Interpreting common garden studies to understand cueing mechanisms of spring leafing phenology in temperate and boreal tree species

Trees are particularly susceptible to climate change due to their long lives and slow dispersal. However, trees can adjust the timing of their growing season in response to weather conditions without evolutionary change or long-distance migration. This makes understanding phenological cueing mechanisms a critical task to forecast climate change impacts on forests. Because of slow data accumulation, unconventional and repurposed information is valuable in the study of phenology. Here, I develop and use a framework to interpret what phenological patterns among provenances of a species in a common garden reveal about their leafing cues. and potential climate change responses. Species whose high elevation/latitude provenances leaf first likely have little chilling requirement, or for latitude gradients only. a critical photoperiod cue met relatively early in the season. Species with low latitude/elevation origins leafing first have stronger controls against premature leafing; I argue that these species are likely less phonologically flexible in responding to climate change. Among published studies, the low to high order is predominant among frost-sensitive ring-porous species. Narrow-xylemed species show nearly all possible patterns, sometimes with strong contrasts even within genera for both conifers and angiosperms. Some also show complex patterns, indicating multiple mechanisms at work, and a few are largely undifferentiated across broad latitude gradients, suggesting phenotypic plasticity to a wanner climate. These results provide valuable evidence on which temperate and boreal tree species are most likely to adjust in place to climate change, and provide a framework for interpreting historic or newly-planted common garden studies of phenology

Thinking outside the plot: monitoring forest biodiversity for social-ecological research

Protecting biodiversity, either for its own sake or for its value to humanity, is a principal goal of conservation efforts worldwide. For this reason, many studies on the social science of resource management and governance seek to quantify biodiversity outcomes. Here, we focus on the International Forestry Resources and Institutions program to demonstrate some of the challenges of quantitative biodiversity assessment and suggest ways to overcome them. One of this program's research goals is to understand the causes of biodiversity loss, which is explicitly assessed using plot-based forest sampling. Plot-based methods to capture biodiversity changes require huge amounts of data. Even if sampling is sufficient, existing protocols can only capture changes in the types of species actually sampled, typically trees. Other elements of biodiversity are not censused, including animals, herbs, shrubs, fungi, and epiphytes that may provide medicine, food, wildlife habitat, trade items, or cultural goods. Using case studies of two sites in Uganda, we demonstrate that more spatially extensive surveys targeting multiple types of data can give a broader picture of forest status and changes than can plot-based sampling alone; many relevant variables can be observed while traveling among plot points with little additional effort. Reviewing the ecological literature, we identify correlates of forest status that can supplement plot-based sampling. These include large trees, epiphyte-laden trees, culturally or commercially valuable species, large stumps, and evidence of hunting and trapping. Further, data elicited from local resource users can play an important role in biodiversity monitoring. These findings suggest that effective biodiversity monitoring may be within easier reach than previously thought, although robust comparisons among sites remains a challenge, especially when climate, soils, or site history differ greatly

Fair payments for effective environmental conservation

Incentive-based measures are increasingly popular to alleviate ongoing biodiversity loss and greenhouse gas emissions from land use change. However, effectively using scarce conservation funds remains a major challenge. Using behavioral economic experiments in the buffer zone of a Vietnamese national park, we show that unfair payment distributions that are beyond land users’ control can reduce the environmental effectiveness of incentives, and that women exert more effort. Our study region is threatened by forest degradation and is part of the nationwide Vietnamese Payments for Forest Ecosystem Services program, making it an important and relevant context for improving the effectiveness of conservation measures. These results show that policymakers aiming for effective and efficient programs should pay close attention to fairness and gender

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

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-ecolgical 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 productiviy. 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

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 satellite-field phenological bridging framework for characterizing community-level spring forest phenology using multi-scale satellite imagery

Forest phenology, as a sensitive indicator of a forest's response to climate change and variability, has long been monitored using remote sensing, yet has seldom been interpreted or validated with spatially compatible, community-level field phenological observations. In temperate deciduous forests, multiple spring phenological phases are critical for modeling carbon storage and biogeochemical cycles. The simultaneous detection of all these critical phenological phases at the community level remains a long-standing challenge. To tackle these challenges, the objective of this study is to develop a novel satellite-field phenological bridging framework for characterizing all key spring phenological phases of a fragmented deciduous forest using multi-scale satellite time series. The framework consists of four key components: deep learning-based spatiotemporal image fusion, satellite-based forest phenology modeling, satellite-based forest phenological metric extraction, and field-based forest community phenological characterization. With the devised framework, we extract a total of 24 satellite phenological metrics of Trelease Woods, a forest fragment near Urbana, IL, USA. From weekly field phenological observations of 148 canopy trees of 15 common species of the forest community, we devise three summative field phenological indices to characterize community-level phenological states in spring. Under the satellite-field bridging framework, events during each key spring forest phenological phase (i.e., bud swell, budburst/leafing out, leaf expansion, and leaf maturity) are successfully detected using the fusion imagery (MAE from 1.1 to 2.9 days and bias from -2.4 to 1.5 days). However, the satellite detection of the earliest field events may be influenced by understory plants, soil background, and snow. The subsequent multi-scale, satellite phenological analysis underscores the importance of taking into account spatial scale and representation from both satellite and field phenological perspectives in building corresponding bridging relationships. Among the extracted pheno-metrics, bridging the threshold-based metrics to field phenological indices results in the highest accuracy (MAE less than 3 days and bias less than 2 days). The strong agreement among the field indices demonstrates the effectiveness of our field phenological surveying approach in generating community-wide forest phenological representation. Our study innovatively scales up the field phenological observations from the individual trees to the species to the community level, and the devised framework enables accurate retrieval of all key phenological events of community-wide, spring canopy development of the forest fragment