Remotely sensed vegetation phenology and productivity along a climatic gradient: on the value of incorporating the dimension of woody plant cover

Aim Woody plants affect vegetation–environment interactions by modifying microclimate, soil moisture dynamics and carbon cycling. In examining broad‐scale patterns in terrestrial vegetation dynamics, explicit consideration of variation in the amount of woody plant cover could provide additional explanatory power that might not be available when only considering landscape‐scale climate patterns or specific vegetation assemblages. Here we evaluate the interactive influence of woody plant cover on remotely sensed vegetation dynamics across a climatic gradient along a sky island. Location The Santa Rita Mountains, Arizona, USA. Methods Using a satellite‐measured normalized difference vegetation index (NDVI) from 2000 to 2008, we conducted time‐series and regression analyses to explain the variation in functional attributes of vegetation (productivity, seasonality and phenology) related to: (1) vegetation community, (2) elevation as a proxy for climate, and (3) woody plant cover, given the effects of the other environmental variables, as an additional ecological dimension that reflects potential vegetation–environment feedbacks at the local scale. Results NDVI metrics were well explained by interactions among elevation, vegetation community and woody plant cover. After accounting for elevation and vegetation community, woody plant cover explained up to 67% of variation in NDVI metrics and, notably, clarified elevation‐ and community‐specific patterns of vegetation dynamics across the gradient. Main conclusions In addition to the environmental factors usually considered – climate, reflecting resources and constraints, and vegetation community, reflecting species composition and relative dominance – woody plant cover, a broad‐scale proxy of many vegetation–environment interactions, represents an ecological dimension that provides additional process‐related understanding of landscape‐scale patterns of vegetation function.     

A model of the extent and distribution of woody linear features in rural Great Britain

Hedges and lines of trees (woody linear features) are important boundaries that connect and enclose habitats, buffer the effects of land management, and enhance biodiversity in increasingly impoverished landscapes. Despite their acknowledged importance in the wider countryside, they are usually not considered in models of landscape function due to their linear nature and the difficulties of acquiring relevant data about their character, extent, and location. We present a model which uses national datasets to describe the distribution of woody linear features along boundaries in Great Britain. The method can be applied for other boundary types and in other locations around the world across a range of spatial scales where different types of linear feature can be separated using characteristics such as height or width. Satellite‐derived Land Cover Map 2007 (LCM2007) provided the spatial framework for locating linear features and was used to screen out areas unsuitable for their occurrence, that is, offshore, urban, and forest areas. Similarly, Ordnance Survey Land‐Form PANORAMA®, a digital terrain model, was used to screen out where they do not occur. The presence of woody linear features on boundaries was modelled using attributes from a canopy height dataset obtained by subtracting a digital terrain map (DTM) from a digital surface model (DSM). The performance of the model was evaluated against existing woody linear feature data in Countryside Survey across a range of scales. The results indicate that, despite some underestimation, this simple approach may provide valuable information on the extents and locations of woody linear features in the countryside at both local and national scales.     

Biome transitions as centres of diversity: habitat heterogeneity and diversity patterns of West African bat assemblages across spatial scales

It is widely accepted that species diversity is contingent upon the spatial scale used to analyze patterns and processes. Recent studies using coarse sampling grains over large extents have contributed much to our understanding of factors driving global diversity patterns. This advance is largely unmatched on the level of local to landscape scales despite being critical for our understanding of functional relationships across spatial scales. In our study on West African bat assemblages we employed a spatially explicit and nested design covering local to regional scales. Specifically, we analyzed diversity patterns in two contrasting, largely undisturbed landscapes, comprising a rainforest area and a forest‐savanna mosaic in Ivory Coast, West Africa. We employed additive partitioning, rarefaction, and species richness estimation to show that bat diversity increased significantly with habitat heterogeneity on the landscape scale through the effects of beta diversity. Within the extent of our study areas, habitat type rather than geographic distance explained assemblage composition across spatial scales. Null models showed structure of functional groups to be partly filtered on local scales through the effects of vegetation density while on the landscape scale both assemblages represented random draws from regional species pools. We present a mixture model that combines the effects of habitat heterogeneity and complexity on species richness along a biome transect, predicting a unimodal rather than a monotonic relationship with environmental variables related to water. The bat assemblages of our study by far exceed previous figures of species richness in Africa, and refute the notion of low species richness of Afrotropical bat assemblages, which appears to be based largely on sampling biases. Biome transitions should receive increased attention in conservation strategies aiming at the maintenance of ecological and evolutionary processes.     

Natural disturbances are spatially diverse but temporally synchronized across temperate forest landscapes in Europe

Natural disturbance regimes are changing substantially in forests around the globe. However, large‐scale disturbance change is modulated by a considerable spatiotemporal variation within biomes. This variation remains incompletely understood particularly in the temperate forests of Europe, for which consistent large‐scale disturbance information is lacking. Here, our aim was to quantify the spatiotemporal patterns of forest disturbances across temperate forest landscapes in Europe using remote sensing data and determine their underlying drivers. Specifically, we tested two hypotheses: (1) Topography determines the spatial patterns of disturbance, and (2) climatic extremes synchronize natural disturbances across the biome. We used novel Landsat‐based maps of forest disturbances 1986–2016 in combination with landscape analysis to compare spatial disturbance patterns across five unmanaged forest landscapes with varying topographic complexity. Furthermore, we analyzed annual estimates of disturbances for synchronies and tested the influence of climatic extremes on temporal disturbance patterns. Spatial variation in disturbance patterns was substantial across temperate forest landscapes. With increasing topographic complexity, natural disturbance patches were smaller, more complex in shape, more dispersed, and affected a smaller portion of the landscape. Temporal disturbance patterns, however, were strongly synchronized across all landscapes, with three distinct waves of high disturbance activity between 1986 and 2016. All three waves followed years of pronounced drought and high peak wind speeds. Natural disturbances in temperate forest landscapes of Europe are thus spatially diverse but temporally synchronized. We conclude that the ecological effect of natural disturbances (i.e., whether they are homogenizing a landscape or increasing its heterogeneity) is strongly determined by the topographic template. Furthermore, as the strong biome‐wide synchronization of disturbances was closely linked to climatic extremes, large‐scale disturbance episodes are likely in Europe's temperate forests under climate changes.     

Consequences of the Armed Conflict, Forced Human Displacement, and Land Abandonment on Forest Cover Change in Colombia: A Multi-scaled Analysis

Most studies of land change have focused on patterns, rates, and drivers of deforestation, but much less is known about the dynamics associated with agricultural abandonment and ecosystem recovery. Furthermore, most studies are conducted at a single spatial scale, and few have included variables related with internal socio-political conflicts. Here we evaluated the effect of environmental, demographic, and socio-economic variables on woody cover change in Colombia between 2001 and 2010 at the country, biome, and ecoregion scales. We also incorporated factors that reflect the unique history of Colombia such as the presence of illegal-armed groups and forced human displacement. Environmental variables explained the patterns of deforestation and forest regrowth at all scales because they can restrict or encourage different land uses across multiple spatial scales. Demographic variables were important at the biome and ecoregion scales and appear to be a consequence of the armed conflict, particularly through forced human displacement (for example, rural–urban migration), which in some areas has resulted in forest regrowth. In other areas, the impact of illegal armed groups has reduced forest cover, particularly in areas rich in gold and lands appropriate for cattle grazing. This multi-scale and multivariate approach provides a new insight into the complex relationship between woody cover change and land abandonment triggered mainly by armed conflict.     

Integrating a global agro-climatic classification with bioregional boundaries in Australia

Aim Stratification of major differences in the biophysical features of landscapes at the continental scale is necessary to collectively assess local observations of landscape response to management actions for consistency and difference. Such a stratification is an important step in the development of generalizations concerning how landscapes respond to different management regimes. As part of the development of a comparative framework for this purpose, we propose a climate classification adapted from an existing broad scale global agro‐climatic classification, which is closely aligned with natural vegetation formations and common land uses across Australia. Location The project considered landscapes across the continent of Australia. Methods The global agro‐climatic classification was adapted by using elevation‐dependent thin plate smoothing splines to clarify the spatial extents of the 18 global classes found in Australia. The clarified class boundaries were interpolated from known classes at 822 points across Australia. These classes were then aligned with the existing bioregional classification, Interim Biogeographic Regionalization for Australia IBRA 5.1. Results The aligned climate classes reflect major patterns in plant growth temperature and moisture indices and seasonality. These in turn reflect broad differences in cropping and other land use characteristics. Fifty‐two of the 85 bioregions were classified entirely into one of the 18 agro‐climatic classes. The remaining bioregions were classified according to sub‐bioregional boundaries. A small number of these sub‐bioregions were split to better reflect agro‐climatic boundaries. Main conclusions The agro‐climatic classification provided an explicit global context for the analysis. The topographic dependence of the revised climate class boundaries clarified the spatial extents of poorly sampled highland classes and facilitated the alignment of these classes with the bioregional classification. This also made the classification amenable to explicit application. The bioregional and subregional boundaries reflect discontinuities in biophysical features. These permit the integrated classification to reflect major potential differences in landscape function and response to management. The refined agro‐climatic classification and its integration with the IBRA bioregions are both available for general use and assessment.     

Variation in plant responses to neighbors at local and regional scales

Differences in the responses of plant species to neighbors may determine their distribution among contrasting environments, but no studies have compared variation in competitive or facilitative abilities both within and among environments. We determined whether the responses of plants to interspecific interactions varied at large scales (between environments) and small scales (among sites within an environment) across a tree line. We separated the effects of above- and belowground interactions on seedlings of grasses and trees grown in prairie or forest using vegetation removals at several sites. Species interactions generally had no significant effect on transplant survival. Competition reduced seedling growth by about 33%-89% in both prairie and forest environments. Despite the strong suppression of growth by neighbors, environment and species effects contributed more to variation in transplant performance than did neighbor removals. Responses to neighbors varied among transplant species but generally did not vary significantly between environments or among sites. With vegetation removed, grasses grew significantly faster in prairie and trees grew faster in forest. Thus, in the absence of neighbors, species showed distinct preferences for the environment in which they are most abundant. In summary, the responses of grasses and woody species to neighbors did not vary significantly at either large (between environments) or small (among sites) scales. These results suggest that species responses to interspecific interactions do not vary strongly with environment or smaller-scale site effects.     

A multiscale analysis of herbaceous species richness in a Mediterranean ecosystem

Aims Studies of species distribution patterns traditionally have been conducted at a single scale, often overlooking species–environment relationships operating at finer or coarser scales. Testing diversity-related hypotheses at multiple scales requires a robust sampling design that is nested across scales. Our chief motivation in this study was to quantify the contributions of different predictors of herbaceous species richness at a range of local scales.Methods Here, we develop a hierarchically nested sampling design that is balanced across scales, in order to study the role of several environmental factors in determining herbaceous species distribution at various scales simultaneously. We focus on the impact of woody vegetation, a relatively unexplored factor, as well as that of soil and topography. Light detection and ranging (LiDAR) imaging enabled precise characterization of the 3D structure of the woody vegetation, while acoustic spectrophotometry allowed a particularly high-resolution mapping of soil CaCO 3 and organic matter contents.Important findings We found that woody vegetation was the dominant explanatory variable at all three scales (10, 100 and 1000 m 2), accounting for more than 60% of the total explained variance. In addition, we found that the species richness–environment relationship was scale dependent. Many studies that explicitly address the issue of scale do so by comparing local and regional scales. Our results show that efforts to conserve plant communities should take into account scale dependence when analyzing species richness–environment relationships, even at much finer resolutions than local vs. regional. In addition, conserving heterogeneity in woody vegetation structure at multiple scales is a key to conserving diverse herbaceous communities.     

Novel spatial analysis methods reveal scale‐dependent spread and infer limiting factors of invasion by Sahara mustard

Multiple scale‐dependent ecological processes influence species distributions. Uncovering these drivers of dynamic range boundaries can provide fundamental ecological insights and vital knowledge for species management. We develop a transferable methodology that uses widely available data and tools to determine critical scales in range expansion and to infer dominating scale‐dependent forces that influence spread. We divide a focal geographic region into different sized square cells, representing different spatial scales. We then used herbarium records to determine the species' occupancy of cells at each spatial scale. We calculated the growth in cell occupancy across scales to infer the scale dependent expansion rate. This is the first time such a ‘box‐counting’ method is used to study range expansion. We coupled this multi‐scale analysis with species distribution models to determine the range and spatial scales where suitable climate allows the species to spread, and where other factors may be influencing the expansion. We demonstrate our methodology by assessing the spread of invasive Sahara mustard in North America. We detect critical scales where its spread is limited (100–500 km) or unconstrained (5–50 km) by climatic variables. Using climate‐based models to assess the similarity of climate envelopes in its native and invaded range, we find that the climate in the invaded range generally predicts the native distribution, suggesting that either there has been little local adaptation to climate occurring since introduction or the biological interaction experienced in the invaded range has not driven the species to occupy climatic conditions much different from its native range. Our novel method can be broadly utilized in other studies to generate critical insights into the scale dependency of different ecological drivers that influence the spread and distribution limits, as well as to help parameterizing predictions of future spread, and thus inform management decisions.     

Measures of giant panda habitat selection across multiple spatial scales for species conservation

Examining ecological processes across spatial scales is crucial as animals select and use resources at different scales. We carried out field surveys in September 2005, March–September 2006, and April 2007, and used ecological niche factor analysis to determine habitat preferences for the giant panda (Ailuropoda melanoleuca) across 4 spatial scales: daily movement, core range, home range, and seasonal elevational migration. We found that giant pandas prefer conifer forest and mixed forest at higher than average elevation (2,157 m) of study area in the 4 scale models. However, we also observed significant scale differences in habitat selection. The strength of habitat preference increased with scale for the 2 disturbed forests (sparse forest and fragmented forest), and decreased with scale for 0–30° gentle slope and south- and north-facing aspect. Furthermore, habitat suitability patterns were scale-dependent. These findings highlight the need to determine species–environment associations across multiple scales for habitat management and species conservation. © 2012 The Wildlife Society.     

Spatial scaling of ecosystem C and N in a subtropical savanna landscape

Widely occurred woody encroachment in grass‐dominated ecosystems has the potential to influence soil organic carbon (SOC) and total nitrogen (TN) pools at local, regional, and global scales. Evaluation of this potential requires assessment of both pool sizes and their spatial patterns. We quantified SOC and TN, their relationships with soil and vegetation attributes, and their spatial scaling along a catena (hill‐slope) gradient in the southern Great Plains, USA where woody cover has increased substantially over the past 100 years. Quadrat variance analysis revealed spatial variation in SOC and TN at two scales. The larger scale variation (40–45 m) was approximately the distance between centers of woody plant communities and their adjoining herbaceous patches. The smaller scale variation (10 m) appeared to reflect the local influence of shrubs on SOC and TN. Litter, root biomass, shrub, and tree basal area (a proxy for plant age) exhibited not only similar spatial scales, but also strong correlations with SOC and TN, suggesting invasive woody plants alter both the storage and spatial scaling of SOC and TN through ecological processes related primarily to root turnover and, to a lesser extent litter production, as mediated by time of occupancy. Forb and grass biomass were not significantly correlated with SOC and TN suggesting that changes in herbaceous vegetation have not been the driving force for the observed changes in SOC and TN. Because SOC and TN varied at two scales, it would be inappropriate to estimate SOC and TN pools at broad scales by extrapolating from point sampling at fine scales. Sampling designs that capture variation at multiple scales are required to estimate SOC and TN pools at broader scales. Knowledge of spatial scaling and correlations will be necessary to design field sampling protocols to quantify the biogeochemical consequences of woody plant encroachment at broad scales.     

Soil attributes structure plant assemblages across an Atlantic forest mosaic

Aims Community assembly persists as a key topic in ecology due to the complex variation in the relative importance of assembly forces and mechanisms across spatio-temporal scales and ecosystems. Here we address a forest–savanna vegetation mosaic in the Brazilian Atlantic forest to examine the role played by soil attributes as determinants of community assembly and organization at a landscape spatial scale.Methods We examined soil and plant assemblage attributes across 23 plots of forest and savanna in a 1600 km 2 landscape exposed to the same climatic conditions in the Atlantic forest region of northeast Brazil. Assemblage attributes included species richness, taxonomic and functional composition (community weighted mean, CWM) and functional diversity (quadratic diversity; Rao's quadratic entropy index) relative to plant leaf area, specific leaf area, leaf dry matter content, thickness and succulence.Important findings Our results suggest that forest and savanna patches exposed to the same climatic conditions clearly differ in terms of soil attributes, plant assemblage structure, taxonomic and functional composition. By selecting particular plant strategies relative to resource economy, soil potentially affects community structure, with forest assemblages bearing more acquisitive resource-use strategies, while conservative plant strategies are more frequent in savannas. Accordingly, savanna–forest mosaics in the Atlantic forest region represent spatially organized plant assemblages in terms of taxonomic and functional features, with a signal of trait convergence in both vegetation types. Soil-mediated filtering thus emerges as a potential deterministic assembly force affecting the spatial organization of savanna–forest boundaries and mosaics.     

Relative influence of regional species richness vs local climate on local species richness in China's forests

Disentangling the relative effects of local and regional processes on local species richness (LSR) is critical for understanding the mechanisms underlying large‐scale biodiversity patterns. In this study we used 1098 forest plots from 41 mountains across China, together with regional flora data, to examine the relative influence of local climate vs regional species richness (RSR) on LSR patterns. Both RSR and LSR for woody species and all species combined decreased with increasing latitude, while richness of herbaceous species exhibited a hump‐shaped pattern. The major climatic orrelates of species richness differed across spatial scales. At the regional scale, winter coldness was the best predictor of RSR patterns for both woody and herbaceous species. At the local scale, however, productivity‐related climatic indices were the best predictors of LSR patterns. Local climate and RSR together explained 48, 54 and 23% of the variation in LSR, for overall, woody and herbaceous species, respectively. Both local climate and RSR independently influenced LSR in addition to their joint effects, suggesting that LSR patterns were shaped by local and regional processes together. Local climate and RSR affected LSR of woody species mainly through their joint effects, while there were few shared effects of climate and RSR on the LSR of herbaceous species. Our findings suggest that while geographic RSR patterns are mainly determined by winter coldness, the ecological processes driven by productivity may be critical to the filtering of regional flora into local communities. We also demonstrate that biogeographic region is not a good surrogate for regional richness, at least for our dataset. Consequently, whether biogeographic region can effectively reflect regional effects needs further examination.     

边缘效应的空间尺度与测度

综述了边缘效应的空间尺度类型以及在不同尺度上的测度方法.基于大量的研究整合,认为边缘效应空间尺度的划分,可以根据空间尺度的不同以及边缘效应形成和维持因素,分为大中小3个尺度类型,即大尺度的生物群区交错带、中尺度的景观类型之间的生态交错带和小尺度的斑块(生态系统)之间的群落交错区.大尺度主要是以植被气候带为标志的生物群区间的边缘效应,这种地带性的交错区主要受大气环境条件的影响.中尺度类型主要包括城乡交错带、林草交错带、农牧交错带等类型,是不同生态系统要素的空间交接地带,在物质能量等相互流动的作用下变得更为复杂.小尺度水平上是指斑块之间的交错所形成的边缘效应,受小地形等微环境条件及生物非生物等因子的制约,研究主要集中在群落边缘、林窗边缘和林线交错带等方面.对边缘效应测度的定量化研究有助于更加深入理解边缘效应.在大尺度水平上,边缘效应测度的研究主要是应用数量生态学等方法,研究不同气候带之间界线的划分及其物种分布的梯度规律性.中尺度水平上应用景观生态学的3S技术等方法,侧重于研究交错带的动态变化趋势及位置宽度的判定.小尺度水平上通过对距离边缘的长度,各群落中种群的数量、结构、多样性等定量指标的测定来构建测度公式,从而对边缘效应的强度进行量化,并反映边缘对群落的正负效应.总体上看,主要集中于中小尺度上,未来应该强化大尺度边缘效应测度的研究.     

Spatial scale types and measurement of edge effects in ecology

Classification of spatial scales and measurement of edge effects in ecology were reviewed. The spatial scales can be classified into large scale (biome ecotone), meso-scale (ecological ecotone) and small scale (community ecotone) through the formation and maintenance of edge effects in ecology based on the synthetic analysis of published literatures. The biome ecotone is influenced by climate, regional dominant vegetation and terrain environment. The ecological ecotone is usually distributed in the transitional region with remarkable habitat heterogeneity. It connects adjacent ecosystems and affects the flow of energy and nutrient. Nowadays, study on edge effects in ecology mainly focuses on boundary sensitivity which associates with urban-rural ecotone, forest-grassland ecotone, agro-pastoral ecotone, forest-farmland ecotone, water-land ecotone and forest-swamp ecotone. As to the community ecotone which links with different patches to the interior of the community, previous studies focused on community edge, gap edge and treelines. The borderlines of different biome ecotones and the gradients of species distribution in the biome ecotones have been investigated through the method of quantitative ecology. The dynamic change, location and width of the ecological ecotone have been studied using the Geographic Information System (GIS), Remote Sensing (RS) and Global Positioning System (GPS) technologies and the landscape ecology theory. As important indicators, distance from edge, population, structure and diversity determined for establishing models can be applied to measure the intensity of edge effects and decide the positive or negative impact on communities. Although study on the edge effects in ecology was mostly reported at the meso-scale and small scale, study at large scale should be paid more attention as it is the potential value in ecology and global change fields.     

Extensive land cover change across Arctic–Boreal Northwestern North America from disturbance and climate forcing

A multitude of disturbance agents, such as wildfires, land use, and climate‐driven expansion of woody shrubs, is transforming the distribution of plant functional types across Arctic–Boreal ecosystems, which has significant implications for interactions and feedbacks between terrestrial ecosystems and climate in the northern high‐latitude. However, because the spatial resolution of existing land cover datasets is too coarse, large‐scale land cover changes in the Arctic–Boreal region (ABR) have been poorly characterized. Here, we use 31 years (1984–2014) of moderate spatial resolution (30 m) satellite imagery over a region spanning 4.7 × 10⁶ km² in Alaska and northwestern Canada to characterize regional‐scale ABR land cover changes. We find that 13.6 ± 1.3% of the domain has changed, primarily via two major modes of transformation: (a) simultaneous disturbance‐driven decreases in Evergreen Forest area (?14.7 ± 3.0% relative to 1984) and increases in Deciduous Forest area (+14.8 ± 5.2%) in the Boreal biome; and (b) climate‐driven expansion of Herbaceous and Shrub vegetation (+7.4 ± 2.0%) in the Arctic biome. By using time series of 30 m imagery, we characterize dynamics in forest and shrub cover occurring at relatively short spatial scales (hundreds of meters) due to fires, harvest, and climate‐induced growth that are not observable in coarse spatial resolution (e.g., 500 m or greater pixel size) imagery. Wildfires caused most of Evergreen Forest Loss and Evergreen Forest Gain and substantial areas of Deciduous Forest Gain. Extensive shifts in the distribution of plant functional types at multiple spatial scales are consistent with observations of increased atmospheric CO₂ seasonality and ecosystem productivity at northern high‐latitudes and signal continental‐scale shifts in the structure and function of northern high‐latitude ecosystems in response to climate change.     

Land Cover Change in Colombia: Surprising Forest Recovery Trends between 2001 and 2010

Background

Monitoring land change at multiple spatial scales is essential for identifying hotspots of change, and for developing and implementing policies for conserving biodiversity and habitats. In the high diversity country of Colombia, these types of analyses are difficult because there is no consistent wall-to-wall, multi-temporal dataset for land-use and land-cover change.

Methodology/Principal Findings

To address this problem, we mapped annual land-use and land-cover from 2001 to 2010 in Colombia using MODIS (250 m) products coupled with reference data from high spatial resolution imagery (QuickBird) in Google Earth. We used QuickBird imagery to visually interpret percent cover of eight land cover classes used for classifier training and accuracy assessment. Based on these maps we evaluated land cover change at four spatial scales country, biome, ecoregion, and municipality. Of the 1,117 municipalities, 820 had a net gain in woody vegetation (28,092 km²) while 264 had a net loss (11,129 km²), which resulted in a net gain of 16,963 km² in woody vegetation at the national scale. Woody regrowth mainly occurred in areas previously classified as mixed woody/plantation rather than agriculture/herbaceous. The majority of this gain occurred in the Moist Forest biome, within the montane forest ecoregions, while the greatest loss of woody vegetation occurred in the Llanos and Apure-Villavicencio ecoregions.

Conclusions

The unexpected forest recovery trend, particularly in the Andes, provides an opportunity to expand current protected areas and to promote habitat connectivity. Furthermore, ecoregions with intense land conversion (e.g. Northern Andean Páramo) and ecoregions under-represented in the protected area network (e.g. Llanos, Apure-Villavicencio Dry forest, and Magdalena-Urabá Moist forest ecoregions) should be considered for new protected areas.     

A new method to infer vegetation boundary movement from ‘snapshot’ data

Global change may induce shifts in plant community distributions at multiple spatial scales. At the ecosystem scale, such shifts may result in movement of ecotones or vegetation boundaries. Most indicators for ecosystem change require timeseries data, but here a new method is proposed enabling inference of vegetation boundary movement from one ‘snapshot’ (e.g. an aerial photograph or satellite image) in time. The method compares the average spatial position of frontrunners of both communities along the vegetation boundary. Mathematical analyses and simulation modeling show that the average frontrunner position of retreating communities is always farther away from a so‐called optimal vegetation boundary as compared to that of the expanding community. This feature does not depend on assumptions about plant dispersal or competition characteristics. The method is tested with snapshot data of a northern hardwood‐boreal forest mountain ecotone in Vermont, a forest‐mire ecotone in New Zealand and a subalpine treeline‐tundra ecotone in Montana. The direction of vegetation boundary movement is accurately predicted for these case studies, but we also discuss potential caveats. With the availability of snapshot data rapidly increasing, the method may provide an easy tool to assess vegetation boundary movement and hence ecosystem responses to changing environmental conditions.     

Impact of ecological redundancy on the performance of machine learning classifiers in vegetation mapping

Vegetation maps are models of the real vegetation patterns and are considered important tools in conservation and management planning. Maps created through traditional methods can be expensive and time‐consuming, thus, new more efficient approaches are needed. The prediction of vegetation patterns using machine learning shows promise, but many factors may impact on its performance. One important factor is the nature of the vegetation–environment relationship assessed and ecological redundancy. We used two datasets with known ecological redundancy levels (strength of the vegetation–environment relationship) to evaluate the performance of four machine learning (ML) classifiers (classification trees, random forests, support vector machines, and nearest neighbor). These models used climatic and soil variables as environmental predictors with pretreatment of the datasets (principal component analysis and feature selection) and involved three spatial scales. We show that the ML classifiers produced more reliable results in regions where the vegetation–environment relationship is stronger as opposed to regions characterized by redundant vegetation patterns. The pretreatment of datasets and reduction in prediction scale had a substantial influence on the predictive performance of the classifiers. The use of ML classifiers to create potential vegetation maps shows promise as a more efficient way of vegetation modeling. The difference in performance between areas with poorly versus well‐structured vegetation–environment relationships shows that some level of understanding of the ecology of the target region is required prior to their application. Even in areas with poorly structured vegetation–environment relationships, it is possible to improve classifier performance by either pretreating the dataset or reducing the spatial scale of the predictions.     

Spatial patterns of woody plant and bird diversity: functional relationships or environmental effects?

Aim To understand cross‐taxon spatial congruence patterns of bird and woody plant species richness. In particular, to test the relative roles of functional relationships between birds and woody plants, and the direct and indirect environmental effects on broad‐scale species richness of both groups. Location Kenya. Methods Based on comprehensive range maps of all birds and woody plants (native species > 2.5 m in height) in Kenya, we mapped species richness of both groups. We distinguished species richness of four different avian frugivore guilds (obligate, partial, opportunistic and non‐frugivores) and fleshy‐fruited and non‐fleshy‐fruited woody plants. We used structural equation modelling and spatial regressions to test for effects of functional relationships (resource–consumer interactions and vegetation structural complexity) and environment (climate and habitat heterogeneity) on the richness patterns. Results Path analyses suggested that bird and woody plant species richness are linked via functional relationships, probably driven by vegetation structural complexity rather than trophic interactions. Bird species richness was determined in our models by both environmental variables and the functional relationships with woody plants. Direct environmental effects on woody plant richness differed from those on bird richness, and different avian consumer guilds showed distinct responses to climatic factors when woody plant species richness was included in path models. Main conclusions Our results imply that bird and woody plant diversity are linked at this scale via vegetation structural complexity, and that environmental factors differ in their direct effects on plants and avian trophic guilds. We conclude that climatic factors influence broad‐scale tropical bird species richness in large part indirectly, via effects on plants, rather than only directly as often assumed. This could have important implications for future predictions of animal species richness in response to climate change.