scholarly journals Multi-scale assessment of a grassland productivity model

2021 ◽  
Vol 18 (6) ◽  
pp. 2213-2220
Author(s):  
Shawn D. Taylor ◽  
Dawn M. Browning

Abstract. Grasslands provide many important ecosystem services globally, and projecting grassland productivity in the coming decades will provide valuable information to land managers. Productivity models can be well calibrated at local scales but generally have some maximum spatial scale in which they perform well. Here we evaluate a grassland productivity model to find the optimal spatial scale for parameterization and thus for subsequently applying it in future productivity projections for North America. We also evaluated the model on new vegetation types to ascertain its potential generality. We find the model most suitable when incorporating only grasslands, as opposed to also including agriculture and shrublands, and only in the Great Plains and eastern temperate forest ecoregions of North America. The model was not well suited to grasslands in North American deserts or northwest forest ecoregions. It also performed poorly in agriculture vegetation, likely due to management activities, and shrubland vegetation, likely because the model lacks representation of deep water pools. This work allows us to perform long-term projections in areas where model performance has been verified, with gaps filled in by future modeling efforts.

2020 ◽  
Author(s):  
Shawn D. Taylor ◽  
Dawn M. Browning

Abstract. Grasslands provide many important ecosystem services globally and forecasting grassland productivity in the coming decades will provide valuable information to land managers. Productivity models can be well-calibrated at local scales, but generally have some maximum spatial extent in which they perform well. Here we evaluate a grassland productivity model to find the optimal spatial extent for parameterization, and thus for subsequently applying it in future forecasts for North America. We also evaluated the model on new vegetation types to ascertain its potential generality. We find the model most suitable when incorporating only grasslands, as opposed to also including agriculture and shrublands, and only in the Great Plains and Eastern Temperate Forest ecoregions of North America. The model was not well suited to grasslands in North American Deserts or Northwest Forest ecoregions. It also performed poorly in agriculture vegetation, likely due to management activities, and shrubland vegetation, likely because the model lacks representation of deep water pools. This work allows us to perform long-term forecasts in areas where model performance has been verified, with gaps filled in by future modelling efforts.


1990 ◽  
Vol 122 (3) ◽  
pp. 579-581 ◽  
Author(s):  
R.W. Kieckhefer ◽  
N.C. Elliott

Coccinellids are a conspicuous group of aphidophagous predators in maize, Zea mays L., in the Northern Great Plains of the United States. Numerous studies have been conducted on the ecology of coccinellids in maize in North America (Ewert and Chiang 1966a, 1966b; Smith 1971; Foott 1973; Wright and Laing 1980; Corderre and Tourneur 1986; Corderre et al. 1987). However, there have been few long-term surveys of coccinellids in maize. Foott (1973) reported on the abundance of coccinellid species inhabiting maize in eastern Canada over a 4-year period; no surveys of this type have been reported for the Northern Great Plains. We sampled coccinellids in maize fields at three sites in eastern South Dakota for 13 consecutive years to determine the species inhabiting the crop and levels of variation in their abundances among sites and years.


2021 ◽  
Author(s):  
Sarah Redlich ◽  
Jie Zhang ◽  
Caryl Benjamin ◽  
Maninder Singh Dhillon ◽  
Jana Englmeier ◽  
...  

SummaryClimate and land-use change are key drivers of environmental degradation in the Anthropocene, but too little is known about their interactive effects on biodiversity and ecosystem services. Long-term data on biodiversity trends are currently lacking. Furthermore, previous ecological studies have rarely considered climate and land use in a joint design, did not achieve variable independence or lost statistical power by not covering the full range of environmental gradients.Here, we introduce a multi-scale space-for-time study design to disentangle effects of climate and land use on biodiversity and ecosystem services. The site selection approach coupled extensive GIS-based exploration and correlation heatmaps with a crossed and nested design covering regional, landscape and local scales. Its implementation in Bavaria (Germany) resulted in a set of study plots that maximizes the potential range and independence of environmental variables at different spatial scales.Stratifying the state of Bavaria into five climate zones and three prevailing land-use types, i.e. near-natural, agriculture and urban, resulted in 60 study regions covering a mean annual temperature gradient of 5.6–9.8 °C and a spatial extent of 380×360 km. Within these regions, we nested 180 study plots located in contrasting local land-use types, i.e. forests, grasslands, arable land or settlement (local climate gradient 4.5–10 °C). This approach achieved low correlations between climate and land-use (proportional cover) at the regional and landscape scale with |r ≤0.33| and |r ≤0.29|, respectively. Furthermore, using correlation heatmaps for local plot selection reduced potentially confounding relationships between landscape composition and configuration for plots located in forests, arable land and settlements.The suggested design expands upon previous research in covering a significant range of environmental gradients and including a diversity of dominant land-use types at different scales within different climatic contexts. It allows independent assessment of the relative contribution of multi-scale climate and land use on biodiversity and ecosystem services. Understanding potential interdependencies among global change drivers is essential to develop effective restoration and mitigation strategies against biodiversity decline, especially in expectation of future climatic changes. Importantly, this study also provides a baseline for long-term ecological monitoring programs.


2021 ◽  
Author(s):  
Douglas B. Bamforth

In this volume, Douglas B. Bamforth offers an archaeological overview of the Great Plains, the vast, open grassland bordered by forests and mountain ranges situated in the heart of North America. Synthesizing a century of scholarship and new archaeological evidence, he focuses on changes in resource use, continental trade connections, social formations, and warfare over a period of 15,000 years. Bamforth investigates how foragers harvested the grasslands more intensively over time, ultimately turning to maize farming, and examines the persistence of industrial mobile bison hunters in much of the region as farmers lived in communities ranging from hamlets to towns with thousands of occupants. He also explores how social groups formed and changed, migrations of peoples in and out of the Plains, and the conflicts that occurred over time and space. Significantly, Bamforth's volume demonstrates how archaeology can be used as the basis for telling long-term, problem-oriented human history.


Geoderma ◽  
2006 ◽  
Vol 133 (3-4) ◽  
pp. 160-172 ◽  
Author(s):  
Jingkuan Wang ◽  
Dawit Solomon ◽  
Johannes Lehmann ◽  
Xudong Zhang ◽  
Wulf Amelung

2006 ◽  
Vol 115 (1-4) ◽  
pp. 270-276 ◽  
Author(s):  
M.A. Liebig ◽  
J.R. Gross ◽  
S.L. Kronberg ◽  
J.D. Hanson ◽  
A.B. Frank ◽  
...  

Geosciences ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 157 ◽  
Author(s):  
Jiyang Zhang ◽  
Haochi Zheng ◽  
Xiaodong Zhang ◽  
Jeffrey VanLooy

Long-term snowfall change offers insight for understanding climate change, managing water resources, and assessing climate model performance, especially at regional scales where topography plays an important role in shaping regional climate and water availability. In this study, we examined the changes of annual snowfall using observations from 1961 to 2017 in central North America, a region with high contrast in topographic complexities. There is a general, yet distinct difference in the snowfall trends demarcated approximately along the 105° W meridian. To its east, which is dominated by plains, snowfall had increased overall, except in a limited area south of 42° N, where snowfall decreased slightly. To the west of 105° W, which is dominated by the Rocky Mountains, there was a wide spread of decreasing trend, with only two pockets of area at an elevation of >2000 m exhibiting increasing snowfall trends. Multiple linear regression analysis showed that, in addition to the average annual snowfall, snowfall trends significantly correlated with elevation in the mountain region and with average snow season temperature in the plains region, suggesting different mechanisms potentially shaping snowfall trends in the two regions.


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