Systems Simulation in Agriculture

Dent, J. B.; Blackie, Malcolm; Harrison, S. R.

doi:10.1007/978-94-011-6373-6

Cited by 137 publications

(69 citation statements)

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“…Departures from a 1-to-1 line through the origin indicate model inadequacy. For this end, the simultaneous F-test (Dent & Blackie 1979) was used to test the null hypothesis of slope = 1 and intercept = 0.…”

Section: Methodsmentioning

confidence: 99%

Spatial distribution and structure along ecological gradients: penaeid shrimps in a tropical estuarine habitat of Mexico

Pérez‐Castañeda¹,

Defeo

2004

Mar. Ecol. Prog. Ser.

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The spatial structure of salinity, submerged aquatic vegetation (SAV) and 4 shrimp (Farfantepenaeus spp.) populations along an estuarine habitat was evaluated seasonally, based on data gathered every 1 km along a 1-dimensional transect in Celestun Lagoon, Mexico. Geostatistical techniques were used to evaluate autocorrelation among data points along the transect, and to predict their spatial distribution by kriging. The estuarine habitat was characterized by persistent salinity gradients, decreasing from the seaward (1 km) to the inner (18 km) zone of the lagoon. SAV biomass was almost always spatially structured and best described by spherical variograms. Spatial partitioning between SAV species was evident: the seagrasses Halodule wrightii and Ruppia maritima dominated the seaward and central zones of the lagoon, respectively, whereas the green alga Chara fibrosa was constrained to the inner zone. Shrimp abundance also presented a marked spatial structure best described by spherical variograms. Spatial structure of shrimps, discriminated by species (F. aztecus, F. brasiliensis, F. duorarum and F. notialis) and population components (recruits, juveniles, subadults) was most evident in the Nortes season (i.e. the season of strong northerly winds) and poorly defined in the Dry season. Spatial partitioning among species and population components was not detectable. Total shrimps and recruits were generally most abundant close to the mouth of the lagoon, although juvenile and subadult abundance peaked farther from the mouth than recruits. Distance from the mouth was the most important factor determining the spatial distribution of shrimps along the estuarine habitat. At local scales, abundance and type of SAV beds were crucial factors determining the abundance and spatial distribution of shrimps. Analysis at different spatial scales allowed us to identify the importance of spatial structure in biotic and abiotic variables of this estuarine habitat.

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Section: Methodsmentioning

confidence: 99%

Spatial distribution and structure along ecological gradients: penaeid shrimps in a tropical estuarine habitat of Mexico

Pérez‐Castañeda¹,

Defeo

2004

Mar. Ecol. Prog. Ser.

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“…We used the model parameters obtained from the 0-100 cm interval to extrapolate the function to greater depth and to compare SOC content with actual data. The performance of the extrapolations was evaluated by regression analysis of predicted and observed values through comparison with the 1:1 relationship (Dent and Blackie 1979) and by the MPE. Relative contributions of the differences between the mean predicted and mean observed values (Ubias), slope bias (Uslope), and un-FIG.…”

Section: Estimates Of Deep Socmentioning

confidence: 99%

The Vertical Distribution of Soil Organic Carbon and Its Relation to Climate and Vegetation

Jobbágy

Jackson

2000

Ecological Applications

1,413

130

1,790

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Abstract. As the largest pool of terrestrial organic carbon, soils interact strongly with atmospheric composition, climate, and land cover change. Our capacity to predict and ameliorate the consequences of global change depends in part on a better understanding of the distributions and controls of soil organic carbon (SOC) and how vegetation change may affect SOC distributions with depth. The goals of this paper are (1) to examine the association of SOC content with climate and soil texture at different soil depths; (2) to test the hypothesis that vegetation type, through patterns of allocation, is a dominant control on the vertical distribution of SOC; and (3) to estimate global SOC storage to 3 m, including an analysis of the potential effects of vegetation change on soil carbon storage. We based our analysis on Ͼ2700 soil profiles in three global databases supplemented with data for climate, vegetation, and land use. The analysis focused on mineral soil layers.Plant functional types significantly affected the vertical distribution of SOC. The percentage of SOC in the top 20 cm (relative to the first meter) averaged 33%, 42%, and 50% for shrublands, grasslands, and forests, respectively. In shrublands, the amount of SOC in the second and third meters was 77% of that in the first meter; in forests and grasslands, the totals were 56% and 43%, respectively. Globally, the relative distribution of SOC with depth had a slightly stronger association with vegetation than with climate, but the opposite was true for the absolute amount of SOC. Total SOC content increased with precipitation and clay content and decreased with temperature. The importance of these controls switched with depth, climate dominating in shallow layers and clay content dominating in deeper layers, possibly due to increasing percentages of slowly cycling SOC fractions at depth. To control for the effects of climate on vegetation, we grouped soils within climatic ranges and compared distributions for vegetation types within each range. The percentage of SOC in the top 20 cm relative to the first meter varied from 29% in cold arid shrublands to 57% in cold humid forests and, for a given climate, was always deepest in shrublands, intermediate in grasslands, and shallowest in forests (P Ͻ 0.05 in all cases). The effect of vegetation type was more important than the direct effect of precipitation in this analysis. These data suggest that shoot/root allocations combined with vertical root distributions, affect the distribution of SOC with depth.Global SOC storage in the top 3 m of soil was 2344 Pg C, or 56% more than the 1502 Pg estimated for the first meter (which is similar to the total SOC estimates of 1500-1600 Pg made by other researchers). Global totals for the second and third meters were 491 and 351 Pg C, and the biomes with the most SOC at 1-3 m depth were tropical evergreen forests (158 Pg C) and tropical grasslands/savannas (146 Pg C).Our work suggests that plant functional types, through differences in allocation, help to control SOC distri...

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“…Some useful insights into the quality of predictions may be given by R² and the slope and intercept of the fitted line, and a good test for bias is the simultaneous F-test for slope=1 and intercept=0 (e.g. Dent and Blackie, 1979;Butler, 1993, Mayer et al 1994).…”

Section: Statistical Testsmentioning

confidence: 99%

Evaluating forest growth models

Vanclay

Skovsgaard

1997

Ecological Modelling

350

189

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Effective model evaluation is not a single, simple procedure, but comprises several interrelated steps that cannot be separated from each other or from the purpose and process of model construction. We draw attention to several statistical and graphical procedures that may be used both with data used for model calibration and with data used in the evaluation of the model. We emphasize that the validity of conclusions depends on the validity of assumptions. These principles should be kept in mind throughout model construction and evaluation.

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Systems Simulation in Agriculture

Cited by 137 publications

References 0 publications

Spatial distribution and structure along ecological gradients: penaeid shrimps in a tropical estuarine habitat of Mexico

Spatial distribution and structure along ecological gradients: penaeid shrimps in a tropical estuarine habitat of Mexico

The Vertical Distribution of Soil Organic Carbon and Its Relation to Climate and Vegetation

Evaluating forest growth models

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