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1.
Matthew J. Duveneck Jonathan R. Thompson Eric J. Gustafson Yu Liang Arjan M. G. de Bruijn 《Landscape Ecology》2017,32(7):1385-1397
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.2.
William D. Dijak Brice B. Hanberry Jacob S. Fraser Hong S. He Wen J. Wang Frank R. ThompsonIII 《Landscape Ecology》2017,32(7):1365-1384
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.3.
Melissa S. Lucash Robert M. Scheller Eric J. Gustafson Brian R. Sturtevant 《Landscape Ecology》2017,32(5):953-969
Context
Resilience, the ability to recover from disturbance, has risen to the forefront of scientific policy, but is difficult to quantify, particularly in large, forested landscapes subject to disturbances, management, and climate change.Objectives
Our objective was to determine which spatial drivers will control landscape resilience over the next century, given a range of plausible climate projections across north-central Minnesota.Methods
Using a simulation modelling approach, we simulated wind disturbance in a 4.3 million ha forested landscape in north-central Minnesota for 100 years under historic climate and five climate change scenarios, combined with four management scenarios: business as usual (BAU), maximizing economic returns (‘EcoGoods’), maximizing carbon storage (‘EcoServices’), and climate change adaption (‘CCAdapt’). To estimate resilience, we examined sites where simulated windstorms removed >70% of the biomass and measured the difference in biomass and species composition after 50 years.Results
Climate change lowered resilience, though there was wide variation among climate change scenarios. Resilience was explained more by spatial variation in soils than climate. We found that BAU, EcoGoods and EcoServices harvest scenarios were very similar; CCAdapt was the only scenario that demonstrated consistently higher resilience under climate change. Although we expected spatial patterns of resilience to follow ownership patterns, it was contingent upon whether lands were actively managed.Conclusions
Our results demonstrate that resilience may be lower under climate change and that the effects of climate change could overwhelm current management practices. Only a substantial shift in simulated forest practices was successful in promoting resilience.4.
Louis R. Iverson Frank R. ThompsonIII Stephen Matthews Matthew Peters Anantha Prasad William D. Dijak Jacob Fraser Wen J. Wang Brice Hanberry Hong He Maria Janowiak Patricia Butler Leslie Brandt Christopher Swanston 《Landscape Ecology》2017,32(7):1327-1346
Context
Species distribution models (SDM) establish statistical relationships between the current distribution of species and key attributes whereas process-based models simulate ecosystem and tree species dynamics based on representations of physical and biological processes. TreeAtlas, which uses DISTRIB SDM, and Linkages and LANDIS PRO, process-based ecosystem and landscape models, respectively, were used concurrently on four regional climate change assessments in the eastern Unites States.Objectives
We compared predictions for 30 species from TreeAtlas, Linkages, and LANDIS PRO, using two climate change scenarios on four regions, to derive a more robust assessment of species change in response to climate change.Methods
We calculated the ratio of future importance or biomass to current for each species, then compared agreement among models by species, region, and climate scenario using change classes, an ordinal agreement score, spearman rank correlations, and model averaged change ratios.Results
Comparisons indicated high agreement for many species, especially northern species modeled to lose habitat. TreeAtlas and Linkages agreed the most but each also agreed with many species outputs from LANDIS PRO, particularly when succession within LANDIS PRO was simulated to 2300. A geographic analysis showed that a simple difference (in latitude degrees) of the weighted mean center of a species distribution versus the geographic center of the region of interest provides an initial estimate for the species’ potential to gain, lose, or remain stable under climate change.Conclusions
This analysis of multiple models provides a useful approach to compare among disparate models and a more consistent interpretation of the future for use in vulnerability assessments and adaptation planning.5.
Context
Climate change will have diverse and interacting effects on forests over the next century. One of the most pronounced effects may be a decline in resistance to chronic change and resilience to acute disturbances. The capacity for forests to persist and/or adapt to climate change remains largely unknown, in part because there is not broad agreement how to measure and apply resilience concepts.Objectives
We assessed the interactions of climate change, resistance, resilience, diversity, and alternative management of northern Great Lake forests.Methods
We simulated two landscapes (northern Minnesota and northern lower Michigan), three climate futures (current climate, a low emissions trajectory, and a high emissions trajectory), and four management regimes [business as usual, expanded forest reserves, modified silviculture, and climate suitable planting (CSP)]. We simulated each scenario with a forest landscape simulation model. We assessed resistance as the change in species composition over time. We assessed resilience and calculated an index of resilience that incorporated both recovery of pre-fire tree species composition and aboveground biomass within simulated burned areas.Results
Results indicate a positive relationship between diversity and resistance within low diversity areas. Simulations of the high emission climate future resulted in a decline in both resistance and resilience.Conclusions
Of the management regimes, the CSP regime resulted in some of the greatest resilience under climate change although our results suggest that differences in forest management are largely outweighed by the effects of climate change. Our results provide a framework for assessing resistance and resilience relevant and valuable to a broad array of ecological systems.6.
Synergistic effects of climate and land cover: grassland birds are more vulnerable to climate change
Marta A. Jarzyna Benjamin Zuckerberg Andrew O. Finley William F. Porter 《Landscape Ecology》2016,31(10):2275-2290
Context
Climate change is not occurring over a homogeneous landscape and the quantity and quality of available land cover will likely affect the way species respond to climate change. The influence of land cover on species’ responses to climate change, however, is likely to differ depending on habitat type and composition.Objectives
Our goal was to investigate responses of forest and grassland breeding birds to over 20 years of climate change across varying gradients of forest and grassland habitat. Specifically, we investigated whether (i) increasing amounts of available land cover modify responses of forest and grassland-dependent birds to changing climate and (ii) the effect of increasing land cover amount differs for forest and grassland birds.Methods
We used Bayesian spatially-varying intercept models to evaluate species- and community-level responses of 30 forest and 10 grassland birds to climate change across varying amounts of their associated land cover types.Results
Responses of forest birds to climate change were weak and constant across a gradient of forest cover. Conversely, grassland birds responded strongly to changing climatic conditions. Specifically, increasing temperatures led to higher probabilities of localized extinctions for grassland birds, and this effect was intensified in regions with low amounts of grassland cover.Conclusions
Within the context of northeastern forests and grasslands, we conclude that forests serve as a possible buffer to the impacts of climate change on birds. Conversely, species occupying open, fragmented grassland areas might be particularly at risk of a changing climate due to the diminished buffering capacity of these ecosystems.7.
Jaymi J. LeBrun Jeffrey E. Schneiderman Frank R. ThompsonIII William D. Dijak Jacob S. Fraser Hong S. He Joshua J. Millspaugh 《Landscape Ecology》2017,32(7):1433-1446
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.8.
Rachel A. Loehman Robert E. Keane Lisa M. Holsinger Zhiwei Wu 《Landscape Ecology》2017,32(7):1447-1459
Context
Interactions among disturbances, climate, and vegetation influence landscape patterns and ecosystem processes. Climate changes, exotic invasions, beetle outbreaks, altered fire regimes, and human activities may interact to produce landscapes that appear and function beyond historical analogs.Objectives
We used the mechanistic ecosystem-fire process model FireBGCv2 to model interactions of wildland fire, mountain pine beetle (Dendroctonus ponderosae), and white pine blister rust (Cronartium ribicola) under current and future climates, across three diverse study areas.Methods
We assessed changes in tree basal area as a measure of landscape response over a 300-year simulation period for the Crown of the Continent in north-central Montana, East Fork of the Bitterroot River in western Montana, and Yellowstone Central Plateau in western Wyoming, USA.Results
Interacting disturbances reduced overall basal area via increased tree mortality of host species. Wildfire decreased basal area more than beetles or rust, and disturbance interactions modeled under future climate significantly altered landscape basal area as compared with no-disturbance and current climate scenarios. Responses varied among landscapes depending on species composition, sensitivity to fire, and pathogen and beetle suitability and susceptibility.Conclusions
Understanding disturbance interactions is critical for managing landscapes because forest responses to wildfires, pathogens, and beetle attacks may offset or exacerbate climate influences, with consequences for wildlife, carbon, and biodiversity.9.
Yan Boulanger Anthony R. Taylor David T. Price Dominic Cyr Elizabeth McGarrigle Werner Rammer Guillaume Sainte-Marie André Beaudoin Luc Guindon Nicolas Mansuy 《Landscape Ecology》2017,32(7):1415-1431
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.10.
Context
Due to the spatial heterogeneity of the disturbance regimes and community assemblages along topoclimatic gradients, the response of forest ecosystem to climate change varies at the landscape scale.Objectives
Our objective was to quantify the possible changes in forest ecosystems and the relative effects of climate warming and fire regime changes in different topographic positions.Methods
We used a spatially explicit model (LANDIS PRO) combined with a gap model (LINKAGES) to predict the possible response of boreal larch forests to climate and fire regime changes, and examined how this response would vary in different topographic positions.Results
The result showed that the proportion of landscape occupied by broadleaf species increased under warming climate and frequent fires scenarios. Shifts in species composition were strongly influenced by both climate warming and more frequent fires, while changes in age structure were mainly controlled by shifts in fire regime. These responses varied in the different topographic positions, with forests in valley bottoms being most resilient to climate-fire changes and forests in uplands being more likely to shift their composition from larch-dominant to mixed forests. Such variation in the topographic response may be induced by the heterogeneities of the environmental conditions and fire regime.Conclusions
Fire disturbance could alter the equilibrium of ecosystems and accelerate the response of forests to climate warming. These effects are largely modulated by topographic variations. Our findings suggest that it is imperative to consider topographic complexities when developing appropriate fire management policies for mitigating the effects of climate change.11.
Context
Forest cover change analyses have revealed net forest gain in many tropical regions. While most analyses have focused solely on forest cover, trees outside forests are vital components of landscape integrity. Quantifying regional-scale patterns of tree cover change, including non-forest trees, could benefit forest and landscape restoration (FLR) efforts.Objectives
We analyzed tree cover change in Southwestern Panama to quantify: (1) patterns of change from 1998 to 2014, (2) differences in rates of change between forest and non-forest classes, and (3) the relative importance of social-ecological predictors of tree cover change between classes.Methods
We digitized tree cover classes, including dispersed trees, live fences, riparian forest, and forest, in very high resolution images from 1998 to 2014. We then applied hurdle models to relate social-ecological predictors to the probability and amount of tree cover gain.Results
All tree cover classes increased in extent, but gains were highly variable between classes. Non-forest tree cover accounted for 21% of tree cover gains, while riparian trees constituted 31% of forest cover gains. Drivers of tree cover change varied widely between classes, with opposite impacts of some social-ecological predictors on non-forest and forest cover.Conclusions
We demonstrate that key drivers of forest cover change, including topography, road distance and historical forest cover, do not explain rates of non-forest tree cover change. Consequently, predictions from medium-resolution forest cover change analyses may not apply to finer-scale patterns of tree cover. We highlight the opportunity for FLR projects to target tree cover classes adapted to local social and ecological conditions.12.
Ian M. McCullough Frank W. Davis John R. Dingman Lorraine E. Flint Alan L. Flint Josep M. Serra-Diaz Alexandra D. Syphard Max A. Moritz Lee Hannah Janet Franklin 《Landscape Ecology》2016,31(5):1063-1075
Context
Predicting climate-driven species’ range shifts depends substantially on species’ exposure to climate change. Mountain landscapes contain a wide range of topoclimates and soil characteristics that are thought to mediate range shifts and buffer species’ exposure. Quantifying fine-scale patterns of exposure across mountainous terrain is a key step in understanding vulnerability of species to regional climate change.Objectives
We demonstrated a transferable, flexible approach for mapping climate change exposure in a moisture-limited, mountainous California landscape across 4 climate change projections under phase 5 of the Coupled Model Intercomparison Project (CMIP5) for mid-(2040–2069) and end-of-century (2070–2099).Methods
We produced a 149-year dataset (1951–2099) of modeled climatic water deficit (CWD), which is strongly associated with plant distributions, at 30-m resolution to map climate change exposure in the Tehachapi Mountains, California, USA. We defined climate change exposure in terms of departure from the 1951–1980 mean and historical range of variability in CWD in individual years and 3-year moving windows.Results
Climate change exposure was generally greatest at high elevations across all future projections, though we encountered moderate topographic buffering on poleward-facing slopes. Historically dry lowlands demonstrated the least exposure to climate change.Conclusions
In moisture-limited, Mediterranean-climate landscapes, high elevations may experience the greatest exposure to climate change in the 21st century. High elevation species may thus be especially vulnerable to continued climate change as habitats shrink and historically energy-limited locations become increasingly moisture-limited in the future.13.
E. L. Loudermilk R. M. Scheller P. J. Weisberg Alec Kretchun 《Landscape Ecology》2017,32(7):1461-1472
Context
Forest landscapes are increasingly managed for fire resilience, particularly in the western US which has recently experienced drought and widespread, high-severity wildfires. Fuel reduction treatments have been effective where fires coincide with treated areas. Fuel treatments also have the potential to reduce drought-mortality if tree density is uncharacteristically high, and to increase long-term carbon storage by reducing high-severity fire probability.Objective
Assess whether fuel treatments reduce fire intensity and spread and increase carbon storage under climate change.Methods
We used a simulation modeling approach that couples a landscape model of forest disturbance and succession with an ecosystem model of carbon dynamics (Century), to quantify the interacting effects of climate change, fuel treatments and wildfire for carbon storage potential in a mixed-conifer forest in the western USA.Results
Our results suggest that fuel treatments have the potential to ‘bend the C curve’, maintaining carbon resilience despite climate change and climate-related changes to the fire regime. Simulated fuel treatments resulted in reduced fire spread and severity. There was partial compensation of C lost during fuel treatments with increased growth of residual stock due to greater available soil water, as well as a shift in species composition to more drought- and fire-tolerant Pinus jeffreyi at the expense of shade-tolerant, fire-susceptible Abies concolor.Conclusions
Forest resilience to global change can be achieved through management that reduces drought stress and supports the establishment and dominance of tree species that are more fire- and drought-resistant, however, achieving a net C gain from fuel treatments may take decades.14.
Brian Young John Yarie David Verbyla Falk Huettmann Keiko Herrick F. Stuart ChapinIII 《Landscape Ecology》2017,32(2):397-413
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.15.
Shengli Tao Qinghua Guo Fangfang Wu Le Li Shaopeng Wang Zhiyao Tang Baolin Xue Jin Liu Jingyun Fang 《Landscape Ecology》2016,31(8):1711-1723
Context
Spatial scale and pattern play important roles in forest aboveground biomass (AGB) estimation in remote sensing. Changes in the accuracy of satellite images-estimated forest AGBs against spatial scales and pixel distribution patterns has not been evaluated, because it requires ground-truth AGBs of fine resolution over a large extent, and such data are difficult to obtain using traditional ground surveying methods.Objectives
We intend to quantify the accuracy of AGB estimation from satellite images on changing spatial scales and varying pixel distribution patterns, in a typical mixed coniferous forest in Sierra Nevada mountains, California.Methods
A forest AGB map of a 143 km2 area was created using small-footprint light detection and ranging. Landsat Thematic Mapper images were chosen as typical examples of satellite images, and resampled to successively coarser resolutions. At each spatial scale, pixels forming random, uniform, and clustered spatial patterns were then sampled. The accuracies of the AGB estimation based on Landsat images associated with varying spatial scales and patterns were finally quantified.Results
The changes in the accuracy of AGB estimation from Landsat images are not monotonic, but increase up to 60–90 m in spatial scale, and then decrease. Random and uniform spatial patterns of pixel distributions yield better accuracy for AGB estimation than clustered spatial patterns. The corrected NDVI (NDVIc) was the best predictor of AGB estimation.Conclusions
A spatial scale of 60–90 m is recommended for forest AGB estimation at the Sierra Nevada mountains using Landsat images and those with similar spectral resolutions.16.
Anantha M. Prasad Louis R. Iverson Stephen N. Matthews Matthew P. Peters 《Landscape Ecology》2016,31(9):2187-2204
Context
No single model can capture the complex species range dynamics under changing climates—hence the need for a combination approach that addresses management concerns.Objective
A multistage approach is illustrated to manage forested landscapes under climate change. We combine a tree species habitat model—DISTRIB II, a species colonization model—SHIFT, and knowledge-based scoring system—MODFACs, to illustrate a decision support framework.Methods
Using shortleaf pine (Pinus echinata) and sugar maple (Acer saccharum) as examples, we project suitable habitats under two future climate change scenarios (harsh, Hadley RCP8.5 and mild CCSM RCP4.5 at ~2100) at a resolution of 10 km and assess the colonization likelihood of the projected suitable habitats at a 1 km resolution; and score biological and disturbance factors for interpreting modeled outcomes.Results
Shortleaf pine shows increased habitat northward by 2100, especially under the harsh scenario of climate change, and with higher possibility of natural migration confined to a narrow region close to the current species range boundary. Sugar maple shows decreased habitat and has negligible possibility of migration within the US due to a large portion of its range being north of the US border. Combination of suitable habitats with colonization likelihoods also allows for identification of potential locations appropriate for assisted migration, should that be deemed feasible.Conclusion
The combination of these multiple components using diverse approaches leads to tools and products that may help managers make management decisions in the face of a changing climate.17.
Context
Fires and insect outbreaks are important agents of forest landscape change, but the classification and distribution of these combined processes remain unstudied aspects of forest disturbance regimes.Objectives
We sought to map areas of land characterized by homogenous fire regime (HFR) attributes and by distinctive combinations of fire, bark beetles and defoliating insect outbreaks, and how their distribution might change should current climatic trends continue.Methods
We used a 41-year history of mapped fires and forest insect outbreaks to classify HFRs and combined fire and insect disturbance regimes (HDRs). Spatially constrained cluster analysis of 2524 20-km grid cells used mean annual area burned, ignition Julian date, fire size and fire frequency to delineate HFR zones. Mean annual areas burned, affected by bark beetles, and affected by defoliators were used to delineate HDR zones. Random forests classification used climate associations of HDRs to project likely changes in their distribution.Results
Eighteen HFR zones accounted for 30% of variance, compared to 27 HDR zones accounting for 59% of variance. Fire regime designation had low predictive power in explaining 23 homogenous insect outbreak regimes or the 27 HDRs. Climate change projections indicate a northward migration of current HDR zones. Conditions suitable for defoliator outbreaks are projected to increase, resulting in a projected increase in the total rate of forest disturbance.Conclusions
When describing forest disturbance regimes, it is important to consider the combined and possibly interacting agents of tree mortality, which can result in emergent properties not predictable from any single agent.18.
Context
Natural disturbances can have a considerable negative impact on the productivity of forest landscapes. Yet, disturbances are also important drivers of diversity, with diversity generally contributing positively to forest productivity. While the direct effects of disturbance have been investigated extensively it remains unclear how disturbance-mediated changes in diversity influence landscape productivity. Considering that disturbances are increasing in many ecosystems a better understanding of disturbance impacts is of growing importance for ecosystem management.Objectives
Here, our objectives were to study the effect of disturbance on tree species diversity at different spatial scales (α and β diversity), and to analyze how a disturbance-mediated variation in tree species diversity affects forest productivity.Methods
To account for long-term interactions between disturbance, diversity, and productivity and test a range of disturbance scenarios we used simulation modeling, focusing on a temperate forest landscape in Central Europe.Results
We found an overall positive effect of disturbance on tree species diversity both with regard to α and β diversity, persisting under elevated disturbance frequencies. Productivity was enhanced by within- and between-stand diversity, with the effect of α diversity decreasing and that of β diversity increasing through the successional development. Positive diversity effects were found to be strongly contingent on the available species pool, with landscapes containing species with different life-history strategies responding most strongly to disturbance-mediated diversity.Conclusions
We conclude that, rather than homogenizing disturbed areas, forest managers should incorporate the diversity created by disturbances into stand development to capitalize on a positive diversity effect on productivity.19.
Context
Biodiversity in arid regions is usually concentrated around limited water resources, so natural resource managers have constructed artificial water catchments in many areas to supplement natural waters. Because invasive species may also use these waters, dispersing into previously inaccessible areas, the costs and benefits of artificial waters must be gauged and potential invasion- and climate change-management strategies assayed.Objectives
We present a network analysis framework to identify waters that likely contribute to the spread of invasive species.Methods
Using the Sonoran Desert waters network and the American bullfrog (Lithobates catesbeianus)—a known predator, competitor, and carrier of pathogens deadly to other amphibians—as an example, we quantified the structural connectivity of the network to predict regional invasion potential under current and two future scenarios (climate change and management reduction) to identify waters to manage and monitor for invasive species.Results
We identified important and vulnerable waters based on connectivity metrics under scenarios representing current conditions, projected climate-limited conditions, and conditions based on removal of artificial waters. We identified 122,607 km2 of land that could be used as a buffer against invasion and 67,745 km2 of land that could be augmented by artificial water placement without facilitating invasive species spread.Conclusions
Structural connectivity metrics can be used to evaluate alternative management strategies for invasive species and climate mitigation.20.
Thomas Ibanez Vanessa Hequet Céline Chambrey Tanguy Jaffré Philippe Birnbaum 《Landscape Ecology》2017,32(8):1671-1687