Search

Mountainous regions experience complex phenological behavior along climatic, vegetational and topographic gradients. In this paper, we use a MODIS time series of the Normalized Difference Vegetation Index (NDVI) to understand the causes of variations in spring and autumn timing from 2000 to 2015, for a landscape renowned for its biological diversity. By filtering for cover type, topography and disturbance history, we achieved an improved understanding of the effects of seasonal weather variation on land surface phenology (LSP). Elevational effects were greatest in spring and were more important than site moisture effects. The spring and autumn NDVI of deciduous forests were found to increase in response to antecedent warm temperatures, with evidence of possible cross-seasonal lag effects, including possible accelerated green-up after cold Januarys and early brown-down following warm springs. Areas that were disturbed by the hemlock woolly adelgid and a severe tornado showed a weaker sensitivity to cross-year temperature and precipitation variation, while low severity wildland fire had no discernable effect. Use of ancillary datasets to filter for disturbance and vegetation type improves our understanding of vegetation’s phenological responsiveness to climate dynamics across complex environmental gradients. [ABSTRACT FROM AUTHOR]

Efforts to monitor the broad-scale impacts of drought on forests often come up short. Drought is a direct stressor of forests as well as a driver of secondary disturbance agents, making a full accounting of drought impacts challenging. General impacts can be inferred from moisture deficits quantified using precipitation and temperature measurements. However, derived meteorological indices may not meaningfully capture drought impacts because drought responses can differ substantially among species, sites and regions. Meteorology-based approaches also require the characterization of current moisture conditions relative to some specified time and place, but defining baseline conditions over large, ecologically diverse regions can be as difficult as quantifying the moisture deficit itself. In contrast, remote sensing approaches attempt to observe immediate, secondary, and longer-term changes in vegetation response, yet they too are no panacea. Remote sensing methods integrate responses across entire mixed-vegetation pixels and rarely distinguish the effects of drought on a single species, nor can they disentangle drought effects from those caused by various other disturbance agents. Establishment of suitable baselines from remote sensing may be even more challenging than with meteorological data. Here we review broad-scale drought monitoring methods, and suggest that an integrated data-mining approach may hold the most promise for enhancing our ability to resolve drought impacts on forests. A big-data approach that integrates meteorological and remotely sensed data streams, together with other datasets such as vegetation type, wildfire occurrence and pest activity, can clarify direct drought effects while filtering indirect drought effects and consequences. This strategy leverages the strengths of meteorology-based and remote sensing approaches with the aid of ancillary data, such that they complement each other and lead toward a better understanding of drought impacts. [ABSTRACT FROM AUTHOR]

Eddy covariance data from regional flux networks are direct in situ measurement of carbon, water, and energy fluxes and are of vital importance for understanding the spatio-temporal dynamics of the the global carbon cycle. FLUXNET links regional networks of eddy covariance sites across the globe to quantify the spatial and temporal variability of fluxes at regional to global scales and to detect emergent ecosystem properties. This study presents an assessment of the representativeness of FLUXNET based on the recently released FLUXNET2015 data set. We present a detailed high resolution analysis of the evolving representativeness of FLUXNET through time. Results provide quantitative insights into the extent that various biomes are sampled by the network of networks, the role of the spatial distribution of the sites on the network scale representativeness at any given time, and how that representativeness has changed through time due to changing operational status and data availability at sites in the network. To realize the full potential of FLUXNET observations for understanding emergent ecosystem properties at regional and global scales, we present an approach for upscaling eddy covariance measurements. Informed by the representativeness of observations at the flux sites in the network, the upscaled data reflects the spatio-temporal dynamics of the carbon cycle captured by the in situ measurements. This study presents a method for optimal use of the rich point measurements from FLUXNET to derive an understanding of upscaled carbon fluxes, which can be routinely updated as new data become available, and direct network expansion by identifying regions poorly sampled by the current network. [ABSTRACT FROM AUTHOR]

Changing climate may pose a threat to forest tree species, forcing three potential population-level responses: toleration/adaptation, movement to suitable environmental conditions, or local extirpation. Assessments that prioritize and classify tree species for management and conservation activities in the face of climate change will need to incorporate estimates of the risk posed by climate change to each species. To assist in such assessments, we developed a set of four quantitative metrics of potential climate change pressure on forest tree species: (1) percent change in suitable area, (2) range stability over time, (3) range shift pressure, and (4) current realized niche occupancy. All four metrics are derived from climate change environmental suitability maps generated using the Multivariate Spatio-Temporal Clustering (MSTC) technique, which combines aspects of traditional geographical information systems and statistical clustering techniques. As part of the Forecasts of Climate-Associated Shifts in Tree Species (ForeCASTS) project, we calculated the predicted climate change pressure statistics for North American tree species using occurrence data from the USDA Forest Service Forest Inventory and Analysis (FIA) program. Of 172 modeled tree species, all but two were projected to decline in suitable area in the future under the Hadley B1 Global Circulation Model/scenario combination. Eastern species under Hadley B1 were predicted to experience a greater decline in suitable area and less range stability than western species, although predicted range shift did not differ between the regions. Eastern species were more likely than western species, on average, to be habitat generalists. Along with the consideration of important species life-history traits and of threats other than climate change, the metrics described here should be valuable for efforts to determine which species to target for monitoring efforts and conservation actions. [ABSTRACT FROM AUTHOR]

The article focuses on land surface phenology and its role in the development of national early warning system for forest disturbance. It discloses that its capacity to characterize normal expected conditions can be used in determining the area and time of change of vegetation. It asserts that deployment of operational observation and monitoring system, the establishment of change-detection system, and the addition of methods are the main consideration in the development of the system.

A multi-stressor risk assessment was conducted at Yuma Proving Ground, Arizona, as a demonstration of the Military Ecological Risk Assessment Framework. The focus of the assessment was a testing program at Cibola Range, which involved an Apache Longbow helicopter firing Hellfire missiles at moving targets, that is, M60-A1 tanks. This article focuses on the wildlife risk assessment for the helicopter overflight. The primary stressors were sound and the view of the aircraft. Exposure to desert mule deer (Odocoileus hemionus crooki) was quantified using Air Force sound contour programs NOISEMAP and MR_NMAP, which gave very different results. Slant distance from helicopters to deer was also used as a measure of exposure that integrated risk from sound and view of the aircraft. Exposure-response models for the characterization of effects consisted of behavioral thresholds in sound exposure level or maximum sound level units or slant distance. Available sound thresholds were limited for desert mule deer, but a distribution of slant-distance thresholds was available for ungulates. The risk characterization used a weight-of-evidence approach and concluded that risk to mule deer behavior from the Apache overflight is uncertain, but that no risk to mule deer abundance and reproduction is expected. [ABSTRACT FROM AUTHOR]

A multiple stressor risk assessment was conducted at Yuma Proving Ground, Arizona, as a demonstration of the Military Ecological Risk Assessment Framework (MERAF). The focus was a testing program at Cibola Range that involved an Apache Longbow helicopter firing Hellfire missiles at moving targets, that is, M60-A1 tanks. This article describes the ecological risk assessment, using the MERAF, for the tracked vehicle movement component of the testing program. The principal stressor associated with tracked vehicle movement was soil disturbance, and a resulting, secondary stressor was hydrological change. Water loss to desert wash vegetation was hypothesized to result from increased infiltration and/or evaporation associated with vehicle disturbances to surrounding desert pavement, potentially affecting mule deer as well as vegetation. The simulated exposure of wash vegetation to water loss was quantified using estimates of disturbed land area from a digital orthogonal quarter quadrangle aerial photo and field observations, a 30-m digital elevation model, the flow accumulation feature of ESRI ArcInfo GIS, and a two-step runoff process dependent on soil characteristics and the extent of disturbance. In all simulated scenarios, the absolute amount of water lost increased with distance from the disturbance downslope in the washes; however, the percentage of water lost was greatest in land areas immediately downslope of a disturbance. Potential effects on growth and survival of desert wash trees were quantified by comparing water availability from the hydrologic model to water volume thresholds required for wash trees to survive and persist, derived from a local study. For both the incremental risk of the test program and for the combination of test and pretest disturbances, this demonstration of MERAF found no significant risk to either wash vegetation growth and survival or mule deer abundance and reproduction. [ABSTRACT FROM AUTHOR]