scholarly journals Choosing what is left: the spatial structure of a wild herbivore population within a livestock-dominated landscape

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8945
Author(s):  
Milagros Antún ◽  
Ricardo Baldi
Keyword(s):  
Spatial Structure ◽  
Land Surface ◽  
Domestic Sheep ◽  
Related Factors ◽  
Lama Guanicoe ◽  
Argentine Patagonia ◽  
Surface Models ◽  
Natural Landscapes ◽  
Density Surface ◽  
Stocking Rates

Shrublands and grasslands comprise over 30% of the land surface and are among the most exploited ecosystems for livestock production. Across natural landscapes, the distribution and abundance of wild herbivores are affected by interspecific competition for foraging resources, hunting and the development of infrastructure among other factors. In Argentine Patagonia, the abundance of domestic sheep grazing on native vegetation outnumbers the widely distributed guanaco (Lama guanicoe) and sheep ranching monopolizes the most productive lands. In this work, we aimed to assess the spatial variation in the abundance of guanacos in Península Valdés, a representative landscape of Patagonia, investigating the incidence of natural and human-related factors. We conducted ground surveys during the austral autumn in 2017 totaling 383.4 km along areas with and without sheep ranching. We built density surface models to account for the variation in guanaco abundance and obtained a map of guanaco density at a resolution of 4 km2. We estimated an overall density of 11.71 guanacos.km−2 for a prediction area of 3,196 km2, although the density of guanacos tripled in areas where sheep ranching was terminated (in around 20% of the surface of Península Valdés) compared to areas with sheep. Guanacos were more abundant at lower values of primary productivity and sheep stocking rates and further from inhabited ranch buildings, suggesting competition with sheep and conflict with humans. Although guanacos selected open, grass-dominated habitats across sheep-free sites, fences dividing properties and paddocks played a significant role in the spatial structure of their population in Península Valdés affecting negatively the abundance of guanacos. Our results indicate that actions to improve habitat connectivity for guanacos, favor the coexistence among guanacos and sheep ranching, and promote responsible human activities and attitudes towards wildlife are needed.

Analysis of the spatial variation in the abundance of lesser rheas using density surface models

2018 ◽  
Vol 45 (1) ◽  
pp. 47 ◽  
Author(s):  
Milagros Antún ◽  
Ricardo Baldi ◽  
Lucas M. Bandieri ◽  
Romina L. D' Agostino
Keyword(s):  
Spatial Variation ◽  
Vegetation Index ◽  
Austral Summer ◽  
High Resolution Data ◽  
Argentine Patagonia ◽  
Lesser Rhea ◽  
Normalised Difference Vegetation Index ◽  
Surface Models ◽  
Density Surface ◽  
Sampling Procedures

Context The study of the spatial variation in abundance of wild populations and the identification of factors explaining the observed patterns are key both to understand aspects of basic ecology and the effects of human activities. This is usually difficult to evaluate for low-density and widely distributed species, such as the lesser rhea (Rhea pennata pennata), an endemic bird from South America. Recent advances in spatial modelling such as the density surface models (DSM) combine distance-sampling procedures with modelling techniques to produce maps of spatial variation in abundance, and its relationship with predictive variables. Aims We aimed to analyse the spatial distribution and abundance of lesser rhea, and the variables that affect its abundance in Península Valdés (PV) Argentine Patagonia. Methods We conducted 338.4 km of ground surveys of lesser rheas in PV during the end of the Austral summer of 2015. Spatial models were constructed using DSM. Ecological and human-related variables were included in the models to account for variation in the abundance of animals at 4-km2 spatial resolution. Key results We estimated an overall density of 0.44 birds km–2 (CV = 32%) for the prediction area of 3320 km2. High values of normalised difference vegetation index, a correlate of plant productivity, were associated with increased numbers of lesser rheas. The location of ranch buildings, indicators of human presence, had a strong negative effect on lesser rheas, although their abundance increased at high sheep stocking rates. Conclusions As reported by previous studies in different sites, the abundance of lesser rheas in our study area was low. The use of DSM allowed a detailed examination of the spatial variation, as well as the variables involved and the uncertainty of the prediction. Implications The use of DSM techniques can be a useful tool for conservation planning and monitoring. Spatial, high-resolution data combined with knowledge on the factors affecting the number of animals are crucial to target specific conservation actions and monitor their results, and should allow government agencies to make better decisions concerning conservation-oriented management.

scholarly journals Eco‐evolutionary optimality as a means to improve vegetation and land‐surface models

2021 ◽  
Author(s):  
Sandy P. Harrison ◽  
Wolfgang Cramer ◽  
Oskar Franklin ◽  
Iain Colin Prentice ◽  
Han Wang ◽  
...  
Keyword(s):  
Land Surface ◽  
Land Surface Models ◽  
Surface Models ◽  
Evolutionary Optimality

scholarly journals The CarboEurope Regional Experiment Strategy

2006 ◽  
Vol 87 (10) ◽  
pp. 1367-1380 ◽  
Author(s):  
A. J. Dolman ◽  
J. Noilhan ◽  
P. Durand ◽  
C. Sarrat ◽  
A. Brut ◽  
...  
Keyword(s):  
Land Surface ◽  
Major Product ◽  
State Variables ◽  
Land Surface Models ◽  
Quality Metric ◽  
Key Characteristics ◽  
Surface Models ◽  
Global Soil ◽  
Standard Deviations ◽  
Model Agreement

The Second Global Soil Wetness Project (GSWP-2) is an initiative to compare and evaluate 10-year simulations by a broad range of land surface models under controlled conditions. A major product of GSWP-2 is the first global gridded multimodel analysis of land surface state variables and fluxes for use by meteorologists, hydrologists, engineers, biogeochemists, agronomists, botanists, ecologists, geographers, climatologists, and educators. Simulations by 13 land models from five nations have gone into production of the analysis. The models are driven by forcing data derived from a combination of gridded atmospheric reanalyses and observations. The resulting analysis consists of multimodel means and standard deviations on the monthly time scale, including profiles of soil moisture and temperature at six levels, as well as daily and climatological (mean annual cycle) fields for over 50 land surface variables. The monthly standard deviations provide a measure of model agreement that may be used as a quality metric. An overview of key characteristics of the analysis is presented here, along with information on obtaining the data.

scholarly journals Permafrost temperature and active-layer thickness of Yakutia with 0.5-degree spatial resolution for model evaluation

2013 ◽  
Vol 5 (2) ◽  
pp. 305-310 ◽  
Author(s):  
C. Beer ◽  
A. N. Fedorov ◽  
Y. Torgovkin
Keyword(s):  
Layer Thickness ◽  
Spatial Resolution ◽  
Active Layer ◽  
Land Surface ◽  
Grid Cell ◽  
Active Layer Thickness ◽  
East Siberia ◽  
Permafrost Temperature ◽  
Surface Models ◽  
The Mean

Abstract. Based on the map of landscapes and permafrost conditions in Yakutia (Merzlotno-landshaftnaya karta Yakutskoi0 ASSR, Gosgeodeziya SSSR, 1991), rasterized maps of permafrost temperature and active-layer thickness of Yakutia, East Siberia were derived. The mean and standard deviation at 0.5-degree grid cell size are estimated by assigning a probability density function at 0.001-degree spatial resolution. The gridded datasets can be accessed at the PANGAEA repository (doi:10.1594/PANGAEA.808240). Spatial pattern of both variables are dominated by a climatic gradient from north to south, and by mountains and the soil type distribution. Uncertainties are highest in mountains and in the sporadic permafrost zone in the south. The maps are best suited as a benchmark for land surface models which include a permafrost module.

scholarly journals Discontinuous Daily Temperatures in the WATCH Forcing Datasets

2015 ◽  
Vol 16 (1) ◽  
pp. 465-472 ◽  
Author(s):  
Henning W. Rust ◽  
Tim Kruschke ◽  
Andreas Dobler ◽  
Madlen Fischer ◽  
Uwe Ulbrich
Keyword(s):  
Land Surface ◽  
Water Cycle ◽  
Research Unit ◽  
Climatic Research Unit ◽  
Daily Maximum ◽  
Monthly Means ◽  
Tropical Africa ◽  
Average Temperature ◽  
Surface Models ◽  
The Tropics

Abstract The Water and Global Change (WATCH) forcing datasets have been created to support the use of hydrological and land surface models for the assessment of the water cycle within climate change studies. They are based on 40-yr ECMWF Re-Analysis (ERA-40) or ECMWF interim reanalysis (ERA-Interim) with temperatures (among other variables) adjusted such that their monthly means match the monthly temperature dataset from the Climatic Research Unit. To this end, daily minimum, maximum, and mean temperatures within one calendar month have been subjected to a correction involving monthly means of the respective month. As these corrections can be largely different for adjacent months, this procedure potentially leads to implausible differences in daily temperatures across the boundaries of calendar months. We analyze day-to-day temperature fluctuations within and across months and find that across-months differences are significantly larger, mostly in the tropics and frigid zones. Average across-months differences in daily mean temperature are typically between 10% and 40% larger than their corresponding within-months average temperature differences. However, regions with differences up to 200% can be found in tropical Africa. Particularly in regions where snowmelt is a relevant player for hydrology, a few degrees Celsius difference can be decisive for triggering this process. Daily maximum and minimum temperatures are affected in the same regions, but in a less severe way.

scholarly journals Evaluation and Comparison of Noah and Pleim–Xiu Land Surface Models in MM5 Using GÖTE2001 Data: Spatial and Temporal Variations in Near-Surface Air Temperature

2007 ◽  
Vol 46 (10) ◽  
pp. 1587-1605 ◽  
Author(s):  
J-F. Miao ◽  
D. Chen ◽  
K. Borne
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Land Surface ◽  
Model Performance ◽  
Surface Air Temperature ◽  
Near Surface ◽  
Surface Models ◽  
Urban Heat ◽  
Soil Moisture Initialization ◽  
Evident Difference

Abstract In this study, the performance of two advanced land surface models (LSMs; Noah LSM and Pleim–Xiu LSM) coupled with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), version 3.7.2, in simulating the near-surface air temperature in the greater Göteborg area in Sweden is evaluated and compared using the GÖTE2001 field campaign data. Further, the effects of different planetary boundary layer schemes [Eta and Medium-Range Forecast (MRF) PBLs] for Noah LSM and soil moisture initialization approaches for Pleim–Xiu LSM are investigated. The investigation focuses on the evaluation and comparison of diurnal cycle intensity and maximum and minimum temperatures, as well as the urban heat island during the daytime and nighttime under the clear-sky and cloudy/rainy weather conditions for different experimental schemes. The results indicate that 1) there is an evident difference between Noah LSM and Pleim–Xiu LSM in simulating the near-surface air temperature, especially in the modeled urban heat island; 2) there is no evident difference in the model performance between the Eta PBL and MRF PBL coupled with the Noah LSM; and 3) soil moisture initialization is of crucial importance for model performance in the Pleim–Xiu LSM. In addition, owing to the recent release of MM5, version 3.7.3, some experiments done with version 3.7.2 were repeated to reveal the effects of the modifications in the Noah LSM and Pleim–Xiu LSM. The modification to longwave radiation parameterizations in Noah LSM significantly improves model performance while the adjustment of emissivity, one of the vegetation properties, affects Pleim–Xiu LSM performance to a larger extent. The study suggests that improvements both in Noah LSM physics and in Pleim–Xiu LSM initialization of soil moisture and parameterization of vegetation properties are important.

scholarly journals On the utility of land surface models for agricultural drought monitoring

2012 ◽  
Vol 16 (9) ◽  
pp. 3451-3460 ◽  
Author(s):  
W. T. Crow ◽  
S. V. Kumar ◽  
J. D. Bolten
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Cross Correlation ◽  
Root Zone ◽  
Vegetation Indices ◽  
Agricultural Drought ◽  
Drought Monitoring ◽  
Global Evaluation ◽  
Land Surface Models ◽  
Surface Models

Abstract. The lagged rank cross-correlation between model-derived root-zone soil moisture estimates and remotely sensed vegetation indices (VI) is examined between January 2000 and December 2010 to quantify the skill of various soil moisture models for agricultural drought monitoring. Examined modeling strategies range from a simple antecedent precipitation index to the application of modern land surface models (LSMs) based on complex water and energy balance formulations. A quasi-global evaluation of lagged VI/soil moisture cross-correlation suggests, when globally averaged across the entire annual cycle, soil moisture estimates obtained from complex LSMs provide little added skill (< 5% in relative terms) in anticipating variations in vegetation condition relative to a simplified water accounting procedure based solely on observed precipitation. However, larger amounts of added skill (5–15% in relative terms) can be identified when focusing exclusively on the extra-tropical growing season and/or utilizing soil moisture values acquired by averaging across a multi-model ensemble.

Toward a Robust Canopy Hydrology Scheme with Precipitation Subgrid Variability

2007 ◽  
Vol 8 (3) ◽  
pp. 439-446 ◽  
Author(s):  
Dagang Wang ◽  
Guiling Wang
Keyword(s):  
Land Surface ◽  
Surface Characteristics ◽  
Hydrological Processes ◽  
Canopy Interception ◽  
Time Step ◽  
Covered Area ◽  
Surface Models ◽  
Physically Based ◽  
Interception Loss ◽  
The Impact

Abstract Representation of the canopy hydrological processes has been challenging in land surface modeling due to the subgrid heterogeneity in both precipitation and surface characteristics. The Shuttleworth dynamic–statistical method is widely used to represent the impact of the precipitation subgrid variability on canopy hydrological processes but shows unwanted sensitivity to temporal resolution when implemented into land surface models. This paper presents a canopy hydrology scheme that is robust at different temporal resolutions. This scheme is devised by applying two physically based treatments to the Shuttleworth scheme: 1) the canopy hydrological processes within the rain-covered area are treated separately from those within the nonrain area, and the scheme tracks the relative rain location between adjacent time steps; and 2) within the rain-covered area, the canopy interception is so determined as to sustain the potential evaporation from the wetted canopy or is equal to precipitation, whichever is less, to maintain somewhat wet canopy during any rainy time step. When applied to the Amazon region, the new scheme establishes interception loss ratios of 0.3 at a 10-min time step and 0.23 at a 2-h time step. Compared to interception loss ratios of 0.45 and 0.09 at the corresponding time steps established by the original Shuttleworth scheme, the new scheme is much more stable under different temporal resolutions.

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