Understory plants evade shading in a temperate deciduous forest amid climate variability by shifting phenology in synchrony with canopy trees.

Global warming is leading understory and canopy plant communities of temperate deciduous forests to grow leaves earlier in spring and drop them later in autumn. If understory species extend their leafy seasons less than canopy trees, they will intercept less light. We look for mismatched phenological shifts between canopy and understory in 28 years (1995-2022) of weekly data from Trelease Woods, Urbana, IL, USA. The observations cover 31 herb species of contrasting seasonality (for 1995-2017), three sapling species, and the 15 most dominant canopy tree species for all years, combined with solar radiation, temperature and canopy light transmittance data. We estimate how understory phenology, cold temperatures, canopy phenology, and solar radiation have individually limited understory plants' potential light interception over >2 decades. Understory and canopy phenology were the two factors most limiting to understory light availability, but which was more limiting varied greatly among species and among/within seasonality groups; solar radiation ranked third and cold fourth. Understory and canopy phenology shifts usually occurred in the same direction; either both strata were early or both were late, offsetting each other's effects. The four light-limiting factors combined showed significant temporal trends for six understory species, five toward less light interception. Warmer springs were significantly associated with shifts toward more light interception in three sapling species and 19 herb species. Canopy phenology became more limiting in warmer years for all three saplings species and 31 herb species. However, in aggregate, these variables mostly offset one another; only one sapling and seven herb species showed overall significant (and negative) relationships between light interception and spring temperature. The few understory species mismatched with canopy phenology due to changing climate are likely to intercept less light in future warmer years. The few species with data for carbon assimilation show broadly similar patterns to light interception.

Conformity and tradition are more important than environmental values in constraining resource overharvest.

We present the results of a hybrid research design that borrows from both experimental techniques-experimental games-and observational techniques-surveys-to examine the relationships between basic human values and exposure to natural ecosystems, on the one hand, and collective action for resource governance, on the other. We initially hypothesize that more frequent exposure to forests, and more pro-environmental values will be associated with more conservation action. However, we find that other values-tradition and conformity-are more important than pro-environmental values or exposure to nature. Our results imply that resource governance is likely to be more successful where resource users hold values that facilitate cooperation, not necessarily strong pro-environmental values.

How many people need to classify the same image? A method for optimizing volunteer contributions in binary geographical classifications.

Involving members of the public in image classification tasks that can be tricky to automate is increasingly recognized as a way to complete large amounts of these tasks and promote citizen involvement in science. While this labor is usually provided for free, it is still limited, making it important for researchers to use volunteer contributions as efficiently as possible. Using volunteer labor efficiently becomes complicated when individual tasks are assigned to multiple volunteers to increase confidence that the correct classification has been reached. In this paper, we develop a system to decide when enough information has been accumulated to confidently declare an image to be classified and remove it from circulation. We use a Bayesian approach to estimate the posterior distribution of the mean rating in a binary image classification task. Tasks are removed from circulation when user-defined certainty thresholds are reached. We demonstrate this process using a set of over 4.5 million unique classifications by 2783 volunteers of over 190,000 images assessed for the presence/absence of cropland. If the system outlined here had been implemented in the original data collection campaign, it would have eliminated the need for 59.4% of volunteer ratings. Had this effort been applied to new tasks, it would have allowed an estimated 2.46 times as many images to have been classified with the same amount of labor, demonstrating the power of this method to make more efficient use of limited volunteer contributions. To simplify implementation of this method by other investigators, we provide cutoff value combinations for one set of confidence levels.

Fair payments for effective environmental conservation.

Global efforts for biodiversity protection and land use-based greenhouse gas mitigation call for increases in the effectiveness and efficiency of environmental conservation. Incentive-based policy instruments are key tools for meeting these goals, yet their effectiveness might be undermined by such factors as social norms regarding whether payments are considered fair. We investigated the causal link between equity and conservation effort with a randomized real-effort experiment in forest conservation with 443 land users near a tropical forest national park in the Vietnamese Central Annamites, a global biodiversity hotspot. The experiment introduced unjustified payment inequality based on luck, in contradiction of local fairness norms that were measured through responses to vignettes. Payment inequality was perceived as less fair than payment equality. In agreement with our preregistered hypotheses, participants who were disadvantaged by unequal payments exerted significantly less conservation effort than other participants receiving the same payment under an equal distribution. No effect was observed for participants advantaged by inequality. Thus, equity effects on effort can have consequences for the effectiveness and efficiency of incentive-based conservation instruments. Furthermore, we show that women exerted substantially more conservation effort than men, and that increasing payment size unexpectedly reduced effort. This emphasizes the need to consider social comparisons, local equity norms, and gender in environmental policies using monetary incentives to motivate behavioral change.

Games as Tools to Address Conservation Conflicts.

Conservation conflicts represent complex multilayered problems that are challenging to study. We explore the utility of theoretical, experimental, and constructivist approaches to games to help to understand and manage these challenges. We show how these approaches can help to develop theory, understand patterns in conflict, and highlight potentially effective management solutions. The choice of approach should be guided by the research question and by whether the focus is on testing hypotheses, predicting behaviour, or engaging stakeholders. Games provide an exciting opportunity to help to unravel the complexity in conflicts, while researchers need an awareness of the limitations and ethical constraints involved. Given the opportunities, this field will benefit from greater investment and development.

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.

Resilience and Alternative Stable States of Tropical Forest Landscapes under Shifting Cultivation Regimes.

Shifting cultivation is a traditional agricultural practice in most tropical regions of the world and has the potential to provide for human livelihoods while hosting substantial biodiversity. Little is known about the resilience of shifting cultivation to increasing agricultural demands on the landscape or to unexpected disturbances. To investigate these issues, we develop a simple social-ecological model and implement it with literature-derived ecological parameters for six shifting cultivation landscapes from three continents. Analyzing the model with the tools of dynamical systems analysis, we show that such landscapes exhibit two stable states, one characterized by high forest cover and agricultural productivity, and another with much lower values of these traits. For some combinations of agricultural pressure and ecological parameters both of these states can potentially exist, and the actual state of the forest depends critically on its historic state. In many cases, the landscapes' 'ecological resilience', or amount of forest that could be destroyed without shifting out of the forested stability domain, declined substantially at lower levels of agricultural pressure than would lead to maximum productivity. A measure of 'engineering resilience', the recovery time from standardized disturbances, was independent of ecological resilience. These findings suggest that maximization of short-term agricultural output may have counterproductive impacts on the long-term productivity of shifting cultivation landscapes and the persistence of forested areas.

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 °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.

Comparing forests across climates and biomes: qualitative assessments, reference forests and regional intercomparisons.

Communities, policy actors and conservationists benefit from understanding what institutions and land management regimes promote ecosystem services like carbon sequestration and biodiversity conservation. However, the definition of success depends on local conditions. Forests' potential carbon stock, biodiversity and rate of recovery following disturbance are known to vary with a broad suite of factors including temperature, precipitation, seasonality, species' traits and land use history. Methods like tracking over-time changes within forests, or comparison with "pristine" reference forests have been proposed as means to compare the structure and biodiversity of forests in the face of underlying differences. However, data from previous visits or reference forests may be unavailable or costly to obtain. Here, we introduce a new metric of locally weighted forest intercomparison to mitigate the above shortcomings. This method is applied to an international database of nearly 300 community forests and compared with previously published techniques. It is particularly suited to large databases where forests may be compared among one another. Further, it avoids problematic comparisons with old-growth forests which may not resemble the goal of forest management. In most cases, the different methods produce broadly congruent results, suggesting that researchers have the flexibility to compare forest conditions using whatever type of data is available. Forest structure and biodiversity are shown to be independently measurable axes of forest condition, although users' and foresters' estimations of seemingly unrelated attributes are highly correlated, perhaps reflecting an underlying sentiment about forest condition. These findings contribute new tools for large-scale analysis of ecosystem condition and natural resource policy assessment. Although applied here to forestry, these techniques have broader applications to classification and evaluation problems using crowdsourced or repurposed data for which baselines or external validations are not available.

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.

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 there 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.

Individual-scale variation, species-scale differences: inference needed to understand diversity.

As ecological data are usually analysed at a scale different from the one at which the process of interest operates, interpretations can be confusing and controversial. For example, hypothesised differences between species do not operate at the species level, but concern individuals responding to environmental variation, including competition with neighbours. Aggregated data from many individuals subject to spatio-temporal variation are used to produce species-level averages, which marginalise away the relevant (process-level) scale. Paradoxically, the higher the dimensionality, the more ways there are to differ, yet the more species appear the same. The aggregate becomes increasingly irrelevant and misleading. Standard analyses can make species look the same, reverse species rankings along niche axes, make the surprising prediction that a species decreases in abundance when a competitor is removed from a model, or simply preclude parameter estimation. Aggregation explains why niche differences hidden at the species level become apparent upon disaggregation to the individual level, why models suggest that individual-level variation has a minor impact on diversity when disaggregation shows it to be important, and why literature-based synthesis can be unfruitful. We show how to identify when aggregation is the problem, where it has caused controversy, and propose three ways to address it.

Ecological and environmental factors constrain sprouting ability in tropical trees.

Most theories of forest biodiversity focus on the role of seed dispersal and seedling establishment in forest regeneration. In many ecosystems, however, sprouting by damaged stems determines which species occupies a site. Damaged trees can quickly recover from disturbance and out-compete seedlings. Links among species' traits, environmental conditions and sprouting could offer insight into species' resilience to changes in climate, land use, and disturbance. Using data for 25 Neotropical tree species at two sites with contrasting rainfall and soil, we tested hypotheses on how four functional traits (seed mass, leaf mass per area, wood density and nitrogen fixation) influence species' sprouting responses to disturbance and how these relationships are mediated by a tree's environmental context. Most species sprouted in response to cutting, and many species' sprouting rates differed significantly between sites. Individual traits showed no direct correlation with sprouting. However, interactions among traits and site variables did affect sprouting rates. Many species showed increased sprouting in the higher-quality site. Most nitrogen-fixing species showed the opposite trend, sprouting more frequently where resources are scarce. This study highlights the use of functional traits as a proxy for life histories, and demonstrates the importance of environmental effects on demography.