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Laurent, Ed
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Expertise Search
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Scott Robinson: Southeast Aquatic Resources Partnership
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Coordinator Scott Robinson addresses the obstacles of data collection, preparation, and development and how the LCCs can help standardized this process for all partners to use that will help professionals implement conservation actions.
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Our Community
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Voices from the Community
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Conservation Planning Process
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Dr. Robert Baldwin of Clemson University explains in this video the steps involved in the conservation planning process.
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Resources
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Archive GIS
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GIS & Planning
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Lee, Danny
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Danny is Director of the Eastern Forest Environmental Threat Assessment Center of the USDA Forest Service's Southern Research Station in Asheville, NC. He lead a diverse team of reearchers working to develop tools and information needed to detect, assess, and predict environmental treats to eastern forests.
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Expertise Search
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Analysis of monotonic greening and browning trends from global NDVI time-series
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Remotely sensed vegetation indices are widely used to detect greening and browning trends; especially the global coverage of time-series normalized difference vegetation index (NDVI) data which are available from 1981. Seasonality and serial auto-correlation in the data have previously been dealt with by integrating the data to annual values; as an alternative to reducing the temporal resolution, we apply harmonic analyses and non-parametric trend tests to the GIMMS NDVI dataset (1981–2006). Using the complete dataset, greening and browning trends were analyzed using a linear model corrected for seasonality by subtracting the seasonal component, and a seasonal non-parametric model. In a third approach, phenological shift and variation in length of growing season were accounted for by analyzing the time-series using vegetation development stages rather than calendar days. Results differed substantially between the models, even though the input data were the same. Prominent regional greening trends identified by several other studies were confirmed but the models were inconsistent in areas with weak trends. The linear model using data corrected for seasonality showed similar trend slopes to those described in previous work using linear models on yearly mean values. The non-parametric models demonstrated the significant influence of variations in phenology; accounting for these variations should yield more robust trend analyses and better understanding of vegetation trends.
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Resources
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Climate Science Documents
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Bird population trends are linearly affected by climate change along species thermal ranges
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Beyond the effects of temperature increase on local population trends and on species distribution shifts, how populations of a given species are affected by climate change along a species range is still unclear. We tested whether and how species responses to climate change are related to the populations locations within the species thermal range. We compared the average 20 year growth rates of 62 terrestrial breeding birds in three European countries along the latitudinal gradient of the species ranges. After controlling for factors already reported to affect bird population trends (habitat specialization, migration distance and body mass), we found that populations breeding close to the species thermal maximum have lower growth rates than those in other parts of the thermal range, while those breeding close to the species thermal minimum have higher growth rates. These results were maintained even after having controlled for the effect of latitude per se. Therefore, the results cannot solely be explained by latitudinal clines linked to the geographical structure in local spring warming. Indeed, we found that populations are not just responding to changes in temperature at the hottest and coolest parts of the species range, but that they show a linear graded response across their European thermal range. We thus provide insights into how populations respond to climate changes. We suggest that projections of future species distributions, and also management options and conservation assessments, cannot be based on the assumption of a uniform response to climate change across a species range or at range edges only.
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Resources
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Climate Science Documents
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Climate change hotspots in the United States
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We use a multi-model, multi-scenario climate model ensemble to identify climate change hotspots in the continental United States. Our ensemble consists of the CMIP3 atmosphere-ocean general circulation models, along with a high-resolution nested climate modeling system. We test both high (A2) and low (B1) greenhouse gas emissions trajectories, as well as two different statistical metrics for identifying regional climate change hotspots. We find that the pattern of peak responsiveness in the CMIP3 ensemble is persistent across variations in GHG concentration, GHG trajectory, and identification method. Areas of the southwestern United States and northern Mexico are the most persistent hotspots. The high-resolution climate modeling system produces highly localized hotspots within the basic GCM structure, but with a higher sensitivity to the identification method. Across the ensemble, the pattern of relative climate change hotspots is shaped primarily by changes in interannual variability of the contributing variables rather than by changes in the long-term mean
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Climate Science Documents
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A dispersal-induced paradox: synchrony and stability in stochastic metapopulations
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Understanding how dispersal influences the dynamics of spatially distributed populations is a major priority of both basic and applied ecologists. Two well-known effects of dispersal are spatial synchrony (positively correlated population dynamics at different points in space) and dispersal-induced stability (the phenomenon whereby populations have simpler or less extinction-prone dynamics when they are linked by dispersal than when they are isolated). Although both these effects of dispersal should occur simultaneously, they have primarily been studied separately. Herein, I summarise evidence from the literature that these effects are expected to interact, and I use a series of models to characterise that interaction. In particular, I explore the observation that although dispersal can promote both synchrony and stability singly, it is widely held that synchrony paradoxically prevents dispersal-induced stability. I show here that in many realistic scenarios, dispersal is expected to promote both synchrony and stability at once despite this apparent destabilising influence of synchrony. This work demonstrates that studying the spatial and temporal impacts of dispersal together will be vital for the conservation and management of the many communities for which human activities are altering natural dispersal rates.
Keywords
Autoregressive model, correlated environmental stochasticity, dispersal, dispersal-induced stability, metapopulation, negative binomial model, Ricker model, spatial heterogeneity, synchrony.
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Resources
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Climate Science Documents
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Climate Change Challenges and Opportunities for Global Health
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Editorial: Journal of the American Medical Association. Health is inextricably linked to climate change. It is important for clinicians to understand this relationship in order to discuss associated health risks with their patients and to inform public policy. To provide new US-based temperature projections from downscaledclimate modeling and to review recent studies on health risks related to climate change and the cobenefits of efforts to mitigate greenhouse gas emissions. We searched PubMed from 2009 to 2014 for articles related to climate change and health, focused on governmental reports, predictive models, and empirical epidemiological studies. Of the more than 250 abstracts reviewed, 56 articles were selected. In addition, we analyzed climate data averaged over 13 climate models and based future projections on downscaled probability distributions of the daily maximum temperature for 2046-2065. We also compared maximum daily 8-hour average with air temperature data taken from the National Oceanic and Atmospheric Administration National Climate Data Center. By 2050, many US cities may experience more frequent extreme heat days. For example, New York and Milwaukee may have 3 times their current average number of days hotter than 32°C (90°F). The adverse health aspects related to climate change may include heat-related disorders, such as heat stress and economic consequences of reduced work capacity; and respiratory disorders, including those exacerbated by fine particulate pollutants, such as asthma and allergic disorders; infectious diseases, including vectorborne diseases and water-borne diseases, such as childhood gastrointestinal diseases; food insecurity, including reduced crop yields and an increase in plant diseases; and mental health disorders, such as posttraumatic stress disorder and depression, that are associated with natural disasters. Substantial health and economic co-benefits could be associated with reductions in fossil fuel combustion. For example, the cost of greenhouse gas emission policies may yield net economic benefit, with health benefits from air quality improvements potentially offsetting the cost of US carbon policies. Evidence over the past 20 years indicates that climate change can be associated with adverse health outcomes. Health care professionals have an important role in understanding and communicating the related potential health concerns and the cobenefits from reducing greenhouse gas emissions.
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Climate Science Documents
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A paradigm shift in understanding and quantifying the effects of forest harvesting on floods in snow environments
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A well-established precept in forest hydrology is that any reduction of forest cover will always have a progressively smaller effect on floods with increasing return period. The underlying logic in snow environments is that during the largest snowmelt events the soils and vegetation canopy have little additional storage capacity and under these conditions much of the snowmelt will be converted to runoff regardless of the amount or type of vegetation cover. Here we show how this preconceived physical understanding, reinforced by the outcomes of numerous paired watershed studies, is indefensible because it is rationalized outside the flood frequency distribution framework. We conduct a meta-analysis of postharvest data at four catchments (3–37 km2) with moderate level of harvesting (33%–40%) to demonstrate how harvesting increases the magnitude and frequency of all floods on record (19–99 years) and how such effects can increase unchecked with increasing return period as a consequence of changes to both the mean (þ11% to þ35%) and standard deviation (12% to þ19%) of the flood frequency distribution. We illustrate how forest harvesting has substantially increased the frequency of the largest floods in all study sites regardless of record length and this also runs counter to the prevailing wisdom in hydrological science. The dominant process responsible for these newly emerging insights is the increase in net radiation associated with the conversion from longwave-dominated snowmelt beneath the canopy to shortwave-dominated snowmelt in harvested areas, further amplified or mitigated by basin characteristics such as aspect distribution, elevation range, slope gradient, amount of alpine area, canopy closure, and drainage density. Investigating first order environmental controls on flood frequency distributions, a standard research method in stochastic hydrology, represents a paradigm shift in the way harvesting effects are physically explained and quantified in forest hydrology literature.
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