Changes in the Onset of Spring and Uncertainty in 21st Century Terrestrial Carbon Sinks

A growing imperative in climate change research is to understand the relative carbon balance of terrestrial ecosystems when they are perturbed by warming and other climate changes. A key limit on potential carbon fixation by deciduous forests is growing season length, a variable know to be sensitive to temperature. Models are a tempting method to untangle species' budburst cues and forecast phenology under warmer climate scenarios. I tested two models' ability to recover parameters used to simulate budburst data. The simpler model was cued only by spring warmth while the complex one modulated warmth requirements with chilling exposure. For the simple model, parameters could be recovered consistently from some, but not all, regions of parameter space. The complex model's parameters were largely unrecoverable. To understand the consequences of parameter uncertainty, I applied both models to an 18 year phenological record of 13 deciduous tree species. While a few species fell into identifiable regions of the simple model's parameter space, most did not, and projected budburst dates had wide parameter-derived uncertainty intervals. These bands were wider still under a 5-degree Celsius warming scenario. Even greater uncertainty resulted from the complex model. These results suggest that attempts to forecast the timing trees' growing seasons, and therefore their potential for carbon fixation in warmer climates, should be treated with caution

Comparing the quality of crowdsourced data contributed by expert and non-experts

There is currently a lack of in-situ environmental data for the calibration and validation of remotely sensed products and for the development and verification of models. Crowdsourcing is increasingly being seen as one potentially powerful way of increasing the supply of in-situ data but here are a number of concerns over the subsequent use of the data, in particular over data quality. This paper examined crowdsourced data from the Geo-Wiki crowdsourcing tool for land cover validation to determine whether there were significant differences in quality between the answers provided by experts and non-experts in the domain of remote sensing and therefore the extent to which crowdsourced data describing human impact and land cover can be used in further scientific research. The results showed that there was little difference between experts and non-experts in identifying human impact although results varied by land cover while experts were better than non-experts in identifying the land cover type. This suggests the need to create training materials with more examples in those areas where difficulties in identification were encountered, and to offer some method for contributors to reflect on the information they contribute, perhaps by feeding back the evaluations of their contributed data or by making additional training materials available. Accuracies were also found to be higher when the volunteers were more consistent in their responses at a given location and when they indicated higher confidence, which suggests that these additional pieces of information could be used in the development of robust measures of quality in the future

A global dataset of crowdsourced land cover and land use reference data

Global land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land use is typically more difficult to map and in many cases cannot be remotely sensed. In-situ or ground-based data and high resolution imagery are thus an important requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Here we describe the global land cover and land use reference data derived from the Geo-Wiki crowdsourcing platform via four campaigns. These global datasets provide information on human impact, land cover disagreement, wilderness and land cover and land use. Hence, they are relevant for the scientific community that requires reference data for global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general

Within-species leaf trait variation and ecological flexibility in resprouting tropical trees

Plants have an inherent flexibility to respond to different environmental conditions. One axis of plant ecophysiological strategy is seen in the spectrum of leaf functional traits. Flexibility in these traits would be suggestive of plants' phenotypic plasticity in response to environmental changes. This research seeks to identify differences between leaves of sprout and non-sprout shoots of a broad ecological range of neotropical tree species. Using a functional-trait approach, this study assesses a large pool of species for within-species physiological flexibility. Leaf mass per area (LMA) and leaf area were measured for plants of sprout and non-sprout origin for 26 tree species grown in a reforestation plantation in Panama. Sprouts had a consistently lower LMA than non-sprouts, but there was no consistent pattern for leaf area. These trends show that sprouts are more like pioneer species than conspecific saplings, a finding in general agreement with fast sprout growth seen in previous studies. Further, later-successional (high LMA) species showed a greater reduction of LMA in sprouts. These results show that tropical tree species adjust physiologically to changing ecological roles and suggest that certain species may be more resilient than realized to changing climate and disturbance patterns

Climatic niche shifts in the serpentine soil flora of California

QUESTION: Soil properties are known to have a profound effect on the geographic distribution of plants. Unusual soils seem to allow species to occur outside their "typical" (realized) climatic niche. However, the generality of this pattern, and the mechanisms that drive it, are poorly known. Here, we focus on the tendency for some plant species to occur at unusually low elevations on infertile substrates, especially serpentine soils. We ask whether there is a flora-wide trend in the state of California toward lower elevations and warmer thermal limits on infertile serpentine soils than on other soils. LOCATION: State of California, USA. METHODS: We used herbarium data from 19 institutions. We only used species collected from both serpentine and non-serpentine soils. To focus on plant response to recent climate, we discarded records from before 1979. Finally, we discarded records that did not report latitude and longitude. The final data set consisted of 36 045 specimens representing 814 species. Latitude and longitude were used to infer elevation, temperature and soil type. We then developed a simulation modelling approach to test for significant differences in elevational and thermal distribution between serpentine and non-serpentine soils. RESULTS: Serpentine populations are found at lower elevations than non-serpentine populations, at both the low and high ends of elevation distributions (two tailed t-test, P<0.01). This pattern is partially matched by temperature: both high and low temperature data indicate that serpentine populations are limited to less extreme temperatures than non-serpentine populations (two tailed t-test, P<0.01). CONCLUSIONS: We show that there is a flora-wide trend toward lower elevation limits on serpentine soils in the state of California. Temperature data suggest a slightly different pattern, with serpentine plants occupying more moderate temperatures. We suggest that this difference may be due to a decoupling of elevation and temperature in some parts of California. Overall, our results are consistent with two mechanisms of plant range limitation: (1) a biotic mechanism at lower elevations (high temperatures), where serpentine provides a refuge from competition; and (2) an abiotic limit at upper elevations (low temperatures), where the effect of cold is exacerbated by the infertility of serpentine

Using light to predict fuels-reduction and group-selection effects on succession in Sierran mixed-conifer forest

Many semi-arid coniferous forests in western North America have reached historically unprecedented densities over the past 150 years and are dominated by shade-tolerant trees. Silvicultural treatments generally open the canopy but may not restore shade-intolerant species. We determined crossover-point irradiance (CPI) (light at which the height growth rank of pairs of species changes) for seedlings in Sierra Nevada mixed-conifer forest and used these to interpret light environments produced by fuels-reduction thinning and group selection with reserved large trees. Nine of 21 species pairs had well-defined CPIs. The CPI of the most common shade-tolerant and intolerant species (white fir (Abies concolor (Gordon & Glendl.) Lindl. ex Hildebr.) and ponderosa pine (Pinus ponderosa Douglas ex P. Lawson & C. Lawson)) was 22.5 mol m^(-2) day^(-1) or 41% of full sun. Median understory irradiance increased from 9.2 mol m^(-2) day^(-1) (17% full sun) in pretreatment forest to 13 mol m^(-2 day^(-1) (24% full sun) in lightly and 15.5 mol m^(-2) day^(-1) (28% full sun) in moderately thinned stands and 37 mol m^(-2) day^(-1) (67% full sun) in group-selection openings. We estimate that 5%-20% of ground area in lightly to moderately thinned stands would have enough light to favor shade-intolerant over shade-tolerant growth compared with 89% of ground area in group-selection openings. The CPI provides a tool to assess regeneration implications of treatment modification such as increasing heterogeneity of thinning to enhance regeneration or reserving large trees in group-selection openings to maintain wildlife habitat

Detecting landscape-level changes in tree biomass and biodiversity: Methodological constraints and challenges of plot-based approaches

Understanding how human-impacted landscapes are changing is crucial for effective adaptive management and payment for ecosystem services programs. Landscape-level shifts in land use pose challenges not seen in typical ecological studies of well-protected forests. In human-modified landscapes, forests are often monitored using unique sets of randomized plots at each visit rather than re-censusing in the same permanent plots. We contrast field-based forest change monitoring using these two techniques and investigate whether sampling more plots or bigger plots better detects forest changes. Our empirical analysis employs long-term data sets from old-growth, second-growth, and managed tropical forests. We find that resampling in permanent plots reduces variation among subsequent censuses, but more importantly, it enables more powerful statistical tests. Increasing the number of plots improves detection of forest biomass changes more effectively than enlarging existing plot sizes, cost considerations being equal. This effect arises from more extensive capture of spatial heterogeneity by sampling in a greater number of locations. We further show that typical sampling techniques poorly assess the biodiversity of tropical forests and struggle to identify big changes in populations of common species. We conclude with practical suggestions for forest sampling in human-impacted tropical landscapes, including defining monitoring goals and delineating forests vs. entire landscapes as study areas

The seasonal timing of warming that controls onset of the growing season

Forecasting how global warming will affect onset of the growing season is essential for predicting terrestrial productivity, but suffers from conflicting evidence. We show that accurate estimates require ways to connect discrete observations of changing tree status (e.g., pre- vs. post budbreak) with continuous responses to fluctuating temperatures. By coherently synthesizing discrete observations with continuous responses to temperature variation, we accurately quantify how increasing temperature variation accelerates onset of growth. Application to warming experiments at two latitudes demonstrates that maximum responses to warming are concentrated in late winter, weeks ahead of the main budbreak period. Given that warming will not occur uniformly over the year, knowledge of when temperature variation has the most impact can guide prediction. Responses are large and heterogeneous, yet predictable. The approach has immediate application to forecasting effects of warming on growing season length, requiring only information that is readily available from weather stations and generated in climate models

Temperature alone does not explain phenological variation of diverse temperate plants under experimental warming

Anthropogenic climate change has altered temperate forest phenology, but how these trends will play out in the future is controversial. We measured the effect of experimental warming of 0.6-5.0 degrees C on the phenology of a diverse suite of 11 plant species in the deciduous forest understory (Duke Forest, North Carolina, USA) in a relatively warm year (2011) and a colder year (2013). Our primary goal was to dissect how temperature affects timing of spring budburst, flowering, and autumn leaf coloring for functional groups with different growth habits, phenological niches, and xylem anatomy. Warming advanced budburst of six deciduous woody species by 5-15 days and delayed leaf coloring by 18-21 days, resulting in an extension of the growing season by as much as 20-29 days. Spring temperature accumulation was strongly correlated with budburst date, but temperature alone cannot explain the diverse budburst responses observed among plant functional types. Ring-porous trees showed a consistent temperature response pattern across years, suggesting these species are sensitive to photoperiod. Conversely, diffuse-porous species responded differently between years, suggesting winter chilling may be more important in regulating budburst. Budburst of the ring-porous 'Quercus alba' responded nonlinearly to warming, suggesting evolutionary constraints may limit changes in phenology, and therefore productivity, in the future. Warming caused a divergence in flowering times among species in the forest community, resulting in a longer flowering season by 10-16 days. Temperature was a good predictor of flowering for only four of the seven species studied here. Observations of interannual temperature variability overpredicted flowering responses in spring-blooming species, relative to our warming experiment, and did not consistently predict even the direction of flowering shifts. Experiments that push temperatures beyond historic variation are indispensable for improving predictions of future changes in phenology