Morales JM, Moorcroft PR, Matthiopoulos J, Frair JL, Kie JG, Powell RA, Merrill EH, Haydon DT.
Building the bridge between animal movement and population dynamics. Philosophical Transactions of the Royal Society B-Biological Sciences. 2010;365 :2289-2301.
AbstractWhile the mechanistic links between animal movement and population dynamics are ecologically obvious, it is much less clear when knowledge of animal movement is a prerequisite for understanding and predicting population dynamics. GPS and other technologies enable detailed tracking of animal location concurrently with acquisition of landscape data and information on individual physiology. These tools can be used to refine our understanding of the mechanistic links between behaviour and individual condition through 'spatially informed' movement models where time allocation to different behaviours affects individual survival and reproduction. For some species, socially informed models that address the movements and average fitness of differently sized groups and how they are affected by fission-fusion processes at relevant temporal scales are required. Furthermore, as most animals revisit some places and avoid others based on their previous experiences, we foresee the incorporation of long-term memory and intention in movement models. The way animals move has important consequences for the degree of mixing that we expect to find both within a population and between individuals of different species. The mixing rate dictates the level of detail required by models to capture the influence of heterogeneity and the dynamics of intra-and interspecific interaction.
morales_2289_2010.full_.pdf Desai AR, Helliker BR, Moorcroft PR, Andrews AE, Berry JA.
Climatic controls of interannual variability in regional carbon fluxes from top-down and bottom-up perspectives. Journal of Geophysical Research-Biogeosciences. 2010;115.
AbstractObservations of regional net ecosystem exchange (NEE) of CO(2) for 1997-2007 were analyzed for climatic controls on interannual variability (IAV). Quantifying IAV of regional (10(4)-10(6) km(2)) NEE over long time periods is key to understanding potential feedbacks between climate and the carbon cycle. Four independent techniques estimated monthly regional NEE for 10(4) km(2) in a spatially heterogeneous temperate-boreal transition region of the north central United States, centered on the Park Falls, Wisconsin, United States, National Oceanic and Atmospheric Administration tall tower site. These techniques included two bottom-up methods, based on flux tower upscaling and forest inventory based demographic modeling, respectively, and two top-down methods, based on tall tower equilibrium boundary layer budgets and tracer-transport inversion, respectively. While all four methods revealed a moderate carbon sink, they diverged significantly in magnitude. Coherence of relative magnitude and variability of NEE anomalies was strong across the methods. The strongest coherence was a trend of declining carbon sink since 2002. Most climatic controls were not strongly correlated with IAV. Significant controls on IAV were those related to hydrology, such as water table depth, and atmospheric CO(2). Weaker relationships were found with phenological controls such as autumn soil temperature. Hydrologic relationships were strongest with a 1 year lag, potentially highlighting a previously unrecognized predictor of IAV in this region. These results highlight a need for continued development of techniques to estimate regional IAV and incorporation of hydrologic cycling into couple carbon-climate models.
desai_etal_jgr_2010.pdf Yang WZ, Ni-Meister W, Kiang NY, Moorcroft PR, Strahler AH, Oliphant A.
A clumped-foliage canopy radiative transfer model for a Global Dynamic Terrestrial Ecosystem Model II: Comparison to measurements. Agricultural and Forest Meteorology. 2010;150 :895-907.
AbstractIn a previous paper, we developed an analytical clumped two-stream model (ACTS) of canopy radiative transfer from an analytical geometric-optical and radiative transfer (GORT) scheme (Ni-Meister et al., 2010). The ACTS model accounts for clumping of foliage and the influence of trunks in vegetation canopies for modeling of photosynthesis, radiative fluxes and surface albedo in dynamic global vegetation models (DGVMs), and particularly for the Ent Dynamic Global Terrestrial Ecosystem Model (DGTEM). This study evaluates the gap probability and transmittance estimates from the ACTS model by comparing the modeled results with ground-based data, as well as with the original full GORT model and a layered Beer's law scheme. The ground data used in this study include vertical profile measurements of incident photosynthetically active radiation (PAR) in (1) mixed deciduous forests in Morgan-Monroe State Forest, IN, USA, (2) coniferous forests in central Canada, (3) mixed deciduous forests in Harvard Forest, MA, and (4) ground lidar measurements of the canopy gap fraction in woodland in Australia.The model comparisons with these measurements demonstrate that the ACTS model achieves better or similar performance compared to the full GORT and the layered Beer's law schemes with regard to agreements with field measurements and computational cost. The ACTS model has excellent accuracy and flexibility to model the canopy gap probability and transmittance for various forest scenarios. Also, it has advantages relative to the currently widely used two-stream scheme through better radiation estimation for photosynthesis by accounting for the impact of both vertical and horizontal structure heterogeneity of complex vegetation on radiative transfer. Currently the ACTS is being implemented in Ent and will be further tested for how it improves surface energy balance and carbon flux estimates. (C) 2010 Elsevier B.V. All rights reserved.
yang_etal_2010_afm.pdf Kie JG, Matthiopoulos J, Fieberg J, Powell RA, Cagnacci F, Mitchell MS, Gaillard JM, Moorcroft PR.
The home-range concept: are traditional estimators still relevant with modern telemetry technology?. Philosophical Transactions of the Royal Society B-Biological Sciences. 2010;365 :2221-2231.
AbstractRecent advances in animal tracking and telemetry technology have allowed the collection of location data at an ever-increasing rate and accuracy, and these advances have been accompanied by the development of new methods of data analysis for portraying space use, home ranges and utilization distributions. New statistical approaches include data-intensive techniques such as kriging and nonlinear generalized regression models for habitat use. In addition, mechanistic home-range models, derived from models of animal movement behaviour, promise to offer new insights into how home ranges emerge as the result of specific patterns of movements by individuals in response to their environment. Traditional methods such as kernel density estimators are likely to remain popular because of their ease of use. Large datasets make it possible to apply these methods over relatively short periods of time such as weeks or months, and these estimates may be analysed using mixed effects models, offering another approach to studying temporal variation in space-use patterns. Although new technologies open new avenues in ecological research, our knowledge of why animals use space in the ways we observe will only advance by researchers using these new technologies and asking new and innovative questions about the empirical patterns they observe.
kie_etal_2010.pdf Hatala JA, Crabtree RL, Halligan KQ, Moorcroft PR.
Landscape-scale patterns of forest pest and pathogen damage in the Greater Yellowstone Ecosystem. Remote Sensing of Environment. 2010;114 :375-384.
AbstractPathogen and pest outbreaks are recognized as key processes in the dynamics of Western forest ecosystems, yet the spatial patterns of stress and mortality are often complex and difficult to describe in an explicit spatial context, especially when considering the concurrent effects of multiple agents. Blister rust, a fungal pathogen, and mountain pine beetle, an insect pest, are two dominant sources of stress and mortality to high-altitude whitebark pine within the Greater Yellowstone Ecosystem (GYE). In whitebark pine populations infested with blister rust or mountain pine beetle, the shift from green to red needles at the outer-most branches is an early sign of stress and infestation. In this analysis, we investigated a method that combines field surveys with a remote sensing classification and spatial analysis to differentiate the effects of these two agents of stress and mortality within whitebark pine. Hyperspectral remotely sensed images from the airborne HyMap sensor were classifled to determine the locations of stress and mortality in whitebark pine crowns through sub-pixel mixture-tuned matched-filter analysis in three areas of the GYE in September 2000 and July 2006. Differences in the spatial pattern of blister rust and mountain pine beetle infestation allowed us to separate areas dominated by mountain pine beetle versus blister rust by examining changes in the spatial scale of significant stress and mortality clusters computed by the Ripley's K algorithm. At two field sites the distance between clusters of whitebark pine stress and mortality decreased from 2000 to 2006, indicating domination by the patchy spatial pattern of blister rust infestation. At another site, the distance between significant stress and mortality clusters increased from 2000 to 2006, indicating that the contiguous pattern of mountain pine beetle infestation was the primary source of disturbance. Analysis of these spatial stress and mortality patterns derived from remote sensing yields insight to the relative importance of blister rust and mountain pine beetle dynamics in the landscape. (C) 2009 Elsevier Inc. All rights reserved.
hatala_etal_rse_2010.pdf Hurtt GC, Fisk J, Thomas RQ, Dubayah R, Moorcroft PR, Shugart HH.
Linking models and data on vegetation structure. Journal of Geophysical Research-Biogeosciences. 2010;115.
AbstractFor more than a century, scientists have recognized the importance of vegetation structure in understanding forest dynamics. Now future satellite missions such as Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI) hold the potential to provide unprecedented global data on vegetation structure needed to reduce uncertainties in terrestrial carbon dynamics. Here, we briefly review the uses of data on vegetation structure in ecosystem models, develop and analyze theoretical models to quantify model-data requirements, and describe recent progress using a mechanistic modeling approach utilizing a formal scaling method and data on vegetation structure to improve model predictions. Generally, both limited sampling and coarse resolution averaging lead to model initialization error, which in turn is propagated in subsequent model prediction uncertainty and error. In cases with representative sampling, sufficient resolution, and linear dynamics, errors in initialization tend to compensate at larger spatial scales. However, with inadequate sampling, overly coarse resolution data or models, and nonlinear dynamics, errors in initialization lead to prediction error. A robust model-data framework will require both models and data on vegetation structure sufficient to resolve important environmental gradients and tree-level heterogeneity in forest structure globally.
hurtt_jgrg533_2010.pdf Albani M, Moorcroft PR, Ellison AM, Orwig DA, Foster DR.
Predicting the impact of hemlock woolly adelgid on carbon dynamics of eastern United States forests. Canadian Journal of Forest Research-Revue Canadienne De Recherche ForestiereCanadian Journal of Forest Research-Revue Canadienne De Recherche ForestiereCanadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere. 2010;40 :119-133.
AbstractThe hemlock woolly adelgid (HWA Adelges tsugae Annand) is ail introduced insect pest that threatens to decimate eastern hemlock (Tsuga canadensis (L.) Carriere) populations. In this study, we used the ecosystem demography model in conjunction with a stochastic model of HWA spread to predict the impact of HWA infestation oil the current and future forest composition, Structure, and carbon (C) dynamics in the eastern United States. The spread model predicted that oil average the hemlock stands south and east of the Great Lakes would be infested by 2015, southern Michigan would be reached by 2020, and northeastern Minnesota by 2030. For the period 2000-2040, the ecosystem demography model predicted a mean reduction of 0.011 Pg C.year(-1) (Pg C = 10(15) g C), in 8% decrease, in the uptake of carbon from eastern United States forests as a result of HWA-caused mortality, followed by an increased uptake of 0.015 Pg C.year(-1) (a 12% increase) in the period 2040-2100, as the area recovers from the loss of hemlock. Overall. we conclude that while locally severe, HWA infestation is unlikely to have a significant impact oil the regional patterns of carbon fluxes, given that eastern hemlock represents a limited friction of the standing biomass of eastern forests and that it has relatively low productivity compared with the tree species that are likely to replace it.
albani_etal_cjfr_2010.pdf Medvigy D, Wofsy SC, Munger JW, Moorcroft PR.
Responses of terrestrial ecosystems and carbon budgets to current and future environmental variability. Proc Natl Acad Sci USA. 2010;107 :8275-8280.
AbstractWe assess the significance of high-frequency variability of environmental parameters (sunlight, precipitation, temperature) for the structure and function of terrestrial ecosystems under current and future climate. We examine the influence of hourly, daily, and monthly variance using the Ecosystem Demography model version 2 in conjunction with the long-term record of carbon fluxes measured at Harvard Forest. We find that fluctuations of sunlight and precipitation are strongly and nonlinearly coupled to ecosystem function, with effects that accumulate through annual and decadal timescales. Increasing variability in sunlight and precipitation leads to lower rates of carbon sequestration and favors broad-leaved deciduous trees over conifers. Temperature variability has only minor impacts by comparison. We also find that projected changes in sunlight and precipitation variability have important implications for carbon storage and ecosystem structure and composition. Based on Intergovernmental Panel on Climate Change model estimates for changes in high-frequency meteorological variability over the next 100 years, we expect that terrestrial ecosystems will be affected by changes in variability almost as much as by changes in mean climate. We conclude that terrestrial ecosystems are highly sensitive to high-frequency meteorological variability, and that accurate knowledge of the statistics of this variability is essential for realistic predictions of ecosystem structure and functioning.
medvigy_etal_pnas_2010.pdf Ise T, Moorcroft PR.
Simulating boreal forest dynamics from perspectives of ecophysiology, resource availability, and climate change. Ecological Research. 2010;25 :501-511.
AbstractBoreal forests are under strong influences from climate change, and alterations in forest dynamics will have significant impacts on global climate-biosphere feedback as well as local to regional conservation and resource management. To understand the mechanisms of forest dynamics and to assess the fate of boreal forests, simulation studies should be based on plant ecophysiological responses onto environmental conditions. In central Canadian boreal forests, local geomorphology created by past glacial activities often generates a mosaic of very distinctive forest types. On sandy hilltop of a glacial till, due to limitations in moisture availability and short fire return intervals, drought-tolerant and fire-adapted jack pine usually becomes the dominant species. On mesic and nutrient-rich slopes, fast-growing and resource-demanding trembling aspen forms mixed forests with coniferous species. In bottomland, black spruce, slowly growing but tolerant species, is often the only species that can survive to the adult stage. These three very distinctive forest types often occur within a scale of 10 m. Simulation models of boreal forests should be able to reproduce this heterogeneity in forest structure and composition as an emergent property of plant ecophysiological responses to varying environmental properties. In this study, a process-based forest dynamics model, ecosystem demography model version 1.0, is used to mechanically reproduce the landscape heterogeneity due to edaphic variations. First, boreal tree species of northern Manitoba, Canada, are parameterized according to field observations, and, to explicitly capture interactions among tree saplings, allometric equations based on diameter at height of 0.15 m, instead of the conventional breast height of 1.37 m, is parameterized. Then, soil moisture regime and nutrient concentrations are statistically incorporated from a dataset. The resultant simulation successfully reproduces the distinctive forest dynamics influenced by the edaphic heterogeneity. The sequences of succession and the trajectories of forest development are generally consistent with the field observations. The differences in resource availability are the essential control on equilibrium values of total forest leaf area index. Next, to show the effect of anthropogenic atmospheric changes, changes in temperature and CO2 concentrations are studied by a set of factorial experiments. The magnitude of CO2 fertilization is largely affected by soil fertility. The temperature rise will increase the length of growing season, but can have a negative impact on forest growth by increasing aridity and autotrophic respiration. Overall, the boreal forest responses to climate change are complex due to the inherent edaphic variations and ecophysiological responses.
ise_etal_2010.pdf Smouse PE, Focardi S, Moorcroft PR, Kie JG, Forester JD, Morales JM.
Stochastic modelling of animal movement. Philosophical Transactions of the Royal Society B-Biological Sciences. 2010;365 :2201-2211.
AbstractModern animal movement modelling derives from two traditions. Lagrangian models, based on random walk behaviour, are useful for multi-step trajectories of single animals. Continuous Eulerian models describe expected behaviour, averaged over stochastic realizations, and are usefully applied to ensembles of individuals. We illustrate three modern research arenas. (i) Models of homerange formation describe the process of an animal 'settling down', accomplished by including one or more focal points that attract the animal's movements. (ii) Memory-based models are used to predict how accumulated experience translates into biased movement choices, employing reinforced random walk behaviour, with previous visitation increasing or decreasing the probability of repetition. (iii) Levy movement involves a step-length distribution that is over-dispersed, relative to standard probability distributions, and adaptive in exploring new environments or searching for rare targets. Each of these modelling arenas implies more detail in the movement pattern than general models of movement can accommodate, but realistic empiric evaluation of their predictions requires dense locational data, both in time and space, only available with modern GPS telemetry.
smouse_etal_2010.pdf