Abstract We introduce a new “ecosystem‐scale” experiment at the Cedar Creek Ecosystem Science Reserve in central Minnesota, USA to test long‐term ecosystem consequences of tree diversity and composition. The experiment—the largest of its kind in North America—was designed to provide guidance on forest restoration efforts that will advance carbon sequestration goals and contribute to biodiversity conservation and sustainability.The new Forest and Biodiversity (FAB2) experiment uses native tree species in varying levels of species richness, phylogenetic diversity and functional diversity planted in 100 m2and 400 m2plots at 1 m spacing, appropriate for testing long‐term ecosystem consequences. FAB2 was designed and established in conjunction with a prior experiment (FAB1) in which the same set of 12 species was planted in 16 m2plots at 0.5 m spacing. Both are adjacent to the BioDIV prairie‐grassland diversity experiment, enabling comparative investigations of diversity and ecosystem function relationships between experimental grasslands and forests at different planting densities and plot sizes.Within the first 6 years, mortality in 400 m2monoculture plots was higher than in 100 m2plots. The highest mortality occurred inTilia americanaandAcer negundomonocultures, but mortality for both species decreased with increasing plot diversity. These results demonstrate the importance of forest diversity in reducing mortality in some species and point to potential mechanisms, including light and drought stress, that cause tree mortality in vulnerable monocultures. The experiment highlights challenges to maintaining monoculture and low‐diversity treatments in tree mixture experiments of large extent.FAB2 provides a long‐term platform to test the mechanisms and processes that contribute to forest stability and ecosystem productivity in changing environments. Its ecosystem‐scale design, and accompanying R package, are designed to discern species and lineage effects and multiple dimensions of diversity to inform restoration of ecosystem functions and services from forests. It also provides a platform for improving remote sensing approaches, including Uncrewed Aerial Vehicles (UAVs) equipped with LiDAR, multispectral and hyperspectral sensors, to complement ground‐based monitoring. We aim for the experiment to contribute to international efforts to monitor and manage forests in the face of global change.
more »
« less
Guidelines for including bamboos in tropical ecosystem monitoring
Abstract Bamboos are a diverse and ecologically important group of plants that have the potential to modulate the structure, composition, and function of forests. With the aim of increasing the visibility and representation of bamboo in forest surveys, and to standardize techniques across ecosystems, we present a protocol for bamboo monitoring in permanent research plots. A bamboo protocol is necessary because measurements and sampling schemes that are well‐suited to trees are inadequate for monitoring most bamboo species and populations. Our protocol suggests counting all bamboo culms (stems) in the study plot and determining bamboo dimensions based on two different approaches: (a) measuring a random subset of 60 culms and calculating the average dimensions or (b) measuring all culms. With data from 1‐ha plots in the Peruvian Andes, we show that both approaches provide very similar estimates of bamboo basal area. We suggest including all mature culms rooted inside change the to each plot from all woody bamboo species with maximum diameters ≥1 cm. We also present recommendations on how to collect vouchers of bamboo species for identification. Data collected according to our proposed protocols will increase our understanding of regional and global patterns in bamboo diversity and the role of bamboo in forest dynamics. Abstract in Spanish is available with online material.
more »
« less
- Award ID(s):
- 1754664
- PAR ID:
- 10457454
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Biotropica
- Volume:
- 52
- Issue:
- 3
- ISSN:
- 0006-3606
- Page Range / eLocation ID:
- p. 427-443
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Tropical forest understory regeneration occurs rapidly after disturbance with compositional trajectories that depend on species availability and environmental conditions. To predict future tropical forest regeneration dynamics, we need a deeper understanding of how pulse disturbance events, like hurricanes, interact with environmental variability to affect understory demography and composition. We examined fern and sapling mortality, recruitment, and community composition in relation to solar radiation and soil moisture using 17 years of forest dynamics data (2003–2019) from the Canopy Trimming Experiment in the Luquillo Experimental Forest, Puerto Rico. Solar radiation increased 150% and soil moisture increased 40% following canopy trimming of experimental plots relative to control plots. All plots were disturbed in 2017 by Hurricanes Irma and Maria, so experimentally trimmed plots presented the opportunity to study the effects of multiple hurricanes, while control plots isolated the effects of a single natural hurricane. Recruitment rates maximized at 0.14 individuals/plot/month for ferns and 0.20 stems/plot/month for saplings. Recruitment and mortality were distributed more evenly over the 17 years of monitoring in experimentally trimmed plots than in control plots; however, following Hurricane Maria demographic rates substantially increased in control plots only. In experimentally trimmed plots, the largest community compositional shifts occurred as a result of the trimming events, and compositional changes were greatest for control plots after Hurricane Maria in 2017. Pioneer tree and fern species increased in abundance in response to both simulated and natural hurricanes. Following Hurricane Maria, two dominant pioneer species,Cyathea arboreaandCecropia schreberiana, recruited abundantly, but only in control plots. In trimmed plots, increased solar radiation and soil moisture shifted understory species composition steadily toward pioneer and secondary‐successional species, with soil moisture interacting strongly with canopy trimming. Thus, both solar radiation and soil moisture are environmental drivers affecting pioneer species recruitment following disturbance, which interact with canopy opening following hurricanes. Our results suggest that if hurricane disturbances increase in frequency and severity, as suggested by climate change predictions, the understory regeneration of late‐successional species, such asManilkara bidentataandSloanea berteroana, which prefer deeper shade and slightly drier soil microsites, may become imperiled.more » « less
-
Abstract Understanding the determinants of urban forest diversity and structure is important for preserving biodiversity and sustaining ecosystem services in cities. However, comprehensive field assessments are resource‐intensive, and landscape‐level approaches may overlook heterogeneity within urban regions. To address this challenge, we combined remote sensing with field inventories to comprehensively map and analyze urban forest attributes in forest patches across the Minneapolis‐St. Paul Metropolitan Area (MSPMA) in a multistep process. First, we developed predictive machine learning models of forest attributes by integrating data from forest inventories (from 40 12.5‐m‐radius plots) with Global Ecosystem Dynamics Investigation (GEDI) observations and Sentinel‐2‐derived land surface phenology (LSP). These models enabled accurate predictions of forest attributes, specifically nine metrics of plant diversity (tree species richness, tree abundance, and understory plant abundance), structure (average canopy height, dbh, and canopy density), and structural complexity (variability in canopy height, dbh, and canopy density) with relative errors ranging between 11% and 21%. Second, we applied these machine learning models to predict diversity metrics for 804 additional plots from GEDI and Sentinel‐2. Finally, we applied Bayesian multilevel models to the predicted diversity metrics to assess the influence of multiple factors—patch dimensions, landscape attributes, plot position, and jurisdictional agency—on these forest attributes across the 804 predicted plots. The models showed all predictors have some degree of effect on forest attributes, presenting varying explanatory power withR2values ranging from 0.071 to 0.405. Overall, plot characteristics (e.g., distance to nearest trail, proximity to forest edge) and jurisdictional agency explained a large portion of the variability across patches, whereas patch and landscape characteristics did not. The relative effect of plot versus management sets of predictors on the marginal ΔR2was heterogeneous across metrics and ecological subsections (an ecological classification designation). The multiplicity of determinants influencing urban forests emphasizes the intricate nature of urban ecosystems and highlights nuanced, heterogeneous relationships between urban ecological and anthropogenic factors that determine forest properties. Effectively enhancing biodiversity in urban forests requires assessments, management, and conservation strategies tailored for context‐specific characteristics.more » « less
-
Abstract Forest disturbances associated with edge effects, wildfires, and windthrow events have impacted large swaths of the tropics. Defining the levels of forest disturbance that cause ecologically relevant reductions in fruit and seed (FS) production is key to understanding forest resilience to current and future global changes. Here, we tested the hypotheses that: (1) low‐intensity experimental fires alone would cause minor changes in FS production and diversity in a tropical forest, whereas synergistic disturbance effects resulting from edge effects, wildfires, droughts, and blowdowns would drive long‐term reductions in FS diversity and production; and (2) the functional composition of FS in disturbed forests would shift toward tree species with acquisitive strategies. To test these hypotheses, we quantified FS production between 2005 and 2018 in a large‐scale fire experiment in southeast Amazonia. The experimental treatments consisted of three 50‐ha plots: a Control plot, a plot burned annually (B1yr) and a plot burned every three years (B3yr) between 2004 and 2010. These plots were impacted by edge effects, two droughts (2007 and 2010), and a blowdown event in 2012. Our results show that FS production remained relatively high following low‐intensity fires, but declined where fires were most severe (i.e., forest edge of B3yr). The number of species‐producing FS declined sharply when fires co‐occurred with droughts and a windthrow event, and species composition shifted throughout the experiment. Along the edge of both burned plots, the forest community became dominated by species with faster relative growth, thinner leaves, thinner bark, and lower height. We conclude that compounding disturbances changed FS patterns, with a strong effect on species composition and potentially large effects on the next generation of trees. This is largely due to reductions in the diversity of species‐producing FS where fires are severe, causing a shift toward functional traits typically associated with pioneer and generalist species.more » « less
-
Amazon forests are becoming increasingly vulnerable to disturbances such as droughts, fires, windstorms, logging, and forest fragmentation, all of which lead to forest degradation. Nevertheless, quantifying the extent and severity of disturbances and their cumulative impact on forest degradation remains a significant challenge. In this study, we combined multispectral data from Landsat sensors with hyperspectral data from the Earth Observing-One (Hyperion/EO-1) sensor to evaluate the efficacy of multiple vegetation indices in detecting forest responses to disturbances in an experimentally burned forest in southeastern Amazonia. Our experimental area was adjacent to an agricultural field and consisted of three 50-ha treatments – an unburned Control, a plot burned every three years, and a plot burned annually from 2004 to 2010. All plots were monitored to assess vegetation recovery after fire disturbance. These areas were also affected by three drought events (2007, 2010, and 2016) over the study period. We evaluated a total of 18 Vegetation Indices (VI), one unique to Landsat, 12 unique to Hyperion/EO-1, and five commons to both satellites (i.e., 6 total from Landsat and 17 from Hyperion). We used linear models (LM) to evaluate how changes in ground observations of forest structure (biomass, leaf area index [LAI], and litter production) associated with fire were captured by the two VIs most sensitive to forest degradation. Our results indicate that the Plant Senescence Reflectance Index (PSRI) derived from Hyperion/EO-1 was the most sensitive to vegetation changes associated with forest fires, increasing by 94% in burned vs. unburned forests. Of the Landsat-derived VIs, we found that the Green-Red Normalized Difference (GRND) were the most sensitive to forest degradation by fire, showing a marked decline (87%) in the burned plots compared with the unburned Control. However, compared to PSRI, the GRND was a better predictor of changes associated with fire, both in the forest interior or forest edge, for the three ground variables: biomass stocks (r2 =0.5–0.8), LAI (r2=0.8–0.9), and litter production (r2=0.4–0.7). This study demonstrate that VIs can detect forest responses to fire and other disturbances over time, highlighting the relative strengths of each VI. In doing so, it shows how the integration of multispectral and hyperspectral data can be useful for monitoring tropical forest degradation and recovery. Moreover, it provides valuable insights into the limitations of existing approaches, which can inform the design of next-generation sensors for global forest monitoring.more » « less
An official website of the United States government
