Plant water relations of thornscrub shrub species, north-eastern Mexico

As an approach to understand how diurnal and seasonal plant water potentials (Ψ) are related to soil water-content and evaporative demand components, the responses of six thornscrub shrubs species (Havardia pallens, Acacia rigidula, Eysenhardtia texana, Diospyros texana, Randia rhagocarpa, and Bernardia myricaefolia) of the north-eastern region of Mexico to drought stress were investigated during the course of 1 year. All study species showed the typical diurnal pattern of variation in Ψ. That is, Ψ decreased gradually from predawn (Ψ_pd) maximal values to reach minima at midday (Ψ_md) and began to recover in the late afternoon. On a diurnal basis and with adequate soil water-content (>0.20 kg kg⁻¹), diurnal Ψ values differed among shrub species and were negatively and significantly (p<0.001) correlated with air temperature (r=−0.741 to −0.883) and vapor pressure deficit (r=−0.750 to −0.817); in contrast, a positive and significant (p<0.001) relationship was found to exist with relative humidity (r=0.758–0.842). On a seasonal basis, during the wettest period (soil water-content>0.20 kg kg⁻¹), higher Ψ_pd (−0.10 MPa) and Ψ_md (−1.16 MPa) values were observed in R. rhagocarpa, whereas lower figures (−0.26 and −2.73 MPa, respectively) were detected in A. rigidula. On the other hand, during the driest period (soil water-content<0.15 kg kg⁻¹), Ψ_pd and Ψ_md values were below −7.3 MPa; i.e. when shrubs species faced severe water deficit. Soil water-content at different soil layers, monthly mean relative humidity and monthly precipitation were significantly correlated with both Ψ_pd (r=0.538–0.953; p<0.01) and Ψ_md (r=0.431–0.906; p<0.05). Average soil water-content in the 0–50 cm soil depth profile explained between 70% and 87% of the variation in Ψ_pd. Results have shown that when gravimetric soil water-content values were above 0.15 kg kg⁻¹, Ψ_pd values were high and constant; below this threshold value, Ψ declined gradually. Among all shrub species, A. rigidula appeared to be the most drought tolerant of the six species since during dry periods it tends to sustain significantly higher Ψ_pd in relation to B. myricaefolia. The remaining species showed an intermediate pattern. It is concluded that the ability of shrub species to cope with drought stress depends on the pattern of water uptake and the extent to control water loss through the transpirational flux.     

Use of Thermal Infrared Multispectral Scanner (TIMS) imagery to investigate upslope particle size controls on arid piedmont morphology

Geomorphic differences between slopes backing two distinct desert piedmont types provide a proxy indicator for the kind of landform developed at the corresponding mountain base. Here, the term ‘bedrock pediment’ describes subaerial bedrock platforms that emanate from a mountain base while ‘alluvial slope’ describes suballuvial bedrock platforms that extend from the mountain. Mountain slopes backing bedrock pediments have been demonstrated to be mantled by larger clast sizes than corresponding slopes backing alluvial slopes in the Phoenix region, Arizona, USA. The present research focuses on using the disparate particle sizes between slopes backing bedrock pediments and alluvial slopes as an indicator for the piedmont form developed at the mountain base, and uses high-resolution remotely sensed digital data as a medium for quantitative landform assessments. A gravel + bedrock versus soil index developed from airborne midinfrared multispectral imagery acquired by the Thermal Infrared Multispectral Scanner (TIMS) indicates the presence of slopes mantled with larger particle sizes versus slopes mantled with smaller particle sizes and greater soil coverage. Two test areas confirm the applicability of this method and further demonstrate the usefulness of high-resolution midinfrared multispectral imagery as a geomorphic tool in arid regions.     

<Emphasis Type="Italic">Bosmina</Emphasis> remains in lake sediment as indicators of zooplankton community composition

We measured Bosmina spp. mucro and antennule lengths in surface sediment samples from Wisconsin lakes to test whether such measures could be used to reconstruct zooplankton community composition and size structure in paleolimnological studies. Our data set included 58 lakes of various depths, water chemistry, trophic state, macrophyte cover, and zooplankton community composition. We used non-metric multidimensional scaling ordination (NMS) and simple correlation analysis to assess whether mucro and antennule measurements reflect the zooplankton community size structure. Bosmina mucro length (r = 0.727, p < 0.05) and antennule length (r = 0.360, p < 0.05) correlated with the NMS axis, which essentially represents zooplankton community size structure. Bosmina mucro length correlated positively with the abundance of the large-bodied zooplankter Epischura lacustris (r = 0.364, p < 0.01), as well as Diacyclops thomasi (r = 0.256, p < 0.05), and Leptodiaptomus minutus (r = 0.578, p ≤ 0.001), but correlated negatively with the abundance of the small-bodied zooplankter Tropocyclops prasinus (r = −0.385, p < 0.01). Bosmina antennule length correlated positively with the abundance of L. minutus (r = 0.344, p < 0.01) and negatively with T. prasinus (r = −0.258, p < 0.05). This broad, spatial scale assessment supports the use of Bosmina mucro and antennule lengths as a proxy for zooplankton community size structure. Mucro length is a stronger indicator of zooplankton community size structure as seen in its strong correlation with the NMS axis 1 and the significant correlations with abundance of predatory copepods.     

Exploring some relationships between biological soil crusts, soil aggregation and wind erosion

A portable wind tunnel was used to test the contribution of biological and physical elements to overall soil aggregation on a soil dominated by biological soil crusts in south-eastern Australia. After moderate disturbance and simulated wind erosion, 90% of surface aggregates on the loamy soil and 76% on the sandy soil were dominated by biological elements (cryptogams). Lower levels of biological bonding were observed on the severely disturbed treatment. Linear regression indicated a significant positive relationship (r²=0·72) between biological soil crust cover and dry aggregation levels greater than 0·85mm. To maintain sediment transport below an erosion control target of 5gm⁻¹s⁻¹ for a 65kmh⁻¹ wind at 10m height, a crust cover of approximately 20% is required. When a multiple regression model which sequentially fitted biological crust cover and dry aggregation greater than 0·85mm was applied to the data, dry aggregation accounted for more of the variation in sediment transport rate than biological crust cover. These data were used to develop a conceptual model which integrates crust cover and dry aggregation, and provides a useful framework within which to predict the likely impacts of changes in soil crust cover and aggregation.     

The influence of seasonal and local weather conditions on rock surface changes on the shore platform at Kaikoura Peninsula, South Island, New Zealand

A traversing micro-erosion meter (TMEM) was used to measure micro-scale surface changes in a 45 cm² area of an intertidal mudstone shore platform on Kaikoura Peninsula, New Zealand, with hourly readings taken over 5 days for two seasons, within 4 h either side of low tide. For all monitoring events, the relative height of a total of 120 co-ordinates were obtained, resulting in 4200 and 4800 measurements for the summer and winter seasons respectively. Within seasons, samples were grouped according to the presence of rain or no rain. Significant changes were found in the micro-topography with variations in temperature and among rain and no rain sample groups. For both seasons, in the absence of rain, there were positive linear relationships between rock surface temperatures and rock surface elevations, and regression analysis explained 42.3% and 46.5% of this variation for the summer (y = 0.098 + 0.004x; p-value = 0.007) and winter (y = 0.007 + 0.012x; p-value < 0.001) seasons respectively. It is suggested that incorporating weather readings alongside measurements of surface change could not only improve extrapolations of shore platform erosion from short-term studies, but also differentiate fluctuations in rock surfaces due to changes in rock surface temperatures from other processes involved in shore platform erosion.     

Forest dynamics and the importance of place in western Honduras

Analyses of landscape change using remotely sensed satellite imagery constitute a large component of forest transition research, allowing for assessments of large areas. In the western highlands of Honduras is an area of complex forest dynamics (～45,000 ha) that has seen significant forest regeneration in recent years. However, analysis of the larger region (～500,000 ha) shows net forest loss. The comparative aspects highlight the importance of site selection and scale in forest transition analysis, a process often ignored in the land-use and land-cover change (LULCC) and forest transition literature. Results also highlight the importance of analyzing human-induced fragmentation at a variety of selected sites and a range of spatial scales, and producing quality, accurate forest cover and change maps.     

Deriving hillslope sediment budgets in wildfire-affected forests using fallout radionuclide tracers

Information on post-fire sediment and nutrient redistribution is required to underpin post-fire catchment management decisions. Fallout radionuclide budgets (²¹⁰Pb_xs, ¹³⁷Cs and ⁷Be) were derived to quantify soil redistribution and sediment yield in forested terrain following a moderately severe wildfire in a small (89 ha) water supply catchment in SE Australia. Application of these techniques in burnt terrain requires careful consideration of the partitioning of radionuclides between organic and mineral soil components. Beryllium-7 and ²¹⁰Pb_xs were shown to be closely associated with ash, litter and soil organic matter whereas ¹³⁷Cs was more closely associated with subsurface coarse mineral soil. Comparison of the three tracer budgets indicated that the dominant sediment source areas were ridgetops and steep valley sideslopes, from which burnt surface material was conveyed to the stream network via pre-existing gullies. Erosion was predominantly driven by sheetwash, enhanced by soil water repellency, and modified by bioturbation which both supplies subsurface sediment and provides sinks for erosive overland flow. Footslope and riparian zones were not important sediment source areas. The estimated event-based (wildfire and subsequent rainfall) sediment yield is 58 ± 25 t km^− 2, based on fallout ⁷Be measurements. The upper estimate of total particulate phosphorus yield (0.70 kg ha^− 1) is more than 10 times that at equivalent unburnt sites. This illustrates that, soon after fire, burnt eucalypt forest can produce nutrient loads similar to those of agricultural catchments. The tracer budgets indicate that wildfire is an important control on sediment and phosphorus inputs to the stream network over the decadal timeframe and the pulsed nature of this release is an important concern for water quality management.     

The response of drainage basins to the late Quaternary tectonics in the Sicilian side of the Messina Strait (NE Sicily)

Despite more than 40 yr of research attributing temporal changes in streambank erosion rates to subaerial processes, little quantitative information is available on the relationships between streambank erodibility (k_d) and critical shear stress (τ_c) and the environmental conditions and processes that enhance streambank erosion potential. The study goal was to evaluate temporal changes in k_d and τ_c from soil desiccation and freeze–thaw cycling. Soil erodibility and τ_c were measured monthly in situ using a multiangle, submerged jet test device. Soil moisture, temperature, and bulk density as well as precipitation, air temperature, and stream stage were measured continuously to determine changes in soil moisture content and state. Pairwise Mann–Whitney tests indicted k_d was 2.9 and 2.1 times higher (p < 0.0065) during the winter (December–March) than in the spring/fall (April–May, October–November) and the summer (June–September), respectively. Regression analysis showed 80% of the variability in k_d was explained by freeze–thaw cycling alone. Study results also indicated soil bulk density was highly influenced by winter weather conditions (r² = 0.86): bulk density was inversely related to both soil water content and freeze–thaw cycling. Results showed that significant changes in the resistance of streambank soils to fluvial erosion can be attributed to subaerial processes. Water resource professionals should consider the implications of increased soil erodibility during the winter in the development of channel erosion models and stream restoration designs.     

Indicators of vegetation productivity under a changing climate in British Columbia,Canada

Understanding the relationship between vegetation and climate is essential for predicting the impact of climate change on broad-scale landscape processes. Utilizing vegetation indicators derived from remotely sensed imagery, we present an approach to forecast shifts in the future distribution of vegetation. Remotely sensed metrics representing cumulative greenness, seasonality, and minimum cover have successfully been linked to species distributions over broad spatial scales. In this paper we developed models between a historical time series of Advanced Very High Resolution Radiometer (AVHRR) satellite imagery from 1987 to 2007 at 1 km spatial resolution with corresponding climate data using regression tree modeling approaches. We then applied these models to three climate change scenarios produced by the Canadian Centre for Climate Modeling and Analysis (CCCma) to predict and map productivity indices in 2065. Our results indicated that warming may lead to increased cumulative greenness in northern British Columbia and seasonality in vegetation is expected to decrease for higher elevations, while levels of minimum cover increase. The Coast Mountains of the Pacific Maritime region and high elevation edge habitats across British Columbia were forecasted to experience the greatest amount of change. Our approach provides resource managers with information to mitigate and adapt to future habitat dynamics. Forecasting vegetation productivity levels presents a novel approach for understanding the future implications of climate change on broad scale spatial patterns of vegetation.     

Cocoons and hatchlings ofAporrectodea caliginosa(Savigny 1826) (Oligochaeta: Lumbricidae) in Benghazi, Libya

Field and laboratory studies were conducted during the period May 1993–April 1994 on the cocoons and hatchlings ofAporrectodea calignosa(Savigny 1826), a common earthworm found in Benghazi, Libya. Cocoon production started in August 1993 and continued until April 1994. A positive correlation between soil moisture (r=0.74;p< 0.05) and cocoon production, and a negative one between soil temperature (r=−0.85;p< 0.05) on cocoon production were found. Mean incubation time was 47 days. Some cocoons contained a single worm (single hatchling) whereas the majority of them (68%) contained two, the first hatchling and second hatchling. The rate of change of body mass (F=2.18;p>0.05) and the average body mass (F=1.25;p>0.05) of the single, first and second hatchlings were similar.     

Modeling spatial and temporal change of soil erosion based on multi-temporal remotely sensed data

In order to monitor the pattern, distribution, and trend of land use/cover change (LUCC) and its impacts on soil erosion, it is highly appropriate to adopt Remote Sensing (RS) data and Geographic Information System (GIS) to analyze, assess, simulate, and predict the spatial and temporal evolution dynamics. In this paper, multi-temporal Landsat TM/ETM+ remotely sensed data are used to generate land cover maps by image classification, and the Cellular Automata Markov (CA_Markov) model is employed to simulate the evolution and trend of landscape pattern change. Furthermore, the Revised Universal Soil Loss Equation (RUSLE) is used to evaluate the situation of soil erosion in the case study mining area. The trend of soil erosion is analyzed according to total/average amount of soil erosion, and the rainfall (R), cover management (C), and support practice (P) factors in RUSLE relevant to soil erosion are determined. The change trends of soil erosion and the relationship between land cover types and soil erosion amount are analyzed. The results demonstrate that the CA_Markov model is suitable to simulate and predict LUCC trends with good efficiency and accuracy, and RUSLE can calculate the total soil erosion effectively. In the study area, there was minimal erosion grade and this is expected to continue to decline in the next few years, according to our prediction results.     

Soil disturbance by native animals along grazing gradients in an arid grassland

Domestic grazing animals that congregate around watering points in arid rangelands create clearly-defined trampling-induced grazing gradients. Grazing and trampling alter soil and vegetation condition, often leading to substantial reductions in ecological function. We measured foraging pits and mounds created by native soil foraging animals over 12 months at three watering points in a Chihuahuan Desert grassland, and hypothesized that the density and cover of their disturbances would increase with increasing distance from water. We recorded an average of 3756 disturbances ha⁻¹ and cover of 34.18 m² ha⁻¹ across the grazing gradients, which comprised mainly pits (43%) and mounds (25%) of heteromyid rodents, ants and spiders. Soil turnover was estimated at 1.43 m³ ha⁻¹. We detected no differences in density, cover, soil volume or composition of disturbances in relation to distance from water, but there were significant, though ill-defined, differences across the five sampling periods, with generally more activity in the warm–wet months. Small animal-created mounds and pits are important sources of soil and sinks for litter within grazing gradients, and may represent the only sites where plants can establish given a relaxation in grazing pressure.     

Increasing the spatial resolution of agricultural land cover maps using a Hopfield neural network

Land cover class composition of remotely sensed image pixels can be estimated using soft classification techniques increasingly available in many GIS packages. However, their output provides no indication of how such classes are distributed spatially within the instantaneous field of view represented by the pixel. Techniques that attempt to provide an improved spatial representation of land cover have been developed, but not tested on the difficult task of mapping from real satellite imagery. The authors investigated the use of a Hopfield neural network technique to map the spatial distributions of classes reliably using information of pixel composition determined from soft classification previously. The approach involved designing the energy function to produce a ‘best guess’ prediction of the spatial distribution of class components in each pixel. In previous studies, the authors described the application of the technique to target identification, pattern prediction and land cover mapping at the sub-pixel scale, but only for simulated imagery. We now show how the approach can be applied to Landsat Thematic Mapper (TM) agriculture imagery to derive accurate estimates of land cover and reduce the uncertainty inherent in such imagery. The technique was applied to Landsat TM imagery of small-scale agriculture in Greece and largescale agriculture near Leicester, UK. The resultant maps provided an accurate and improved representation of the land covers studied, with RMS errors for the Landsat imagery of the order of 0.1 in the new fine resolution map recorded. The results showed that the neural network represents a simple efficient tool for mapping land cover from operational satellite sensor imagery and can deliver requisite results and improvements over traditional techniques for the GIS analysis of practical remotely sensed imagery at the sub pixel scale.     

Is exotic plant invasion enhanced by a traditional wildlife habitat management technique?

Soil disturbance is a wildlife habitat management tool that retards succession and promotes early seral vegetation. Our objective was to determine responses of two invasive herbaceous species (Pennisetum ciliare and Salsola iberica) and native perennial grasses to disking on different soils. Two 10 ×40 m plots were delineated within each of 4 blocks on Ramadero loams and 4 blocks on Delmita fine sandy loams. On Delmita soils, canopy cover of P. ciliare, S. iberica, and native perennial grasses averaged across all years was not affected by disking (ANOVA, P>0.05). On Ramadero soils, P. ciliare canopy cover was similar (Tukey's, P>0.05) on control and disked plots for the first 4 years post-disturbance, but P. ciliare cover was 10-fold greater (Tukey's, P=0.02) the 5th year after disking on disked versus control plots. On Ramadero soils, S. iberica canopy cover averaged across all years was 221 times greater (ANOVA, P=0.05) on disked plots than on control plots. Disking did not affect native perennial grass canopy cover. Land managers should consider soil series when disking for wildlife management, as disking disturbance may exacerbate exotic plant ingress and establishment on certain soils.     

WyomingView: No-Cost Remotely Sensed Data for Geographic Education

Abstract

Learning enhanced by visual examples and remotely sensed imagery is a valuable classroom resource for teaching students geographic concepts in a meaningful context. Barriers to the use of imagery include difficulty finding appropriate imagery and the cost of moderate resolution satellite imagery. A program in Wyoming called WyomingView and analogous programs in other states are providing no-cost, preprocessed satellite imagery delivered over the Internet that can help teachers better communicate geospatial knowledge to their students.     

A diatom dataset and diatom-salinity inference model for southeast Australian estuaries and coastal lakes

To quantify the relationship between diatom species assemblages and the water chemistry of southeast Australian estuaries and coastal lakes, a new dataset of 81 modern diatom samples and water chemistry data was created. Three hundred and ninety-nine species from 53 genera were identified in 36 samples from 32 coastal water bodies in eastern Tasmania and 45 samples from 13 coastal water bodies in southern Victoria. Multivariate statistical analyses revealed that the sampling sites were primarily distributed along salinity and nutrient gradients, and that salinity, nitrate + nitrite, phosphate and turbidity explained independent portions of variance in the diatom data. Species salinity optima and tolerances were determined and a diatom-salinity inference model (WAinv r ² = 0.72, r ²jack = 0.58, RMSEP = 0.09 log ppt) was developed. This new information on diatom species’ salinity preferences provides a useful tool for quantitatively reconstructing salinity changes over time from diatom microfossils preserved in the sediments of a range of estuaries and coastal lakes in southeast Australia. This is valuable for studies investigating long-term human impacts and climate change in the region.     

Tree biomass and soil organic carbon densities across the Sudanese woodland savannah: A regional carbon sequestration study

Mean tree biomass and soil carbon (C) densities for 39 map sheet grids (1° lat. × 1.5° long.) covering the Acacia woodland savannah region of Sudan (10–16° N; 21–36° E) are presented. Data from the National Forest Inventory of Sudan, Harmonized World Soil Database and FAO Local Climate Estimator were used to calculate C densities, mean annual precipitation (MAP) and mean annual temperature (MAT). Above-ground biomass C and soil organic carbon (SOC, 1 m) densities averaged 112 and 5453 g C m⁻², respectively. Below-ground biomass C densities, estimated using root shoot ratios, averaged 33 g C m⁻². Biomass C densities and MAP increased southwards across the region while SOC densities were lowest in the centre of the region and increased westwards and eastwards. Both above-ground biomass C and SOC densities were significantly (p < 0.05) correlated with MAP (r_s = 0.84 and r_s = 0.34, respectively) but showed non-significant correlations with MAT (r_s = −0.22 and r_s = 0.24, respectively). SOC densities were significantly correlated with biomass C densities (r_s = 0.34). The results indicated substantial under stocking of trees and depletion of SOC, and potential for C sequestration. Up-to-date regional and integrated soil and forest inventories are required for planning improved land-use management and restoration.     

A new approach to quantifying soil temperature responses to changing air temperature and snow cover

Seasonal snow cover provides an effective insulating barrier, separating shallow soil (0.25 m) from direct localized meteorological conditions. The effectiveness of this barrier is evident in a lag in the soil temperature response to changing air temperature. The causal relationship between air and soil temperatures is largely because of the presence or absence of snow cover, and is frequently characterized using linear regression analysis. However, the magnitude of the dampening effect of snow cover on the temperature response in shallow soils is obscured in linear regressions. In this study the author used multiple linear regression (MLR) with dummy predictor variables to quantify the degree of dampening between air and shallow soil temperatures in the presence and absence of snow cover at four Greenland sites. The dummy variables defining snow cover conditions were z = 0 for the absence of snow and z = 1 for the presence of snow cover. The MLR was reduced to two simple linear equations that were analyzed relative to z = 0 and z = 1 to enable validation of the selected equations. Compared with ordinary linear regression of the datasets, the MLR analysis yielded stronger coefficients of multiple determination and less variation in the estimated regression variables.     

Physical and chemical properties of soils under some piñon-juniper-oak canopies in a semi-arid ecosystem in New Mexico

Piñon (Pinus edulis)-juniper (Juniperus monosperma)-ecosystems increased substantially in the western USA during the 20th century. Sustainability of these ecosystems primarily depends on soil quality and water availability. This study was undertaken with the objective of assessing the effect of tree species on soil physical quality in a semi-arid region in the western part of Sugarite Canyon, northeast of Raton, Colfax County, NM (37°56′32″N and 104°23′00″W) USA. Three cores and three bulk soil samples were obtained from the site under the canopy of three juniper, Gambel oak (Quercus gambelii) and piñon trees for 0–10 and 10–20 cm depths. These samples were analyzed for particle size distribution, soil bulk density (ρ_b), water stable aggregation (WSA), mean weight diameter (MWD) of aggregates, pH, electrical conductivity (EC) and soil organic carbon (SOC) and total nitrogen (TN) concentrations and stocks. Sand content was greater under juniper (48%) than oak (32%), whereas clay content followed the opposite trend. The ρ_b, WSA, MWD, pH and EC were similar under juniper, piñon, oak canopies for both depths. Estimated (from Philip and Green and Ampt infiltration models) and measured water infiltration parameters did not vary among these sites and were in accord with the values for ρ_b, WSA and MWD. The SOC concentrations and stocks were greater under oak (43.1 Mg ha⁻¹ for 0–10 and 37.5 Mg ha⁻¹ for 10–20 cm depths) than piñon (23.3 Mg ha⁻¹ for 0–10 and 18.5 Mg ha⁻¹ for 10–20 cm depths). The TN concentrations were greater under oak (3.4 g kg⁻¹) than piñon (1.7 g kg⁻¹) for the 0–10 cm depth only. Accumulation of detritus material under tree canopies reduced soil compaction and crusting caused by raindrop impact and increased SOC, and TN concentrations, and water infiltration. Coefficients of variation ranged from low to moderate for most soil properties except infiltration rate at 2.5 h, which was highly variable. Overall, soil quality for each site was good and soil aggregation, water infiltration and SOC concentrations were high, and soil ρ_b was low.     

The Coyote Brush Invasion of Southern California Grasslands and the Legacy of Mechanical Disturbance

This study investigates the recent invasion of exotic grasslands by coyote brush in La Jolla Valley, California. We test the “event dependent” hypothesis that mechanical disturbances during the past century were a key cause. To examine the relationship between past mechanical disturbances and vegetation dynamics we first conducted a review of the historical literature on practices of shrub removal and documented disturbance history using historical imagery. We next analyzed vegetation‐cover change over time using remotely sensed imagery and a vegetation map to document the history of native shrub advancement into exotic grassland by species association. Finally, we determined the topographic characteristics associated with different phases of shrub advancement. We found that mechanical disturbances historically varied by topography with upper and steeper slopes being least intensively disturbed. We found that shrub advancement rates, following release from grazing, varied by slope, elevation, and time period, and that Baccharis pilularis (coyote brush) was the main species to invade the more intensively disturbed sites at lower elevations. Our results indicate that mechanical disturbances played an important role in modifying the original vegetation cover with long‐lasting consequences, including a facilitating role for the subsequent Baccharis pilularis invasion. We concluded that the practice of grazing often included exotic mechanical disturbances that had long‐lasting impacts on native plants.