Landscape Model Research Articles

Метод построения кадастровых карт затопления речных долин на основе гидродинамического и геоинформационного моделирования

The method of creating cadastral maps for flood areas with special conditions of use based on geoinformation and hydrodynamic modeling is described. This approach is used primarily for settlements located in river valleys. The hardware and software complex “EcoGIS-2D-Simulation” is used to conduct simulation experiments to study the dynamics of surface waters in a specific area in the vicinity of a river system. The computational module uses the Combined Smooth Particle Hydrodynamics — Total Variation Diminishing numerical algorithm for parallel integration of shallow water equations on GPUs with CUDA technology. The module for building a digital model of hydrological landscapes is an important component. This module includes a digital elevation model and sets of parameters that determine the hydrological resistance to river flow. The boundaries of the flood areas for some settlements of the Volgograd region at different values of flood probability are constructed.

Cadastral and landscape modeling of lakes as a prerequisite for protected and recreational nature resource management

The cadastral information about the lakes of the nature reserve fund (NRF) should be based on landscape-geographic principles using modern geo-information systems.Within the research, based on the instrumental field research and the use of software packages ArcGIS Desktop and ReefMaster Software, a bathymetric map of Lake Serednie (Nobel National Natural Park, Ukraine) and other spatial models were developed. The main hydrological and morphometric parameters of the lake basin were calculated, a landscape map of the natural aquatic complex was created and its landscape metric analysis was carried out at the level of aquatic tracts and facies. The research revealed changes in the level regime and shoreline of the lake caused by the long dry periods of 2016-2021 and life activity of beavers. The created integrated cadastral landscape model of the lake with limnology parameters should serve as a basis for the recreational nature use, monitoring and geo-ecological certification of the reservoirs of the NRF.

Monitoring and simulating landscape changes: how do long-term changes in land use and long-term average climate affect regional biophysical conditions in southern Malawi?

We set out to reveal the effects of long-term changes in land use and long-term average climate on the regional biophysical environment in southern Malawi. Object-oriented supervised image classification was performed on Landsat 5 and 8 satellite images from 1990 to 2020 to identify and quantify past and present land use-land cover changes using a support vector machine classifier. Subsequently, using 2000 and 2010 land use-land cover in an artificial neural network, land use-land cover for 2020 driven by elevation, slope, precipitation and temperature, population density, poverty, distance to major roads, and distance to villages data was simulated. Between 1990 and 2020, area of land cover increased in built-up (209%), bare land (10%), and cropland (10%) and decreased in forest (30%), herbaceous (4%), shrubland (20%), and water area (20%). Overall, the findings reveal that southern Malawi is dominantly an agro-mosaic landscape shaped by the combined effects of urban and agricultural expansions and climate. The findings also suggest the need to enhance the machine learning algorithms to improve capacity for landscape modelling and, ultimately, prevention, preparedness, and response to environmental risks.

Boundary green infrastructure: a green infrastructure connecting natural and artificial spaces

As a naturally-based solution (NBS), green infrastructural network constructing can improve urban ecological resilience and support sustainable urban development. However, as the Frontier of urban expansion, the boundary of built-up areas has little research on the boundary green infrastructure (BGI) connecting natural and artificial spaces. In order to make up for the shortcomings of relevant research, we propose a method for identifying BGI and analyze its landscape pattern characteristics. We selected 15 European cities as cases to extract the boundaries of built-up areas. Moreover, we used morphological pattern analysis (MSPA) to identify the ecological source and select the best distance threshold for the landscape connectivity model to identify the BGI range. Through the gradient area method and MSPA, the BGI landscape pattern characteristics of the case cities were analyzed quantitatively. The BGI scale was affected by the area of the built-up area and the threshold of GI landscape connectivity distance. Additionally, the BGI space contained a small number of large ecological sources and many scattered and small fragmented patches. The best landscape model of BGI was the surrounding pattern, followed by the aggregation pattern, which had good landscape connectivity; however, the fragmentation of the scattered pattern was high. Lastly, the ecological core area in BGI was the main landscape type; it has a high landscape connection function for the GI network inside and outside the built-up area and promotes biological exchange inside and outside the built-up area. This study proves that BGI has an important ecological significance, can guarantee the scientific nature of the NBS method, and ensures the ecological security pattern of cities.

PESTIPOND: A descriptive model of pesticide fate in artificial ponds: I. Model development

Some artificial ponds (APs) are designed to collect part of the agricultural water fluxes and dissipate their pesticide contamination through a synergy of physicochemical processes. As part of a two-paper series, this paper describes the development of PESTIPOND, a process-based model for pesticide fate in AP. PESTIPOND comprises a hydrological model and a pesticide transfer model. A test-case simulation shows that PESTIPOND can predict the mass dynamics of different pesticides within AP compartments. Sensitivity analysis evidenced that adsorption–desorption, biotransformation, and photolysis have the most significant impact on the behavior of dissolved pesticides in APs. PESTIPOND is a promising tool for better understanding the performance of ponds and can help improve AP's efficiency in preserving water quality. A second paper addresses the application of PESTIPOND in a real-case scenario and its validation (Bahi et al., 2023a). The model can thus be integrated into landscape modeling tools (e.g., surface water assessment tools) to predict pesticide transfer at the watershed scale.

Landscape models can predict the distribution of aquatic insects across agricultural areas

Landscape models can predict the distribution of aquatic insects across agricultural areas

Modelling the potential of forest management to mitigate climate change in Eastern Canadian forests

Climate change poses a serious risk to sustainable forest management, particularly in boreal forests where natural disturbances have been projected to become more severe. In three Quebec boreal forest management units, biomass carbon storage under various climate change and management scenarios was projected over 300 years (2010–2310) with a process-based dynamic landscape model (PnET-succession for Landis-II). Several strategies varying in their use of partial cuts and clear cuts, including business as usual (BAU) (clear-cut applied on more than 95% of the managed area), were tested and compared to conservation scenarios (no-harvest). Based on simulation results at the landscape scale, the clearcut-based scenarios such as BAU could result in a decrease of biomass carbon stock by 10 tC ha−1 yr−1 compared to the natural scenario. However, this reduction in carbon stock could be offset in the long term through changes in composition, as clearcut systems promote the expansion of trembling aspen and white birch. In contrast, the use of strategies based on partial cuts on more than 75% or 50% of the managed area was closer to or better than the natural scenario and resulted in greater coniferous cover retention. These strategies seemed to be the best to maximize and stabilize biomass carbon storage and ensure wood supply under different climate change scenarios, yet they would require further access and appropriate infrastructure. Furthermore, these strategies could maintain species compositions and age structures similar to natural scenarios, and thus may consequently help achieve forest ecosystem-based management targets. This study presents promising strategies to guide sustainable forest management in Eastern Canada in the context of climate change.

Modeling Ecological Resilience of Alpine Forest under Climate Change in Western Sichuan

The ecological resilience of forests is the ability to return to a stable state after being subjected to external disturbances, and it is among the critical indicators of forest status. Climate change has significant effects on forest ecological resilience and diversity. In this research, we selected Mao County as the study region, and employed the forest landscape model LANDIS-II to simulate the effect of different climate scenarios on the ecological resilience of alpine forests in western Sichuan during the next 300 years from the forest composition and structure perspective. The findings revealed that: (1) climate change will favor an increase in forest ecological resilience values in short simulations, but future climate scenarios will negatively impact the ecological resilience of forests as the simulation progresses through the middle and long term. (2) The rate of change of forest ecological resilience in the MTDF and SCF ecotones, which have a higher proportion of Fir (Abies fabri) and Spruce (Picea asperata), was greater than that in the rest of the ecotones in the short-term simulation. In contrast, it was the opposite in the medium-term simulation. The rate of change of forest ecological resilience was more significant in the long-term simulation in all four ecotones. (3) The high values of forest ecological resilience in the short- and medium-term simulations were primarily concentrated within the MTDF and SCF ecotones among the midwestern and northern parts of the study region. When the simulation proceeded to a later stage, the ecological resilience of the forests decreased significantly throughout the study region, with high values occurring only in some areas within the western parts of the study region. The research results can grasp the influence of future climate on the ecological resilience of high mountain forests within western Sichuan and provide an essential reference for the sustainable development of local forests.

Ultrametric identities in glassy models of natural evolution

Spin-glasses constitute a well-grounded framework for evolutionary models. Of particular interest for (some of) these models is the lack of self-averaging of their order parameters (e.g. the Hamming distance between the genomes of two individuals), even in asymptotic limits, much as like what happens to the overlap between the configurations of two replica in mean-field spin-glasses. In the latter, this lack of self-averaging is related to a peculiar behavior of the overlap fluctuations, as described by the Ghirlanda–Guerra identities and by the Aizenman–Contucci polynomials, that cover a pivotal role in describing the ultrametric structure of the spin-glass landscape. As for evolutionary models, such identities may therefore be related to a taxonomic classification of individuals, yet a full investigation on their validity is missing. In this paper, we study ultrametric identities in simple cases where solely random mutations take place, while selective pressure is absent, namely in flat landscape models. In particular, we study three paradigmatic models in this setting: the one parent model (which, by construction, is ultrametric at the level of single individuals), the homogeneous population model (which is replica symmetric), and the species formation model (where a broken-replica scenario emerges at the level of species). We find analytical and numerical evidence that in the first and in the third model nor the Ghirlanda–Guerra neither the Aizenman–Contucci constraints hold, rather a new class of ultrametric identities is satisfied; in the second model all these constraints hold trivially. Very preliminary results on a real biological human genome derived by The 1000 Genome Project Consortium and on two artificial human genomes (generated by two different types neural networks) seem in better agreement with these new identities rather than the classic ones.

A coupled modelling framework for predicting tree species’ altitudinal migration velocity in montane forest

Climate change is projected to cause rapid elevational migration of mountain plants. However, it is poorly understood the direction and magnitude of elevational range shifts across species because species’ life history traits are highly individualistic. Species with limited dispersal ability, reproductive rate, and ecological generalization may hardly expand into new regions under climate change. Therefore, such species’ shifts may not keep pace with climate change. We used a new framework for coupling a forest ecosystem model (LINKAGES) and a landscape model (LANDIS PRO), that accounted for climate change, population dynamics, and species’ life history traits to predict tree species’ migrations. We quantified the velocity of tree migration under different climate scenarios. We further investigated the effects of climate change and life history traits on tree species’ elevational migration. We found climate change accelerated the upward shifts at the optimum elevation and the leading edge, and limited the downward migration capacity of tree species at optimum elevation and the rear edge. The velocities of tree species’ elevational shifts (usually < 1.5 m/year) lagged behind those of climate change (about 25 m/year) under the climate change scenario. Range shifts at the leading edge, optimum elevation, and rear edge tended to be associated with temperature, precipitation, and thermal tolerance. However, species’ drought tolerance, shade tolerance, and seed dispersal ability had little effect on the velocity of simulated range shifts. Our results suggest that wide variation in tree range shift is likely driven by individual species’ life history traits in response to interacting environmental factors. This study underscores the importance of understanding the role of species’ life history traits when predicting future tree species’ distribution.

Towards the incorporation of hydrogeochemistry into the modelling of permafrost environments: a review of recent recommendations, considerations, and literature

This study is a meta-analysis of recent global research articles on hydrogeochemical modelling of permafrost regions to determine trends and consensus on research gaps and future research directions. The hydrogeochemical response of permafrost to climate change remains challenging to estimate and forecast despite evidence of large-scale impacts on freshwater and ecological cycles. We investigate the feasibility, need, and potential for hydrogeochemical modelling of permafrost landscapes by reviewing recommendations from previous modelling, review, and primer papers, including discussing ways to advance this type of modelling science. Key permafrost hydrogeochemical processes are discussed, including heat transfer and associated freeze–thaw regimes, biogeochemical processes and rates, and surface and subsurface flow. Modelling considerations (i.e., model dimension, scale, heterogeneity, and permafrost zonation) and model parameters are subsequently examined. Finally, limitations and additional considerations for advancing permafrost hydrogeochemical modelling efforts are reviewed. The findings of this review are summarized in recommendations, tables, and two schematics incorporating key considerations for future hydrogeochemical modelling initiatives in permafrost environments.

Current management in national and state forests has important but limited impacts on sustaining oaks in temperate forests of the eastern U.S

Active management for promoting oaks (Quercus spp.) and restraining maples (Acer spp.) is mostly conducted in public forests (e.g., national forests [NF] and state forests [SF]) because of oaks' ecological and economic importance. Studies have shown that current management efforts have limited success, meanwhile, oak-dominant forests continue to shift in composition and structure to shade-tolerant, fire-sensitive mesophytic species (e.g., red maple A. rubrum). It remains to be evaluated whether current management can achieve its objectives in public forests and at regional scales. In this study, we investigated the long-term outcomes of business-as-usual (BAU) and alternative management (AltMgt) scenarios in a large, temperate hardwood forest landscape in southern Ohio, US. The BAU approach simulates contemporary management, informed by harvest records across public lands and a geospatial disturbance database (i.e., LANDFIRE) to infer private land management. Whereas the AltMgt scenario increases the pace and scale of forest management on public lands through two-stage oak shelterwood harvests, treated every ten years across 10% of the land area with private land remaining as BAU. We used a spatially explicit and dynamic forest landscape model to project species compositional and structural changes under these two scenarios. Our results demonstrate that BAU management in public forests may not successfully sustain oak but instead favors the colonization of maples. Further, management objectives to promote oaks could be achieved on public forests under the AltMgt scenario, but such alternative management had limited impacts at the regional scale when including private lands. The management of NF and SF has a crucial role in driving regional changes in oak and maple abundance, particularly when private lands continued their BAU management. Starting conditions by landownership are also important considerations for oak-maple dynamics through time, implying the need to have a range of priorities and objectives, under different time frames, when developing long-term conservation plans for oak forests at regional-scales.

Modeling flood susceptibility zones using hybrid machine learning models of an agricultural dominant landscape of India.

Flooding events are determining a significant amount of damages, in terms of economic loss and also casualties in Asia and Pacific areas. Due to complexity and ferocity of severe flooding, predicting flood-prone areas is a difficult task. Thus, creating flood susceptibility maps at local level is though challenging but an inevitable task. In order to implement a flood management plan for the Balrampur district, an agricultural dominant landscape of India, and strengthen its resilience, flood susceptibility modeling and mapping are carried out. In the present study, three hybrid machine learning (ML) models, namely, fuzzy-ANN (artificial neural network), fuzzy-RBF (radial basis function), and fuzzy-SVM (support vector machine) with 12 topographic, hydrological, and other flood influencing factors were used to determine flood-susceptible zones. To ascertain the relationship between the occurrences and flood influencing factors, correlation attribute evaluation (CAE) and multicollinearity diagnostic tests were used. The predictive power of these models was validated and compared using a variety of statistical techniques, including Wilcoxon signed-rank, t-paired tests and receiver operating characteristic (ROC) curves. Results show that fuzzy-RBF model outperformed other hybrid ML models for modeling flood susceptibility, followed by fuzzy-ANN and fuzzy-SVM. Overall, these models have shown promise in identifying flood-prone areas in the basin and other basins around the world. The outcomes of the work would benefit policymakers and government bodies to capture the flood-affected areas for necessary planning, action, and implementation.

Discovering pathways through ribozyme fitness landscapes using information theoretic quantification of epistasis.

The identification of catalytic RNAs is typically achieved through primarily experimental means. However, only a small fraction of sequence space can be analyzed even with high-throughput techniques. Methods to extrapolate from a limited data set to predict additional ribozyme sequences, particularly in a human-interpretable fashion, could be useful both for designing new functional RNAs and for generating greater understanding about a ribozyme fitness landscape. Using information theory, we express the effects of epistasis (i.e., deviations from additivity) on a ribozyme. This representation was incorporated into a simple model of the epistatic fitness landscape, which identified potentially exploitable combinations of mutations. We used this model to theoretically predict mutants of high activity for a self-aminoacylating ribozyme, identifying potentially active triple and quadruple mutants beyond the experimental data set of single and double mutants. The predictions were validated experimentally, with nine out of nine sequences being accurately predicted to have high activity. This set of sequences included mutants that form a previously unknown evolutionary "bridge" between two ribozyme families that share a common motif. Individual steps in the method could be examined, understood, and guided by a human, combining interpretability and performance in a simple model to predict ribozyme sequences by extrapolation.

Modelling the Functioning of Agricultural Landscapes in the Zhytomyr Region

Purpose: To establish and substantiate the aspects of modeling the functioning of agricultural landscapes in the Zhytomyr region; to analyse the processes of landscape modeling construction; to provide a historical and landscape interpretation of changes in the nature of the Zhytomyr region under the influence of agricultural land use. Design / Methodology / Approach: Landscape modelling, cartographic, calculation and design, analysis and evaluation of ecological and landscape land management for modelling the functioning of agricultural land use. Findings: The article examines and substantiates the process of modelling and functioning of agricultural landscapes of the Zhytomyr region. It was established that the ability of mankind to use and adapt the environment to create a comfortable life and favourable production conditions requires increased attention to regional issues of nature protection and society’s attitude to it, interaction of various types of human activity with the geographical environment. It has been proven that the most important task today is the regulation of society's relationship with nature, its rational use and protection, which is understood as the prevention of damage and adverse consequences of human intervention, as well as reasonable forecasting of possible environmental changes. As a result of the research, it was found that the agricultural landscape arises as a result of intensive agricultural production (vegetables, horticulture, livestock, poultry, etc.). The creation of such a landscape is accompanied not only by changing the territory with the removal of those objects that interfere with work, but also by the construction of embankments, ponds, irrigation canals, etc. The territorial arrangement of the agricultural landscape is important, especially for the optimization of economic activity. Its task is the rational distribution of territories of various functional purposes and uses. Originality / Value: As a result of the research, it was found that the agricultural landscape arises as a result of intensive agricultural production (vegetables, horticulture, livestock, poultry, etc.). The creation of such a landscape is accompanied not only by changing the territory with the removal of those objects that interfere with work, but also by the construction of embankments, ponds, irrigation canals, etc. The territorial arrangement of the agricultural landscape is important, especially for the optimization of economic activity. Its task is the rational distribution of territories of various functional purposes and uses. As a result, prerequisites are created for increasing the efficiency of land use, agrotechnical technologies, implementation of rational and ecologically clean farming systems, implementation of measures to increase fertility and soil protection. Intensive use of nature has led to deterioration of soil and surface water quality; accumulation of significant volumes of solid and liquid waste; air pollution from vehicles and industrial production; landscape changes and biodiversity. Practical Meaning: Modelling the functioning of agricultural landscapes in the Zhytomyr region is important for understanding the geographical patterns of the spatial organisation of nature and human activity. Further Research: The obtained results can be used in the further study of agricultural landscapes of the Zhytomyr region. Theoretical and practical material of scientific research can be used in the process of retraining and improving the qualifications of teachers of biology, ecology, geography.

A methodological framework to create an urban greenway network promoting avian connectivity: A case study of Curitiba City

Integrating landscape models into urban planning can promote the use of green infrastructure tools in cities, which are essential for meeting future sustainability requirements. The city of Curitiba, the capital of Paraná State, Brazil, provides an opportunity to research methodologies related to habitat connectivity in urban areas. Our study aims to propose a network of greenways that connect the most ecologically relevant green areas. Our methodology integrates avian movement and environmental indicators to enhance urban ecology by leveraging the spatial characteristics of the landscape. In designing the path network, we adapted the parameters to fit the minimum cumulative resistance model, which was based on studies of birds in the urban environment and their dispersion behavior. Our findings indicated that impervious surfaces were the predominant land cover class in the city landscape, while larger forest fragments were primarily situated in the south and northwestern regions. By utilizing least-cost paths, we identified twenty-six priority areas that could be connected to form an ecological network spanning the landscape. Our analysis revealed that the path network was more densely distributed in peripheral areas, where the largest habitats were located, primarily within the city's green belt. Regarding land cover classes along the paths, we found that 39% consisted of forest, 25% of impervious surface, 19% of grass, 16% of bare soil, and 1% of water. Despite being highly urbanized, Curitiba possesses significant potential for restoring avian-related functional connectivity through the urban forest. To aid in the recovery and conservation of ecological corridors along the greenways, we developed a set of guidelines. The information gathered from this study may prove useful for future interventions in the city, and the proposed methodology could serve as a model for greenway planning in other urban areas.

TRADE-OFFS IN TREE SPECIES SELECTION AND CARBON OFFSET ON FARMS ADJACENT TO KAKAMEGA-NANDI FOREST ECOSYSTEM IN KENYA

&lt;p&gt;&lt;strong&gt;Background:&lt;/strong&gt; Growing of trees on-farms has contributed significantly in easing pressure on the Kakamega–Nandi Forest Ecosystem. There are however concerns that &lt;em&gt;Eucalyptus&lt;/em&gt; species is becoming the dominant tree in this landscape and may have adverse effects on the environment. &lt;strong&gt;Objectives&lt;/strong&gt;: To determine the trade-offs in tree species selection and carbon offsets on farms in the margins of the Kakamega - Nandi Forest Ecosystem. &lt;strong&gt;Methodology:&lt;/strong&gt; It employed a nested experimental design where the study area was divided into three 3x1 km sentinel blocks. Three different landscape models were chosen: &lt;em&gt;Eucalyptus&lt;/em&gt; dominated tree stand, mixed tree stands and pure native tree stands. A sample plot comprised a main plot of 20m by 10m plot for measuring trees with a diameter at breast height (DBH) ≥ 10 cm, a sub-plot of 10m by 5m nested within the main plot for measuring saplings and shrubs of DBH less than 10cm. Data was collected on tree species type, stem DBH for trees, tree height, counts of trees, saplings and shrubs. The data was subjected to both exploratory and inferential statistical analysis using R Gui Version 4.2.1. Woody species diversity and carbon stocks were subjected to analysis of variance (ANOVA) at 5% significance level. &lt;strong&gt;Results:&lt;/strong&gt; Native dominated tree stands had the highest biomass carbon (0.50-512.84 MgC ha&lt;sup&gt;-1&lt;/sup&gt;) followed by mixed tree stands (0.10-110.82 MgC ha&lt;sup&gt;-1&lt;/sup&gt;). &lt;em&gt;Eucalyptus&lt;/em&gt; dominated was the least (0.10- 68.58 MgC ha&lt;sup&gt;-1&lt;/sup&gt;) The above ground biomass in the &lt;em&gt;Eucalyptus&lt;/em&gt; dominated tree stands and mixed trees stands was significantly lower than in the adjacent native trees stands (p=0.001). The mean carbon estimated in the treatments was 2.62 MgC ha&lt;sup&gt;-1&lt;/sup&gt; in the &lt;em&gt;Eucalyptus &lt;/em&gt;trees dominated stands, 3.09 MgC ha&lt;sup&gt;-1&lt;/sup&gt; in mixed trees species stands and 19.05 MgC ha&lt;sup&gt;-1&lt;/sup&gt; in native tree species stand. &lt;strong&gt;Implications:&lt;/strong&gt; Increase in the concentration of &lt;em&gt;Eucalyptus&lt;/em&gt; trees led to a reduction in tree diversity. Trees in the &lt;em&gt;Eucalyptus &lt;/em&gt;dominated tree stand and mixed trees stand had significantly lower stem diameters, basal area and tree biomass than in the adjacent indigenous trees stand. The fast rate of growth of &lt;em&gt;Eucalyptus &lt;/em&gt;trees may have ensured that the trees grow fast at the expense of other woody species due to water and nutrient competition. &lt;strong&gt;Conclusion:&lt;/strong&gt; The study revealed a general trend of increasing biomass carbon with increasing tree size in all the treatments. The majority of large trees were found in native tree stand indicating that they store majority of biomass carbon stocks. Across the treatment, carbon sequestration in the trees was directly related to above ground biomass production.&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;

Dynamic behaviours of black hole phase transitions near quadruple points

Treating the horizon radius as an order parameter in a thermal fluctuation, the free energy landscape model sheds light on the dynamic behaviour of black hole phase transitions. Here we carry out the first investigation of the dynamics of the recently discovered multicriticality in black holes. We specifically consider black hole quadruple points in D = 4 Einstein gravity coupled to non-linear electrodynamics. We observe thermodynamic phase transitions between the four stable phases at a quadruple point as well as weak and strong oscillatory phenomena by numerically solving the Smoluchowski equation describing the evolution of the probability distribution function. We analyze the dynamic evolution of the different phases at various ensemble temperatures and find that the probability distribution of a final stationary state is closely tied to the structure of its off-shell Gibbs free energy.

A trait-based approach to both forestry and timber building can synchronize forest harvest and resilience.

Along with forest managers, builders are key change agents of forest ecosystems' structure and composition through the specification and use of wood products. New forest management approaches are being advocated to increase the resilience and adaptability of forests to climate change and other natural disturbances. Such approaches call for a diversification of our forests based on species' functional traits that will dramatically change the harvested species composition, volume, and output of our forested landscapes. This calls for the wood-building industry to adapt its ways of operating. Accordingly, we expand the evaluation of the ecological resilience of forest ecosystems based on functional diversification to include a trait-based approach to building with wood. This trait-based plant-building framework can illustrate how forecasted forest changes in the coming decades may impact and guide decisions about wood-building practices, policies, and specifications. We apply this approach using a fragmented rural landscape in temperate southeastern Canada. We link seven functional groups based on the ecological traits of tree species in the region to a similar functional grouping of building traits to characterize the push and pull of managing forests and wood buildings together. We relied on a process-based forest landscape model to simulate long-term forest dynamics and timber harvesting to evaluate how various novel management approaches will interact with the changing global environment to affect the forest-building relationships. Our results suggest that adopting a whole system, plant-building approach to forests and wood buildings, is key to enhancing forest ecological and timber construction industry resilience.

Cycles‐L: A Coupled, 3‐D, Land Surface, Hydrologic, and Agroecosystem Landscape Model

AbstractManaging landscapes to increase agricultural productivity and environmental stewardship can be informed by spatially‐distributed models that operate at spatial and temporal scales that are intervention‐relevant. This paper presents Cycles‐L, a landscape‐scale agroecosystem and hydrologic modeling system, using as a test case a watershed in Pennsylvania. Cycles‐L emerges from melding the landscape and hydrology structure of Flux‐PIHM, a 3‐D land surface hydrologic model, with the agroecosystem processes in the Cycles model. Consequently, Cycles‐L can simulate processes affected by topography, soil heterogeneity, and management practices, owing to its physically‐based hydrology that can simulate horizontal and vertical transport of solutes with water. The model was tested at a 730‐ha experimental watershed within the Mahantango Creek watershed. Cycles‐L simulated well stream water and mineral nitrogen discharge (Nash‐Sutcliffe coefficient 0.55 and 0.60, respectively) and grain yield (root mean square error 1.2 Mg ha−1). Cycles‐L outputs are as good or better than those obtained with the uncoupled Flux‐PIHM (water discharge) and Cycles (grain yield) models. Modeled spatial patterns of nitrogen fluxes like denitrification illustrate the combined control of crop management and topography. For example, denitrification is almost twice as high when simulated with Cycles‐L than when simulated with Cycles 1‐D. Due to its spatial and temporal resolution, Cycles‐L fills a gap in the availability of models that operate at a scale relevant to evaluate interventions in the landscape. Cycles‐L can become a central component in tools for climate change scenario analysis, precision agriculture, precision conservation, and artificial intelligence‐based decision support systems.