cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5063/aa/nceas.184.2
title: NPP Cropland: Gridded Estimates for the Central U.S.A., 1982-1996

description: Net primary productivity (NPP) of agricultural regions, where most of the land is sown with a few well-studied crops, was estimated from crop harvested yield, as recorded in national agricultural statistics. The magnitudes and inter-annual variations in NPP of croplands in the US Mid-West were estimated using crop area and yield data from the US National Agricultural Statistics Service (NASS). Total NPP, including estimates of both above and below-ground components, was calculated from harvested yield data by (1) conversion from reporting units of yield of the crop product, usually in volume, to mass; (2) conversion from fresh weight to dry weight; (3) estimation of above-ground yield using crop harvest indices, defined as the ratio of economic product (e.g. grain) dry weight to plant above-ground dry weight; and (4) estimation of below-ground yield as a function of above-ground biomass. This approach was applied to corn, soybean, sorghum, sunflower, oats, barley, wheat and hay in Illinois, Indiana, Iowa, Michigan, Minnesota, North Dakota, Ohio and Wisconsin for 1992, and in Iowa from 1982 to 1996. Many counties in these eight states had over 70 per cent coverage of these crops. In Iowa, corn and soybean accounted for over 50 per cent of the land area in most counties. County-level NPP in 1992 ranged from 4 Mg/ha/yr (400 g/m2/yr, dry biomass, or 200 gC/m2/yr in terms of carbon content) in North Dakota, Wisconsin and Minnesota, to over 17 Mg/ha/yr (1700 g/m2/yr, dry biomass, or 850 gC/m2/yr) in central Iowa, Illinois and Ohio. Areas of highest NPP were dominated by corn and soybean cultivation. NPP for counties in Iowa varied between years by a factor of 2, with the lowest NPP in 1983 which had an unusually wet Spring, in 1988 which was a drought year, and in 1993 which experienced floods. A sensitivity analysis, conducted by varying harvest index and root:shoot ratio by 10-50 per cent, indicated that the limit of accuracy of the method is about 1 Mg/ha/yr (100 g/m2/yr, dry biomass).
DOI: 10.5063/aa/nceas.184.6
title: NPP Cropland: Gridded Estimates for the Central U.S.A., 1982-1996

description: Net primary productivity (NPP) of agricultural regions, where most of the land is sown with a few well-studied crops, was estimated from crop harvested yield, as recorded in national agricultural statistics. The magnitudes and inter-annual variations in NPP of croplands in the US Mid-West were estimated using crop area and yield data from the US National Agricultural Statistics Service (NASS). Total NPP, including estimates of both above and below-ground components, was calculated from harvested yield data by (1) conversion from reporting units of yield of the crop product, usually in volume, to mass; (2) conversion from fresh weight to dry weight; (3) estimation of above-ground yield using crop harvest indices, defined as the ratio of economic product (e.g. grain) dry weight to plant above-ground dry weight; and (4) estimation of below-ground yield as a function of above-ground biomass. This approach was applied to corn, soybean, sorghum, sunflower, oats, barley, wheat and hay in Illinois, Indiana, Iowa, Michigan, Minnesota, North Dakota, Ohio and Wisconsin for 1992, and in Iowa from 1982 to 1996. Many counties in these eight states had over 70 per cent coverage of these crops. In Iowa, corn and soybean accounted for over 50 per cent of the land area in most counties. County-level NPP in 1992 ranged from 4 Mg/ha/yr (400 g/m2/yr, dry biomass, or 200 gC/m2/yr in terms of carbon content) in North Dakota, Wisconsin and Minnesota, to over 17 Mg/ha/yr (1700 g/m2/yr, dry biomass, or 850 gC/m2/yr) in central Iowa, Illinois and Ohio. Areas of highest NPP were dominated by corn and soybean cultivation. NPP for counties in Iowa varied between years by a factor of 2, with the lowest NPP in 1983 which had an unusually wet Spring, in 1988 which was a drought year, and in 1993 which experienced floods. A sensitivity analysis, conducted by varying harvest index and root:shoot ratio by 10-50 per cent, indicated that the limit of accuracy of the method is about 1 Mg/ha/yr (100 g/m2/yr, dry biomass).
DOI: 10.5063/aa/nceas.184.7
title: NPP Cropland: Gridded Estimates for the Central U.S.A., 1982-1996

description: Net primary productivity (NPP) of agricultural regions, where most of the land is sown with a few well-studied crops, was estimated from crop harvested yield, as recorded in national agricultural statistics. The magnitudes and inter-annual variations in NPP of croplands in the US Mid-West were estimated using crop area and yield data from the US National Agricultural Statistics Service (NASS). Total NPP, including estimates of both above and below-ground components, was calculated from harvested yield data by (1) conversion from reporting units of yield of the crop product, usually in volume, to mass; (2) conversion from fresh weight to dry weight; (3) estimation of above-ground yield using crop harvest indices, defined as the ratio of economic product (e.g. grain) dry weight to plant above-ground dry weight; and (4) estimation of below-ground yield as a function of above-ground biomass. This approach was applied to corn, soybean, sorghum, sunflower, oats, barley, wheat and hay in Illinois, Indiana, Iowa, Michigan, Minnesota, North Dakota, Ohio and Wisconsin for 1992, and in Iowa from 1982 to 1996. Many counties in these eight states had over 70 per cent coverage of these crops. In Iowa, corn and soybean accounted for over 50 per cent of the land area in most counties. County-level NPP in 1992 ranged from 4 Mg/ha/yr (400 g/m2/yr, dry biomass, or 200 gC/m2/yr in terms of carbon content) in North Dakota, Wisconsin and Minnesota, to over 17 Mg/ha/yr (1700 g/m2/yr, dry biomass, or 850 gC/m2/yr) in central Iowa, Illinois and Ohio. Areas of highest NPP were dominated by corn and soybean cultivation. NPP for counties in Iowa varied between years by a factor of 2, with the lowest NPP in 1983 which had an unusually wet Spring, in 1988 which was a drought year, and in 1993 which experienced floods. A sensitivity analysis, conducted by varying harvest index and root:shoot ratio by 10-50 per cent, indicated that the limit of accuracy of the method is about 1 Mg/ha/yr (100 g/m2/yr, dry biomass).
DOI: 10.5063/aa/nceas.184.8
title: NPP Cropland: Gridded Estimates for the Central U.S.A., 1982-1996

description: Net primary productivity (NPP) of agricultural regions, where most of the land is sown with a few well-studied crops, was estimated from crop harvested yield, as recorded in national agricultural statistics. The magnitudes and inter-annual variations in NPP of croplands in the US Mid-West were estimated using crop area and yield data from the US National Agricultural Statistics Service (NASS). Total NPP, including estimates of both above and below-ground components, was calculated from harvested yield data by (1) conversion from reporting units of yield of the crop product, usually in volume, to mass; (2) conversion from fresh weight to dry weight; (3) estimation of above-ground yield using crop harvest indices, defined as the ratio of economic product (e.g. grain) dry weight to plant above-ground dry weight; and (4) estimation of below-ground yield as a function of above-ground biomass. This approach was applied to corn, soybean, sorghum, sunflower, oats, barley, wheat and hay in Illinois, Indiana, Iowa, Michigan, Minnesota, North Dakota, Ohio and Wisconsin for 1992, and in Iowa from 1982 to 1996. Many counties in these eight states had over 70 per cent coverage of these crops. In Iowa, corn and soybean accounted for over 50 per cent of the land area in most counties. County-level NPP in 1992 ranged from 4 Mg/ha/yr (400 g/m2/yr, dry biomass, or 200 gC/m2/yr in terms of carbon content) in North Dakota, Wisconsin and Minnesota, to over 17 Mg/ha/yr (1700 g/m2/yr, dry biomass, or 850 gC/m2/yr) in central Iowa, Illinois and Ohio. Areas of highest NPP were dominated by corn and soybean cultivation. NPP for counties in Iowa varied between years by a factor of 2, with the lowest NPP in 1983 which had an unusually wet Spring, in 1988 which was a drought year, and in 1993 which experienced floods. A sensitivity analysis, conducted by varying harvest index and root:shoot ratio by 10-50 per cent, indicated that the limit of accuracy of the method is about 1 Mg/ha/yr (100 g/m2/yr, dry biomass).
DOI: 10.5063/aa/nceas.185.1
title: NPP Grassland: Consistent Worldwide Site Estimates, 1954-1990

description: In many grasslands, aboveground net primary productivity (ANPP) is commonly estimated by measuring peak aboveground biomass. Estimates of belowground net primary productivity (BNPP), and consequently, total net primary productivity (NPP), are more difficult. We addressed one of the three main objectives of the Global Primary Productivity Data Initiative for grassland systems - to develop simple models or algorithms to estimate missing components of total system NPP. Any estimate of BNPP requires an accounting of total root biomass, the percentage of living biomass, and annual turnover of live roots. We derived a relationship using aboveground peak biomass and mean annual temperature as predictors of belowground biomass (r2 = 0.54; P=0.01). The percentage of live material was 0.6, based on published values. We used three different functions to describe root turnover: constant, a direct function of aboveground biomass, or as a positive exponential relationship with mean annual temperature. We tested the various models against a large database of global grassland NPP and the constant turnover and direct function models were approximately equally descriptive (r2 =0.31 and 0.37), while the exponential function had a stronger correlation with the measured values (r2=0.40) and had a better fit than the other two models at the productive end of the BNPP gradient. When applied to extensive data we assembled from two grassland sites with reliable estimates of total NPP, the direct function was most effective, especially at lower productivity sites. We provide some caveats for its use in systems that lie at the extremes of the grassland gradient and stress that there are large uncertainties associated with measured and modeled estimates of BNPP.
DOI: 10.5063/aa/nceas.185.2
title: NPP Grassland: Consistent Worldwide Site Estimates, 1954-1990

description: In many grasslands, aboveground net primary productivity (ANPP) is commonly estimated by measuring peak aboveground biomass. Estimates of belowground net primary productivity (BNPP), and consequently, total net primary productivity (NPP), are more difficult. We addressed one of the three main objectives of the Global Primary Productivity Data Initiative for grassland systems - to develop simple models or algorithms to estimate missing components of total system NPP. Any estimate of BNPP requires an accounting of total root biomass, the percentage of living biomass, and annual turnover of live roots. We derived a relationship using aboveground peak biomass and mean annual temperature as predictors of belowground biomass (r2 = 0.54; P=0.01). The percentage of live material was 0.6, based on published values. We used three different functions to describe root turnover: constant, a direct function of aboveground biomass, or as a positive exponential relationship with mean annual temperature. We tested the various models against a large database of global grassland NPP and the constant turnover and direct function models were approximately equally descriptive (r2 =0.31 and 0.37), while the exponential function had a stronger correlation with the measured values (r2=0.40) and had a better fit than the other two models at the productive end of the BNPP gradient. When applied to extensive data we assembled from two grassland sites with reliable estimates of total NPP, the direct function was most effective, especially at lower productivity sites. We provide some caveats for its use in systems that lie at the extremes of the grassland gradient and stress that there are large uncertainties associated with measured and modeled estimates of BNPP.
DOI: 10.5063/aa/nceas.185.3
title: NPP Grassland: Consistent Worldwide Site Estimates, 1954-1990

description: In many grasslands, aboveground net primary productivity (ANPP) is commonly estimated by measuring peak aboveground biomass. Estimates of belowground net primary productivity (BNPP), and consequently, total net primary productivity (NPP), are more difficult. We addressed one of the three main objectives of the Global Primary Productivity Data Initiative for grassland systems - to develop simple models or algorithms to estimate missing components of total system NPP. Any estimate of BNPP requires an accounting of total root biomass, the percentage of living biomass, and annual turnover of live roots. We derived a relationship using aboveground peak biomass and mean annual temperature as predictors of belowground biomass (r2 = 0.54; P=0.01). The percentage of live material was 0.6, based on published values. We used three different functions to describe root turnover: constant, a direct function of aboveground biomass, or as a positive exponential relationship with mean annual temperature. We tested the various models against a large database of global grassland NPP and the constant turnover and direct function models were approximately equally descriptive (r2 =0.31 and 0.37), while the exponential function had a stronger correlation with the measured values (r2=0.40) and had a better fit than the other two models at the productive end of the BNPP gradient. When applied to extensive data we assembled from two grassland sites with reliable estimates of total NPP, the direct function was most effective, especially at lower productivity sites. We provide some caveats for its use in systems that lie at the extremes of the grassland gradient and stress that there are large uncertainties associated with measured and modeled estimates of BNPP.
DOI: 10.5063/aa/nceas.185.4
title: NPP Grassland: Consistent Worldwide Site Estimates, 1954-1990

description: In many grasslands, aboveground net primary productivity (ANPP) is commonly estimated by measuring peak aboveground biomass. Estimates of belowground net primary productivity (BNPP), and consequently, total net primary productivity (NPP), are more difficult. We addressed one of the three main objectives of the Global Primary Productivity Data Initiative for grassland systems - to develop simple models or algorithms to estimate missing components of total system NPP. Any estimate of BNPP requires an accounting of total root biomass, the percentage of living biomass, and annual turnover of live roots. We derived a relationship using aboveground peak biomass and mean annual temperature as predictors of belowground biomass (r2 = 0.54; P=0.01). The percentage of live material was 0.6, based on published values. We used three different functions to describe root turnover: constant, a direct function of aboveground biomass, or as a positive exponential relationship with mean annual temperature. We tested the various models against a large database of global grassland NPP and the constant turnover and direct function models were approximately equally descriptive (r2 =0.31 and 0.37), while the exponential function had a stronger correlation with the measured values (r2=0.40) and had a better fit than the other two models at the productive end of the BNPP gradient. When applied to extensive data we assembled from two grassland sites with reliable estimates of total NPP, the direct function was most effective, especially at lower productivity sites. We provide some caveats for its use in systems that lie at the extremes of the grassland gradient and stress that there are large uncertainties associated with measured and modeled estimates of BNPP.
DOI: 10.5063/aa/nceas.186.1
title: NPP Tropical Forest: Consistent Worldwide Site Estimates, 1967-1999

description: It is clear that the currently available data on net primary production in tropical forests are extremely limited and that even our best estimates for this biome can only be thought of as rough approximations within wide bounds. Nevertheless, this study has provided a basis for evaluating the quality and utility of the data generated by past studies and of the NPP estimates that have been reported in the literature for tropical forests. Clearly, the most important knowledge gap is with respect to the belowground components of NPP in these ecosystems. In particular, fine root losses are likely to be a substantial proportion of NPP in many tropical forests, and they as yet remain unquantified. It is also clear that there have been many of the previous NPP studies in this biome have involved methodological problems and poor documentation. Henceforward, it is paramount that such studies be carefully designed and reported so as to avoid these pitfalls. A third issue that needs to be addressed is that of sampling bias and the lack of replication in either time or space for NPP studies in these forests. Given the very small and subjectively located plots that are the basis for most of the existing data, it is possible that the existing understanding of NPP processes in tropical forests is highly skewed toward the highest biomass patches (flat sites with large trees, no gaps) and is unrepresentative of the larger forest landscapes.
DOI: 10.5063/aa/nceas.186.2
title: NPP Tropical Forest: Consistent Worldwide Site Estimates, 1967-1999

description: It is clear that the currently available data on net primary production in tropical forests are extremely limited and that even our best estimates for this biome can only be thought of as rough approximations within wide bounds. Nevertheless, this study has provided a basis for evaluating the quality and utility of the data generated by past studies and of the NPP estimates that have been reported in the literature for tropical forests. Clearly, the most important knowledge gap is with respect to the belowground components of NPP in these ecosystems. In particular, fine root losses are likely to be a substantial proportion of NPP in many tropical forests, and they as yet remain unquantified. It is also clear that there have been many of the previous NPP studies in this biome have involved methodological problems and poor documentation. Henceforward, it is paramount that such studies be carefully designed and reported so as to avoid these pitfalls. A third issue that needs to be addressed is that of sampling bias and the lack of replication in either time or space for NPP studies in these forests. Given the very small and subjectively located plots that are the basis for most of the existing data, it is possible that the existing understanding of NPP processes in tropical forests is highly skewed toward the highest biomass patches (flat sites with large trees, no gaps) and is unrepresentative of the larger forest landscapes.
DOI: 10.5063/aa/nceas.186.3
title: NPP Tropical Forest: Consistent Worldwide Site Estimates, 1967-1999

description: It is clear that the currently available data on net primary production in tropical forests are extremely limited and that even our best estimates for this biome can only be thought of as rough approximations within wide bounds. Nevertheless, this study has provided a basis for evaluating the quality and utility of the data generated by past studies and of the NPP estimates that have been reported in the literature for tropical forests. Clearly, the most important knowledge gap is with respect to the belowground components of NPP in these ecosystems. In particular, fine root losses are likely to be a substantial proportion of NPP in many tropical forests, and they as yet remain unquantified. It is also clear that there have been many of the previous NPP studies in this biome have involved methodological problems and poor documentation. Henceforward, it is paramount that such studies be carefully designed and reported so as to avoid these pitfalls. A third issue that needs to be addressed is that of sampling bias and the lack of replication in either time or space for NPP studies in these forests. Given the very small and subjectively located plots that are the basis for most of the existing data, it is possible that the existing understanding of NPP processes in tropical forests is highly skewed toward the highest biomass patches (flat sites with large trees, no gaps) and is unrepresentative of the larger forest landscapes.
DOI: 10.5063/aa/nceas.186.4
title: Published data from tropical forest sites with data on forest biomass and at least one component of NPP, with documentation of the methods underlying these data (and associated references)

description: It is clear that the currently available data on net primary production in tropical forests are extremely limited and that even our best estimates for this biome can only be thought of as rough approximations within wide bounds. Nevertheless, this study has provided a basis for evaluating the quality and utility of the data generated by past studies and of the NPP estimates that have been reported in the literature for tropical forests. Clearly, the most important knowledge gap is with respect to the belowground components of NPP in these ecosystems. In particular, fine root losses are likely to be a substantial proportion of NPP in many tropical forests, and they as yet remain unquantified. It is also clear that there have been many of the previous NPP studies in this biome have involved methodological problems and poor documentation. Henceforward, it is paramount that such studies be carefully designed and reported so as to avoid these pitfalls. A third issue that needs to be addressed is that of sampling bias and the lack of replication in either time or space for NPP studies in these forests. Given the very small and subjectively located plots that are the basis for most of the existing data, it is possible that the existing understanding of NPP processes in tropical forests is highly skewed toward the highest biomass patches (flat sites with large trees, no gaps) and is unrepresentative of the larger forest landscapes.
DOI: 10.5063/aa/nceas.19.1
title: Insights on community dynamics from large-scale, long-term data: time series for zooplankton and environmental variates from 35 North American lakes

description: NCEAS-1998-2244-NonDist-Dataset: The NCEAS Community Dynamics Working Group brought together theoretical and empirical ecologists to evaluate the relative importance of intrinsic and extrinsic sources of variability in natural communities. We focused on zooplankton community dynamics, in part because we had access to extensive time series data on zooplankton community structure from 35 North American lakes. Thirty-four of the lakes were concentrated at 5 sites: the North Temperate Lakes LTER site in Wisconsin; the University of Notre Dame Environmental Research Center in Michigan; the Dorset Environmental Research Centre, the Experimental Lakes Area, and the Sudbury region, all in Ontario. We also have data for saline Mono Lake in California. Our database has many strengths, including the length of the time series (5-21 years); consistent sampling methodologies, particularly for zooplankton; and the availability of information on environmental factors, including phytoplankton, physical parameters, and water chemistry. Another unique aspect of our dataset is that it includes data from both undisturbed reference lakes and experimentally manipulated lakes. The whole-lake experiments include food web manipulations, nutrient enrichments, acidifications and limings, and an unplanned invasion of an exotic species. Some of the experimental manipulations are even replicated within and among sites, providing a unique opportunity to explore the extent to which responses to a particular perturbation are consistent across lakes. In addition to determining how manipulations change the dynamics of zooplankton communities, we are using the data from the reference lakes to establish bounds on