A simple and cost-effective method for cable root detection and extension measurement in estuary wetland forests

This work presents the development of a low-cost method to measure the length cable roots of black mangrove (Avicennia germinans) trees to define the boundaries of central part of the anchoring root system (CPRS) without the need to fully expose root systems. The method was tested to locate and measure the length shallow woody root systems. An ultrasonic Doppler fetal monitor (UD) and a stock of steel rods (SR) were used to probe root locations without removing sediments from the surface, measure their length and estimate root-soil plate dimensions. The method was validated by comparing measurements with root lengths taken through direct measurement of excavated cable roots and from root-soil plate radii (exposed root-soil material when a tree tips over) of five up-rooted trees with stem diameters (D130) ranging between 10 and 50 cm. The mean CPRS radius estimated with the use of the Doppler was directly correlated with tree stem diameter and was not significantly different from the root-soil plate mean radius measured from up-rooted trees or from CPRS approximated by digging trenches. Our method proved to be effective and reliable in following cable roots for large amounts of trees of both black and white mangrove trees. In a period of 40 days of work, three people were capable of measuring 648 roots belonging to 81 trees, out of which 37% were found grafted to other tree roots. This simple method can be helpful in following shallow root systems with minimal impact and help map root connection networks of grafted trees

Resilience trinity: safeguarding ecosystem functioning and services across three different time horizons and decision contexts

Ensuring ecosystem resilience is an intuitive approach to safeguard the functioning of ecosystems and hence the future provisioning of ecosystem services (ES). However, resilience is a multi‐faceted concept that is difficult to operationalize. Focusing on resilience mechanisms, such as diversity, network architectures or adaptive capacity, has recently been suggested as means to operationalize resilience. Still, the focus on mechanisms is not specific enough. We suggest a conceptual framework, resilience trinity, to facilitate management based on resilience mechanisms in three distinctive decision contexts and time‐horizons: 1) reactive, when there is an imminent threat to ES resilience and a high pressure to act, 2) adjustive, when the threat is known in general but there is still time to adapt management and 3) provident, when time horizons are very long and the nature of the threats is uncertain, leading to a low willingness to act. Resilience has different interpretations and implications at these different time horizons, which also prevail in different disciplines. Social ecology, ecology and engineering are often implicitly focussing on provident, adjustive or reactive resilience, respectively, but these different notions of resilience and their corresponding social, ecological and economic tradeoffs need to be reconciled. Otherwise, we keep risking unintended consequences of reactive actions, or shying away from provident action because of uncertainties that cannot be reduced. The suggested trinity of time horizons and their decision contexts could help ensuring that longer‐term management actions are not missed while urgent threats to ES are given priority

Making predictions in a changing world: The benefits of individual-based ecology

Ecologists urgently need a better ability to predict how environmental change affects biodiversity. We examine individual-based ecology (IBE), a research paradigm that promises better a predictive ability by using individual-based models (IBMs) to represent ecological dynamics as arising from how individuals interact with their environment and with each other. A key advantage of IBMs is that the basis for predictions-fitness maximization by individual organisms-is more general and reliable than the empirical relationships that other models depend on. Case studies illustrate the usefulness and predictive success of long-term IBE programs. The pioneering programs had three phases: conceptualization, implementation, and diversification. Continued validation of models runs throughout these phases. The breakthroughs that make IBE more productive include standards for describing and validating IBMs, improved and standardized theory for individual traits and behavior, software tools, and generalized instead of system-specific IBMs. We provide guidelines for pursuing IBE and a vision for future IBE research

Extended biomass allometric equations for large mangrove trees from terrestrial LiDAR data

International audienceAccurately determining biomass of large trees is crucial for reliable biomass analyses in most tropical forests, but most allometric models calibration are deficient in large trees data. This issue is a major concern for high-biomass mangrove forests, especially when their role in the ecosystem carbon storage is considered. As an alternative to the fastidious cutting and weighing measurement approach, we explored a non-destructive terrestrial laser scanning approach to estimate the aboveground biomass of large mangroves (diameters reaching up to 125 cm). Because of buttresses in large trees, we propose a pixel-based analysis of the composite 2D flattened images, obtained from the successive thin segments of stem point-cloud data to estimate wood volume. Branches were considered as successive best-fitted primitive of conical frustums. The product of wood volume and height-decreasing wood density yielded biomass estimates. This approach was tested on 36 A. germinans trees in French Guiana, considering available biomass models from the same region as references. Our biomass estimates reached ca. 90% accuracy and a correlation of 0.99 with reference biomass values. Based on the results, new tree biomass model, which had R² of 0.99 and RSE of 87.6 kg of dry matter. This terrestrial LiDAR-based approach allows the estimates of large tree biomass to be tractable, and opens new opportunities to improve biomass estimates of tall mangroves. The method could also be tested and applied to other tree species

Nonparametric upscaling of bark beetle infestations and management from plot to landscape level by combining individual-based with Markov chain models

Linked to climate change, drivers such as increased temperatures and decreased water availability affect forest health in complex ways by simultaneously weakening tree vitality and promoting insect pest activity. One major beneficiary of climate-induced changes is the European spruce bark beetle (Ips typographus). To improve the mechanistic understanding of climate change impacts on long-term beetle infestation risks, individual-based simulation models (IBM) such as the bark beetle dispersion model IPS-SPREADS have been proven as effective tools. However, the computational costs of IBMs limit their spatial scale of application. While these tools are best suitable to simulate bark beetle dynamics on the plot level, upscaling the process to larger areas is challenging. The larger spatial scale is, nevertheless, often required to support the selection of adequate management intervention. Here, we introduce a novel two-step approach to address this challenge: (1) we use the IPS-SPREADS model to simulate the bark beetle dispersal at a local scale by dividing the research area into 250 × 250 m grid cells; and (2) we then apply a metamodel framework to upscale the results to the landscape level. The metamodel is based on Markov chains derived from the infestation probabilities of IPS-SPREADS results and extended by considering neighbor interaction and spruce dieback of each focal cell. We validated the metamodel by comparing its predictions with infestations observed in 2017 and 2018 in the Saxon Switzerland national park, Germany, and tested sanitation felling as a measure to prevent potential further outbreaks in the region. Validation showed an improvement in predictions by introducing the model extension of beetle spreading from one cell to another. The metamodel forecasts indicated an increase in the risk of infestation for adjacent forest areas. In case of a beetle mass outbreak, sanitation felling intensities of 80 percent and above seem to mitigate further outbreak progression

Driving forces of Antarctic krill abundance

Antarctic krill, crucial to the Southern Ocean ecosystem and a vital fisheries resource, is endangered by climate change. Identifying drivers of krill biomass is therefore essential for determining catch limits and designating protection zones. We present a modeling approach to pinpointing effects of sea surface temperature, ice cover, chlorophyll levels, climate indices, and intraspecific competition. Our study reveals that larval recruitment is driven by both competition among age classes and chlorophyll levels. In addition, while milder ice and temperature in spring and summer favor reproduction and early larval survival, both larvae and juveniles strongly benefit from heavier ice and colder temperatures in winter. We conclude that omitting top-down control of resources by krill is only acceptable for retrospective or single-year prognostic models that use field chlorophyll data but that incorporating intraspecific competition is essential for longer-term forecasts. Our findings can guide future krill modeling strategies, reinforcing the sustainability of this keystone species

pyMANGA: A modular, open and extendable software platform for modeling of forest and vegetation dynamics

Agent-based vegetation models are a widely used tool in ecology, for example, to understand and predict the response of vegetation to environmental change. Models are based on well-established descriptions of processes such as vegetation establishment, growth and mortality. However, they are often developed from scratch, which can be inefficient. Here we present pyMANGA, a free and open-source platform for plant growth modelers. pyMANGA's modular design allows for the combination of different concepts and theories of how plants establish, grow or compete in response to above- and below-ground resource availability. New or alternative modules describing, e.g., competition or facilitation, can be easily added. The interchangeability of modules supports the systematic testing of different hypotheses, e.g., on dominant processes in soil-plant feedback loops. Here we further present the thorough benchmarking strategy to maintain the platform and how pyMANGA can be used to compare models with different levels of abstraction and complexity

Small‐scale heterogeneity shapes grassland diversity in low‐to‐intermediate resource environments

Questions Soil resource heterogeneity influences the outcome of plant–plant interactions and, consequently, species co-existence and diversity patterns. The magnitude and direction of heterogeneity effects vary widely, and the processes underlying such variations are not fully understood. In this study, we explored how and under what resource conditions small-scale heterogeneity modulates grassland plant diversity. Location Oderhänge Mallnow, Potsdam, Brandenburg, Germany. Methods We expanded the individual-based plant community model (IBC-grass) to incorporate dynamic below-ground resource maps, simulating spatial heterogeneity of resource availability. Empirical centimeter-scale data of soil C/N ratio were integrated into the model, accounting for both configurational and compositional heterogeneity. We then analyzed the interplay between small-scale heterogeneity and resource availability on the interaction and co-existence of plant species and overall diversity. Results Our results showed significant differences between the low- and high-resource scenarios, with both configurational and compositional heterogeneity having a positive effect on species richness and Simpson's diversity, but only under low-resource conditions. As compositional heterogeneity in the fine-scale C/N ratio increased, we observed a positive shift in Simpson's diversity and species richness, with the highest effects at the highest level of variability tested. We observed little to no effect in nutrient-rich scenarios, and a shift to negative effects at the intermediate resource level. The study demonstrates that site-specific resource levels underpin how fine-scale heterogeneity influences plant diversity and species co-existence, and partly explains the divergent effects recorded in different empirical studies. Conclusions This study provides mechanistic insights into the complex relationship between resource heterogeneity and diversity patterns. It highlights the context-dependent effects of small-scale heterogeneity, which can be positive under low-resource, neutral under high-resource, and negative under intermediate-resource conditions. These findings provide a foundation for future investigations into small-scale heterogeneity–diversity relationships, contributing to a deeper understanding of the processes that promote species co-existence in plant communities

Individual-based modeling to discover the ecological importance of tree networks

Background/Question/Methods Two of the oldest living trees known on earth, the Pando and the Old Tjikko, are clonal plants. Their longevity has been attributed to the mutual benefit of resource sharing and the accumulation of beneficial somatic mutations. Similar effects are known for mycorrhizal networks and trees connected by grafted roots. Could it be that networking is generally advantageous increasing forest integrity under resource limitation or harsh conditions? This would revolutionize our understanding of forest dynamics, which so far is believed to be driven by the inference of competition and facilitation among single trees, and not among single trees and tree networks. Natural root grafting could play a pivotal role in forest resilience, since grafting can be a facilitative interaction potentially increasing individual fitness. To find this out, it is necessary to systematically investigate under which conditions the sharing of resources (e.g. water under drought stress) is beneficial for a group of trees compared to individual trees. Logistical problems hinder such investigations. Individual-based models, however, allow to synthesize the few existing empirical results and to develop new concepts on the functioning of tree networks, the fitness of groups and its impact on forest dynamics. Results/Conclusions We provide an individual-based model serving as a virtual laboratory to investigate the formation of networks in plant populations depending on spatio-temporal patterns of resource availability. As an example, we designed simulation experiments mimicking black mangroves exposed to water stress, and compared the results with field data from Mexico. As expected, root grafting depends on trees constellation, tree density and water scarcity. The probability of root grafting is a sigmoid function increasing with trees size, but its shape is influenced by the dynamics of water limitation. Under more stressful conditions, the reflection point of the function is earlier (smaller trees graft) and steeper (the maximum number of grafted trees is earlier achieved). Impressively, the tree networks are small with 4 - 5 connected trees in average and have a predominant linear structure. The latter is in agreement with evolutionary game theory, which predicts that cooperation flourishes most if organisms are strongly pairwise tied since the costs (for grafting) are quickly pay-offed by reciprocated benefits (share of water, nutrients etc.). Our findings thus challenge the recent hypothesis that root networking is an evolutionary beneficial, adaptive behavior, which improves resource acquisition of trees favoring its survival under stressful environmental conditions

Understanding smallholder farmer decision making in forest land restoration using agent-based modeling

Success of forest restoration at farm level depends on the farmer ́s decision-making and the constraints to farmers’ actions. There is a gap between the intentions and the actual behavior towards restoration in Sub- Saharan Africa and the Global South. To understand this discrepancy, our study uses empirical household survey data to design and parameterize an agent-based model. WEEM (Woodlot Establishment and Expansion Model) has been designed based on household socio-demographics and projects the temporal dynamics of woodlot numbers in Uganda. The study contributes to a mechanistic understanding of what determines the current gap between farmer’s intention and actual behavior. Results reveal that an increase in knowledge of the current forest policies laws and regulations (PLRs) from 18% to 50% and to 100% reduces the average number of woodlots by 18% and 79% respectively. Lack of labor reduces the number of woodlots by 80%. Increased labor requirement from 4 to 8 and to 12 man-days, reduces the number of woodlots by 26% and 61% respectively. WEEM indicates that absence of household labor and de facto misconception of PLRs “perceived tenure insecurity” constrains the actual behavior of farmers. We recommend forest PLRs to provide full rights of use and ownership of trees established on private farmland. Tree fund in the case of Uganda should be operationalized to address the transaction costs and to achieve the long-term targets of forest land restoration