Conservation planning with spatially explicit models: a case for horseshoe bats in complex mountain landscapes

Context

Context Bats are considered as an ecological indicator of habitat quality due to their sensitivity to human-induced ecosystem changes. Hence, we will focus the study on two indicator species of bats as a proxy to evaluate structure and composition of the landscape to analyze anthropic pressures driving changes in patterns.

Objectives

This study develops a spatially-explicit model to highlight key habitat nodes and corridors which are integral for maintaining functional landscape connectivity for bat movement. We focus on a complex mountain landscape and two bat species: greater (Rhinolophus ferrumequinum) and lesser (Rhinolophus hipposideros) horseshoe bats which are known to be sensitive to landscape composition and configuration.

Methods

Species distribution models are used to delineate high-quality foraging habitat for each species using opportunistic ultrasonic bat data. We then performed connectivity analysis combining (modelled) suitable foraging habitat and (known) roost sites. We use graph-theory and the deviation in the probability of connectivity to quantify resilience of the landscape connectivity to perturbations.

Results

Both species were confined to lowlands (<1000 m elevation) and avoided areas with high road densities. Greater horseshoe bats were more generalist than lesser horseshoe bats which tended to be associated with broadleaved and mixed forests.

Conclusions

The spatially-explicit models obtained were proven crucial for prioritizing foraging habitats, roost sites and key corridors for conservation. Hence, our results are being used by key stakeholders to help integrate conservation measures into forest management and conservation planning at the regional level. The approach used can be integrated into conservation initiatives elsewhere.

     

Using multiple metrics to estimate seasonal landscape connectivity for Blanding’s turtles (<Emphasis Type="Italic">Emydoidea blandingii</Emphasis>) in a fragmented landscape

Context

Landscapes and animal behavior can exhibit temporal variability and connectivity estimates should consider this phenomenon. In many species, timing of activities such as nesting, mate searching, and hibernation occurs during distinct periods in which movement events may differ, along with physical characteristics of the surrounding landscape.

Objectives

We estimate movement, landscape conductance, and patch importance for a turtle species across two seasonal activity periods (spring, late summer) in a fragmented agricultural region. Three connectivity approaches are compared to identify their advantages and disadvantages.

Methods

A least-cost distance model, circuit-based approach, and patch-based index were used to collectively describe the potential functional connectivity of Blanding’s turtle (Emydoidea blandingii) across a multi-temporal scale in an agricultural region of south western Ontario.

Results

Connectivity decreased further into the active season exhibited through lower conductance of the landscape and fewer pathways, while the importance of habitat nodes shifted due to temporal variability in the number and distribution of nodes. Models provided different yet complimentary information, with least-cost models overestimating discrete pathways yet providing a secondary measure of landscape barriers. The circuit-based model estimated corridors of least resistance providing an overall characterization of the landscape, while patch-based indices provided key information on the importance of individual habitat patches.

Conclusion

Findings highlight the importance of including a temporal aspect in connectivity modelling as results demonstrate a change in functional connectivity over time. We also recommend employing multiple connectivity metrics to capture variation in movement behavior.

     

Synthetic Aperture Radar (SAR) images improve habitat suitability models

Context

The ability to detect ecological networks in landscapes is of utmost importance for managing biodiversity and planning corridors.

Objectives

The objective of this study was to evaluate the information provided by a synthetic aperture radar (SAR) image for landscape connectivity modeling compared to aerial photographs (APs).

Methods

We present a novel method that integrates habitat suitability derived from remote sensing imagery into a connectivity model to explain species abundance. More precisely, we compared how two resistance maps constructed using landscape and/or local metrics derived from AP or SAR imagery yield different connectivity values (based on graph theory), considering hedgerow networks and forest carabid beetle species as a model.

Results

We found that resistance maps using landscape and local metrics derived from SAR imagery improve landscape connectivity measures. The SAR model is the most informative, explaining 58% of the variance in forest carabid beetle abundance. This model calculates resistance values associated with homogeneous patches within hedgerows according to their suitability (canopy cover density and landscape grain) for the model species.

Conclusions

Our approach combines two important methods in landscape ecology: the construction of resistance maps and the use of buffers around sampling points to determine the importance of landscape factors. This study was carried out through an interdisciplinary approach involving remote sensing scientists and landscape ecologists. This study is a step forward in developing landscape metrics from satellites to monitor biodiversity.

     

Integrating a generic focal species,metapopulation capacity,and connectivity to identify opportunities to link fragmented habitat

Context

A challenge devising revegetation strategies in fragmented landscapes is conserving for the widest spectrum of biodiversity. Habitat network reconstruction should improve landscape capacity to maintain species populations. However, the location of revegetation often fails to account for species occurrence and dispersal processes operating across spatial scales.

Objectives

Our objective was to integrate metapopulation theory with estimates of landscape capacity and dispersal pathways to highlight connectivity gaps. Maintenance of populations could thereby be facilitated through reconnecting habitat networks across regional and broader scales, with assumed benefit for the dispersal needs of less sensitive species.

Methods

Predicted occupancy and metapopulation capacity were calculated for a generic focal species derived from fragmentation-sensitive woodland birds, mammals and reptiles. A metapopulation connectivity analysis predicted regional dispersal links to identify likely routes through which individuals may move to contribute to the viability of the population. We used the revegetation programmes of the Brigalow–Nandewar Biolinks project, eastern New South Wales, Australia, to demonstrate our approach.

Results

Landscape capacity of the current landscape varied across the region. Low-value links between populations provided greatest opportunities for revegetation and improved landscape capacity. Where regional connectivity did not indicate a pathway between populations, broader scale connectivity provided guidance for revegetation.

Conclusions

The metapopulation-based model, coupled with a habitat dispersal network analysis, provided a platform to inform revegetation locations and better support biodiversity. Our approach has application for directing on-ground action to support viable populations, assess the impact of revegetation schemes or monitor the progress of staged implementations.

     

A multi-species approach for assessing the impact of land-cover changes on landscape connectivity

Context

Land-cover changes (LCCs) could impact wildlife populations through gains or losses of natural habitats and changes in the landscape mosaic. To assess such impacts, we need to focus on landscape connectivity from a diachronic perspective.

Objectives

We propose a method for assessing the impact of LCCs on landscape connectivity through a multi-species approach based on graph theory. To do this, we combine two approaches devised to spatialize the variation of multi-species connectivity and to quantify the importance of types of LCCs for single-species connectivity by highlighting the possible contradictory effects.

Methods

We begin with a list of landscape species and create virtual species with similar ecological requirements. We model the ecological network of these virtual species at two dates and compute the variation of a local and global connectivity metric to assess the impacts of the LCCs on their dispersal capacities.

Results

The spatial variation of multi-species connectivity showed that local impacts range from ?6.4% to +3.2%. The assessment of the impacts of types of LCCs showed a variation in global connectivity ranging from ?45.1% for open-area reptiles to +170.2% for natural open-area birds with low-dispersion capacities.

Conclusions

This generic approach can be reproduced in a large variety of spatial contexts by adapting the selection of the initial species. The proposed method could inform and guide conservation actions and landscape management strategies so as to enhance or maintain connectivity for species at a landscape scale.

     

Assessing wild bees in perennial bioenergy landscapes: effects of bioenergy crop composition,landscape configuration,and bioenergy crop area

Context

Wild bee populations are currently under threat, which has led to recent efforts to increase pollinator habitat in North America. Simultaneously, U.S. federal energy policies are beginning to encourage perennial bioenergy cropping (PBC) systems, which have the potential to support native bees.

Objectives

Our objective was to explore the potentially interactive effects of crop composition, total PBC area, and PBC patches in different landscape configurations.

Methods

Using a spatially-explicit modeling approach, the Lonsdorf model, we simulated the impacts of three perennial bioenergy crops (PBC: willow, switchgrass, and prairie), three scenarios with different total PBC area (11.7, 23.5 and 28.8% of agricultural land converted to PBC) and two types of landscape configurations (PBC in clustered landscape patterns that represent realistic future configurations or in dispersed neutral landscape models) on a nest abundance index in an Illinois landscape.

Results

Our modeling results suggest that crop composition and PBC area are particularly important for bee nest abundance, whereas landscape configuration is associated with bee nest abundance at the local scale but less so at the regional scale.

Conclusions

Strategies to enhance wild bee habitat should therefore emphasize the crop composition and amount of PBC.

     

Spatial dynamics of coastal forest bird assemblages: the influence of landscape context,forest type,and structural connectivity

Context

Complex structural connectivity patterns can influence the distribution of animals in coastal landscapes, particularly those with relatively large home ranges, such as birds. To understand the nuanced nature of coastal forest avifauna, where there may be considerable overlap in assemblages of adjacent forest types, the concerted influence of regional landscape context and vegetative structural connectivity at multiple spatial scales warrants investigation.

Objectives

This study determined whether species compositions of coastal forest bird assemblages differ with regional landscape context or with forest type, and if this is influenced by structural connectivity patterns measured at multiple spatial scales.

Methods

Three replicate bird surveys were conducted in four coastal forest types at ten survey locations across two regional landscape contexts in northeast Australia. Structural connectivity patterns of 11 vegetation types were quantified at 3, 6, and 12 km spatial scales surrounding each survey location, and differences in bird species composition were evaluated using multivariate ordination analysis.

Results

Bird assemblages differed between regional landscape contexts and most coastal forest types, although Melaleuca woodland bird assemblages were similar to those of eucalypt woodlands and rainforests. Structural connectivity was primarily correlated with differences in bird species composition between regional landscape contexts, and correlation depended on vegetation type and spatial scale.

Conclusions

Spatial scale, landscape context, and structural connectivity have a combined influence on bird species composition. This suggests that effective management of coastal landscapes requires a holistic strategy that considers the size, shape, and configuration of all vegetative components at multiple spatial scales.

     

Characterising landscape connectivity for conservation planning using a dispersal guild approach

Context

Land use changes have modified the extent and structure of native vegetation, resulting in fragmentation of native species habitat. Connectivity is increasingly seen as a requirement for effective conservation in these landscapes, but the question remains: ‘connectivity for which species?’.

Objective

The aim of this study was to develop and then apply a rapid, expert-based, dispersal guild approach where species are grouped on similar fine-scale dispersal behaviour (such as between scattered trees) and habitat characteristics.

Methods

Dispersal guilds were identified using clustering techniques to compare dispersal and habitat parameters elicited from experts. We modelled least-cost paths and corridors between patches and individual movement probabilities within these corridors for each of the dispersal guilds using Circuitscape. We demonstrate our approach with a case study in the Tasmanian Northern Midlands, Australia.

Results

The dispersal guild approach grouped the 12 species into five dispersal guilds. The connectivity modelling of those five guilds found that broadly dispersing species in this landscape, such as medium-sized carnivorous mammals, were unaffected by fragmentation while from the perspective of the three dispersal guilds made up of smaller mammals, the landscape appeared highly fragmented.

Conclusions

Our approach yields biologically defensible outputs that are broadly applicable, particularly for conservation planning where data and resources are limited. It is a useful first step in multi-species conservation planning which aims to identify those species most in need of conservation efforts.

     

Using animal movement behavior to categorize land cover and predict consequences for connectivity and patch residence times

Context

Landscape-scale population dynamics are driven in part by movement within and dispersal among habitat patches. Predicting these processes requires information about how movement behavior varies among land cover types.

Objectives

We investigated how butterfly movement in a heterogeneous landscape varies within and between habitat and matrix land cover types, and the implications of these differences for within-patch residence times and among-patch connectivity.

Methods

We empirically measured movement behavior in the Baltimore checkerspot butterfly (Euphydryas phaeton) in three land cover classes that broadly constitute habitat and two classes that constitute matrix. We also measured habitat preference at boundaries. We predicted patch residence times and interpatch dispersal using movement parameters estimated separately for each habitat and matrix land cover subclass (5 categories), or for combined habitat and combined matrix land cover classes (2 categories). We evaluated the effects of including edge behavior on all metrics.

Results

Overall, movement was slower within habitat land cover types, and faster in matrix cover types. Butterflies at forest edges were biased to remain in open areas, and connectivity and patch residence times were most affected by behavior at structural edges. Differences in movement between matrix subclasses had a greater effect on predictions about connectivity than differences between habitat subclasses. Differences in movement among habitat subclasses had a greater effect on residence times.

Conclusions

Our findings highlight the importance of careful classification of movement and land cover in heterogeneous landscapes, and reveal how subtle differences in behavioral responses to land cover can affect landscape-scale outcomes.

     

The relative importance of local versus landscape variables on site occupancy in bats of the Brazilian Cerrado

Context

Species site-occupancy patterns may be influenced by habitat variables at both local and landscape scales. Although local habitat variables influence whether the site is suitable for a given species, the broader landscape context can also influence site occupancy, particularly for species that are sensitive to land-use change.

Objectives

To examine the relative importance of local versus landscape variables in explaining site occupancy of eight bat species within the Brazilian Cerrado, a Neotropical savanna that is experiencing widespread habitat loss and fragmentation.

Methods

Bats were surveyed within 16 forest patches over two years. We used a multi-model information-theoretic approach, adjusted for species detection bias, to assess whether landscape variables (percent cover and number of patches of natural vegetation within a 2- and 8-km radius of each forest site) or local site variables (canopy cover, understory height, number of trees, and number of lianas) best explained site occupancy in each species.

Results

Landscape variables were among the best models (ΔAIC_c or ΔQAIC_c < 2) for four species (top-ranked model for black myotis), whereas local variables were among the best for five species (top-ranked model for vampire bats). Neither local nor landscape variables explained site occupancy in two frugivorous species.

Conclusion

Species associated with a particular habitat type will not respond similarly to the amount, distribution or relative suitability of that habitat, or even at the same scale. This reinforces the challenge of species distribution modelling, especially in the context of forecasting species’ responses to future land-use or climate-change scenarios.

     

Habitat alteration and habitat fragmentation differentially affect beta diversity of stream fish communities

Context

The cumulative impact of broad scale environmental change includes altered land-cover and fragmentation. Both altered land-cover and fragmentation have a negative effect on species diversity, but the scale they act on may differ because land-cover alters environmental characteristics, whereas fragmentation alters movement among sites.

Objectives

We evaluated the scale specific effects of land-cover, fragmentation, and habitat size on alpha and beta diversity (total, turnover, and nestedness).

Methods

Stream fish communities were sampled across five urbanizing watersheds. Generalized mixed linear models were used to test how diversity (alpha and beta) is affected by land-cover, connectivity, and habitat size. Indices of land-cover were calculated from correspondence analyses on land-cover data, fragmentation was estimated with the dendritic connectivity index, and habitat size was calculated as the length of the stream segment (alpha diversity) or the length of the stream network (beta diversity).

Results

Alpha diversity was most strongly related to land-cover variables associated with urban development and agriculture (negative relationship with urbanization). Whereas, beta diversity was most strongly influenced by habitat size (positive relationship) and fragmentation (positive relationship). Turnover was positively correlated with fragmentation and habitat size, whereas species loss was negatively correlated with habitat size.

Conclusions

Land-cover has a larger effect on alpha diversity because it alters the environmental conditions at a site, whereas fragmentation has a larger effect on beta diversity because it affects the movement of individuals among sites. Assessing the cumulative impact of environmental change requires a multiscale approach that simultaneously considers alpha and beta diversity.

     

Connectivity and habitat type shape divergent dispersal behavior in a desert-dwelling fish

Context

Dispersal has important fitness consequences for individuals, populations, and species. Despite growing theoretical insights into the evolution of dispersal, its behavioral underpinnings remain empirically understudied, limiting our understanding of the extent and impact of responses to landscape-level heterogeneity of environments, and increasing the risk of inferring species-level responses from biased population sampling.

Objectives

We asked if predictable ecological variation among naturally fragmented arid waterbodies is correlated with disparate dispersal responses of populations of the desert goby Chlamydogobius eremius, which naturally inhabits two habitat “types” (permanent springs, ephemeral rivers), and different levels of hydrological connectivity (high and low) that potentially convey different costs and benefits of dispersal.

Methods

To test for possible behavioral divergence between such populations, we experimentally compared the movement behaviors (correlates of emigration and exploration) of wild-caught fish. We used two biologically relevant spatial scales to test movement relevant to different stages of the dispersal process.

Results

Behavior differed at both spatial scales, suggesting that alternative dispersal strategies enable desert gobies to exploit diverse habitat patches. However, while emigration was best predicted by the connectivity (flood risk) of fish habitats, exploration was linked to their habitat type (spring versus river).

Conclusions

Our findings demonstrate that despite a complex picture of ecological variation, key landscape factors have an overarching effect on among-population variation in dispersal traits. Implications include the maintenance of within-species variation, potentially divergent evolutionary trajectories of naturally or anthropogenically isolated populations, and the direction of future experimental studies on the ecology and evolution of dispersal behavior.

     

The influence of landscape relative to site and patch variables on primate distributions in the Colombian Llanos

Context

Primates are an important component of biodiversity in tropical regions. However, many studies on the effects of habitat change on primates ignore the relative influence of landscape composition and configuration.

Objectives

This study addresses the question: how important are landscape-scale forest area and composition relative to patch-scale (1–1080 ha) and site-scale (transect of 1 km) habitat variables for the occupancy and abundance of four primate species in the Colombian Llanos.

Methods

Using a randomly stratified survey design, 81 fragments were surveyed for primate occupancy and abundance. We used zero-inflated models to test the relative influence of landscape-scale, patch-scale and site-scale variables on occupancy and abundance for each species. A 95% confidence set of models was constructed using the cumulative Akaike weight for each model and the relative importance of each set of variables calculated for each primate species.

Results

Occupancy was determined by a combination of site-scale, patch-scale and landscape-scale variables but this varied substantially among the primate species.

Conclusion

Our study highlights the importance of managing primates at a range of scales that considers the relative importance of site-, patch- and landscape-scale variables.

     

Interactive effects of landscape-wide intensity of farming practices and landscape complexity on wild bee diversity

Context

The local intensity of farming practices is considered as an important driver of biodiversity in agricultural landscapes and its effect on biodiversity has been shown to interact with landscape complexity. But the influence of landscape-wide intensity of farming practices on biodiversity and its combined effect with landscape complexity have been little explored.

Objective

In this study, we tested the interactive effect of the landscape-wide intensity of farming practices and landscape complexity on the local species richness and abundance of farmland wild bee communities.

Methods

We captured wild bees in 96 crop fields and explored the effect of landscape-wide intensity of various farming practices along a gradient of landscape complexity (proportion of semi-natural habitats).

Results

We found that species richness and abundance of wild bees were more positively influenced by landscape complexity in highly insecticide-sprayed landscapes than in less intensively managed landscapes. In contrast, we found that the positive effect of landscape complexity on bee species richness only occurred in landscapes with low nitrogen inputs.

Conclusions

Our study demonstrates the interactive effects of landscape-wide farming intensity and landscape complexity in shaping the diversity of farmland wild bee communities. We conclude that the management of farming intensity at the landscape-scale could mitigate the effects of habitat loss on wild bee decline and would help to maintain pollination services in agricultural landscapes.

     

Employing landscape metrics in an open population model to estimate demographic parameters of a grassland bird

Context

The importance of landscape context is increasingly recognized when studying relationships between populations. Recent advances in open population modeling allow the employment of landscape metrics to estimate demographic parameters underlying population variation through time and space.

Objectives

Our primary objectives were to (1) describe the influence of landscape metrics on demographic parameters in the grasshopper sparrow (Ammodramus savannarum) and (2) quantify the contributions of these demographic parameters in influencing variation in territory counts through time. We anticipated results would allow us to make recommendations for prioritizing site conservation for this grassland-obligate species of regional conservation concern.

Methods

We employed territory counts spanning 13 years from Massachusetts, USA in open population models to estimate the effects of landscape metrics, territory density, and site quality on three demographic parameters.

Results

The best model estimated highest initial numbers of territories in larger, more distant sites. Overall growth rates <1 were estimated during 1993–2005, while growth rates >1 were estimated in larger sites with a higher habitat quality index and low to medium relative density. Highest rates of annual immigration were estimated for larger sites. Growth rate explained the greatest proportion of variation in territory counts through time.

Conclusions

Open population models allowed us to identify the effects of landscape context on multiple grasshopper sparrow demographic parameters. We encourage further application of these and related models to grassland birds. Beyond maintaining grasslands in the region, we recommend the conservation of large, distant, and previously occupied sites to benefit regional populations.

     

Metapopulation modelling of long-term urban habitat-loss scenarios

Context

Increasing human populations in urban areas pose a threat to species’ persistence through habitat loss and fragmentation. It is therefore essential that we develop methods to investigate critical habitat loss thresholds and least detrimental landscape configurations.

Objectives

We develop a framework to assess how the pattern of habitat loss impacts the ecological and social characteristics of a landscape and how this varies depending on the species and criteria by which it is judged.

Methods

We use a scenario-based approach to test six propositions in which habitat is lost preferentially based on patch characteristics. We use eight bird and two amphibian species as indicator species. To compare scenarios, we present a method combining the output from a metapopulation model with measures of social impacts of land-cover change in a multiple criteria decision analysis. We also determine whether a habitat loss threshold exists, below which small loss of habitat can lead to large loss of species’ occupancy.

Results

We found that, of the scenarios presented, preferentially losing common habitats and smaller patches was least detrimental for both ecological and social factors. Threshold effects were found for all but the generalist bird species.

Conclusions

We have outlined a workflow which allows for transparent, repeatable comparison between landscapes. This workflow can be used to compare urban landscape plans, or to develop general understanding of the impacts of different forms of habitat loss. Reassuringly, the recommendations based on the scenarios presented are in keeping with received conservation wisdom: to prioritise larger and/or rarer patches.

     

A multi-method approach to delineate and validate migratory corridors

Context

Managers are faced with numerous methods for delineating wildlife movement corridors, and often must make decisions with limited data. Delineated corridors should be robust to different data and models.

Objectives

We present a multi-method approach for delineating and validating wildlife corridors using multiple data sources, which can be used conserve landscape connectivity. We used this approach to delineate and validate migration corridors for wildebeest (Connochaetes taurinus) in the Tarangire Ecosystem of northern Tanzania.

Methods

We used two types of locational data (distance sampling detections and GPS collar locations), and three modeling methods (negative binomial regression, logistic regression, and Maxent), to generate resource selection functions (RSFs) and define resistance surfaces. We compared two corridor detection algorithms (cost-distance and circuit theory), to delineate corridors. We validated corridors by comparing random and wildebeest locations that fell within corridors, and cross-validated by data type.

Results

Both data types produced similar RSFs. Wildebeest consistently selected migration habitat in flatter terrain farther from human settlements. Validation indicated three of the combinations of data type, modeling, and corridor detection algorithms (detection data with Maxent modeling, GPS collar data with logistic regression modeling, and GPS collar data with Maxent modeling, all using cost-distance) far outperformed the other seven. We merged the predictive corridors from these three data-method combinations to reveal habitat with highest probability of use.

Conclusions

The use of multiple methods ensures that planning is able to prioritize conservation of migration corridors based on all available information.

     

Revision and application of the LINKAGES model to simulate forest growth in central hardwood landscapes in response to climate change

Context

Global climate change impacts forest growth and methods of modeling those impacts at the landscape scale are needed to forecast future forest species composition change and abundance. Changes in forest landscapes will affect ecosystem processes and services such as succession and disturbance, wildlife habitat, and production of forest products at regional, landscape and global scales.

Objectives

LINKAGES 2.2 was revised to create LINKAGES 3.0 and used it to evaluate tree species growth potential and total biomass production under alternative climate scenarios. This information is needed to understand species potential under future climate and to parameterize forest landscape models (FLMs) used to evaluate forest succession under climate change.

Methods

We simulated total tree biomass and responses of individual tree species in each of the 74 ecological subsections across the central hardwood region of the United States under current climate and projected climate at the end of the century from two general circulation models and two representative greenhouse gas concentration pathways.

Results

Forest composition and abundance varied by ecological subsection with more dramatic changes occurring with greater changes in temperature and precipitation and on soils with lower water holding capacity. Biomass production across the region followed patterns of soil quality.

Conclusions

Linkages 3.0 predicted realistic responses to soil and climate gradients and its application was a useful approach for considering growth potential and maximum growing space under future climates. We suggest Linkages 3.0 can also can used to inform parameter estimates in FLMs such as species establishment and maximum growing space.

     

Wood fibre value simulation model: a new tool to assist measuring changes in forest landscapes by evaluating forest inventory

Context

A challenging issue in landscape ecology is the evaluation of changes in a forest landscape following a disturbance. This evaluation usually entails examining changes in the forest inventory, which represents the best information available for a given forest region.

Objectives

Our aim was to extend existing methods used to evaluate forest inventory to include additional variables, such as value-based forest product options, wood fibre attributes, and ecosystem services. Inclusion of such variables in forest inventory evaluations would allow research results to be presented from an economic perspective, which is often required for policy development and forest management decision-making.

Methods

We developed a value-based framework to evaluate forest inventory and implemented it in the wood fibre value simulation model. We then used a local data set from Manitoba, Canada, to show how the model can be applied to the mapping of new inventory layers to facilitate the evaluation of landscape changes.

Results

Five new inventory layers are mapped including bioenergy and heating value that can be directly used for evaluating landscape changes, and wood density, fibre length, and pulp yield, which can be combined with total wood volume to derive new variables or indices to express changes in landscape conditions.

Conclusions

Our model can contribute to the assessment of landscape changes by indicating the values a forest can have when it is used for different conservation or utilization purposes. The model can also support improved decision-making with respect to the management of forest resources.