A frame-based spatially explicit model of subarctic vegetation response to climatic change: comparison with a point model

An important challenge in global-change research is to simulate short-term transient changes in climate, disturbance regime, and recruitment that drive long-term vegetation distributions. Spatial features (e.g., topographic barriers) and processes, including disturbance propagation and seed dispersal, largely control these short-term transient changes. Here we present a frame-based spatially explicit model (ALFRESCO) that simulates landscape-level response of vegetation to transient changes in climate and explicitly represents the spatial processes of disturbance propagation and seed dispersal. The spatial model and the point model from which it was developed showed similar results in some cases, but diverged in situations where interactions among neighboring cells (fire spread and seed dispersal) were crucial. Topographic barriers had little influence on fire size in low-flammability vegetation types, but reduced the average fire size and increased the number of fires in highly flammable vegetation (dry grassland). Large fires were more common in landscapes with large contiguous patches of two vegetation types while a more heterogeneous vegetation distribution increased fires in the less flammable vegetation type. When climate was held constant for thousands of years on a hypothetical landscape with the same initial vegetation, the spatial and point models produced identical results for some climates (cold, warm, and hot mesic), but produced markedly different results at current climate and when much drier conditions were imposed under a hot climate. Spruce migration into upland tundra was slowed or prevented by topographic barriers, depending on the size of the corridor. We suggest that frame-based, spatially explicit models of vegetation response to climate change are a useful tool to investigate both short- and long-term transients in vegetation at the regional scale. We also suggest that it is difficult to anticipate when non-spatial models will be reliable and when spatially explicit models are essential. ALFRESCO provides an important link between models of landscape-level vegetation dynamics and larger spatio-temporal models of global climate change.     

Linking vegetation patterns to environmental gradients and human impacts in a mediterranean-type island ecosystem

Vegetation patterns at the landscape scale are shaped by myriad processes and historical events, and understanding the relative importance of these processes aids in predicting current and future plant distributions. To quantify the influence of different environmental and anthropogenic patterns on observed vegetation patterns, we used simultaneous autoregressive modeling to analyze data collected by the Carnegie Airborne Observatory over Santa Cruz Island (SCI; California, USA). SCI is a large continental island, and its limited suite of species and well documented land use history allowed us to consider many potential determinants of vegetation patterns, such as topography, substrate, and historical grazing intensity. As a metric of vegetation heterogeneity, we used the normalized difference vegetation index (NDVI) stratified into three vegetation height classes using LiDAR (short, medium, and tall). In the SAR models topography and substrate type were important controls, together explaining 8–15 % of the total variation in NDVI, but historical grazing and spatial autocorrelation were also key components of the models, together explaining 17–21 % of the variation in NDVI. Optimal spatial autocorrelation distances in the short and medium height vegetation models (600–700 m) were similar to the home range sizes of two crucial seed dispersers on the island– the island fox (Urocyon littoralis santacruzae) and the island scrub-jay (Aphelocoma insularis)—suggesting that these animals may be important drivers of the island’s vegetation patterns. This study highlights the importance of dynamic processes like dispersal limitation and disturbance history in determining present-day vegetation patterns.     

Multi-scale study of bird species distribution and of their response to vegetation change: a Mediterranean example

Land use changes operate at different scales. They trigger a cascade of effects that simultaneously modify the composition or structure of the landscape and of the local vegetation. Mobil animals, and birds in particular, can respond quickly to such multi-scalar changes. We took advantage of a long term study on the response of songbirds to land-use changes on four Mediterranean islands in Corsica and Sardinia to explore the benefits of a multi-scale analysis of the relationships between songbird distribution, vegetation structure and landscape dynamics. Field data and aerial photographs were used to describe the vegetation at three different scales. Birds were censused by point counts. We used statistical variance decomposition to study how bird distribution and vegetation at various scales were linked. We analysed multi-scale vegetation changes (floristic composition, plot vegetation type, and landscape structure) and their consequences on bird distribution with multivariate and non-parametrical tests. The distribution of most species was linked to at least two spatial scales. The weight of a given scale was consistent with life-history traits for species whose biology was well-known. In the examples studied, vegetation composition, vegetation type and landscape changes that resulted from land abandonment negatively affected birds depending on open or heterogeneous areas. Our results emphasize that multi-scale analyses can greatly enhance our understanding of bird distribution and of their changes. Management of these populations should take into account measures at various spatial scales depending on the sensitivity of the species.     

Growth response of Ficus benjamina to limited soil volume and soil dilution in a skeletal soil container study

The interactive effects of rooting volume and nutrient availability in a skeletal soil medium designed to meet street tree and pavement needs were observed in a containerized experiment. Benjamin fig (Ficus benjamina L.) was grown in a stone-soil blended skeletal soil material (CU-Soil™) and compared to a loam soil. The same topsoil used as the soil component in the skeletal soil material was used as the sole component in the comparison soil-only treatment.Plants grown in the skeletal soil material had reduced leaf tissue N content and depressed growth compared with plants grown in non-diluted soil. No other mineral deficiencies were found. Leaf number, chlorophyll concentration, shoot weight, and root characteristics were all affected.Reduced growth from soil dilution could be offset by the provision of an enlarged rooting volume for root development. Large containers of skeletal soil were observed to have smaller root systems compared to equivalent net volumes of loam soil at the first two harvest dates of the study. By the end of the study, the large containers of skeletal soil were observed to have developed larger root systems compared to equivalent net volumes of loam soil; resulting in comparable leaf N levels and total plant dry matter. Plants in skeletal soil had lower shoot: root ratios at the end of the study. Investing resources to further root growth in times of nutrient shortages is a probable plant reaction as evidenced by differences in specific root length between treatments. The study allowed a method for directly partitioning the containerization effect by having equivalent amounts of soil over two volumes.     

Spatial sensitivity of maize gene-flow to landscape pattern: a simulation approach

Pollen dispersal is a critical process defining connectivity among plant populations. In the context of genetically modified (GM) crops in conventional agricultural systems, strategies based on spatial separation are promoted to reduce functional connectivity between GM and non-GM crop fields. Field experiments as well as simulation studies have stressed the dependence of maize gene flow on distances between source and receptor fields and on their spatial configuration. However, the influence of whole landscape patterns is still poorly understood. Spatially explicit models, such as MAPOD-maize, are thus useful tools to address this question. In this paper we developed a methodological approach to investigate the sensitivity of cross-pollination rates among GM and non-GM maize in a landscape simulated with MAPOD-maize. The influence of landscape pattern on model output was studied at the landscape and field scales, including interactions with other model inputs such as cultivar characteristics and wind conditions. At the landscape scale, maize configuration (proportion of and spatial arrangement in a given field pattern) was shown to be an important factor influencing cross-pollination rate between GM and non-GM maize whereas the effect of the field pattern itself was lower. At the field scale, distance to the nearest GM maize field was confirmed as a predominant factor explaining cross-pollination rate. The metrics describing the pattern of GM maize in the area surrounding selected non-GM maize fields appeared as pertinent complementary variables. In contrast, field geometry and field pattern resulted in little additional information at this scale. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Spatial vegetation patterns as early signs of desertification: a case study of a desert steppe in Inner Mongolia,China

Proper assessment and early detection of land degradation and desertification is extremely important in arid and semi-arid ecosystems. Recent research has proposed to use the characteristics of spatial vegetation patterns, such as parameters derived from power-law modeling of vegetation patches, for detecting the early signs of desertification. However, contradictory results have been reported regarding the suitability of those proposed indicators. We used an experiment with multiple grazing intensities as an analog of a desertification gradient and evaluated the performance of two predictors of desertification: percent plant cover and a transition from a patch-area distribution characterized by a power law to another portrayed by a truncated power law, in a desert steppe in Inner Mongolia, China. We found that spatial metrics, such as the largest patch index and coefficient of variation of mean patch area had negative linear relationships with grazing intensity, suggesting that vegetation patches became more fragmented and homogeneous under higher grazing pressure. Using a binning-based method to analyze our dataset, we found that the patch-area relationship deviated from a power-law to a truncated power-law model with increasing grazing pressure, while the truncated power law was a better fit than the power law for all plots when binning was not used. These results suggest that the selection of methodology is crucial in using power-law models to detect changes in vegetation patterns. Plant cover was significantly correlated with stocking rate and all spatial metrics evaluated; however, the relationship between cover and vegetation spatial pattern still deserves a thorough examination, especially in other types of ecosystems, before using cover as a universal early sign of desertification. Our results highlight a strong connection between the vegetation spatial pattern and the desertification associated with heavy grazing and suggest that future studies should incorporate information about vegetation spatial pattern in monitoring desertification processes.     

Feedbacks between vegetation pattern and resource loss dramatically decrease ecosystem resilience and restoration potential in a simple dryland model

Conceptual frameworks of dryland degradation commonly include ecohydrological feedbacks between landscape spatial organization and resource loss, so that decreasing cover and size of vegetation patches result in higher water and soil losses, which lead to further vegetation loss. However, the impacts of these feedbacks on dryland dynamics in response to external stress have barely been tested. Using a spatially-explicit model, we represented feedbacks between vegetation pattern and landscape resource loss by establishing a negative dependence of plant establishment on the connectivity of runoff-source areas (e.g., bare soils). We assessed the impact of various feedback strengths on the response of dryland ecosystems to changing external conditions. In general, for a given external pressure, these connectivity-mediated feedbacks decrease vegetation cover at equilibrium, which indicates a decrease in ecosystem resistance. Along a gradient of gradual increase of environmental pressure (e.g., aridity), the connectivity-mediated feedbacks decrease the amount of pressure required to cause a critical shift to a degraded state (ecosystem resilience). If environmental conditions improve, these feedbacks increase the pressure release needed to achieve the ecosystem recovery (restoration potential). The impact of these feedbacks on dryland response to external stress is markedly non-linear, which relies on the non-linear negative relationship between bare-soil connectivity and vegetation cover. Modelling studies on dryland vegetation dynamics not accounting for the connectivity-mediated feedbacks studied here may overestimate the resistance, resilience and restoration potential of drylands in response to environmental and human pressures. Our results also suggest that changes in vegetation pattern and associated hydrological connectivity may be more informative early-warning indicators of dryland degradation than changes in vegetation cover.     

Erosion regulation as a function of human disturbances to vegetation cover: a conceptual model

Human-induced land cover changes are causing important effects on the ecological services rendered by mountain ecosystems, and the number of case-studies of the impact of humans on soil erosion and sediment yield has mounted rapidly. In this paper, we present a conceptual model that allows evaluating overall changes in erosion regulation after human disturbances. The basic idea behind this model is that soil erosion mechanisms are independent of human impact, but that the frequency–magnitude distributions of erosion rates change as a response to human disturbances. Pre-disturbance (or natural) erosion rates are derived from in situ produced ¹⁰Be concentrations in river sediment, while post-disturbance (or modern) erosion rates are derived from sedimentation rates in small catchments. In its simplicity, the model uses vegetation cover change as a proxy of human disturbance. The erosion regulation model is here applied in two mountainous regions with different vegetation dynamics, climatic and geological settings: the Austro Ecuatoriano, and the Spanish Betic Cordillera. Natural erosion benchmarks are necessary to assess human-induced changes in erosion rates. While the Spanish Betic Cordillera is commonly characterized as a degraded landscape, there is no significant difference between modern catchment-wide erosion and long-term denudation rates. The opposite is true for the Austro Ecuatoriano where the share of natural erosion in the total modern erosion rate is minimal for most disturbed sites. When pooling pre- and post-disturbance erosion data from both regions, the data suggest that the human acceleration of erosion is related to vegetation disturbances. The empirical regression model predicts human acceleration of erosion, here defined as the ratio of post-disturbance to pre-disturbance (or natural benchmark) erosion rate, as an exponential function of vegetation disturbance. This suggests that the sensitivity to human-accelerated erosion would be ecosystem dependent, and related to the potential vegetation cover disturbances as a result of human impact. It may therefore be expected that the potential for erosion regulation is larger in well-vegetated ecosystem where strong differences may exist in vegetation cover between human disturbed and undisturbed or restored sites.     

Behavioral and social mechanisms behind pattern formation: an experimental study of animal movement

Context

Although animal movement behaviors are influenced by spatial heterogeneity, such behaviors can also generate spatial heterogeneity via interactions with the emergent spatial structure and other individuals (i.e., the social landscape).

Objective

Elucidate the behavioral and ecological mechanisms of pattern formation in a homogeneous resource landscape.

Methods

We analyzed the movement pathways and space-use patterns of the lesser grain borer (Rhyzopertha dominica) within homogeneous resource landscapes (wheat kernels). Experimental trials consisted of individual beetles foraging alone or paired with a member of the same or different sex.

Results

We identified two sources of pattern formation: (1) beetles were attracted to areas where they or another beetle had previously fed, leading to increased patchiness via positive reinforcement; and (2) the presence of conspecifics affected whether and at what scales patchiness occurred. Solitary males had lower rates of movement and less tortuous pathways than solitary females, but both sexes generated fine-scale patchiness in the resource distribution. Patchy resource landscapes were also generated by male–female pairs, but not by same-sex pairings. Paired females in particular exhibited significantly greater daily net displacements and more random space use than solitary females.

Conclusions

Pattern formation is a complex process, even in a relatively simple, homogeneous resource landscape. In particular, patterns created by individuals when foraging alone versus in pairs underscores how social interactions can fundamentally alter the resultant pattern of heterogeneity that emerges in resource landscapes.

     

The response of elephants to the spatial heterogeneity of vegetation in a Southern African agricultural landscape

Based on the agricultural landscape of the Sebungwe in Zimbabwe, we investigated whether and how the spatial distribution of the African elephant (Loxodonta africana) responded to spatial heterogeneity of vegetation cover based on data of the early 1980s and early 1990s. We also investigated whether and how elephant distribution responded to changes in spatial heterogeneity between the early 1980s and early 1990s. Vegetation cover was estimated from a normalised difference vegetation index (NDVI). Spatial heterogeneity was estimated from a new approach based on the intensity (i.e., the maximum variance exhibited when a spatially distributed landscape property such as vegetation cover is measured with a successively increasing window size or scale) and dominant scale (i.e., the scale or window size at which the intensity is displayed). We used a variogram to quantify the dominant scale (i.e., range) and intensity (i.e., sill) of NDVI based congruent windows (i.e., 3.84 km × 3.84 km in a 61 km × 61 km landscape). The results indicated that elephants consistently responded to the dominant scale of spatial heterogeneity in a unimodal fashion with the peak elephant presence occurring in environments with dominant scales of spatial heterogeneity of around 457–734 m. Both the intensity and dominant scale of spatial heterogeneity predicted 65 and 68% of the variance in elephant presence in the early 1980s and in the early 1990s respectively. Also, changes in the intensity and dominant scale of spatial heterogeneity predicted 61% of the variance in the change in elephant distribution. The results imply that management decisions must take into consideration the influence of the levels of spatial heterogeneity on elephants in order to ensure elephant persistence in agricultural landscapes.     

Changes in antioxidative system and membrane damage of lettuce in response to salinity and boron toxicity

Individual and combined effects of salinity and B toxicity on growth, the major antioxidant enzymes (superoxide dismutase, SOD; catalase, CAT; ascorbate peroxidase, APX) activities, ascorbic acid, proline, and H₂O₂ accumulation, and stomatal resistance (SR), malondialdehyde (MDA), membrane permeability (MP) and the concentrations of sodium (Na), chloride (Cl) and boron (B) of lettuce were investigated. Boron toxicity and salinity reduced growth of lettuce plants. Under B toxicity, B concentration of the plants was increased, but in the presence of NaCl, the concentration of B was significantly reduced. Sodium and Cl concentrations were increased in B + NaCl and NaCl treatments. Membrane damage was more pronounced in NaCl and B + NaCl treatments. Stomatal resistance of the plants was significantly increased by salinity treatments. The accumulation of proline and ascorbic acid was the highest in the B + NaCl treatment. In general, stress conditions significantly increased H₂O₂ and antioxidant enzyme (SOD, CAT and APX) activities. The present results indicate that stomatal closure is an important response of lettuce against NaCl and B + NaCl stress. Furthermore NaCl and B + NaCl toxicity-induced oxidative stress in lettuce resulting in lipid peroxidation and membrane damage. Increased antioxidant enzyme activities and also accumulation of ascorbic acid and proline are involved in order to overcome B- and NaCl-induced oxidative stress.     

Landscape planning: a working method applied to a case study of soil conservation

A working method for landscape planning is proposed. There are 11 steps in this method. In step one, an issue (or set of related issues) is identified as posing a problem or an opportunity to people and/or the environment. In step two, a goal (or several goals) is established to address the problem. In steps three and four, ecological inventories and analyses are conducted at two scales, first at the regional level (drainage basins are suggested as an appropriate unit) and then at the landscape level (watersheds are recommended). These inventories and analyses consider human ecology as well as bio-physical processes. Step five involves detailed studies, such as suitability analyses, that link inventory and analysis information to the problem(s) and goal(s). In step six, concepts are developed that lead to a landscape (watershed) master plan in step seven. During step eight, the plan is explained through a systematic educational effort to the affected public. In step nine, detailed designs are developed. In step 10 the plan and designs are implemented. Step 11 involves administering and monitoring the plan. The method is explained through an example of soil conservation planning. The case study was undertaken in the Missouri Flat Creek watershed of the Palouse region in the Pacific Northwest (U.S.A.) to help achieve the goals for erosion control established by the federal Food Security Act of 1985 and state clean water legislation.     

Spatial scale and pattern dependences of aboveground biomass estimation from satellite images: a case study of the Sierra National Forest,California

Context

Spatial scale and pattern play important roles in forest aboveground biomass (AGB) estimation in remote sensing. Changes in the accuracy of satellite images-estimated forest AGBs against spatial scales and pixel distribution patterns has not been evaluated, because it requires ground-truth AGBs of fine resolution over a large extent, and such data are difficult to obtain using traditional ground surveying methods.

Objectives

We intend to quantify the accuracy of AGB estimation from satellite images on changing spatial scales and varying pixel distribution patterns, in a typical mixed coniferous forest in Sierra Nevada mountains, California.

Methods

A forest AGB map of a 143 km² area was created using small-footprint light detection and ranging. Landsat Thematic Mapper images were chosen as typical examples of satellite images, and resampled to successively coarser resolutions. At each spatial scale, pixels forming random, uniform, and clustered spatial patterns were then sampled. The accuracies of the AGB estimation based on Landsat images associated with varying spatial scales and patterns were finally quantified.

Results

The changes in the accuracy of AGB estimation from Landsat images are not monotonic, but increase up to 60–90 m in spatial scale, and then decrease. Random and uniform spatial patterns of pixel distributions yield better accuracy for AGB estimation than clustered spatial patterns. The corrected NDVI (NDVIc) was the best predictor of AGB estimation.

Conclusions

A spatial scale of 60–90 m is recommended for forest AGB estimation at the Sierra Nevada mountains using Landsat images and those with similar spectral resolutions.

     

Spatial patterns of a subtropical,coastal urban forest: Implications for land tenure,hurricanes, and invasives

Spatial patterns of tree structure and composition were studied to assess the effects of land tenure, management regimes, and the environment on a coastal, subtropical urban forest. A total of 229 plots in remnant natural areas, private residential, public non-residential, and private non-residential land tenures were analyzed in a 1273 km² study area encompassing the urbanized portion of Miami-Dade County, USA. Statistical mixed models of structure, composition, location, and land tenure data were used to analyze spatial patterns across the study area. A total of 1200 trees were measured of which 593 trees (49%) were located in residential areas, 67 (6%) in public non-residential areas, 135 trees (11%) in private non-residential areas, and 405 (34%) in remnant, natural areas. A total of 107 different tree species belonging to 90 genera were sampled. Basal area in residential land tenures increased towards the coast while private residential land tenures and natural areas had higher species diversity than non-residential areas. Tree height, crown light exposure, and crown area might indicate the effects of past hurricane impacts on urban forest structure. Land tenure, soil types, and urban morphology influenced composition and structure. Broadleaf evergreen trees are the most common growth form, followed by broadleaf deciduous, palms, and conifers. Exotic tree species originated mainly from Asia and 15% of all trees measured were considered exotic-highly invasive species. We discuss the use of these results as an ecological basis for management and resilience towards hurricane damage and identifying occurrence of invasive, exotic trees.     

Involvement of bFGF in the lung response to silica in a mouse model

AIM: To investigate the relationship between basic fibroblast growth factor (bFGF) and the development of silicosis in mice. METHODS: MTT test was utilized to examine the effects of bFGF-neutralizing antibody and the bronchoalveolar lavage fluid (BALF) of the mice exposed to silica on lung fibroblast cell growth. RESULTS: BALF from mice treated intrabronchially with silica promoted the growth of lung fibroblasts and anti-bFGF antibody inhibited the effect of BALF dramatically. CONCLUSION: These results indicates that bFGF secretion increases in lung in a mice silicosis model and participates in the development of silicosis.     

Effect of interplanted rice on the growth of tomato in deep solution culture and on the response to salinity

Summary

Tomatoes were grown for 66 d in deep solution culture (a) without aeration, (b) with interplanted rice and (c) with air bubbled through the solution, in factorial combination with two electrical conductivities (4 and 8 mS cm^?1). Root growth was seriously restricted in the poorly aerated solutions (a) and (b). Interplanted rice stimulated shoot growth compared with the un-aerated treatment, and increased the total dry weight, leaf area and fruit yield (fresh weight) by up to 26, 34 and 22% respectively. The total dry weight of plants grown with rice was only 60% of that of the aerated ones but the area of corresponding upper leaves was 73%. Water and nutrient uptake were reduced by poor aeration but, after allowing for the uptake by the interplanted rice, only the uptakes of P and Ca by tomatoes in that treatment were significantly higher than those of the un-aerated plants. The higher salinity reduced growth and the uptake of nutrients. No interaction between aeration and salinity was found.     

Spatial spread of an alien tree species in a heterogeneous forest landscape: a spatially realistic simulation model

The effect of environmental heterogeneity on spatial spread of invasive species has received little attention in the literature. Altering landscape heterogeneity may be a suitable strategy to control invaders in man-made landscapes. We use a population-based, spatially realistic matrix model to explore mechanisms underlying the observed invasion patterns of an alien tree species, Prunus serotina Ehrh., in a heterogeneous managed forest. By altering several parameters in the simulation, we test for various hypotheses regarding the role of several mechanisms on invasion dynamics, including spatial heterogeneity, seed dispersers, site of first introduction, large-scale natural disturbances, and forest management. We observe that landscape heterogeneity makes the invasion highly directional resulting from two mechanisms: (1) irregular jumps, which occur rarely via long-distance dispersers and create new founder populations in distant suitable areas, and (2) regular, continuous diffusion toward adjacent cells via short- and mid-distance vectors. At the landscape scale, spatial heterogeneity increases the invasion speed but decreases the final invasion extent. Hence, natural disturbances (such as severe storms) appear to facilitate invasion spread, while forest management can have contrasting effects such as decreasing invasibility at the stand scale by increasing the proportion of light interception at the canopy level. The site of initial introduction influences the invasion process but without altering the final outcome. Our model represents the real landscape and incorporates the range of dispersal modes, making it a powerful tool to explore the interactions between environmental heterogeneity and invasion dynamics, as well as for managing plant invaders. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Correction to: Individual based modelling of fish migration in a 2-D river system: model description and case study

Landscape Ecology - In the original publication of the article, the third author name has been misspelt. The correct name is given in this Correction. The original version of this article was revised.     

Use of landscape pattern metrics and multiscale data in aquatic species distribution models: a case study of a freshwater mussel

The distributions of freshwater mussels are controlled by landscape factors operating at multiple spatial scales. Changes in land use/land cover (LULC) have been implicated in severe population declines and range contractions of freshwater mussels across North America. Despite widespread recognition of multiscale influences few studies have addressed these issues when developing distribution models. Furthermore, most studies have disregarded the role of landscape pattern in regulating aquatic species distributions, focusing only on landscape composition. In this study, the distribution of Rabbitsfoot (Quadrula cylindrica) in the upper Green River system (Ohio River drainage) is modeled with environmental variables from multiple scales: subcatchment, riparian buffer, and reach buffer. Four types of landscape environment metrics are used, including: LULC pattern, LULC composition, soil composition, and geology composition. The study shows that LULC pattern metrics are very useful in modeling the distribution of Rabbitsfoot. Together with LULC compositional metrics, pattern metrics permit a more detailed analysis of functional linkages between aquatic species distributions and landscape structure. Moreover, the inclusion of multiple spatial scales is necessary to accurately model the hierarchical processes in stream systems. Geomorphic features play important roles in regulating species distributions at intermediate and large scales while LULC variables appear more influential at proximal scales.