Woody Vegetation Cover Research Articles

Landscape-level vegetation classification and fractional woody and herbaceous vegetation cover estimation over the dryland ecosystems by unmanned aerial vehicle platform

The change of fraction vegetation cover (FVC) is the key ecological index for vegetation dynamics of dryland ecosystem. However, it is difficult to directly map woody vegetation and herbaceous vegetation in the dryland from the satellite images due to the mixture of their distribution at small scale. Emerging UAV remote sensing provides a good opportunity to capture and quantify the distribution of the sparse vegetation in the drylands ecosystem. In this study, we proposed a new method to classify woody vegetation and herbaceous vegetation and calculate their FVC based on the high-resolution orthomosaic generated from UAV images by the machine learning algorithm of classification and regression tree (CART). This proposed method was validated and evaluated by visual interpretation, the detailed ground measurement dataset of 4832 trees and 18,798 shrubs and three popular machine learning algorithms of Support Vector Machine(SVM), Random Forest(RF), Gradient Boosting Decision Tree(GBDT). The overall assessments showed good overall accuracy (0.78), average accuracy (0.76), and the Kappa coefficient (0.64). The FVC of woody vegetation calculated from orthomosaic agreed well with that estimated from ground measurements. Both group of FVC have a stable linear relationship over different spatial scales. The proposed method showed higher efficiency of 166%, 111% and 290% than SVM, RF, GBDT respectively. A new optimized model was developed to reduce the workload of vegetation investigation and to design more efficient sampling strategies. The proposed method was incorporated into an interactive web-based software “UAV- High Resolution imagery Analysis Platform” (UAV-HiRAP, http://www.uav-hirap.org). Our study demonstrates that UAV-HiRAP combined with UAV platform can be a powerful tool to classify woody vegetation and herbaceous vegetation and calculate their FVC for sparse vegetation in the drylands. The new optimization model will inspire researchers to design more effective sampling strategies for future field investigation.

Beyond bioproductivity: Engaging local perspectives in land degradation monitoring and assessment

Land degradation monitoring and assessment in the Sahel zone has relied substantially on temporal trends of remote sensing-based vegetation indices, which are proxies for the bioproductivity of the land. However, prior studies have shown that negative or positive trends in bioproductivity are not necessarily associated with degradation or improvement of land condition. In this short communication, while acknowledging the contributions of remote sensing-based indices and global-scale datasets to dismantling an outdated desertification narrative, we argue that local land users have much to contribute to our understanding of land degradation, and particularly to ensuring that scientific assessments of degradation capture variables relevant to them. We used the participatory photo elicitation method in three sites in the Senegalese Ferlo in order to elicit local pastoralists' perspectives on land degradation and identify the indicators that they use to characterize pasture quality, while empowering them to lead the discussion. The discussion revealed indicators far beyond bioproductivity, including livestock performance as well as composition and quality of the herbaceous and woody vegetative cover, invasive species, soil quality and water availability. We found that the pastoralists’ knowledge and interest in the issue could potentially be harnessed more systematically, and at larger scales, in order to build a spatially explicit field-based knowledge base of land degradation complementary to remote sensing-based maps of trends in bioproductivity. Such a dataset could serve as a standalone product or as a reference dataset for development and validation of remote sensing-based indicators.

Impact of Soil Reflectance Variation Correction on Woody Cover Estimation in Kruger National Park Using MODIS Data

Time-series of imagery acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) has previously been used to estimate woody and herbaceous vegetation cover in savannas. However, this is challenging due to the mixture of woody and herbaceous plant functional types with specific contributions to the phenological signal and variations in soil background reflectance signatures observed from satellite. These factors cause variations in the accuracy and precision of woody cover estimates from different modelling approaches and datasets. Here, woody cover is estimated over Kruger National Park (KNP) from the MODIS 16-day composite time-series data using dry season NDVI/SAVI images and applying NDVIsoil determination methods. The woody cover estimates when NDVIsoil was ignored had R² = 0.40, p < 0.01, slope = 1.01, RMSE (root mean square error) = 15.26% and R² = 0.32, p < 0.03, slope = 0.79, RMSE = 16.39% for NDVIpixel and SAVIpixel, respectively, when compared to field plot data of plant functional type fractional cover. The woody cover estimated from the soil determination methods had a slope closer to 1 for both NDVI and SAVI but also a slightly higher RMSE. For a soil-invariant method, RMSE = 19.04% and RMSE = 17.34% were observed for NDVI and SAVI respectively, while for a soil-variant method, RMSE = 18.28% and RMSE = 19.17% were found for NDVI and SAVI. The woody cover estimated from all models had a high correlation and significant relationship with LiDAR/SAR based estimates and a woody cover map produced by Bucini. Woody cover maps are required for vegetation succession monitoring, grazing impact assessment, climate change mitigation and adaptation research and dynamic vegetation model validation.

Woody vegetation dynamics in the tropical and subtropical Andes from 2001 to 2014: Satellite image interpretation and expert validation.

The interactions between climate and land‐use change are dictating the distribution of flora and fauna and reshuffling biotic community composition around the world. Tropical mountains are particularly sensitive because they often have a high human population density, a long history of agriculture, range‐restricted species, and high‐beta diversity due to a steep elevation gradient. Here we evaluated the change in distribution of woody vegetation in the tropical Andes of South America for the period 2001–2014. For the analyses we created annual land‐cover/land‐use maps using MODIS satellite data at 250 m pixel resolution, calculated the cover of woody vegetation (trees and shrubs) in 9,274 hexagons of 115.47 km2, and then determined if there was a statistically significant (p < 0.05) 14 year linear trend (positive—forest gain, negative—forest loss) within each hexagon. Of the 1,308 hexagons with significant trends, 36.6% (n = 479) lost forests and 63.4% (n = 829) gained forests. We estimated an overall net gain of ~500,000 ha in woody vegetation. Forest loss dominated the 1,000–1,499 m elevation zone and forest gain dominated above 1,500 m. The most important transitions were forest loss at lower elevations for pastures and croplands, forest gain in abandoned pastures and cropland in mid‐elevation areas, and shrub encroachment into highland grasslands. Expert validation confirmed the observed trends, but some areas of apparent forest gain were associated with new shade coffee, pine, or eucalypt plantations. In addition, after controlling for elevation and country, forest gain was associated with a decline in the rural population. Although we document an overall gain in forest cover, the recent reversal of forest gains in Colombia demonstrates that these coupled natural‐human systems are highly dynamic and there is an urgent need of a regional real‐time land‐use, biodiversity, and ecosystem services monitoring network.

Six decades of urban green change in a neotropical city: a case study of Xalapa, Veracruz, Mexico

The process of expansion of human settlements commonly occurs without proper urban planning, which can directly affect green areas located within cities and adjacent areas. This study focuses on: (1) a spatiotemporal analysis to quantify the growth of the city of Xalapa (1950s to 2010s), (2) changes in woody vegetation cover within the boundaries of the city, and (3) land use and landscape changes and urban sprawl by decade from the 1980s to 2010s. To achieve this, we used digital images (i.e., ortho-photos, SPOT images), which were classified and integrated into a geographic information system. Based on the processed imagery, we delimited the urban polygon of the city, and quantified its woody vegetation cover changes and land use changes in areas surrounding the city for each decade of study. We found that over the past six decades, the city of Xalapa has grown in similar proportions per decade, mostly concentrated southward, fitting strongly and significantly to quadratic and linear growth patterns. Urban sprawl increased over the study period, Shannon’s relative entropy increasing from 0.58 to 0.73. Woody cover within the city occupied a similar proportion (19–29%) of total city area throughout the study period because of the addition of patches of woody vegetation from formerly outlying areas, despite infill urbanization replacing preexisting urban green areas. Land use change in the area surrounding the city went from a transition through different uses (e.g., woody vegetation to cropland to urban; 1980s–2000s), to a direct change from woody vegetation to urban use (2000s–2010s), and exhibited landscape fragmentation over the period of study. Our results show that an integrated combination of remotely-sensed data and landscape metrics can be used to monitor urban patterns and processes, and that the results obtained can be incorporated into urban planning and management.

Impacts of Restoration Projects on a Sahelian Woody Vegetation after 21 Years: The Simiri Plateaus (Niger) Case Study

To face the soil and vegetation degradation in Niger, anti-erosion structures, such as scarification of the surface of the ground, half-moons, benches, trenches, stony cordons, were built in 1989 on three Simiri plateaus. Native and introduced woody species were planted and grasses were sown within the structures. This study aims at evaluating what has become the restoration of the woody vegetation cover compared to an un-restored woody cover located on a nearby similar site. Dendrometric parameters and alpha and beta diversities of the four woody stands in 36 sampled plots were analyzed and compared. The following dendrometric values were found significantly lower in the control than in the restored stands: 3.9% against 12.4-16.8% for the recovery rate, 4.3 against 6.3-10.2 cm for the largest stem diameter, 0.2 against 0.8-1.2 m²/ha for the basal area, and 1.6 against 2.0-2.5 m for the tree height. However, the number of stems per trees was found significantly greater in the un-restored stand (6.6) than in the restored ones (1.8-2.7). The values of dendrometric parameters remained low, as well as the alpha and beta diversities whatever the stand. Nevertheless, population perceptions on the restoration impacts that were collected through focus groups indicated positive impacts on downstream crop yields.

Automatic detection of woody vegetation in repeat landscape photographs using a convolutional neural network

Repeat photography is an efficient method for documenting long-term landscape changes. So far, the usage of repeat photographs for quantitative analyses is limited to approaches based on manual classification. In this paper, we demonstrate the application of a convolutional neural network (CNN) for the automatic detection and classification of woody regrowth vegetation in repeat landscape photographs. We also tested if the classification results based on the automatic approach can be used for quantifying changes in woody vegetation cover between image pairs. The CNN was trained with 50 × 50 pixel tiles of woody vegetation and non-woody vegetation. We then tested the classifier on 17 pairs of repeat photographs to assess the model performance on unseen data. Results show that the CNN performed well in differentiating woody vegetation from non-woody vegetation (accuracy = 87.7%), but accuracy varied strongly between individual images. The very similar appearance of woody vegetation and herbaceous species in photographs made this a much more challenging task compared to the classification of vegetation as a single class (accuracy = 95.2%). In this regard, image quality was identified as one important factor influencing classification accuracy. Although the automatic classification provided good individual results on most of the 34 test photographs, change statistics based on the automatic approach deviated from actual changes. Nevertheless, the automatic approach was capable of identifying clear trends in increasing or decreasing woody vegetation in repeat photographs. Generally, the use of repeat photography in landscape monitoring represents a significant added value to other quantitative data retrieved from remote sensing and field measurements. Moreover, these photographs are able to raise awareness on landscape change among policy makers and public as well as they provide clear feedback on the effects of land management.

A century after introduction: variability in Cepaea hortensis (Müller, 1774) in Sibiu, central Romania

AbstractThe polymorphic land snail Cepaea hortensis was introduced to the city of Sibiu, central Romania, in the first decade of the 20th century and has spread widely across the city. A total of 97 locations were examined in 2017 across the city to determine the habitat preferences and variation in shell size, shape, colour and banding polymorphism of C. hortensis, and to relate these to the same features in the likely source population from Mannheim, Germany, and the first established population in Sibiu. We found that C. hortensis was largely restricted to sites with some woody vegetation cover and showed a marked preference for abandoned and overgrown private gardens. Mean adult shell size in present-day populations was almost always smaller than in both the presumed population of origin from Germany and the first recorded population from Sibiu. Populations showed a wide range of variation in frequencies of shell colours and banding morphs. This variation was not related to habitat or cover, and there was no evident geographical structure in the patterns. Comparisons with a smaller-scale sampling in 2004/5 showed that some populations had gone extinct, some remained stable and in some morph frequencies had changed drastically, but in no consistent direction. These results are similar to those obtained for the related species C. nemoralis in comparable circumstances, but differ from those obtained from regions where C. hortensis is long established and where habitats have been stable. The patterns we observed most likely reflect the effect of passive dispersal by humans, genetic drift and founder effects.

Machine learning and multi-sensor based modelling of woody vegetation in the Molopo Area, South Africa

Bush encroachment is a highly relevant environmental issue in South African savannas, influencing ecological processes as well as the grazing capacity of the land. However the drivers of bush encroachment are not yet fully revealed which can partly be attributed to the problem that large-scale data of woody vegetation cover are missing. Using a multi-scale and a multi-sensor approach, this study aimed at providing the status of woody vegetation cover for the Molopo Area in South Africa. Training data for woody vegetation was derived from unsupervised classification of high-resolution aerial image tiles. To derive spatially continuous estimates of fractional woody cover for the entire Molopo Area, Sentinel-1 and Sentinel-2 data were applied in a machine learning based modelling approach. Therefore, a database of training samples was generated by aggregating the classified aerial image tiles to the geometry of the Sentinel data. A Random Forest algorithm with a forward feature variable selection was then trained to relate the spectral and radar information to fractional woody cover. The model was applied to make spatial predictions of fractional woody cover at 10 m resolution for the entire Molopo Area for the year 2016. Spatial cross-validation revealed a prediction error in fractional cover of 12%. The derived model and cover data show the potential for upcoming time series analysis of Sentinel-based woody cover estimates which can serve as a basis to bring new insights into the drivers of bush encroachment.

Assessment of Land Cover Changes in the Hinterland of Barranquilla (Colombia) Using Landsat Imagery and Logistic Regression

Barranquilla is known as a dynamically growing city in the Colombian Caribbean. Urbanisation induces land use and land cover (LULC) changes in the city and its hinterland affecting the region’s climate and biodiversity. This paper aims to identify the trends of land use and land cover changes in the hinterland of Barranquilla corresponding to 13 municipalities in the north of the Department Atlántico. Landsat TM/ETM/OLI imagery from 1985 to 2017 was used to map and analyse the spatio-temporal development of land use and land cover changes. During the investigation period, the settlement areas grew by approximately 50% (from 103.3 to 153.6 km2), while areas with woody vegetation cover experienced dynamic changes and increased in size since 2001. Peri-urban and rural areas were characterized by highly dynamic changes, particularly regarding clearing and recovery of vegetated areas. Regression analyses were performed to identify the impact factors of detected vegetation cover changes. Computed logistic regression models included 20 independent variables, such as relief, climate, soil, proximity characteristics and socio-economic data. The results of this study may act as a basis to enable researchers and decision-makers to focus on the most important signals of systematic landscape transformations and on the conservation of ecosystems and the services they provide.

Cropland Abandonment in South African Smallholder Communal Lands: Land Cover Change (1950–2010) and Farmer Perceptions of Contributing Factors

Despite agricultural land abandonment threatening the food security and the livelihoods of smallholder farmers, it is pervasive globally and in developing countries. Yet land abandonment is an understudied aspect of land use change in social–ecological systems. Here we provide more information on this phenomenon by exploring cropland abandonment during 1950–2010 in four former South African ‘homelands’—part of the ‘Apartheid’ era racially-based land allocation programs—characterized by rural, smallholder farmers. Cropland abandonment 1950–2010 was widespread in all surveyed sites (KwaZulu: 0.08% year−1, Transkei: 0.13% year−1, Lebowa: 0.23% year−1, Venda: 0.28% year−1), with rates peaking between 1970 and 1990, with concomitant increases (up to 0.16% year−1) of woody vegetation cover at the expense of grassland cover. Active and past farmers attributed cropland abandonment to a lack of draught power, rainfall variability and droughts, and a more modernized youth disinclined to living a marginal agrarian lifestyle. We discuss the potential social and ecological implications of abandoned croplands at the local and regional scales, as the deagrarianization trend is unlikely to abate considering the failure of current South African national agricultural incentives.

Drivers of woody plant encroachment over Africa

While global deforestation induced by human land use has been quantified, the drivers and extent of simultaneous woody plant encroachment (WPE) into open areas are only regionally known. WPE has important consequences for ecosystem functioning, global carbon balances and human economies. Here we report, using high-resolution satellite imagery, that woody vegetation cover over sub-Saharan Africa increased by 8% over the past three decades and that a diversity of drivers, other than CO2, were able to explain 78% of the spatial variation in this trend. A decline in burned area along with warmer, wetter climates drove WPE, although this has been mitigated in areas with high population growth rates, and high and low extremes of herbivory, specifically browsers. These results confirm global greening trends, thereby bringing into question widely held theories about declining terrestrial carbon balances and desert expansion. Importantly, while global drivers such as climate and CO2 may enhance the risk of WPE, managing fire and herbivory at the local scale provides tools to mitigate continental WPE.

Current and predicted future distributions of wallabies in mainland New Zealand

ABSTRACTBennett's (Notamacropus rufogriseus) and dama (N. eugenii) wallabies have been increasing in numbers and distribution in mainland New Zealand. Here, we update their current distributions; estimate current rates of spread to predict their future distributions; and describe the extent of suitable habitat for each species. Current distributions based on breeding populations and probable distributions based on outlier confirmed sightings resulting from natural dispersal and illegal liberations suggest that Bennett's and dama wallabies currently occupy between 5322–15,229 km2 (532,200–1,522,900 ha) and 1865–4126 km2 (186,500–412,600 ha), respectively. In 50 years, best- and worst-case estimates predict that they could occupy as much as 5883–44,226 km2 (588,300–4,422,600 ha) and 1912–40,579 km2 (191,200–4,057,900 ha), respectively. Habitat suitability was predicted to be high in the North and South islands, except for areas of high elevation, intensive agriculture with limited woody vegetative cover and large urban centres. In the absence of widespread intensive control, the ranges currently occupied by Bennett's and dama wallabies are predicted to increase by up to 7- and 20-fold (respectively) in 50 years. As their distributions continue to expand, they will become more difficult to control and their impacts more widespread. We suggest that progressively containing wallabies within increasingly smaller distributions and reducing their numbers to minimise damage within those distributions should be considered the top management priorities. If progressive containment is feasible it could lead to eventual eradication.

Habitat selection of an endangered European farmland bird, the Ortolan BuntingEmberiza hortulana, in two contrasting landscapes: implications for management

SummaryEffective conservation measures for any bird species across their distribution ranges require detailed knowledge of landscape-specific differences in habitat associations. The Ortolan BuntingEmberiza hortulanais a farmland bird species, which experienced massive population declines during the recent decades and has become a conservation priority in many European countries. Thus, identification of the key habitat features is an important prerequisite for the conservation of the species. Here we investigate habitat associations of the Ortolan Bunting for the remaining breeding population of the species in the Czech Republic. This population is remarkable by its distribution in two markedly different environments – farmland and post-mining landscapes. The main objectives of this study were to identify habitat features associated with Ortolan Bunting occurrence within the two contrasting landscapes and at two spatial scales. Our results reveal a high degree of habitat plasticity by Ortolan Buntings in the Czech Republic which was revealed by the landscape- and scale- specific habitat associations. Habitat heterogeneity, in terms of compositional and configurational diversity, and the cover of bare ground were the most important predictors of Ortolan Bunting occurrence in both landscape types. In farmland, the species occurrence was positively associated with shrub and woody vegetation, poppy fields and set-asides, and negatively associated with grasslands, gardens/orchards, seedlings and urban habitats. In the post-mining landscape, the cover of herb vegetation and greater slope steepness and terrain ruggedness were most important habitat features. Ortolan Buntings in the post-mining landscape appear to avoid patches with a higher cover of shrub and woody vegetation, forests, seedlings and urban areas. We propose that conservation measures for Ortolan Buntings should focus on enhancing farmland habitat heterogeneity, but also on regulating the rate of succession in disturbed environments, such as post-mining landscapes.

Testing the assumptions of the pyrodiversity begets biodiversity hypothesis for termites in semi-arid Australia.

Fire shapes the composition and functioning of ecosystems globally. In many regions, fire is actively managed to create diverse patch mosaics of fire-ages under the assumption that a diversity of post-fire-age classes will provide a greater variety of habitats, thereby enabling species with differing habitat requirements to coexist, and enhancing species diversity (the pyrodiversity begets biodiversity hypothesis). However, studies provide mixed support for this hypothesis. Here, using termite communities in a semi-arid region of southeast Australia, we test four key assumptions of the pyrodiversity begets biodiversity hypothesis (i) that fire shapes vegetation structure over sufficient time frames to influence species' occurrence, (ii) that animal species are linked to resources that are themselves shaped by fire and that peak at different times since fire, (iii) that species’ probability of occurrence or abundance peaks at varying times since fire and (iv) that providing a diversity of fire-ages increases species diversity at the landscape scale. Termite species and habitat elements were sampled in 100 sites across a range of fire-ages, nested within 20 landscapes chosen to represent a gradient of low to high pyrodiversity. We used regression modelling to explore relationships between termites, habitat and fire. Fire affected two habitat elements (coarse woody debris and the cover of woody vegetation) that were associated with the probability of occurrence of three termite species and overall species richness, thus supporting the first two assumptions of the pyrodiversity hypothesis. However, this did not result in those species or species richness being affected by fire history per se. Consequently, landscapes with a low diversity of fire histories had similar numbers of termite species as landscapes with high pyrodiversity. Our work suggests that encouraging a diversity of fire-ages for enhancing termite species richness in this study region is not necessary.

Impacts of a mineral lick-centred land use system on woody vegetation cover in an East African Savannah

Evaluation of woody vegetation changes with distance from a salt crater was conducted in the semi‐arid rangelands of southern Ethiopia. Data on live woody plants were collected over three seasons at 0, 1, 4, 6, 9 and 12 km from the salt crater. The density and diversity of woody plants differed significantly (p < .01) along the distance gradient. Six woody plant families were identified of which Fabaceae and Burseraceae were the dominant families. Acacia drepanolobium, Acacia nilotica, Commiphora africana and Acacia mellifera were among the severely encroaching woody species. There were high proportions of seedlings and saplings recorded closer to the salt crater showing a vigorous recruitment by woody plants. Woody plant encroachment along the 12‐km transect ranged from a low to severe encroachment, which could be translated into poor rangeland condition. Changes in soil characteristics increased grazing pressure and sedentary settlement around the salt crater, and the breakdown of traditional institutions seems to be major contributing factors to these vegetation changes. We suggest that severely encroached areas could be improved through a combination of methods such as bush clearing, prescribed fire, browsing animals and proper grazing management.

Estimation of urban woody vegetation cover using multispectral imagery and LiDAR

Urban vegetation is an important resource in built up environments, and estimation of urban canopy cover arising from trees and shrubs is an important metric in assessments of landscape quality. We used an image classification approach to estimate urban vegetation cover consisting of trees and shrubs only within two medium-sized cities in the United States. Four-band aerial imagery with 1 m spatial resolution, a vegetation index derived from this imagery, and two LiDAR-derived maps were used to examine the added value of LiDAR for this purpose. The classification results showed that using LiDAR derived data along with multispectral data or LiDAR derived data by itself improved the process of identifying woody vegetated areas compared to aerial imagery alone. For Tallahassee, Florida, overall accuracy of six major classes (water, developed, woody vegetation-consisting of trees and shrubs only, bare ground, grass and shadow) ranged from 51% to 69% among all scenarios. The user’s accuracy of vegetation class was 69% when using aerial imagery only. Adding LiDAR derived data into the classification increased the user’s accuracy of vegetation class between 16% and 24%. Aggregating land cover classes into two major classes (woody vegetation-including trees and shrubs only, and non-vegetation-including developed, water, shadow, grass, and bare ground) resulted in over 80% overall accuracy and user’s accuracy across several scenarios. For Tacoma, Washington, the overall accuracy was between 60% and 73% for six major land cover classes. Similar to Tallahassee, using aerial imagery alone produced the lowest user’s accuracy of the woody vegetation class (67%) while scenarios including LiDAR plus visible imagery resulted in over 80% of user’s accuracy of woody vegetation class. Additionally, the overall accuracy for two major classes (woody vegetation and non-vegetation) was over 80%. The user’s accuracy of the woody vegetation class using LiDAR integrated data or LiDAR data by itself exceeded 80%, while using NAIP imagery alone the user’s accuracy was 70%. For both cities, estimates of woody vegetation using NAIP imagery alone were greater than the estimates of woody vegetation in other scenarios. Our results also suggest that LiDAR-derived information seemed to improve the overall accuracy of the six-class and two-class land cover classification results, when compared to using NAIP imagery alone for this purpose, but improvement was not consistently very significant.

Impacts of Mastication Fuel Treatments on California, USA, Chaparral Vegetation Structure and Composition

Mechanical fuel treatments are a primary pre-fire strategy for potentially mitigating the threat of wildland fire, yet there is limited information on how they impact shrubland ecosystems. Our goal was to assess the impact of mechanical mastication fuel treatments on chaparral vegetation and to determine the extent to which they emulate early post-fire succession. Mastication treatments significantly reduced the height and cover of woody vegetation and increased herbaceous cover and diversity. Non-native cover, density, and diversity were also significantly higher in masticated treatments. Comparisons with post-fire data from two studies showed that certain ephemeral post-fire endemics were absent or of limited occurrence from masticated plots in comparison to their abundance on adjacent burned plots. Structurally, masticated sites differed in the dense woody debris cover, whereas burned sites had little such ground cover. Regional comparison of masticated plots to previously published post-fire studies found that burned sites had greater cover, density, and diversity of native species. However, masticated sites and burned sites were broadly similar in distribution of different growth forms. Results from our study show that the use of mastication fuel treatments in chaparral are not in alignment with some resource conservation goals, but in some cases it is recognized that such sacrifice of natural resources may be an acceptable tradeoff to potentially mitigating fire hazard.

Strong positive effects of termites on savanna bird abundance and diversity are amplified by large herbivore exclusion.

Vast areas of the African savanna landscapes are characterized by tree‐covered Macrotermes termite mounds embedded within a relatively open savanna matrix. In concert with termites, large herbivores are important determinants of savanna woody vegetation cover. The relative cover of woody species has considerable effects on savanna function. Despite the potentially important ecological relationships between termite mounds, woody plants, large herbivores, and birds, these associations have previously received surprisingly little attention. We experimentally studied the effects of termites and large herbivores on the avian community in Lake Mburo National Park, Uganda, where woody vegetation is essentially limited to termite mounds. Our experiment comprised of four treatments in nine replicates; unfenced termite mounds, fenced mounds (excluding large mammals), unfenced adjacent savanna, and fenced savanna. We recorded species identity, abundance, and behavior of all birds observed on these plots over a two‐month period, from late dry until wet season. Birds used termite mounds almost exclusively, with only 3.5% of observations occurring in the treeless intermound savanna matrix. Mean abundance and species richness of birds doubled on fenced (large herbivores excluded) compared to unfenced mounds. Feeding behavior increased when large mammals were excluded from mounds, both in absolute number of observed individuals, and relative to other behaviors. This study documents the fundamental positive impact of Macrotermes termites on bird abundance and diversity in an African savanna. Birds play crucial functional roles in savanna ecosystems, for example, by dispersing fruits or regulating herbivorous insect populations. Thus, the role of birds in savanna dynamics depends on the distribution and abundance of termite mounds.

Techniques to Restore Coastal Scrub at a Reclaimed Quarry in Central California

Restoring large, drastically disturbed sites requires active techniques to create stable, self-sustaining native plant communities. We examined the effectiveness of topsoil preparation, seeding, and planting techniques for restoring coastal scrub at a 16.1 ha reclaimed quarry with steep, harsh slopes. Grading within the quarry created a benched slope spanning approximately 230 vertical meters, with a gradient of two horizontal:one vertical (2H:1V). This gentler slope was achieved by cutting the upper portion of the slope and using the cut material to fill the lower portion. Soils on cut slopes (approximately 9.0 ha) and fill slopes (approximately 7.1 ha) were prepared differently, resulting in two distinct substrates. Work crews hydroseeded native shrubs throughout the entire graded slope and installed native shrubs from container plants across half the site. Container plants were irrigated and protected from herbivory and weed competition. We conducted quantitative monitoring of woody vegetation cover for five years. We found that coastal scrub percent vegetative cover established from seed was significantly higher than that from container plantings on fill slopes amended with composted organic matter. Moreover, coastal scrub cover established from seed was significantly higher on amended fill slopes compared to cover from seed or container plants on unamended cut slopes. We conclude that coastal scrub restoration efforts on large, drastically disturbed sites should focus funds and resources on soil preparation, seed application, and site-wide invasive plant control, rather than on container plant installation and maintenance.