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.

     

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.

     

Cumulative patterns of logging and fire (1940–2009): consequences on the structure of the eastern Canadian boreal forest

Context

Although logging has affected circumboreal forest dynamics for nearly a century, very few studies have reconstructed its influence on landscape structure at the subcontinental scale.

Objectives

This study aims to document spatiotemporal patterns of logging and fire since the introduction of logging in the early twentieth-century, and to evaluate the effects of these disturbances on landscape structure.

Methods

We used historical (1940–2009) logging and fire maps to document disturbance patterns across a 195,000-km² boreal forest landscape of eastern Canada. We produced multitemporal (1970s–2010s) mosaics providing land cover status using Landsat imagery.

Results

Logging significantly increased the rate of disturbance (+74 %) in the study area. The area affected by logging increased linearly with time resulting in a significant rejuvenation of the landscape along the harvesting pattern (south–north progression). From 1940 to 2009, fire was the dominant disturbance and showed a more random spatial distribution than logging. The recent increase of fire influence and the expansion of the proportion of area classified as unproductive terrestrial land suggest that regeneration failures occurred.

Conclusions

This study reveals how logging has modified the disturbances dynamics, following the progression of the logging frontier. Future management practices should aim for a dispersed spatial distribution of harvests to generate landscape structures that are closer to natural conditions, in line with ecosystem-based management. The challenges of defining sustainable practices will remain complex with the predicted increase in fire frequency, since this factor, in combination with logging, can alter both the structure and potentially the resilience of boreal forest.

     

Bird response to future climate and forest management focused on mitigating climate change

Context

Global temperatures are projected to increase and affect forests and wildlife populations. Forest management can potentially mitigate climate-induced changes through promoting carbon sequestration, forest resilience, and facilitated change.

Objectives

We modeled direct and indirect effects of climate change on avian abundance through changes in forest landscapes and assessed impacts on bird abundances of forest management strategies designed to mitigate climate change effects.

Methods

We coupled a Bayesian hierarchical model with a spatially explicit landscape simulation model (LANDIS PRO) to predict avian relative abundance. We considered multiple climate scenarios and forest management scenarios focused on carbon sequestration, forest resilience, and facilitated change over 100 years.

Results

Management had a greater impact on avian abundance (almost 50% change under some scenarios) than climate (<3% change) and only early successional and coniferous forest showed significant change in percent cover across time. The northern bobwhite was the only species that changed in abundance due to climate-induced changes in vegetation. Northern bobwhite, prairie warbler, and blue-winged warbler generally increased in response to warming temperatures but prairie warbler exhibited a non-linear response and began to decline as summer maximum temperatures exceeded 36 °C at the end of the century.

Conclusion

Linking empirical models with process-based landscape change models can be an effective way to predict climate change and management impacts on wildlife, but time frames greater than 100 years may be required to see climate related effects. We suggest that future research carefully consider species-specific effects and interactions between management and climate.

     

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.

     

Recovery dynamics and climate change effects to future New England forests

Context

Forests throughout eastern North America continue to recover from broad-scale intensive land use that peaked in the nineteenth century. These forests provide essential goods and services at local to global scales. It is uncertain how recovery dynamics, the processes by which forests respond to past forest land use, will continue to influence future forest conditions. Climate change compounds this uncertainty.

Objectives

We explored how continued forest recovery dynamics affect forest biomass and species composition and how climate change may alter this trajectory.

Methods

Using a spatially explicit landscape simulation model incorporating an ecophysiological model, we simulated forest processes in New England from 2010 to 2110. We compared forest biomass and composition from simulations that used a continuation of the current climate to those from four separate global circulation models forced by a high emission scenario (RCP 8.5).

Results

Simulated forest change in New England was driven by continued recovery dynamics; without the influence of climate change forests accumulated 34 % more biomass and succeed to more shade tolerant species; Climate change resulted in 82 % more biomass but just nominal shifts in community composition. Most tree species increased AGB under climate change.

Conclusions

Continued recovery dynamics will have larger impacts than climate change on forest composition in New England. The large increases in biomass simulated under all climate scenarios suggest that climate regulation provided by the eastern forest carbon sink has potential to continue for at least a century.

     

Climate change amplifies the interactions between wind and bark beetle disturbances in forest landscapes

Context

Growing evidence suggests that climate change could substantially alter forest disturbances. Interactions between individual disturbance agents are a major component of disturbance regimes, yet how interactions contribute to their climate sensitivity remains largely unknown.

Objectives

Here, our aim was to assess the climate sensitivity of disturbance interactions, focusing on wind and bark beetle disturbances.

Methods

We developed a process-based model of bark beetle disturbance, integrated into the dynamic forest landscape model iLand (already including a detailed model of wind disturbance). We evaluated the integrated model against observations from three wind events and a subsequent bark beetle outbreak, affecting 530.2 ha (3.8 %) of a mountain forest landscape in Austria between 2007 and 2014. Subsequently, we conducted a factorial experiment determining the effect of changes in climate variables on the area disturbed by wind and bark beetles separately and in combination.

Results

iLand was well able to reproduce observations with regard to area, temporal sequence, and spatial pattern of disturbance. The observed disturbance dynamics was strongly driven by interactions, with 64.3 % of the area disturbed attributed to interaction effects. A +4 °C warming increased the disturbed area by +264.7 % and the area-weighted mean patch size by +1794.3 %. Interactions were found to have a ten times higher sensitivity to temperature changes than main effects, considerably amplifying the climate sensitivity of the disturbance regime.

Conclusions

Disturbance interactions are a key component of the forest disturbance regime. Neglecting interaction effects can lead to a substantial underestimation of the climate change sensitivity of disturbance regimes.

     

Changes in forest biomass and tree species distribution under climate change in the northeastern United States

Context

Forests in the northeastern United States are currently in early- and mid-successional stages recovering from historical land use. Climate change will affect forest distribution and structure and have important implications for biodiversity, carbon dynamics, and human well-being.

Objective

We addressed how aboveground biomass (AGB) and tree species distribution changed under multiple climate change scenarios (PCM B1, CGCM A2, and GFDL A1FI) in northeastern forests.

Methods

We used the LANDIS PRO forest landscape model to simulate forest succession and tree harvest under current climate and three climate change scenarios from 2000 to 2300. We analyzed the effects of climate change on AGB and tree species distribution.

Results

AGB increased from 2000 to 2120 irrespective of climate scenario, followed by slight decline, but then increased again to 2300. AGB averaged 10 % greater in the CGCM A2 and GFDL A1FI scenarios than the PCM B1 and current climate scenarios. Climate change effects on tree species distribution were not evident from 2000 to 2100 but by 2300 some northern hardwood and conifer species decreased in occurrence and some central hardwood and southern tree species increased in occurrence.

Conclusions

Climate change had positive effects on forest biomass under the two climate scenarios with greatest warming but the patterns in AGB over time were similar among climate scenarios because succession was the primary driver of AGB dynamics. Our approach, which simulated stand dynamics and dispersal, demonstrated that a northward shift in tree species distributions may take 300 or more years.

     

Using airborne LiDAR to assess spatial heterogeneity in forest structure on Mount Kilimanjaro

Context

Field inventory plots which usually have small sizes of around 0.25–1 ha can only represent a sample of the much larger surrounding forest landscape. Based on airborne laser scanning (LiDAR) it has been shown for tropical forests that the bias in the selection of small field plots may hamper the extrapolation of structural forest attributes to larger spatial scales.

Objectives

We conducted a LiDAR study on tropical montane forest and evaluated the representativeness of chosen inventory plots with respect to key structural attributes.

Methods

We used six forest inventory and their surrounding landscape plots on Mount Kilimanjaro in Tanzania and analyzed the similarities for mean top-of-canopy height (TCH), aboveground biomass (AGB), gap fraction, and leaf-area index (LAI). We also analyzed the similarity in gap-size frequencies for the landscape plots.

Results

Mean biases between inventory and landscape plots were large reaching as much as 77% for gap fraction, 22% for LAI or 15% for AGB. Despite spatial heterogeneity of the landscape, gap-size frequency distributions were remarkably similar between the landscape plots.

Conclusions

The study indicates that biases in field studies of forest structure may be strong. Even when mean values were similar between inventory and landscape plots, the mostly non-normally distributed probability densities of the forest variable indicated a considerable sampling error of the small field plot to approximate the forest variable in the surrounding landscape. This poses difficulties for the spatial extrapolation of forest structural attributes and for assessing biomass or carbon fluxes at larger regional scales.

     

Modeling and mapping forest diversity in the boreal forest of interior Alaska

Context

Patterns of forest diversity are less well known in the boreal forest of interior Alaska than in most ecosystems of North America. Proactive forest planning requires spatially accurate information about forest diversity. Modeling is a cost-efficient way of predicting key forest diversity measures as a function of human and environmental factors.

Objectives

Investigate and predict the patterns and processes in tree species and tree size-class diversity within the boreal forest of Alaska for a first mapped quantitative baseline.

Methods

For the boreal forest of Alaska, USA, we employed Random Forest Analysis (machine learning) and the Boruta algorithm in R to predict tree species and tree size-class diversity for the entire region using a combination of forest inventory data and a suite of 30 predictors from public open-access data archives that included climatic, distance, and topographic variables. We developed prediction maps in a GIS for the current levels (Year 2012) of tree size-class and species diversity.

Results

The method employed here yielded good accuracy for the huge Alaskan landscape despite the exclusion of spectral reflectance data. It’s the first quantified GIS prediction baseline. The results indicate that the geographic pattern of tree species diversity differs from the pattern of tree size-class diversity across this forest type.

Conclusions

The results suggest that human factors combined with topographical factors had a large impact on predicting the patterns of diversity in the boreal forest of interior Alaska.

     

Multiple-scale prediction of forest loss risk across Borneo

Context

The forests of Borneo have among the highest biodiversity and also the highest forest loss rates on the planet.

Objectives

Our objectives were to: (1) compare multiple modelling approaches, (2) evaluate the utility of landscape composition and configuration as predictors, (3) assess the influence of the ratio of forest loss and persistence points in the training sample, (4) identify the multiple-scale drivers of recent forest loss and (5) predict future forest loss risk across Borneo.

Methods

We compared random forest machine learning and logistic regression in a multi-scale approach to model forest loss risk between 2000 and 2010 as a function of topographical variables and landscape structure, and applied the highest performing model to predict the spatial pattern of forest loss risk between 2010 and 2020. We utilized a naïve model as a null comparison and used the total operating characteristic AUC to assess model performance.

Results

Our analysis produced five main results. We found that: (1) random forest consistently outperformed logistic regression and the naïve model; (2) including landscape structure variables substantially improved predictions; (3) a ratio of occurrence to non-occurrence points in the training dataset that does not match the actual ratio in the landscape biases the predictions of both random forest and logistic regression; (4) forest loss risk differed between the three nations that comprise Borneo, with patterns in Kalimantan highly related to distance from the edge of the previous frontier of forest loss, while Malaysian Borneo showed a more diffuse pattern related to the structure of the landscape; (5) we predicted continuing very high rates of forest loss in the 2010–2020 period, and produced maps of the expected risk of forest loss across the full extent of Borneo.

Conclusions

These results confirm that multiple-scale modelling using landscape metrics as predictors in a random forest modelling framework is a powerful approach to landscape change modelling. There is immense immanent risk to Borneo’s forests, with clear spatial patterns of risk related to topography and landscape structure that differ between the three nations that comprise Borneo.

     

Climate change impacts on forest landscapes along the Canadian southern boreal forest transition zone

Context

Forest landscapes at the southern boreal forest transition zone are likely to undergo great alterations due to projected changes in regional climate.

Objectives

We projected changes in forest landscapes resulting from four climate scenarios (baseline, RCP 2.6, RCP 4.5 and RCP 8.5), by simulating changes in tree growth and disturbances at the southern edge of Canada’s boreal zone.

Methods

Projections were performed for four regions located on an east–west gradient using a forest landscape model (LANDIS-II) parameterized using a forest patch model (PICUS).

Results

Climate-induced changes in the competitiveness of dominant tree species due to changes in potential growth, and substantial intensification of the fire regime, appear likely to combine in driving major changes in boreal forest landscapes. Resulting cumulative impacts on forest ecosystems would be manifold but key changes would include (i) a strong decrease in the biomass of the dominant boreal species, especially mid- to late-successional conifers; (ii) increases in abundance of some temperate species able to colonize disturbed areas in a warmer climate; (iii) increases in the proportions of pioneer and fire-adapted species in these landscapes and (iv) an overall decrease in productivity and total biomass. The greatest changes would occur under the RCP 8.5 radiative forcing scenario, but some impacts can be expected even with RCP 2.6.

Conclusions

Western boreal forests, i.e., those bordering the prairies, are the most vulnerable because of a lack of species adapted to warmer climates and major increases in areas burned. Conservation and forest management planning within the southern boreal transition zone should consider both disturbance- and climate-induced changes in forest communities.

     

The formulations of site-scale processes affect landscape-scale forest change predictions: a comparison between LANDIS PRO and LANDIS-II forest landscape models

Context

Forest landscape models (FLMs) are important tools for simulating forest changes over broad spatial and temporal scales. The ability of FLMs to accurately predict forest changes may be significantly influenced by the formulations of site-scale processes including seedling establishment, tree growth, competition, and mortality.

Objective

The objectives of this study were to investigate the effects of site-scale processes and interaction effects of site-scale processes and harvest on landscape-scale forest change predictions.

Methods

We compared the differences in species’ distribution (quantified by species’ percent area), total aboveground biomass, and species’ biomass derived from two FLMs: (1) a model that explicitly incorporates stand density and size for each species age cohort (LANDIS PRO), and (2) a model that explicitly tracks biomass for each species age cohort (LANDIS-II with biomass succession extension), which are variants from the LANDIS FLM family with different formulations of site-scale processes.

Results

For early successional species, the differences in simulated distribution and biomass were small (mostly less than 5 %). For mid- to late-successional species, the differences in simulated distribution and biomass were relatively large (10–30 %). The differences in species’ biomass predictions were generally larger than those for species’ distribution predictions. Harvest mediated the differences on landscape-scale predictions.

Conclusions

The effects of site-scale processes on landscape-scale forest change predictions are dependent on species’ ecological traits such as shade tolerance, seed dispersal, and growth rates.

     

Multi-temporal trajectories of landscape change explain forest biodiversity in urbanizing ecosystems

Context

Forest loss and fragmentation negatively affect biodiversity. However, disturbances in forest canopy resulting from repeated deforestation and reforestation are also likely important drivers of biodiversity, but are overlooked when forest cover change is assessed using a single time interval.

Objectives

We investigated two questions at the nexus of plant diversity and forest cover change dynamics: (1) Do multitemporal forest cover change trajectories explain patterns of plant diversity better than a simple measure of overall forest change? (2) Are specific types of forest cover change trajectories associated with significantly higher or lower levels of diversity?

Methods

We sampled plant biodiversity in forests spanning the Charlotte, NC, region. We derived forest cover change trajectories occurring within nested spatial extents per sample site using a time series of aerial photos from 1938 to 2009, then classified trajectories by spatio-temporal patterns of change. While accounting for landscape and environmental covariates, we assessed the effects of the trajectory classes as compared to net forest cover change on native plant diversity.

Results

Our results indicated that forest stand diversity is best explained by forest change trajectories, while the herb layer is better explained by net forest cover change. Three distinct forest change trajectory classes were found to influence the forest stand and herb layer.

Conclusions

The influence of forest dynamics on biodiversity can be overlooked in analyses that use only net forest cover change. Our results illustrate the utility of assessing how specific trajectories of past land cover change influence biodiversity patterns in the present.

     

Occupancy pattern of a long-horned beetle in a variegated forest landscape: linkages between tree quality and forest cover across spatial scales

Context

Interactions between landscape-scale processes and fine-grained habitat heterogeneity are usually invoked to explain species occupancy in fragmented landscapes. In variegated landscapes, however, organisms face continuous variation in micro-habitat features, which makes necessary to consider ecologically meaningful estimates of habitat quality at different spatial scales.

Objectives

We evaluated the spatial scales at which forest cover and tree quality make the greatest contribution to the occupancy of the long-horned beetle Microplophorus magellanicus (Coleoptera: Cerambycidae) in a variegated forest landscape.

Methods

We used averaged data of tree quality (as derived from remote sensing estimates of the decay stage of single trees) and spatially independent pheromone-baited traps to model the occurrence probability as a function of multiple cross-scale combinations between forest cover and tree quality (with scales ranging between 50 and 400 m).

Results

Model support and performance increased monotonically with the increasing scale at which tree quality was measured. Forest cover was not significant, and did not exhibit scale-specific effects on the occurrence probability of M. magellanicus. The interactive effect between tree quality and forest cover was stronger than the independent (additive) effects of tree quality and particularly forest cover. Significant interactions included tree quality measured at spatial scales ≥200 m, but cross-scale interactions occurred only in four of the seven best-supported models.

Conclusions

M. magellanicus respond to the high-quality trees available in the landscape rather than to the amount of forest per se. Conservation of viable metapopulations of M. magellanicus should consider the quality of trees at spatial scales >200 m.

     

Fire regimes and forest resilience: alternative vegetation states in the West African tropics

Context

Terrestrial ecosystems, including tropical forests, are hypothesized to have tipping points beyond which environmental change triggers rapid and radical shifts to novel alternative states.

Objective

We explored the overarching hypothesis that fire-mediated alternative stable states exist in the semi-deciduous tropical forest zone of Ghana, and that increased fire activity has pushed some forests to a new state in which a novel ecosystem with low tree density is maintained by fire.

Methods

We combined a 30-year time series of remotely-sensed data with field measurements to assess land cover trends, the effects of fire on forest vegetation, and the reciprocal effects of vegetation change on fire regimes, in four forest reserves. We analyzed precipitation trends to determine if shifts in vegetation and fire regime reflected a shift to a drier climate.

Results

Two of the reserves experienced forest loss, were impacted by frequent fires, and transitioned to a vegetation community dominated by shrubs and grasses, which was maintained by fire–vegetation feedbacks. The other two reserves experienced less fire, retained higher levels of forest cover, and resisted fire encroachment from surrounding agricultural areas. Precipitation remained relatively stable, suggesting a hysteresis effect in which different vegetation states and fire regimes coexist within a similar climate.

Conclusion

There is potential for human land use and fire to create novel and persistent non-forest vegetation communities in areas that are climatically suitable for tropical forests. These disturbance-mediated regime shifts should be taken into account when assessing future trajectories of forest landscape change in West Africa.

     

Integrating models across temporal and spatial scales to simulate landscape patterns and dynamics in mountain pasture-woodlands

Context

Pasture-woodlands are semi-natural landscapes that result from the combined influences of climate, management, and intrinsic vegetation dynamics. These landscapes are sensitive to future changes in land use and climate, but our ability to predict the impact on ecosystem service provisioning is limited due to the disparate scales in time and space that govern their dynamics.

Objectives

To develop a process-based model to simulate pasture-woodland landscapes and the provisioning of ecosystem services (i.e., livestock forage, woody biomass and landscape heterogeneity).

Methods

We modified a dynamic forest landscape model to simulate pasture-woodland landscapes in Switzerland. This involved including an annual herbaceous layer, selective grazing from cattle, and interactions between grazing and tree recruitment. Results were evaluated within a particular pasture, and then the model was used to simulate regional vegetation patterns and livestock suitability for a ~198,000 ha landscape in the Jura Vaudois region.

Results

The proportion of vegetation cover types at the pasture level (i.e., open, semi-open and closed forests) was well represented, but the spatial distribution of trees was only broadly similar. The entire Jura Vaudois region was simulated to be highly suitable for livestock, with only a small proportion being unsuitable due to steep slopes and high tree cover. High and low elevation pastures were equally suitable for livestock, as lower forage production at higher elevations was compensated by reduced tree cover.

Conclusions

The modified model is valuable for assessing landscape to regional patterns in vegetation and livestock, and offers a platform to evaluate how climate and management impact ecosystem services.

     

How does forest fragmentation affect tree communities? A critical case study in the biodiversity hotspot of New Caledonia

Context

The biodiversity hotspot for conservation of New Caledonia has facing high levels of forest fragmentation. Remnant forests are critical for biodiversity conservation and can help in understanding how does forest fragmentation affect tree communities.

Objective

Determine the effect of habitat configuration and availability on tree communities.

Methods

We mapped forest in a 60 km² landscape and sampled 93 tree communities in 52 forest fragments following stratified random sampling. At each sampling point, we inventoried all trees with a diameter at breast height ≥10 cm within a radius of 10 m. We then analysed the response of the composition, the structure and the richness of tree communities to the fragment size and isolation, distance from the edge, as well as the topographical position.

Results

Our results showed that the distance from the forest edge was the variable that explained the greatest observed variance in tree assemblages. We observed a decrease in the abundance and richness of animal-dispersed trees as well as a decrease in the abundance of large trees with increasing proximity to forest edges. Near forest edges we found a shift in species composition with a dominance of stress-tolerant pioneer species.

Conclusions

Edge-effects are likely to be the main processes that affect remnant forest tree communities after about a century of forest fragmentation. It results in retrogressive successions at the edges leading to a dominance of stress-tolerant species. The vegetation surrounding fragments should be protected to promote the long process of forest extension and subsequently reduce edge-effects.

     

Sensitivity of resource selection and connectivity models to landscape definition

Context

The definition of the geospatial landscape is the underlying basis for species-habitat models, yet sensitivity of habitat use inference, predicted probability surfaces, and connectivity models to landscape definition has received little attention.

Objectives

We evaluated the sensitivity of resource selection and connectivity models to four landscape definition choices including (1) the type of geospatial layers used, (2) layer source, (3) thematic resolution, and (4) spatial grain.

Methods

We used GPS telemetry data from pumas (Puma concolor) in southern California to create multi-scale path selection function models (PathSFs) across landscapes with 2500 unique landscape definitions. To create the landscape definitions, we identified seven geospatial layers that have been shown to influence puma habitat use. We then varied the number, sources, spatial grain, and thematic resolutions of these layers to create our suite of plausible landscape definitions. We assessed how PathSF model performance (based on AIC) was affected by landscape definition and examined variability among the predicted probability of movement surfaces, connectivity models, and road crossing locations.

Results

We found model performance was extremely sensitive to landscape definition and identified only seven top models out of our suite of definitions (<1%). Spatial grain and the number of geospatial layers selected for a landscape definition significantly affected model performance measures, with finer grains and greater numbers of layers increasing model performance.

Conclusions

Given the sensitivity of habitat use inference, predicted probability surfaces, and connectivity models to landscape definition, out results indicate the need for increased attention to landscape definition in future studies.