scholarly journals Assessing vegetation structure and ANPP dynamics in a grassland–shrubland Chihuahuan ecotone using NDVI–rainfall relationships

2015 ◽  
Vol 12 (10) ◽  
pp. 2907-2925 ◽  
Author(s):  
M. Moreno-de las Heras ◽  
R. Díaz-Sierra ◽  
L. Turnbull ◽  
J. Wainwright
Keyword(s):  
Plant Growth ◽  
Vegetation Change ◽  
Chihuahuan Desert ◽  
Net Primary Production ◽  
Summer Rainfall ◽  
Remotely Sensed ◽  
Shrub Encroachment ◽  
Grass Species ◽  
Natural Habitats ◽  
Herbaceous Vegetation

Abstract. Climate change and the widespread alteration of natural habitats are major drivers of vegetation change in drylands. In the Chihuahuan Desert, large areas of grasslands dominated by perennial grass species have transitioned over the last 150 years to shrublands dominated by woody species, accompanied by accelerated water and wind erosion. Multiple mechanisms drive the shrub-encroachment process, including precipitation variations, land-use change, and soil erosion–vegetation feedbacks. In this study, using a simple ecohydrological modelling framework, we show that herbaceous (grasses and forbs) and shrub vegetation in drylands have different responses to antecedent precipitation due to functional differences in plant-growth and water-use patterns. Therefore, shrub encroachment may be reflected in the analysis of landscape-scale vegetation–rainfall relationships. We analyse the structure and dynamics of vegetation at an 18 km2 grassland–shrubland ecotone in the northern edge of the Chihuahuan Desert (McKenzie Flats, Sevilleta National Wildlife Refuge, NM, USA) by investigating the relationship between decade-scale (2000–2013) records of remotely sensed vegetation greenness (MODIS NDVI) and antecedent rainfall. NDVI–rainfall relationships show a high sensitivity to spatial variations on dominant vegetation types across the grassland–shrubland ecotone, and provide biophysical criteria to (a) classify landscape types as a function of the spatial distribution of dominant vegetation and to (b) decompose the NDVI signal into partial components of annual net primary production (ANPP) for herbaceous vegetation and shrubs. Analysis of remotely sensed ANPP dynamics across the study site indicates that plant growth for herbaceous vegetation is particularly synchronized with monsoonal summer rainfall. For shrubs, ANPP is better explained by winter plus summer precipitation, overlapping the monsoonal period (June–September) of rain concentration. Our results suggest that shrub encroachment was not particularly active in this Chihuahuan ecotone for the period 2000–2013. However, future changes in the amount and temporal pattern of precipitation (i.e. reductions in monsoonal summer rainfall and/or increases in winter precipitation) may enhance the shrub-encroachment process, particularly in the face of expected upcoming increases in aridity for desert grasslands of the southwestern USA.

scholarly journals Assessing vegetation structure and ANPP dynamics in a grassland-shrubland Chihuahuan ecotone using NDVI-rainfall relationships

2015 ◽  
Vol 12 (1) ◽  
pp. 51-92 ◽  
Author(s):  
M. Moreno-de las Heras ◽  
R. Diaz-Sierra ◽  
L. Turnbull ◽  
J. Wainwright
Keyword(s):  
Primary Production ◽  
Vegetation Change ◽  
Chihuahuan Desert ◽  
Plant Biomass ◽  
Net Primary Production ◽  
Larrea Tridentata ◽  
Shrub Encroachment ◽  
Grass Species ◽  
Natural Habitats ◽  
Herbaceous Vegetation

Abstract. Climate change and the widespread alteration of natural habitats are major drivers of vegetation change in drylands. A classic case of vegetation change is the shrub-encroachment process that has been taking place over the last 150 years in the Chihuahuan Desert, where large areas of grasslands dominated by perennial grass species (black grama, Bouteloua eriopoda, and blue grama, B. gracilis) have transitioned to shrublands dominated by woody species (creosotebush, Larrea tridentata, and mesquite, Prosopis glandulosa), accompanied by accelerated water and wind erosion. Multiple mechanisms drive the shrub-encroachment process, including exogenous triggering factors such as precipitation variations and land-use change, and endogenous amplifying mechanisms brought about by soil erosion-vegetation feedbacks. In this study, simulations of plant biomass dynamics with a simple modelling framework indicate that herbaceous (grasses and forbs) and shrub vegetation in drylands have different responses to antecedent precipitation due to functional differences in plant growth and water-use patterns, and therefore shrub encroachment may be reflected in the analysis of landscape-scale vegetation–rainfall relationships. We analyze the structure and dynamics of vegetation at an 18 km2 grassland-shrubland ecotone in the northern edge of the Chihuahuan Desert (McKenzie Flats, Sevilleta National Wildlife Refuge, NM, USA) by investigating the relationship between decade-scale (2000–2013) records of medium-resolution remote sensing of vegetation greenness (MODIS NDVI) and precipitation. Spatial evaluation of NDVI-rainfall relationship at the studied ecotone indicates that herbaceous vegetation shows quick growth pulses associated with short-term (previous 2 months) precipitation, while shrubs show a slow response to medium-term (previous 5 months) precipitation. We use these relationships to (a) classify landscape types as a function of the spatial distribution of dominant vegetation, and to (b) decompose the NDVI signal into partial primary production components for herbaceous vegetation and shrubs across the study site. We further apply remote-sensed annual net primary production (ANPP) estimations and landscape type classification to explore the influence of inter-annual variations in seasonal precipitation on the production of herbaceous and shrub vegetation. Our results suggest that changes in the amount and temporal pattern of precipitation comprising reductions in monsoonal summer rainfall and/or increases in winter precipitation may enhance the shrub-encroachment process in desert grasslands of the American Southwest.

The germinable soil seedbank of Eucalyptus victrix grassy woodlands at Roy Hill station, Pilbara district, Western Australia

2004 ◽  
Vol 26 (1) ◽  
pp. 17 ◽  
Author(s):  
R. A. Graham ◽  
S. K. Florentine ◽  
J. E. D. Fox ◽  
T. M. Luong
Keyword(s):  
Species Composition ◽  
Western Australia ◽  
Perennial Grass ◽  
Summer Rainfall ◽  
Distribution Patterns ◽  
Grass Species ◽  
Surface Areas ◽  
Hill Station ◽  
Soil Seedbank ◽  
Germinable Seed

The paper reports soil seedbank species composition, of Eucalyptus victrix grassy woodlands, of the upper Fortescue River in the Pilbara District, Western Australia. In this study, our objectives were to investigate germinable soil seedbanks and species composition in response to three simulated seasons, using emergence. Variation in seed density from three depths was tested. Four field sites were sampled. Thirty samples were collected in late spring, after seed rain and before summer rainfall. From each sample spot, three soil depths (surface, 1–5, and 6–10 cm) were segregated from beneath surface areas of 100 cm2. Samples were later incubated in a glasshouse to simulate three different seasonal conditions (autumn, winter and spring). Germinating seedlings were recorded on emergence and grown until identified. Forty-one species germinated, comprising 11 grasses (7 annuals and 4 perennials), 25 annual herbs and 5 perennial herbs. Distribution patterns of germinable seed in both the important annual grass Eragrostis japonica and the perennial Eragrostis setifolia (a preferred cattle fodder species), suggest that seedbank accumulation differs among species and between sites. In part, this may be associated with the absence of grazing. Species with most total germinable seed were E. japonica (Poaceae; 603/m2), and the annual herbs Calotis multicaulis (Asteraceae; 346/m2), and Mimulus gracilis (Scrophulariaceae; 168/m2). Perennial grass seed was sparse. Spring simulation gave most germination (1059), followed by autumn (892) and winter (376) sets. Greatest species diversity was produced from the spring simulation (33 species), followed by autumn (26), and winter (22). Of the total germination, 92% came from 17 species that were represented in all three simulations. Of the 1227 grass seedlings counted, most were recruited from the surface soil (735), followed by the 5 (310) and 10 (182) cm depths. Marginally more grass seedlings germinated from the spring simulation (558) than the autumn set (523). Only 11.9% of grass germinants came from the winter simulation. All grass species recruited from the soil seedbanks had a C4 photosynthetic pathway. Except for Cenchrus ciliaris all grass species are native to Australia. Of the four sites sampled, one fenced to exclude cattle five years earlier had significantly more germination than the three unfenced sites. Seedbank sampling produced several new records for plants in the areas sampled.

scholarly journals Classification of Grass and Forb Species on Riverdike Using UAV LiDAR-Based Structural Indices

2021 ◽  
Vol 15 (3) ◽  
pp. 268-273
Author(s):  
Naoko Miura ◽  
Tomoyo F. Koyanagi ◽  
Susumu Yamada ◽  
Shigehiro Yokota ◽  
◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Imperata Cylindrica ◽  
Grass Species ◽  
Herbaceous Vegetation ◽  
Small Complex ◽  
Recent Developments ◽  
Aerial Vehicle ◽  
Conventional Systems ◽  
Structural Indices

Herbaceous vegetation on riverdikes plays an important role in preventing soil erosion, which, otherwise, may lead to the collapse of riverdikes and consequently, severe flooding. It is crucial for managers to keep suitable vegetation conditions, which include native grass species such as Imperata cylindrica, and to secure visibility of riverdikes for inspection. If managers can efficiently find where suitable grass and unsuitable forb species grow on vast riverdikes, it would help in vegetation management on riverdikes. Classification and quantification of herbaceous vegetation is a challenging task. It requires spatial resolution and accuracy high enough to recognize small, complex-shaped vegetation on riverdikes. Recent developments in unmanned aerial vehicle (UAV) technology combined with light detection and ranging (LiDAR) may offer the solution, since it can provide highly accurate, high-spatial resolution, and denser data than conventional systems. This paper aims to develop a model to classify grass and forb species using UAV LiDAR data alone. A combination of UAV LiDAR-based structural indices, V-bottom (presence of vegetation up to 50 cm from the ground) and V-middle (presence of vegetation 50–100 cm from the ground), was tested and validated in 94 plots owing to its ability to classify grass and forb species on riverdikes. The proposed method successfully classified the “upright” grass species and “falling” grass species / forb species with an accuracy of approximately 83%. Managers can efficiently prioritize the inspection areas on the riverdikes by using this method. The method is versatile and adjustable in other grassland environments.

scholarly journals Arsenic Uptake by Two Tolerant Grass Species: Holcus lanatus and Agrostis capillaris Growing in Soils Contaminated by Historical Mining

Plants ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 980
Author(s):  
Agnieszka Dradrach ◽  
Anna Karczewska ◽  
Katarzyna Szopka
Keyword(s):  
Plant Growth ◽  
Field Study ◽  
Greenhouse Experiment ◽  
Grass Species ◽  
Holcus Lanatus ◽  
Agrostis Capillaris ◽  
Soil Fertilization ◽  
Arsenic Uptake ◽  
Historical Mining ◽  
Commercial Cultivars

The study focused on two grass species Holcus lanatus and Agrostis capillaris abundant in the sites of former As mining and processing in the Sudetes. Arsenic uptake from soils was examined to assess a risk associated with its accumulation in grass shoots and to check its dependence on soil fertilization. The research involved a field study and greenhouse experiment. In the field study, soil and plant samples were collected from 33 sites with 72–98,400 mg/kg total soil As. Arsenic uptake by grasses differed widely. Both species indicated a strategy typical for eliminators, although As concentrations in more than 50% of the shoot samples exceeded 4 mg/kg, a maximum permissible value for fodder. In the greenhouse experiment, commercial cultivars of both species were grown in five soils containing 394–19,600 mg/kg, untreated and fertilized. All seedlings died in the soil with highest total As, and considerable phytotoxicity was observed in other soils, particularly in nonfertilized ones. Fertilization resulted in the improvement of plant growth and reduction of As uptake except for Agrostis capillaris fertilized with manure. Further research should focus on identifying tolerant genotypes growing in extremely enriched sites and analysis of factors that will efficiently reduce As phytoaccumulation.

scholarly journals Using APAR to Predict Aboveground Plant Productivity in Semi-Aid Rangelands: Spatial and Temporal Relationships Differ

2018 ◽  
Vol 10 (9) ◽  
pp. 1474 ◽  
Author(s):  
Rowan Gaffney ◽  
Lauren Porensky ◽  
Feng Gao ◽  
J. Irisarri ◽  
Martín Durante ◽  
...  
Keyword(s):  
Temporal Variation ◽  
Net Primary Production ◽  
Spatial Models ◽  
Remotely Sensed ◽  
Plant Functional Groups ◽  
Remotely Sensed Data ◽  
Temporal Models ◽  
Alternative Means ◽  
The Relationship ◽  
Over Time

Monitoring of aboveground net primary production (ANPP) is critical for effective management of rangeland ecosystems but is problematic due to the vast extent of rangelands globally, and the high costs of ground-based measurements. Remote sensing of absorbed photosynthetically active radiation (APAR) can be used to predict ANPP, potentially offering an alternative means of quantifying ANPP at both high temporal and spatial resolution across broad spatial extents. The relationship between ANPP and APAR has often been quantified based on either spatial variation across a broad region or temporal variation at a location over time, but rarely both. Here we assess: (i) if the relationship between ANPP and APAR is consistent when evaluated across time and space; (ii) potential factors driving differences between temporal versus spatial models, and (iii) the magnitude of potential errors relating to space for time transformations in quantifying productivity. Using two complimentary ANPP datasets and remotely sensed data derived from MODIS and a Landsat/MODIS fusion data product, we find that slopes of spatial models are generally greater than slopes of temporal models. The abundance of plant species with different structural attributes, specifically the abundance of C4 shortgrasses with prostrate canopies versus taller, more productive C3 species with more vertically complex canopies, tended to vary more dramatically in space than over time. This difference in spatial versus temporal variation in these key plant functional groups appears to be the primary driver of differences in slopes among regression models. While the individual models revealed strong relationships between ANPP to APAR, the use of temporal models to predict variation in space (or vice versa) can increase error in remotely sensed predictions of ANPP.

scholarly journals Trends in Woody and Herbaceous Vegetation in the Savannas of West Africa

2019 ◽  
Vol 11 (5) ◽  
pp. 576 ◽  
Author(s):  
Julius Y. Anchang ◽  
Lara Prihodko ◽  
Armel T. Kaptué ◽  
Christopher W. Ross ◽  
Wenjie Ji ◽  
...  
Keyword(s):  
Vegetation Change ◽  
Positive Association ◽  
Information Criterion ◽  
West African ◽  
Woody Vegetation ◽  
The West ◽  
Herbaceous Vegetation ◽  
Discernible Effect ◽  
Use Efficiency ◽  
Rain Use Efficiency

We assess 32 years of vegetation change in the West African Sudano-Sahelian region following the drought events of the 1970s and 1980s. Change in decadal mean rain use efficiency is used to diagnose trends in woody vegetation that is expected to respond more slowly to post-drought rainfall gains, while change in the slope of the productivity–rainfall relationship is used to infer changing herbaceous conditions between early and late periods of the time series. The linearity/non-linearity of the productivity–rainfall relationship and its impact on the interpretation of overall greening trends, and specific woody and herbaceous vegetation trends, is also examined. Our results show a mostly positive association between productivity and rainfall (69% of pixels), which can be best described as linear (32%) or saturating (37%). Choosing the ‘best’ model at a specific location using Akaike Information Criterion has no discernible effect on the interpretation of overall greening or herbaceous trends, but does influence the detection of trends in woody vegetation. We conclude that widespread recovery in woody vegetation is responsible for the post-drought greening phenomenon reported elsewhere for the Sahel and Sudanian sub-regions. Meanwhile, trends in herbaceous vegetation are less pronounced, with no consistent indication towards either herbaceous degradation or recovery.

Sign in / Sign up

Export Citation Format

Share Document