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Adaptive ecosystem management is a new paradigm for managing federal forests which requires regular monitoring of ecosystem function and diversity to measure the effects of management. Managers need new ...
Citation Citation
- Title:
- Forest macro-arthropods as potential indicators of ecosystem conditions in Western Idaho : an analysis of community composition, biological diversity, and community structure
- Author:
- Ruby, Margaret E.
Adaptive ecosystem management is a new paradigm for managing federal forests which requires regular monitoring of ecosystem function and diversity to measure the effects of management. Managers need new strategies and tools to help them assess their progress in maintaining healthy, productive and biologically diverse forests. Biomonitoring of select forest macro-arthropod species can provide useful information on the effects of management on forest biodiversity and ecosystem function. The purpose of this study was threefold: (1) to inventory the macro-arthropod community and important environmental variables in the Bear Creek and Indian Creek study area within the Payette National Forest (PNF) in Western Idaho; (2) to compare measures of community composition, diversity, and structure in forest macro-arthropod communities between patches of different sizes and treatment; and (3) to assist PNF managers in their ecosystem management efforts by providing principles to guide the use of macro-arthropods as indicators of changing forest conditions. Transects with pitfall traps were used to collect macro-arthropods at 22 sites in the Bear Creek and Indian Creek study area during the summer of 1994. Five forest patch types in Abies grandis habitat types were sampled. Intact forest patches of 100 or more hectares, and large patches of 50-100 hectares, ranged in age between 50 and 250 years old with multistoried structure. Small patches up to 10 hectares were remnants or fragments of formerly intact forest isolated by logging. A plantation patch was 15 years old with patchy understory and forb cover. Clearcut patches had little or no overstory, and variable understory, and forb layers. At each transect, soil samples were collected and six environmental descriptor variables were analyzed according to patch treatment and patch size. These site descriptors were: basal area (ft²/acre); percent canopy cover for the overstory, understory; and forb layers; litter depth (cm), and percent soil moisture content. Differences detected using an ANOVA and T-tests are discussed in the Results section. Arthropod community composition, diversity, and structure were described according to relative abundance, and four measures of diversity. They were also described by membership in seventeen orders and/or super-families; ten functional groups; two disperser classes (long or short distance); and three species indicator classes. A total of 5455 macro-arthropod individuals, representing 17 orders and/or super-families and 219 species were collected in the Bear Creek and Indian Creek study area. While macro-arthropod fauna relative abundance did not vary significantly by treatment (ANOVA p<0.3), it did vary significantly by patch size (ANOVA p<0.03). Fauna relative abundance was 35% greater in clearcut patches than in large patches (T-test p<0.09). Fauna relative abundance in small patches was twice that of intact (T-test p<0.03) and large (T-test p<0.02) patches. Taxonomic diversity (number of genera/taxa) of beetle, ant, and bug taxa differed significantly according to treatment type(each ANOVA p<0.05). For the top four taxa (beetles, ants, spiders, and bugs), taxonomic diversity was highest in the plantation and clearcut patches. Ants and bugs had their highest taxonomic diversity in the plantation patch (separate T-tests p<0.05) while the taxonomic diversity of beetles was highest in clear-cut patches (T-test p<0.05). Beetle and ant taxonomic diversity varied significantly by patch size (each ANOVA p<0.05). For beetles and bugs, small patches were twice as diverse as intact patches (separate T-tests p<0.04) and 1.5 times that of large patches. Ant diversity was similarly distributed amongst the patch sizes, with significant differences between small and intact and between small and large patches (separate T-tests p<0.05). Of the four species diversity measures employed, only two, [alpha] and JK1 (both measures of richness), were found to vary significantly by patch treatment and size. Evenness (E) and the Shannon Diversity Index (H') failed to detect differences in the majority of tests. Fauna [alpha] and JK1 differed significantly by treatment type (each ANOVA p<0.05). Richness in clearcut patches was nearly twice in intact and large patches, followed by plantation and large patches. Fauna [alpha] and JKl also differed significantly by patch size (each ANOVA p <0.001), with small patch fauna twice as rich as that in large and intact patches (separate T-tests p <0.01). Of the top four functional groups, predators were the most abundant and had the highest taxonomic diversity (number of genera/functional group), followed by herbivores, fungivores and parasites. Predators and herbivores showed increasing taxonomic diversity with decreasing patch size, from intact to large to small (ANOVA p< 0.05). Similarly, predators and herbivores exhibited increasing taxonomic diversity with increasing levels of management: from intact and large to plantation and clear-cuts (ANOVA p< 0.05). Predators and herbivores were most numerous in the managed and small patches. Fungivore taxonomic diversity was also highest in the small and managed patches, though neither patch size nor treatment differences were significant (ANOVA p<0.85). Parasite taxonomic diversity differed by patch size with highest generic diversity in the small patches (ANOVA p<0.l) and by treatment type with generic diversity highest in plantations and clearcuts followed in order by large and intact patches (ANOVA p<0.l). Twice as many genera were long distance dispersers as were short distance dispersers. Relative abundance of long distance dispersers varied significantly by patch treatment and patch size (each ANOVA p<0.0l). Long distance dispersers were most numerous in clear-cut patches, followed in order by plantation, small, large, and intact patches. Relative abundance of short distance dispersers was not significantly different between treatment types (ANOVA p<0.20) but was significantly different between patch sizes (ANOVA p<0.0l). Short distance dispersers were most numerous in small patches followed by plantation, large, and intact and least numerous in clearcut patches. An indicator species analysis of 121 Bear Creek and Indian Creek genera (Dufrene and Legendre 1997), revealed sub-groups of species with 75 to 100 percent "perfect indication" or affiliation for specific patch types. When intact and large patches were pooled and analyzed against all treated patches (plantation and clearcut patches), a list of 36 genera with 75 to 100 percent "perfect affiliation" for intact or large patches was produced (MRPP p<0.05). Small patches had 42 indicators with 75 to 100 percent "perfect indication" when compared with the pooled intact and large patches (MRPP p<0.l). Conclusions Macro-arthropod community composition, diversity and structure did vary, usually significantly, by patch treatment and size. Useful measures of generic diversity include richness estimators [alpha], [beta], and JK1. Examination of taxonomic diversity was also useful, especially for the more mobile arthropods. Pitfall traps provided copious data on the structure of the community in regards to predators and herbivores. Pitfalls, however, did not provide much information about the status of fungivores and parasites in the various different patches. Another trapping method such as the berlaise funnel, would likely provide more information about those functional groups which are likely operating at a finer scale of resolution than that tested by the pitfall trap. Employing both methods would provide a much better assessment of the community of arthropods living on the forest floor. The indicator species analysis program also provided very useful lists of species which are affiliated with particular patch conditions. Taken together, these measures could be adopted for use by forest managers to allow them to assess and monitor the effects of a management regime on the structure and composition of macro-arthropod communities as part of a comprehensive adaptive management plan.
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The forest alpine tundra ecotone (FTE, also known as alpine treeline or subalpine parkland), is a conspicuous feature of mountain landscapes throughout the world. Climate change-driven increases in temperature ...
Citation Citation
- Title:
- Patterns of tree establishment and vegetation composition in relation to climate and topography of a subalpine meadow landscape, Jefferson Park, Oregon, USA
- Author:
- Zald, Harold Samuel James
The forest alpine tundra ecotone (FTE, also known as alpine treeline or subalpine parkland), is a conspicuous feature of mountain landscapes throughout the world. Climate change-driven increases in temperature are believed to result in FTE movement and tree invasion of subalpine meadows, which have been documented throughout the Northern Hemisphere across a wide range of geographic locations, climatic regimes, forest types, land use histories, and disturbance regimes. Climate-driven FTE movement may have numerous ecological effects such as: positive temperature feedbacks, increased net primary productivity and carbon storage, and declines of plant populations and species. The magnitude of these ecological effects is highly uncertain, but will be largely determined by the rates and spatial extent of FTE movement and meadow invasion. FTE movement and meadow invasion are often considered at global or regional spatial scales in relation to climate, yet they are fundamentally driven by tree regeneration processes that are influenced by a variety of climatic and biophysical factors at micro site, landscape, and regional scales. Much of the research on the FTE has not taken a landscape approach incorporating multi-scale processes. For example, species distribution models used to project climate change effects on future species distributions and plant biodiversity in mountainous landscapes rely on species distribution data that is often sparse and incomplete across FTE landscapes. This dissertation attempts to overcome many of the limitations in FTE research by taking a landscape approach to develop a greater understanding of past spatiotemporal patterns of tree invasion, current spatial patterns of vegetation composition and structure, and potential future patterns of climate-driven tree invasion in the FTE. The setting for this research is Jefferson Park, a 260 ha subalpine parkland landscape in the Oregon High Cascades, USA. This study uses field plots, remotely sensed imagery, airborne Light Detection and Ranging (LiDAR), and simulation modeling to: 1) predictively map current fine-scale species distributions, vegetation structure, and tree ages; 2) reconstruct patterns of tree invasion over the last fifty years in subalpine meadows in relation to climatic conditions, landforms, microtopography, and seed dispersal limitations; and 3) develop a statistical model that projects future patterns of tree invasion into subalpine meadows under different climate scenarios in Jefferson Park. In chapter two, I generated fine-scale spatially-explicit predictions of current vegetation composition, structure, and tree ages in the Jefferson Park study area. Objectives of this chapter were threefold: 1) to characterize spatial patterns of tree ages, vegetation composition, and vegetation structure in a FTE landscape in the Oregon Cascades using predictive mapping; 2) determine how vegetation composition and structure were associated with gradients of environmental factors derived from multispectral satellite imagery and Light Detection and Ranging (LiDAR) data; and 3) determine if predictive mapping characterizations of tree age, vegetation composition, and vegetation structure were improved by the inclusion of LiDAR data. Predictive mapping of vegetation attributes was accomplished using gradient analysis with nearest neighbor imputation; integrating field plots, multispectral SPOT 5 satellite imagery, and LiDAR data. Vegetation composition was best described by SPOT 5 imagery and LiDAR-derived topography, while vegetation structure was best described by LiDAR-derived vegetation heights. Predictions of species occurrence were most accurate for tree species, moderate for shrub species and vegetation groups, and highly variable for graminoid species. Tree age, which was the most accurately predicted vegetation structure variable, indicates the study area was largely un-forested in 1600, gradually invaded by trees from 1600 to the 1920's, and rapidly invaded from the 1920's to 1980. Predictive mapping of vegetation structure variables such as basal area and stand density were subject to large amounts of error, possibly resulting from scale incompatibilities between vegetation patterns and plot size, and/or heterogeneous FTE landscapes where forest structure does not develop along consistent trajectories with stand age. This study suggests integrating multispectral satellite imagery, LiDAR data, and field plots can accurately predict fine-scale spatial characterizations of species distributions and tree invasion in the FTE. This study also indicates that sample design can influence spatial patterns of model uncertainty, which needs to be considered if predictive mapping of vegetation and sensitive ecosystems is a component of inventory and monitoring programs. In chapter three, I focused on quantifying spatiotemporal patterns of subalpine parkland tree invasion in Jefferson Park over the past five decades in relation multi-scale climatic and biophysical controls. LiDAR data provided previously unavailable fine-scale spatial characterizations of microtopography and vegetation structure. I utilized LiDAR, georeferenced field plots, and tree establishment reconstructions to quantify spatiotemporal patterns of tree invasion in relation to late season snow persistence, landform types, fine-scale topographic variability, distances from potential seed sources, and climate variation within 130 ha of the subalpine parkland landscape of Jefferson Park. Tree occurrence (i.e. tree presence in 2 m plots and grid cells) occurred in 7.75% of study area meadows in 1950 and increased to 34.7% in 2007. Landform types and finer-scale patterns of topography and vegetation structure influenced summer snow depth, which influenced temporal and spatial patterns of tree establishment. Tree invasion rates were higher on debris flow landforms, which had lower summer snow depth than glacial landforms, suggesting potentially rapid treeline responses to disturbance events. Tree invasion rates were strongly associated with reduced annual snow fall on glacial landforms, but not on debris flows. Tree establishment was spatially constrained to micro sites with high topographic positions and close proximity to overstory canopy, site conditions associated with low summer snow depth. Seed source limitations placed an additional species-specific spatial constraint on where trees invaded meadows. Climate and topography had an interactive effect, with trees establishing on higher topographic positions during both high snow/low temperature and low snow/high temperature periods, but had greater than expected establishment on lower topographic positions during low snow/high temperature periods. Within the context of larger landform types, topography and proximity to overstory trees constrained where trees established in the meadows, even during climate periods with higher temperatures and lower snowfall. Results of this study suggest large scale climate-driven models of vegetation change may overestimate treeline movement and meadow invasion, because they do not account for biophysical controls limiting tree establishment at multiple spatial scales. In chapter four, I used field data and analyses from chapter 3 to parameterize a spatially and temporally explicit statistical model of fine-scale tree invasion within 130 ha of the Jefferson Park study area. The model incorporated both the climatic and biophysical controls found in chapter 3 to influence tree invasion. The model was used in two ways: (1) to spatially project patterns of tree invasion from 1950 to 2007 in response to historical climate; and (2) to project future tree invasion of the study area from 2007 to 2064 under six different annual snowfall scenarios. Modeling addressed the following questions: (1) Can fine-scale (2 m pixel size) patterns of historical tree invasion be accurately predicted? (2) How sensitive is future tree invasion (and therefore meadow persistence) to different future snowfall scenarios? (3) Are non-climatic factors such as landforms and biotic interactions associated with different spatial patterns of tree invasion? From 1950 to 2007, simulated historical meadow area declined from 82% to 65% of the study area. Model outputs of historical area, spatial distributions, and spatial clustering of tree invasion generally agreed with independent validation, and suggest biotic interactions due to young tree establishment facilitation are important on glacial landforms but not debris flows. Simulations of future scenarios indicated meadow declined to 36 to 43% of the study area by 2064. Projected meadow area declined with reduced annual snow fall, but not under prolonged high and low snow fall periods. Meadows persisted under all future scenarios in 2064. This model suggests subalpine meadows may significantly decline under climate warming, but will still persist in 2064. Micro sites and recruitment limitation may be equally or more important factors than climate change in influencing subalpine landscape change, suggesting local high-elevation persistence of subalpine meadows under future climate warming.