Upscaling as ecological information transfer: a simple framework with application to Arctic ecosystem carbon exchange

Transferring ecological information across scale often involves spatial aggregation, which alters information content and may bias estimates if the scaling process is nonlinear. Here, a potential solution, the preservation of the information content of fine-scale measurements, is highlighted using modeled net ecosystem exchange (NEE) of an Arctic tundra landscape as an example. The variance of aggregated normalized difference vegetation index (NDVI), measured from an airborne platform, decreased linearly with log(scale), resulting in a linear relationship between log(scale) and the scale-wise modeled NEE estimate. Preserving three units of information, the mean, variance and skewness of fine-scale NDVI observations, resulted in upscaled NEE estimates that deviated less than 4% from the fine-scale estimate. Preserving only the mean and variance resulted in nearly 23% NEE bias, and preserving only the mean resulted in larger error and a change in sign from CO₂ sink to source. Compressing NDVI maps by 70–75% using wavelet thresholding with the Haar and Coiflet basis functions resulted in 13% NEE bias across the study domain. Applying unique scale-dependent transfer functions between NDVI and leaf area index (LAI) decreased, but did not remove, bias in modeled flux in a smaller expanse using handheld NDVI observations. Quantifying the parameters of statistical distributions to preserve ecological information reduces bias when upscaling and makes possible spatial data assimilation to further reduce errors in estimates of ecological processes across scale.     

Combining top-down and bottom-up dynamics in land use modeling: exploring the future of abandoned farmlands in Europe with the Dyna-CLUE model

Land use change is the result of interactions between processes operating at different scales. Simulation models at regional to global scales are often incapable of including locally determined processes of land use change. This paper introduces a modeling approach that integrates demand-driven changes in land area with locally determined conversion processes. The model is illustrated with an application for European land use. Interactions between changing demands for agricultural land and vegetation processes leading to the re-growth of (semi-) natural vegetation on abandoned farmland are explicitly addressed. Succession of natural vegetation is simulated based on the spatial variation in biophysical and management related conditions, while the dynamics of the agricultural area are determined by a global multi-sector model. The results allow an exploration of the future dynamics of European land use and landscapes. The model approach is similarly suitable for other regions and processes where large scale processes interact with local dynamics.     

Confronting collinearity: comparing methods for disentangling the effects of habitat loss and fragmentation

Estimating the relative importance of habitat loss and fragmentation is necessary to estimate the potential benefits of specific management actions and to ensure that limited conservation resources are used efficiently. However, estimating relative effects is complicated because the two processes are highly correlated. Previous studies have used a wide variety of statistical methods to separate their effects and we speculated that the published results may have been influenced by the methods used. We used simulations to determine whether, under identical conditions, the following 7 methods generate different estimates of relative importance for realistically correlated landscape predictors: residual regression, model or variable selection, averaged coefficients from all supported models, summed Akaike weights, classical variance partitioning, hierarchical variance partitioning, and a multiple regression model with no adjustments for collinearity. We found that different methods generated different rankings of the predictors and that some metrics were strongly biased. Residual regression and variance partitioning were highly biased by correlations among predictors and the bias depended on the direction of a predictor’s effect (positive vs. negative). Our results suggest that many efforts to deal with the correlation between amount and fragmentation may have done more harm than good. If confounding effects are controlled and adequate thought is given to the ecological mechanisms behind modeled predictors, then standardized partial regression coefficients are unbiased estimates of the relative importance of amount and fragmentation, even when predictors are highly correlated.     

Changes in fox squirrel anti-predator behaviors across the urban–rural gradient

Predator stimuli created by humans in the urban environment may alter animals’ anti-predator behaviors. I hypothesized that habituation would cause anti-predator behaviors to decrease in urban settings in response to humans. Additionally, I hypothesized that populations habituated to humans would show reduced responses to other predator stimuli. I observed three populations of squirrels (urban, suburban and rural) responses to human approaches, red-tailed hawk vocalizations (Buteo jamaicensis) and coyote (Canis latrans) vocalizations. Mahalanobis distances of anti-predator behaviors in response to human approaches were consistent with the urban–rural gradient. Flight initiation distances (X ² = 26.33, df = 2, P < 0.001) and amount of time dedicated to anti-predator behavior (X ² = 10.94, df = 2, P = 0.004) in response to human approaches were also consistent with the urban–rural gradient. Supporting the habituation hypothesis, naive juvenile squirrels increased flight initiation distances (X ² = 35.89, df = 1, P < 0.001) and time dedicated to anti-predator behaviors (X ² = 9.46, df = 1, P = 0.002) relative to adult squirrels in the same urban environment. Time dedicated to anti-predator behaviors differed among all three sites in response to both coyote (X ² = 9.83, df = 2, P = 0.007) and hawk (X ² = 6.50, df = 2, P = 0.035) vocalizations. Responses to both vocalizations on rural sites (coyote = 45%, hawk = 55%) greater than twice that found on the urban sites (coyote = 11%, hawk = 20%). This is possibly the first case of a transfer of habituation demonstrated under field conditions.     

Effects of water table management on soil salinity and alfalfa yield in a semi-arid climate

A lysimeter experiment was conducted to investigate the effect of water table management (WTM) on distribution of soil salinity and annual alfalfa (Medicago scutellata) yield. Subirrigations with three levels of water table namely, 0.5 (WT0.5), 0.7 (WT0.7), and 1.0 m (WT1.0) and a free drainage (FD) conventional irrigation treatment were selected for this study. All treatments were arranged in a complete randomized block design with three replicates. The results of this study indicated that the average soil electrical conductivity of the saturated extract (ECe) in the root zone gradually increased and exceeded the designated crop threshold value (4 dS/m) after the first forage harvest in subirrigated lysimeters. A higher salt accumulation was observed at the WT0.5 treatment. The average dry matter yield of annual alfalfa in WT0.5 and WT0.7 treatments was found to be 52 and 73% higher compared with the control treatment, respectively.     

Bahiagrass crop coefficients from eddy correlation measurements in central Florida

Bahiagrass (Paspalum notatum) is a warm-season grass used primarily in pastures and along highways and other low maintenance public areas in Florida. It is also used in landscapes to some extent because of its drought tolerance. Bahiagrass can survive under a range of moisture conditions from no irrigation to very wet conditions. Its well-watered consumptive use has not been reported previously. In this study, bahiagrass crop coefficients (K _c) for an irrigated pasture were determined for July 2003 through December 2006 in central Florida. The eddy correlation method was used to estimate crop evapotranspiration (ET_c) rates. The standardized reference evapotranspiration (ET_o) equation (ASCE-EWRI standardization of reference evapotranspiration task committee report, 2005) was applied to calculate ET_o values using on site weather data. Daily K _c values were estimated from the ratio of the measured ET_c and the calculated ET_o. The recommended K _c values for bahiagrass are 0.35 for January–February, 0.55 for March, 0.80 for April, 0.90 for May, 0.75 for June, 0.70 for July–August, 0.75 for September, 0.70 for October, 0.60 for November, and 0.45 for December in central Florida. The highest K _c value of 0.9 in May corresponded with maximum vapor pressure deficit conditions as well as cloud free conditions and the highest incoming solar radiation as compared to the rest of the year. During the summer (June to August), frequent precipitation events increased the cloud cover and reduced grass water use. The K _c annual trend was similar to estimated K _c values from another well-watered warm-season grass study in Florida.     

Estimation of actual evapotranspiration for a drip-irrigated Merlot vineyard using a three-source model

A study was performed in order to evaluate the three-source model (Clumped model) for direct estimation of actual evapotranspiration (ET_a) and latent heat flux (LE) over a drip-irrigated Merlot vineyard trained on a vertical shoot positioned system (VSP) under semi-arid conditions. The vineyard, with an average fractional cover of 30%, is located in the Talca Valley, Region del Maule, Chile. The performance of the Clumped model was evaluated using an eddy covariance system during the 2006/2007 and 2007/2008 growing seasons. Results indicate that the Clumped model was able to predict ET_a with a root mean square error (RMSE), mean bias error (MBE), and model efficiency (EF) of 0.33, −0.15 mm day⁻¹ and 74%, respectively. Also, the Clumped model simulated the daytime variation of LE with a RMSE of 36 W m⁻², MBE of −8 W m⁻², and EF of 83%. Major disagreement (underestimated values) between observed and estimated values of ET_a was found for clear days after rainfall or foggy days, but underestimated values were less than 10% of the data analysis. The results obtained in this study indicate that the Clumped model could be used to directly estimate vine water requirements for a drip-irrigated vineyard trained on a VSP. However, application of the Clumped model requires a good characterization of the drip-irrigated vineyard architecture.     

Induced thermotolerance and expression of heat shock protein 70 in sea cucumber <Emphasis Type="Italic">Apostichopus japonicus</Emphasis>

ABSTRACT:   Thermal limits, induced thermotolerance and the expression of heat shock protein 70 (Hsp70) in an echinoderm Apostichopus japonicus were studied. The sublethal and lethal temperatures for the juveniles were 30 and 34°C, respectively; a previous sublethal heat shock exposure (30°C, 2 h) could increase the survival rates of the sea cucumbers when they were exposed to 34°C. This induced thermotolerance could last for at least 2 days. Levels of Hsp70 increased substantially after sublethal heat shock exposure and linearly decreased with time. This result indicated that a close relationship existed between the induction of thermotolerance and the levels of Hsp70 in A. japonicus.