site-years of camera imagery and net ecosystem exchange measurements from 17 towers spanning three plant functional types (deciduous broadleaf forest, evergreen needleleaf forest, and grassland/crops) to derive color indices and estimate gross primary productivity (GPP). GPP was strongly correlated with greenness derived from camera imagery in all three plant functional types. Specifically, the beginning of the photosynthetic period in deciduous broadleaf forest and grassland/crops and the end of the photosynthetic period in grassland/crops were both correlated with changes in greenness; changes in redness were correlated with the end of the photosynthetic period in deciduous broadleaf forest. However, it was not possible to accurately identify the beginning or ending of the photosynthetic period using camera greenness in evergreen needleleaf forest. At deciduous broadleaf sites, anomalies in integrated greenness and total GPP were significantly correlated up to 60 days after the mean onset date for the start of spring. More generally, results from this work demonstrate that digital repeat photography can be used to quantify both the duration of the photosynthetically active period as well as total GPP in deciduous broadleaf forest and grassland/crops, but that new and different approaches are required before comparable results can be achieved in evergreen needleleaf forest.

Variation is key to the adaptability of species and their ability to survive changes to the Earth's climate and habitats. Plasticity in movement strategies allows a species to better track spatial dynamics of habitat quality. We describe the mechanisms that shape the movement of a long-distance migrant bird (turkey vulture, Cathartes aura) across two continents using satellite tracking coupled with remote-sensing science. Using nearly 10 years of data from 24 satellite-tracked vultures in four distinct populations, we describe an enormous amount of variation in their movement patterns. We related vulture movement to environmental conditions and found important correlations explaining how far they need to move to find food (indexed by the Normalized Difference Vegetation Index) and how fast they can move based on the prevalence of thermals and temperature. We conclude that the extensive variability in the movement ecology of turkey vultures, facilitated by their energetically efficient thermal soaring, suggests that this species is likely to do well across periods of modest climate change. The large scale and sample sizes needed for such analysis in a widespread migrant emphasizes the need for integrated and collaborative efforts to obtain tracking data and for policies, tools and open datasets to encourage such collaborations and data sharing.

Determining how widespread human-induced changes such as habitat loss, landscape fragmentation, and climate instability affect populations, communities, and ecosystems is one of the most pressing environmental challenges. Critical to this challenge is understanding how these changes are affecting the movement abilities and dispersal trajectories of organisms and what role conservation planning can play in promoting movement among remaining fragments of suitable habitat. Whereas evidence is mounting for how conservation strategies such as corridors impact animal movement, virtually nothing is known for species dispersed by wind, which are often mistakenly assumed to not be limited by dispersal. Here, we combine mechanistic dispersal models, wind measurements, and seed releases in a large-scale experimental landscape to show that habitat corridors affect wind dynamics and seed dispersal by redirecting and bellowing airflow and by increasing the likelihood of seed uplift. Wind direction interacts with landscape orientation to determine when corridors provide connectivity. Our results predict positive impacts of connectivity and patch shape on species richness of wind-dispersed plants, which we empirically illustrate using 12 y of data from our experimental landscapes. We conclude that habitat fragmentation and corridors strongly impact the movement of wind-dispersed species, which has community-level consequences.

Background: This study investigates the ranging behavior of elephants in relation to precipitation-driven dynamics of vegetation. Movement data were acquired for five bachelors and five female family herds during three years in the Marsabit protected area in Kenya and changes in vegetation were mapped using MODIS normalized difference vegetation index time series (NDVI). In the study area, elevations of 650 to 1100 m.a.s.l experience two growth periods per year, while above 1100 m.a.s.l. growth periods last a year or longer., Results: We find that elephants respond quickly to changes in forage and water availability, making migrations in response to both large and small rainfall events. The elevational migration of individual elephants closely matched the patterns of greening and senescing of vegetation in their home range. Elephants occupied lower elevations when vegetation activity was high, whereas they retreated to the evergreen forest at higher elevations while vegetation senesced. Elephant home ranges decreased in size, and overlapped less with increasing elevation., Conclusions: A recent hypothesis that ungulate migrations in savannas result from countervailing seasonally driven rainfall and fertility gradients is demonstrated, and extended to shorter-distance migrations. In other words, the trade-off between the poor forage quality and accessibility in the forest with its year-round water sources on the one hand and the higher quality forage in the low-elevation scrubland with its seasonal availability of water on the other hand, drives the relatively short migrations (the two main corridors are 20 and 90 km) of the elephants. In addition, increased intra-specific competition appears to influence the animals' habitat use during the dry season indicating that the human encroachment on the forest is affecting the elephant population.

FireStem2D, a software tool for predicting tree stem heating and injury in forest fires, is a physically-based, two-dimensional model of stem thermodynamics that results from heating at the bark surface. It builds on an earlier one-dimensional model (FireStem) and provides improved capabilities for predicting fire-induced mortality and injury before a fire occurs by resolving stem moisture loss, temperatures through the stem, degree of bark charring, and necrotic depth around the stem. We present the results of numerical parameterization and model evaluation experiments for FireStem2D that simulate laboratory stem-heating experiments of 52 tree sections from 25 trees. We also conducted a set of virtual sensitivity analysis experiments to test the effects of unevenness of heating around the stem and with aboveground height using data from two studies: a low-intensity surface fire and a more intense crown fire. The model allows for improved understanding and prediction of the effects of wildland fire on injury and mortality of trees of different species and sizes.

Terrestrial plants remove CO2 from the atmosphere through photosynthesis, a process that is accompanied by the loss of water vapour from leaves. The ratio of water loss to carbon gain, or water-use efficiency, is a key characteristic of ecosystem function that is central to the global cycles of water, energy and carbon. Here we analyse direct, long-term measurements of whole-ecosystem carbon and water exchange. We find a substantial increase in water-use efficiency in temperate and boreal forests of the Northern Hemisphere over the past two decades. We systematically assess various competing hypotheses to explain this trend, and find that the observed increase is most consistent with a strong CO2 fertilization effect. The results suggest a partial closure of stomata-small pores on the leaf surface that regulate gas exchange-to maintain a near-constant concentration of CO2 inside the leaf even under continually increasing atmospheric CO2 levels. The observed increase in forest water-use efficiency is larger than that predicted by existing theory and 13 terrestrial biosphere models. The increase is associated with trends of increasing ecosystem-level photosynthesis and net carbon uptake, and decreasing evapotranspiration. Our findings suggest a shift in the carbon- and water-based economics of terrestrial vegetation, which may require a reassessment of the role of stomatal control in regulating interactions between forests and climate change, and a re-evaluation of coupled vegetation-climate models.

Background: The movement of animals is strongly influenced by external factors in their surrounding environment such as weather, habitat types, and human land use. With advances in positioning and sensor technologies, it is now possible to capture animal locations at high spatial and temporal granularities. Likewise, scientists have an increasing access to large volumes of environmental data. Environmental data are heterogeneous in source and format, and are usually obtained at different spatiotemporal scales than movement data. Indeed, there remain scientific and technical challenges in developing linkages between the growing collections of animal movement data and the large repositories of heterogeneous remote sensing observations, as well as in the developments of new statistical and computational methods for the analysis of movement in its environmental context. These challenges include retrieval, indexing, efficient storage, data integration, and analytical techniques., Results: This paper contributes to movement ecology research by presenting a new publicly available system, Environmental-Data Automated Track Annotation (Env-DATA), that automates annotation of movement trajectories with ambient atmospheric observations and underlying landscape information. Env-DATA provides a free and easy-to-use platform that eliminates technical difficulties of the annotation processes and relieves end users of a ton of tedious and time-consuming tasks associated with annotation, including data acquisition, data transformation and integration, resampling, and interpolation. The system is illustrated with a case study of Galapagos Albatross (Phoebastria irrorata) tracks and their relationship to wind, ocean productivity and chlorophyll concentration. Our case study illustrates why adult albatrosses make long-range trips to preferred, productive areas and how wind assistance facilitates their return flights while their outbound flights are hampered by head winds., Conclusions: The new Env-DATA system enhances Movebank, an open portal of animal tracking data, by automating access to environmental variables from global remote sensing, weather, and ecosystem products from open web resources. The system provides several interpolation methods from the native grid resolution and structure to a global regular grid linked with the movement tracks in space and time. The aim is to facilitate new understanding and predictive capabilities of spatiotemporal patterns of animal movement in response to dynamic and changing environments from local to global scales.

Background: Understanding how environmental conditions, especially wind, influence birds' flight speeds is a prerequisite for understanding many important aspects of bird flight, including optimal migration strategies, navigation, and compensation for wind drift. Recent developments in tracking technology and the increased availability of data on large-scale weather patterns have made it possible to use path annotation to link the location of animals to environmental conditions such as wind speed and direction. However, there are various measures available for describing not only wind conditions but also the bird's flight direction and ground speed, and it is unclear which is best for determining the amount of wind support (the length of the wind vector in a bird's flight direction) and the influence of cross-winds (the length of the wind vector perpendicular to a bird's direction) throughout a bird's journey., Results: We compared relationships between cross-wind, wind support and bird movements, using path annotation derived from two different global weather reanalysis datasets and three different measures of direction and speed calculation for 288 individuals of nine bird species. Wind was a strong predictor of bird ground speed, explaining 10-66% of the variance, depending on species. Models using data from different weather sources gave qualitatively similar results; however, determining flight direction and speed from successive locations, even at short (15 min intervals), was inferior to using instantaneous GPS-based measures of speed and direction. Use of successive location data significantly underestimated the birds' ground and airspeed, and also resulted in mistaken associations between cross-winds, wind support, and their interactive effects, in relation to the birds' onward flight., Conclusions: Wind has strong effects on bird flight, and combining GPS technology with path annotation of weather variables allows us to quantify these effects for understanding flight behaviour. The potentially strong influence of scaling effects must be considered and implemented in developing sampling regimes and data analysis.

Carbon (C) uptake rates in many forests are sustained, or decline only briefly, following disturbances that partially defoliate the canopy. The mechanisms supporting such functional resistance to moderate forest disturbance are largely unknown. We used a large-scale experiment, in which > 6700 Populus (aspen) and Betula (birch) trees were stem-girdled within a 39-ha area, to identify mechanisms sustaining C uptake through partial canopy defoliation. The Forest Accelerated Succession Experiment in northern Michigan, USA, employs a suite of C-cycling measurements within paired treatment and control meteorological flux tower footprints. We found that enhancement of canopy light-use efficiency and maintenance of light absorption maintained net ecosystem production (NEP) and aboveground wood net primary production (NPP) when leaf-area index (LAI) of the treatment forest temporarily declined by nearly half its maximum value. In the year following peak defoliation, redistribution of nitrogen (N) in the treatment forest from senescent early successional aspen and birch to non-girdled later successional species facilitated the recovery of total LAI to pre-disturbance levels. Sustained canopy physiological competency following disturbance coincided with a downward shift in maximum canopy height, indicating that compensatory photosynthetic C uptake by undisturbed, later successional subdominant and subcanopy vegetation supported C-uptake resistance to disturbance. These findings have implications for ecosystem management and modeling, demonstrating that forests may tolerate considerable leaf-area losses without diminishing rates of C uptake. We conclude that the resistance of C uptake to moderate disturbance depends not only on replacement of lost leaf area, but also on rapid compensatory photosynthetic C uptake during defoliation by emerging later successional species.

Seed size and dormancy are reproductive traits that interact as adaptations to environmental conditions. Here, we explore the evolution of these traits in environments that differ in overall mean favorability and in the extent of temporal predictability. Our model simulates a population of annual plants living in a range of environments that differ in aridity, namely mean annual precipitation and inter-annual variation of this mean precipitation. The optimal fitness curve is investigated assuming density dependence, three alternative hypothetical relationships between seed mass and seed survival in the soil (negative, positive, and independent of mass), and three alternative relationships between survival in soil and precipitation (strong and intermediate negative relationships, and no relationship). Our results show that seed size and dormancy are not two substitutable evolutionary traits; that specific combinations of these two traits are selected in environments that differ in favorability and temporal predictability; that a certain degree of seed dormancy is advantageous not only in temporally unpredictable environments but also in temporally predictable environments with high competition; and that more than one combination of seed size and dormancy (defined in terms of germination fraction) can be optimal, even in spatially homogeneous environments, potentially allowing selection for more variation in these traits within and among species., (© 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.)

The location of a wind turbine is critical to its power output, which is strongly affected by the local wind field. Turbine operators typically seek locations with the best wind at the lowest level above ground since turbine height affects installation costs. In many urban applications, such as small-scale turbines owned by local communities or organizations, turbine placement is challenging because of limited available space and because the turbine often must be added without removing existing infrastructure, including buildings and trees. The need to minimize turbine hazard to wildlife compounds the challenge. We used an exclusion zone approach for turbine-placement optimization that incorporates spatially detailed maps of wind distribution and wildlife densities with power output predictions for the Ohio State University campus. We processed public GIS records and airborne lidar point-cloud data to develop a 3D map of all campus buildings and trees. High resolution large-eddy simulations and long-term wind climatology were combined to provide land-surface-affected 3D wind fields and the corresponding wind-power generation potential. This power prediction map was then combined with bird survey data. Our assessment predicts that exclusion of areas where bird numbers are highest will have modest effects on the availability of locations for power generation. The exclusion zone approach allows the incorporation of wildlife hazard in wind turbine siting and power output considerations in complex urban environments even when the quantitative interaction between wildlife behavior and turbine activity is unknown.

Forest trees are the dominant species in many parts of the world and predicting how they might respond to climate change is a vital global concern. Trees are capable of long-distance gene flow, which can promote adaptive evolution in novel environments by increasing genetic variation for fitness. It is unclear, however, if this can compensate for maladaptive effects of gene flow and for the long-generation times of trees. We critically review data on the extent of long-distance gene flow and summarise theory that allows us to predict evolutionary responses of trees to climate change. Estimates of long-distance gene flow based both on direct observations and on genetic methods provide evidence that genes can move over spatial scales larger than habitat shifts predicted under climate change within one generation. Both theoretical and empirical data suggest that the positive effects of gene flow on adaptation may dominate in many instances. The balance of positive to negative consequences of gene flow may, however, differ for leading edge, core and rear sections of forest distributions. We propose future experimental and theoretical research that would better integrate dispersal biology with evolutionary quantitative genetics and improve predictions of tree responses to climate change., (© 2012 Blackwell Publishing Ltd/CNRS.)

Deforestation in mid- to high latitudes is hypothesized to have the potential to cool the Earth's surface by altering biophysical processes. In climate models of continental-scale land clearing, the cooling is triggered by increases in surface albedo and is reinforced by a land albedo-sea ice feedback. This feedback is crucial in the model predictions; without it other biophysical processes may overwhelm the albedo effect to generate warming instead. Ongoing land-use activities, such as land management for climate mitigation, are occurring at local scales (hectares) presumably too small to generate the feedback, and it is not known whether the intrinsic biophysical mechanism on its own can change the surface temperature in a consistent manner. Nor has the effect of deforestation on climate been demonstrated over large areas from direct observations. Here we show that surface air temperature is lower in open land than in nearby forested land. The effect is 0.85 ± 0.44 K (mean ± one standard deviation) northwards of 45° N and 0.21 ± 0.53 K southwards. Below 35° N there is weak evidence that deforestation leads to warming. Results are based on comparisons of temperature at forested eddy covariance towers in the USA and Canada and, as a proxy for small areas of cleared land, nearby surface weather stations. Night-time temperature changes unrelated to changes in surface albedo are an important contributor to the overall cooling effect. The observed latitudinal dependence is consistent with theoretical expectation of changes in energy loss from convection and radiation across latitudes in both the daytime and night-time phase of the diurnal cycle, the latter of which remains uncertain in climate models., (© 2011 Macmillan Publishers Limited. All rights reserved)

The even-aged northern hardwood forests of the Upper Great Lakes Region are undergoing an ecological transition during which structural and biotic complexity is increasing. Early-successional aspen (Populus spp.) and birch (Betula papyrifera) are senescing at an accelerating rate and are being replaced by middle-successional species including northern red oak (Quercus rubra), red maple (Acer rubrum), and white pine (Pinus strobus). Canopy structural complexity may increase due to forest age, canopy disturbances, and changing species diversity. More structurally complex canopies may enhance carbon (C) sequestration in old forests. We hypothesize that these biotic and structural alterations will result in increased structural complexity of the maturing canopy with implications for forest C uptake. At the University of Michigan Biological Station (UMBS), we combined a decade of observations of net primary productivity (NPP), leaf area index (LAI), site index, canopy tree-species diversity, and stand age with canopy structure measurements made with portable canopy lidar (PCL) in 30 forested plots. We then evaluated the relative impact of stand characteristics on productivity through succession using data collected over a nine-year period. We found that effects of canopy structural complexity on wood NPP (NPPw) were similar in magnitude to the effects of total leaf area and site quality. Furthermore, our results suggest that the effect of stand age on NPPw is mediated primarily through its effect on canopy structural complexity. Stand-level diversity of canopy-tree species was not significantly related to either canopy structure or NPPw. We conclude that increasing canopy structural complexity provides a mechanism for the potential maintenance of productivity in aging forests.

Understanding the movements of animals is pivotal for understanding their ecology and predicting their survival in the face of rapid global changes to climate, land use, and habitats, thus facilitating more effective habitat management. Migration by flying animals is an extreme form of movement that may be especially influenced by weather. With satellite telemetry studies, and the growing availability of information about the Earth's weather and land surface conditions, many data are collected that can advance our understanding about the mechanisms that shape migrations. We present the track annotation approach for movement data analysis using information about weather from the North American Reanalysis data set, a publicly available, regional, high-resolution model-observation hybrid product, and about topography, from a publicly available high-resolution digital elevation model (DEM). As a case study, we present the analysis of the response to environmental conditions in three contrasting populations of Turkey Vultures (Cathartes aura) across North America, tracked with a three-dimensional GPS-based sensor. Two populations in the east and west coasts of the United States responded similarly to weather, indicating use of both slope and thermal soaring. Continental-interior, "Plains populations," exhibited a different migratory pattern primarily indicative of thermal soaring. These differences help us understand the constraints and behaviors of soaring migrants. The track annotation approach allowed large-scale comparative study of movement in an important migratory species, and will enable similar studies at local to global scales.

Pollen of forest trees can move on the scales of tens to hundreds of kilometers, but the question of its viability during this long distance dispersal (LDD) has yet to be answered. While empirical studies of pollen viability in forest tree species are rare, controlled and scalable data to outdoor studies of the contribution of UV irradiation on pollen viability are not available. A simple protocol that allows the quantification of the viability response of pollen to UV, temperature, and humidity is developed and described here. Bench-scale conditions that approximate a wide range of atmospheric conditions including different humidity, temperature, and UV irradiation condition are used to determine the independent effects of each abiotic stress factor, and empirical functions are fitted and used to scale these bench-scale experiments to outdoor conditions. As a case study, pollen was sampled from two populations of Pinus taeda during two years and was used to quantify the decrease in viability due to atmospheric conditions during LDD. Contrary to maize pollen, P. taeda pollen viability decreased due to humid and cold conditions. The viability response of pollen to UV-A and UV-B corresponded to a viability reduction of about 10% after a full day of exposure. These laboratory findings were corroborated by an outdoor solar exposure experiment. The Fu-Liou online radiation model and a data set of radiosonde observations were used to estimate the typical conditions that would be encountered by LDD pollen. If initially caught in a strong updraft, dispersing P. taeda pollen could be carried many days and thousands of kilometers in the air. The empirical equations for P. taeda pollen viability reduction due to abiotic stresses predicted that 50% of the pollen would survive 24 hours of LDD under typical external conditions. The viable range of the pollen is, therefore, shorter than the physical dispersal distance. The methods used in our experiments are applicable for determination of dispersing pollen viability, especially when effects of different adverse conditions need to be separated. The empirical viability equations that resulted from our experiments can be used in an atmospheric dispersal model to estimate the viable range of tree pollen.

Traits associated with seed dispersal vary tremendously among sympatric wind-dispersed plants. We used two contrasting tropical tree species, seed traps, micrometeorology, and a mechanistic model to evaluate how variation in four key traits affects seed dispersal by wind. The conceptual framework of movement ecology, wherein external factors (wind) interact with internal factors (plant traits) that enable movement and determine when and where movement occurs, fully captures the variable inputs and outputs of wind dispersal models and informs their interpretation. We used model calculations to evaluate the spatial pattern of dispersed seeds for the 16 factorial combinations of four traits. The study species differed dramatically in traits related to the timing of seed release, and a strong species by season interaction affected most aspects of the spatial pattern of dispersed seeds. A rich interplay among plant traits and seasonal differences in atmospheric conditions caused this interaction. Several of the same plant traits are crucial for both seed dispersal and other aspects of life history variation. Observed traits that limit dispersal are likely to be constrained by their life history consequences.