Neighborhood and community interactions determine the spatial pattern of tropical tree seedling survival

Factors affecting survival and recruitment of 3531 individually mapped seedlings of Myristicaceae were examined over three years in a highly diverse neotropical rain forest, at spatial scales of 1–9 m and 25 ha. We found convincing evidence of a community compensatory trend (CCT) in seedling survival (i.e., more abundant species had higher seedling mortality at the 25-ha scale), which suggests that density-dependent mortality may contribute to the spatial dynamics of seedling recruitment. Unlike previous studies, we demonstrate that the CCT was not caused by differences in microhabitat preferences or life history strategy among the study species. In local neighborhood analyses, the spatial autocorrelation of seedling survival was important at small spatial scales (1–5 m) but decayed rapidly with increasing distance. Relative seedling height had the greatest effect on seedling survival. Conspecific seedling density had a more negative effect on survival than heterospecific seedling density and was stronger and extended farther in rare species than in common species. Taken together, the CCT and neighborhood analyses suggest that seedling mortality is coupled more strongly to the landscape-scale abundance of conspecific large trees in common species and the local density of conspecific seedlings in rare species. We conclude that negative density dependence could promote species coexistence in this rain forest community but that the scale dependence of interactions differs between rare and common species

Palms, peccaries and perturbations: widespread effects of small-scale disturbance in tropical forests

<p>Abstract</p> <p>Background</p> <p>Disturbance is an important process structuring ecosystems worldwide and has long been thought to be a significant driver of diversity and dynamics. In forests, most studies of disturbance have focused on large-scale disturbance such as hurricanes or tree-falls. However, smaller sub-canopy disturbances could also have significant impacts on community structure. One such sub-canopy disturbance in tropical forests is abscising leaves of large arborescent palm (Arececeae) trees. These leaves can weigh up to 15 kg and cause physical damage and mortality to juvenile plants. Previous studies examining this question suffered from the use of static data at small spatial scales. Here we use data from a large permanent forest plot combined with dynamic data on the survival and growth of > 66,000 individuals over a seven-year period to address whether falling palm fronds do impact neighboring seedling and sapling communities, or whether there is an interaction between the palms and peccaries rooting for fallen palm fruit in the same area as falling leaves. We tested the wider generalisation of these hypotheses by comparing seedling and sapling survival under fruiting and non-fruiting trees in another family, the Myristicaceae.</p> <p>Results</p> <p>We found a spatially-restricted but significant effect of large arborescent fruiting palms on the spatial structure, population dynamics and species diversity of neighbouring sapling and seedling communities. However, these effects were not found around slightly smaller non-fruiting palm trees, suggesting it is seed predators such as peccaries rather than falling leaves that impact on the communities around palm trees. Conversely, this hypothesis was not supported in data from other edible species, such as those in the family Myristicaceae.</p> <p>Conclusions</p> <p>Given the abundance of arborescent palm trees in Amazonian forests, it is reasonable to conclude that their presence does have a significant, if spatially-restricted, impact on juvenile plants, most likely on the survival and growth of seedlings and saplings damaged by foraging peccaries. Given the abundance of fruit produced by each palm, the widespread effects of these small-scale disturbances appear, over long time-scales, to cause directional changes in community structure at larger scales.</p

Environment and Past Land Use Together Predict Functional Diversity in a Temperate Forest

Environment and human land use both shape forest composition. Abiotic conditions sift tree species from a regional pool via functional traits that influence species’ suitability to the local environment. In addition, human land use can modify species distributions and change functional diversity of forests. However, it is unclear how environment and land use simultaneously shape functional diversity of tree communities. Land-use legacies are especially prominent in temperate forest landscapes that have been extensively modified by humans in the last few centuries. Across a 900-ha temperate deciduous forest in the northeastern United States, comprising a mosaic of different-aged stands due to past human land use, we used four key functional traits—maximum height, rooting depth, wood density, and seed mass—to examine how multiple environmental and land-use variables influenced species distributions and functional diversity. We sampled ~40,000 trees \u3e8 cm DBH within 485 plots totaling 137 ha. Species within plots were more functionally similar than expected by chance when we estimated functional diversity using all traits together (multi-trait), and to a lesser degree, with each trait separately. Multi-trait functional diversity was most strongly correlated with distance from the perennial stream, elevation, slope, and forest age. Environmental and land-use predictors varied in their correlation with functional diversities of the four individual traits. Landscape-wide change in abundances of individual species also correlated with both environment and land-use variables, but magnitudes of trait–environment interactions were generally stronger than trait interactions with land use. These findings can be applied for restoration and assisted regeneration of human-modified temperate forests by using traits to predict which tree species would establish well in relation to land-use history, topography, and soil conditions

Seasonality of reproduction in an ever-wet lowland tropical forest in Amazonian Ecuador

We thank Pablo Alvia, Alvaro Pérez, Zornitza Aguilar, Paola Barriga, Matt Priest, Caroline Whitefoord, and Gorky Villa for assistance in collecting data or identifying species; Elina Gomez for entry of trap data; Hugo Navarrete, Katya Romoleroux and the QCA herbarium staff, and David Lasso and the ECY staff for help with logistics and needed permitting; Rick Condit, Elizabeth Losos, Robin Foster, and Henrik Balslev for initial encouragement to work within the Yasuní Forest Dynamics Plot; Hugo Romero for initially summarizing the YFDP and SSP weather data sets; Pablo Jarrin for setting up the TEAM weather station, and David Lasso and Carlos Padilla for maintaining that equipment and making the data available; and the Ecuadorian Ministerio del Ambiente for permission to work in Yasuní National Park [No 014-2019-IC-PNY-DPAO/AVS, No 012-2018-IC-PNY593-DPAO/AVS, No 008-2017-IC-PNY-DPAO/AVS, No 012-2016-IC-FAU-FLO-DPAO-PNY, No 594-014-2015-FLO-MAE-DPAO-PNY, and earlier permits]. The Forest Dynamics Plot of Yasuní National Park has been made possible through the generous support of the Pontifical Catholic University of Ecuador (PUCE) funds of donaciones del impuesto a la renta, the Government of Ecuador, the US National Science Foundation, the Andrew W. Mellon Foundation, the Smithsonian Tropical Research Institute, and the University of Aarhus of Denmark. The phenology project began while NCG was at the Natural History Museum, London, with funding (2000–2004) from the Department of Botany (NHM), the Andrew W. Mellon Foundation, British Airways, and the Natural Environment Research Council (GR9/04037). It continued with NCG at Southern Illinois University Carbondale (2005–2023). We thank the Center for Tropical Forest Science for transitional funding (2006–2008, 2017–2018) and the National Science Foundation LTREB program for long-term funding (2006–2020; DEB-0614525, DEB-1122634, DEB-1754632, DEB-1754668).Peer reviewedPublisher PD

Developing hierarchical density‐structured models to study the national‐scale dynamics of an arable weed

Population dynamics can be highly variable in the face of environmental heterogeneity, and understanding this variation is central in the study of ecology. Robust management decisions require that we understand how populations respond to management at a range of scales, and under a broad suite of conditions. Population models are potentially valuable tools in addressing this challenge. However, without adequate data, models can fail to produce useful results. Populations of arable weeds are particularly problematic in this respect, as they are widespread and their dynamics are extremely variable. Owing to the inherent cost of collecting data, most studies of plant population dynamics are derived from localized experiments under a small range of environmental conditions, limiting the extent to which variance in population dynamics can be measured. Density‐structured models provide a route to rapid, large‐scale analysis of population dynamics, and can expand the scale of ecological models that are directly tied to data. Here we extend previous density‐structured models to include environmental heterogeneity, variation in management, and to account for inter‐population variation. We develop, parameterize, and test hierarchical density‐structured models for a common agricultural weed, black‐grass (Alopecurus myosuroides). We model the dynamics of this species in response to crop management, using survey data gathered over 4 yr from 364 fields across a network of 45 UK farms. We show that hierarchical density‐structured models provide a substantial improvement over their nonhierarchical counterparts. Using these models, we demonstrate that several alternative crop rotations are effective in reducing weed densities. Rotations with high wheat prevalence exhibit the most severe infestations, and diverse rotations generally have lower weed densities. However, a key outcome is that in many cases the effect of crop rotation is small compared to the high variability arising from spatiotemporal heterogeneity. This result highlights the need to monitor and model population dynamics across large spatial and temporal scales in order to account for variation in the drivers of plant dynamics. Our framework for data collection and modeling provides a means to achieve this

Evaluating the potential of Unmanned Aerial Systems for mapping weeds at field scales: A case study with Alopecurus myosuroides

Summary: Mapping weed densities within crops has conventionally been achieved either by detailed ecological monitoring or by field walking, both of which are time-consuming and expensive. Recent advances have resulted in increased interest in using Unmanned Aerial Systems (UAS) to map fields, aiming to reduce labour costs and increase the spatial extent of coverage. However, adoption of this technology ideally requires that mapping can be undertaken automatically and without the need for extensive ground-truthing. This approach has not been validated at large scale using UAS-derived imagery in combination with extensive ground-truth data. We tested the capability of UAS for mapping a grass weed, Alopecurus myosuroides, in wheat crops. We addressed two questions: (i) can imagery accurately measure densities of weeds within fields and (ii) can aerial imagery of a field be used to estimate the densities of weeds based on statistical models developed in other locations? We recorded aerial imagery from 26 fields using a UAS. Images were generated using both RGB and R mod (R mod 670-750 nm) spectral bands. Ground-truth data on weed densities were collected simultaneously with the aerial imagery. We combined these data to produce statistical models that (i) correlated ground-truth weed densities with image intensity and (ii) forecast weed densities in other fields. We show that weed densities correlated with image intensity, particularly R mod image data. However, results were mixed in terms of out of sample prediction from field-to-field. We highlight the difficulties with transferring models and we discuss the challenges for automated weed mapping using UAS technology

Measuring the effectiveness of management interventions at regional scales by integrating ecological monitoring and modelling

Background: Because of site‐specific effects and outcomes, it is often difficult to know whether a management strategy for the control of pests has worked or not. Population dynamics of pests are typically spatially and temporally variable. Moreover, interventions at the scale of individual fields or farms are essentially unreplicated experiments; a decrease in a target population following management cannot safely be interpreted as success because, for example, it might simply be a poor year for that species. Here, we argue that if large‐scale data are available, population models can be used to measure outcomes against the prevailing mean and variance. We apply this approach to the problem of rotational management of the weed Alopecurus myosuroides. Results: We derived density‐structured population models for a set of fields that were not subject to rotational management (continuous winter wheat) and another group that were (rotated into spring barley to control A. myosuroides). We used these models to construct means and variances of the outcomes of management for given starting conditions, and to conduct transient growth analysis. We show that, overall, this management strategy is successful in reducing densities of weeds, albeit with considerable variance. However, we also show that one variant (rotation to spring barley along with variable sowing) shows little evidence for additional control. Conclusion: Our results suggest that rotational strategies can be effective in the control of this weed, but also that strategies require careful evaluation against a background of spatiotemporal variation

The factors driving evolved herbicide resistance at a national scale

Repeated use of xenobiotic chemicals has selected for the rapid evolution of resistance threatening health and food security at a global scale. Strategies for preventing the evolution of resistance include cycling and mixtures of chemicals and diversification of management. We currently lack large-scale studies that evaluate the efficacy of these different strategies for minimizing the evolution of resistance. Here we use a national scale dataset of occurrence of the weed Alopecurus myosuroides (Blackgrass) in the UK to address this. Weed densities are correlated with assays of evolved resistance, supporting the hypothesis that resistance is driving weed abundance at a national scale. Resistance was correlated with the frequency of historical herbicide applications suggesting that evolution of resistance is primarily driven by intensity of exposure to herbicides, but was unrelated directly to other cultural techniques. We find that populations resistant to one herbicide are likely to show resistance to multiple herbicide classes. Finally, we show that the economic costs of evolved resistance are considerable: loss of control through resistance can double the economic costs of weeds. This research highlights the importance of managing threats to food production and healthcare systems using an evolutionarily informed approach in a proactive not reactive manner

Community Compensatory Trend Prevails from Tropical to Temperate Forest

Community compensatory trend (CCT) is thought to facilitate persistence of rare species and thus stabilize species composition in tropical forests. However, whether CCT acts over broad geographical ranges is still in question. In this study, we tested for the presence of negative density dependence (NDD) and CCT in three forests along a tropical-temperate gradient. Inventory data were collected from forest communities located in three different latitudinal zones in China. Two widely used methods were used to test for NDD at the community level. The first method considered relationships between the relative abundance ratio and adult abundance. The second method emphasized the effect of adult abundance on abundance of established younger trees. Evidence for NDD acting on different growth forms was tested by using the first method, and the presence of CCT was tested by checking whether adult abundance of rare species affected that of established younger trees less than did abundance of common species. Both analyses indicated that NDD existed in seedling, sapling and pole stages in all three plant communities and that this effect increased with latitude. However, the extent of NDD varied among understory, midstory and canopy trees in the three communities along the gradient. Additionally, despite evidence of NDD for almost all common species, only a portion of rare species showed NDD, supporting the action of CCT in all three communities. So, we conclude that NDD and CCT prevail in the three recruitment stages of the tree communities studied; rare species achieve relative advantage through CCT and thus persist in these communities; CCT clearly facilitates newly established species and maintains tree diversity within communities across our latitudinal gradient