Songlin Fei

Macrosystems ecology: novel methods and new understanding of multi-scale patterns and processes

As the global biomes are increasingly threatened by human activities, understanding of macroscale patterns and processes is pressingly needed for effective management and policy making. Macrosystems ecology, which studies multiscale ecological patterns and processes, has gained growing interest in the research community. However, as a relatively new field in ecology, research in macrosystems ecology is facing various challenges. In this special issue, we highlight the following two latest exciting developments in this thriving field: (1) novel tools and methods and (2) new understandings on macroscale patterns and processes. While we believe that the contributions featured in this issue provide promising advancements in macrosystems ecology, we also see multiple challenges for future research including (1) multidisciplinary approaches for long-term and multiscale studies and (2) scaling local patterns and processes to broader scales.

Photographic assessment of temperate forest understory phenology in relation to springtime meteorological drivers

Phenology shows sensitive responses to seasonal changes in atmospheric conditions. Forest understory phenology, in particular, is a crucial component of the forest ecosystem that interacts with meteorological factors, and ecosystem functions such as carbon exchange and nutrient cycling. Quantifying understory phenology is challenging due to the multiplicity of species and heterogeneous spatial distribution. The use of digital photography for assessing forest understory phenology was systematically tested in this study within a temperate forest during spring 2007. Five phenology metrics (phenometrics) were extracted from digital photos using three band algebra and two greenness percentage (image binarization) methods. Phenometrics were compared with a comprehensive suite of concurrent meteorological variables. Results show that greenness percentage cover approaches were relatively robust in capturing forest understory green-up. Derived spring phenology of understory plants responded to accumulated air temperature as anticipated, and with day-to-day changes strongly affected by estimated moisture availability. This study suggests that visible-light photographic assessment is useful for efficient forest understory phenology monitoring and allows more comprehensive data collection in support of ecosystem/land surface models.

Divergence of species responses to climate change

Traits determine species responses to climate change, as most eastern U.S. trees shift westward following moisture change. Climate change can have profound impacts on biodiversity and the sustainability of many ecosystems. Various studies have investigated the impacts of climate change, but large-scale, trait-specific impacts are less understood. We analyze abundance data over time for 86 tree species/groups across the eastern United States spanning the last three decades. We show that more tree species have experienced a westward shift (73%) than a poleward shift (62%) in their abundance, a trend that is stronger for saplings than adult trees. The observed shifts are primarily due to the changes of subpopulation abundances in the leading edges and are significantly associated with changes in moisture availability and successional processes. These spatial shifts are associated with species that have similar traits (drought tolerance, wood density, and seed weight) and evolutionary histories (most angiosperms shifted westward and most gymnosperms shifted poleward). Our results indicate that changes in moisture availability have stronger near-term impacts on vegetation dynamics than changes in temperature. The divergent responses to climate change by trait- and phylogenetic-specific groups could lead to changes in composition of forest ecosystems, putting the resilience and sustainability of various forest ecosystems in question.

Automated content analysis: addressing the big literature challenge in ecology and evolution

Summary 1.The exponential growth of scientific literature—which we call the “big literature” phenomenon—has created great challenges in literature comprehension and synthesis. The traditional manual literature synthesis processes are often unable to take advantage of big literature due to human limitations in time and cognition, creating the need for new literature synthesis methods to address this challenge. 2.In this paper, we discuss a highly useful literature synthesis approach, Automated Content Analysis (ACA), which has not yet been widely adopted in the fields of ecological and evolutionary biology. ACA is a suite of machine-learning tools for the qualitative and quantitative synthesis of big literature commonly used in the social sciences and in medical research. 3.Our goal is to introduce ecologists and evolutionary biologists to ACA and illustrate its capacity to synthesize overwhelming volumes of literature. First, we provide a brief history of the ACA method and summarize the fundamental process of ACA. Next, we present two ACA studies to illustrate the utility and versatility of ACA in synthesizing ecological and evolutionary literature. Finally, we discuss how to maximize the utility and contributions of ACA, as well as potential research directions that may help to advance the use of ACA in future ecological and evolutionary research. 4.Unlike manual methods of literature synthesis, ACA is able to process high volumes of literature at substantially shorter timespans, while helping to mitigate human biases. The overall efficiency and versatility of this method allows for a broad range of applications for literature review and synthesis, including both exploratory reviews and systematic reviews aiming to address more targeted research questions. By allowing for more extensive and comprehensive review of big literature, ACA has the potential to fill an important methodological gap and to therefore contribute to the advancement of ecological and evolutionary research. This article is protected by copyright. All rights reserved.

Identification of understory invasive exotic plants with remote sensing in urban forests.

Abstract Invasive exotic plants (IEP) pose a significant threat to many ecosystems. To effectively manage IEP, it is important to efficiently detect their presences and determine their distribution patterns. Remote sensing has been a useful tool to map IEP but its application is limited in urban forests, which are often the sources and sinks for IEP. In this study, we examined the feasibility and tradeoffs of species level IEP mapping using multiple remote sensing techniques in a highly complex urban forest setting. Bush honeysuckle ( Lonicera maackii ), a pervasive IEP in eastern North America, was used as our modeling species. Both medium spatial resolution (MSR) and high spatial resolution (HSR) imagery were employed in bush honeysuckle mapping. The importance of spatial scale was also examined using an up-scaling simulation from the HSR object based classification. Analysis using both MSR and HSR imagery provided viable results for IEP distribution mapping in urban forests. Overall mapping accuracy ranged from 89.8% to 94.9% for HSR techniques and from 74.6% to 79.7% for MSR techniques. As anticipated, classification accuracy reduces as pixel size increases. HSR based techniques produced the most desirable results, therefore is preferred for precise management of IEP in heterogeneous environment. However, the use of MSR techniques should not be ruled out given their wide availability and moderate accuracy.

Cross-scale contradictions in ecological relationships

ContextNot accounting for spatial heterogeneity in ecological analyses can cause modeled relationships to vary across spatial scales, specifically different levels of spatial resolution. These varying results hinder both the utility of data collected at one spatial scale for analyses at others and the determination of underlying processes.ObjectivesTo briefly review existing methods for analyzing data collected at multiple scales, highlight the effects of spatial heterogeneity on the utility of these methods, and to illustrate a practical statistical method to account for the sources of spatial heterogeneity when they are unknown.MethodsUsing simulated examples, we show how not accounting for the drivers of spatial heterogeneity in statistical models can cause contradictory findings regarding relationship direction across spatial scales. We then show how mixed effects models can remedy this multiscaling issue.ResultsIgnoring sources of spatial heterogeneity in statistical models with coarse spatial scales produced contradictory results to the true underlying relationship. Treating drivers of spatial heterogeneity as random effects in a mixed effects model, however, allowed us to uncover this true relationship.ConclusionsMixed effects models is advantageous as it is not always necessary to know the influential explanatory variables that cause spatial heterogeneity and no additional data are required. Furthermore, this approach is well documented, can be applied to data having various distribution types, and is easily executable using multiple statistical packages.

Evidence of biotic resistance to invasions in forests of the Eastern USA

AbstractContext Detecting biotic resistance to biological invasions across large geographic areas may require acknowledging multiple metrics of niche usage and potential spatial heterogeneity in associations between invasive and native species diversity and dominance.ObjectivesDetermine (1) if native communities are resistant to biological invasions at macroscales; (2) the metrics that best quantify biotic resistance at these scales; and (3) the degree to which the direction and magnitude of invader-native associations vary with scale and/or location.Methods Using a mixed-effects modeling framework to account for potential sub-regional and cross-scale variability in invader-native associations, we modeled the species richness and cover of invasive plants in 42,626 plots located throughout Eastern USA forests in relationship to plot-level estimates of native tree biomass, species richness, and evolutionary diversity.ResultsWe found (1) native tree biomass and evolutionary diversity, but not species richness, to be negatively associated with invader establishment and dominance, and thus indicative of biotic resistance; (2) evidence that evolutionary diversity limits invader dominance more than it does invader establishment; (3) evidence of greater invasion resistance in parts of the agriculturally-dominated Midwest and in and around the more-contiguous forests of the Appalachian Mountains; and (4) the magnitude to which native tree biomass and evolutionary diversity limit invasion varies across the ranges of these metrics.Conclusions These findings illustrate the improved understanding of biotic resistance to invasions that is gained by accounting for sub-regional variability in ecological processes, and underscores the need to determine the factors leading to spatial heterogeneity in biotic resistance.

Next Generation of Ecological Indicators of Wetland Condition

Penn State Cooperative Wetlands Center, Department of Geography, Pennsylvania State University, 302 Walker Building, University Park, PA 16802, USA Center for Statistical Ecology and Environmental Statistics, Department of Statistics, Pennsylvania State University, University Park, PA 16802, USA Department of Forestry, University of Kentucky, 204 T.P. Cooper Building, Lexington, KY 40546-0073, USA Statistics Department, Oregon State University, 44 Kidder Hall, Corvallis, OR 97331, USA School of Forest Resources, Pennsylvania State University, Forest Resources Building, University Park, PA 16802, USA Center for Water and the Environment, Natural Resources Research Institute, University of Minnesota Duluth, 1900 East Camp Street, Ely, MN 55731, USA

Biotic resistance to exotic invasions: its role in forest ecosystems, confounding artifacts, and future directions

Biotic resistance, the ability of communities to resist exotic invasions, has long attracted interest in the research and management communities. However, inconsistencies exist in various biotic resistance studies and less is known about the current status and knowledge gaps of biotic resistance in forest ecosystems. In this paper, we provide a brief review of the history and mechanisms of the biotic resistance hypothesis, and summarize the central topics and knowledge gaps related to biotic resistance with a special emphasis on forest ecosystems. Overall, although the amount of research efforts on biotic resistance in forest ecosystems has increased since the mid-2000s, aspects such as resistance to exotic pests and pathogens remain understudied. In addition, we synthesize ecological and statistical explanations of observed inconsistencies and provide suggestions for future research directions. Some of the observed inconsistencies on biotic resistance can be attributed to (1) the interactive or additive effects of other ecological processes and (2) the statistical artifacts of modifiable areal unit problem. With the advancement of new statistical knowledge and tools, along with availability of big data, biotic resistance research can be greatly improved with the simultaneous consideration of key ecological processes, the attention to various scales involved, and the addition of understudied systems.

Northward migration under a changing climate: a case study of blackgum (Nyssa Sylvatica)

Species are predicted to shift their distribution ranges in response to climate change. Region-wide, empirically-based studies, however, are still limited to support these predictions. We used a model tree species, blackgum (Nyssa sylvatica), to study climate-induced range shift. Data collected from two separate sampling periods (1980s and 2007) by the USDA’s Forestry and Inventory Analysis (FIA) Program were used to investigate changes in abundance and dominance, and shifts in distribution, of blackgum in four ecoregions of the eastern United States. Our results indicated new recruitment of blackgum in the northern portion of its range, along with increases in both density and annual rates of change in importance value (IV). Conversely, declines in recruitment were found in the southern portion of blackgum’s range, along with decreases in density and IV. The center portion of blackgum’s range had mixed patterns of change (i.e., both increases and decreases) throughout. A northward range expansion was also detected by comparing blackgum’s historic range to where it was detected during our two more-recent sampling periods. Our findings suggest that blackgum is migrating north in response to climate change. Our study also suggests two broader implications about tree migration patterns in response to climate change: (1) species can respond to changing climate in relatively short time periods, at least for generalist species such as blackgum, and (2) climate-induced vegetation dynamic patterns can be detected at the regional level, but are inherently complex.