Effects of fragmentation on cattle in African savannas under variable precipitation

Cattle move to access patches that vary in forage quantity and quality. Fragmentation can prevent animals from reaching patches. I used an integrative ecosystem model applied to three African landscapes to explore the sensitivity of cattle populations to fragmentation (here, changes in populations as parcel areas decreased) under different precipitation patterns. I hypothesized that low and high precipitation would yield populations relatively insensitive to fragmentation, intermediate precipitation would yield more sensitive populations, and more variable inter-annual precipitation would reduce sensitivity to fragmentation. Precipitation data were altered to yield averages of 100–1,000 mm year⁻¹ and inter-annual coefficients of variation of 0–60%. A 1,000 km² landscape in each area was divided into progressively smaller parcels and simulations conducted for each parcel. Rainfall at 100 mm year⁻¹ supported low populations that were insensitive to fragmentation. Populations peaked at rainfall levels similar to those observed, and declined under higher precipitation, due in-part to shrub expansion. Fragmenting landscapes caused up to a 62% decline in cattle. High inter-annual variation in precipitation reduced sensitivity to fragmentation when precipitation was above that observed. The pattern was opposite when precipitation was below what was observed. Cattle on the landscape with fine-scale heterogeneity were relatively insensitive to fragmentation, and those on the heterogeneous but coarse-grained landscape were extremely sensitive. Fragmentation in landscapes where populations are sensitive will require more intensive inputs to offset losses, and changes in the frequency of extreme weather associated with climate change will alter the sensitivity of some populations to fragmentation. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

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.     

Shifting concepts of urban spatial heterogeneity and their implications for sustainability

Context

Spatial heterogeneity has myriad influences on ecosystem processes, ecosystem services, and thus the sustainability of urban areas. It acts as a medium for urban design, planning, and management to determine how processes affecting sustainability can operate and interact. Therefore, how spatial heterogeneity is conceptualized and measured in cities is crucial for enhancing sustainability.

Objectives

We show that the two most commonly used, but contrasting paradigms of urban ecology, ecology IN versus ecology OF the city, determine how spatial heterogeneity is thought of and used in different ways. We identify the key implications of these theoretical contrasts for the practice and assessment of sustainability in urban areas.

Methods

We review and compare the different ways in which ecology IN versus ecology OF the city affect how to conceptualize, model and map urban spatial heterogeneity. We present a new framework to guide the comparison of spatial heterogeneity under the two paradigms.

Results and conclusion

The integrative nature of this new framework becomes apparent under the ecology OF the city paradigm, because it recognizes the hybrid social and bioecological nature of heterogeneity in urban ecosystems. The hybrid approach to patchiness resonates with the three pillars of sustainability—environment, society, and economy. We exemplify how the more comprehensive and integrated framework of spatial heterogeneity under the ecology OF the city paradigm (1) supports more effective measurement and integration of the three components of sustainability, (2) improves management of heterogeneous urban ecosystems, and (3) satisfies calls for improved ecological tools to support urban ecosystem design.

     

Using airborne LiDAR to assess spatial heterogeneity in forest structure on Mount Kilimanjaro

Context

Field inventory plots which usually have small sizes of around 0.25–1 ha can only represent a sample of the much larger surrounding forest landscape. Based on airborne laser scanning (LiDAR) it has been shown for tropical forests that the bias in the selection of small field plots may hamper the extrapolation of structural forest attributes to larger spatial scales.

Objectives

We conducted a LiDAR study on tropical montane forest and evaluated the representativeness of chosen inventory plots with respect to key structural attributes.

Methods

We used six forest inventory and their surrounding landscape plots on Mount Kilimanjaro in Tanzania and analyzed the similarities for mean top-of-canopy height (TCH), aboveground biomass (AGB), gap fraction, and leaf-area index (LAI). We also analyzed the similarity in gap-size frequencies for the landscape plots.

Results

Mean biases between inventory and landscape plots were large reaching as much as 77% for gap fraction, 22% for LAI or 15% for AGB. Despite spatial heterogeneity of the landscape, gap-size frequency distributions were remarkably similar between the landscape plots.

Conclusions

The study indicates that biases in field studies of forest structure may be strong. Even when mean values were similar between inventory and landscape plots, the mostly non-normally distributed probability densities of the forest variable indicated a considerable sampling error of the small field plot to approximate the forest variable in the surrounding landscape. This poses difficulties for the spatial extrapolation of forest structural attributes and for assessing biomass or carbon fluxes at larger regional scales.

     

Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example

Many ecological and epidemiological studies occur in systems with mobile individuals and heterogeneous landscapes. Using a simulation model, we show that the accuracy of inferring an underlying biological process from observational data depends on movement and spatial scale of the analysis. As an example, we focused on estimating the relationship between host density and pathogen transmission. Observational data can result in highly biased inference about the underlying process when individuals move among sampling areas. Even without sampling error, the effect of host density on disease transmission is underestimated by approximately 50 % when one in ten hosts move among sampling areas per lifetime. Aggregating data across larger regions causes minimal bias when host movement is low, and results in less biased inference when movement rates are high. However, increasing data aggregation reduces the observed spatial variation, which would lead to the misperception that a spatially targeted control effort may not be very effective. In addition, averaging over the local heterogeneity will result in underestimating the importance of spatial covariates. Minimizing the bias due to movement is not just about choosing the best spatial scale for analysis, but also about reducing the error associated with using the sampling location as a proxy for an individual’s spatial history. This error associated with the exposure covariate can be reduced by choosing sampling regions with less movement, including longitudinal information of individuals’ movements, or reducing the window of exposure by using repeated sampling or younger individuals.

     

Water availability is a principal driver of large-scale land cover spatial heterogeneity in sub-Saharan savannahs

Landscape Ecology - The heterogeneous mosaic nature of African savannah vegetation is a key aspect of its ecology. This study evaluates mosaic distributions and characteristics across sub-Saharan...     

Environmental heterogeneity and biotic interactions as potential drivers of spatial patterning of shorebird nests

Context

Species distributions are driven by a wide variety of abiotic and biotic factors, including nest placement for breeding individuals. As such, the spatial distribution of nests within a landscape can reflect environmental heterogeneity, habitat preferences, or even interactions with predators and other species.

Objectives

We determined the extent to which environmental heterogeneity and predation risk accounted for the observed spatial distribution of nests.

Methods

We assessed the spatial distribution of 112 nests of a migratory shorebird, the Hudsonian Godwit (Limosa haemastica), at Beluga River, Alaska, from 2009 to 2012, and explicitly tested for the relative influence of habitat characteristics and predation risk on nest locations. We also evaluated the effect of nest location, distance to conspecific nests, and proximity to roads on nest fate using 64 nests that were monitored through completion.

Results

Hudsonian Godwit nests were clustered across the landscape despite a lack of significant spatial autocorrelation (i.e., patchiness) in vegetation characteristics at either the micro- or landscape scale. Nest fate also was not predicted by either the distance to the nearest conspecific neighbor or proximity to roads. Thus, neither habitat characteristics nor predation risk explained the clustering of godwit nests.

Conclusions

These results suggest that godwits may select nest locations based more on social cues than underlying heterogeneity in vegetation or predation risk. As such, intra- and inter-specific interactions should be considered when developing management plans for species of conservation concern.

     

Ownership and ecosystem as sources of spatial heterogeneity in a forested landscape,Wisconsin, USA

The interaction between physical environment and land ownership in creating spatial heterogeneity was studied in largely forested landscapes of northern Wisconsin, USA. A stratified random approach was used in which 2500-ha plots representing two ownerships (National Forest and private non-industrial) were located within two regional ecosystems (extremely well-drained outwash sands and moderately well-drained moraines). Sixteen plots were established, four within each combination of ownership and ecosystem, and the land cover on the plots was classified from aerial photographs using a modified form of the Anderson (U.S. Geological Survey) land use and land cover classification system.Upland deciduous forests dominated by northern hardwoods were common on the moraines for both ownerships. On the outwash, the National Forest was dominated by pine plantations, upland deciduous forests, and upland regenerating forests (as defined by <50% canopy coverage). In contrast, a more even distribution among the classes of upland forest existed on private land/outwash. A strong interaction between ecosystem and ownership was evident for most comparisons of landscape structure. On the moraine, the National Forest ownership had a finer grain pattern with more complex patch shapes compared to private land. On the outwash, in contrast, the National Forest had a coarser grain pattern with less complex patch shapes compared to private land. When patch size and shape were compared between ecosystems within an ownership, statistically significant differences in landscape structure existed on public land but not on private land. On public land, different management practices on the moraine and outwash, primarily related to timber harvesting and road building, created very different landscape patterns. Landscape structure on different ecosystems on private land tended to be similar because ownership was fragmented in both ecosystems and because ownership boundaries often corresponded to patch boundaries on private land. A complex relationship exits between ownership, and related differences in land use, and the physical environment that ultimately constrains land use. Studies that do not consider these interactions may misinterpret the importance of either variable in explaining variation in landscape patterns.     

Consequences of spatial heterogeneity for ecosystem services in changing forest landscapes: priorities for future research

Changes in key drivers (e.g., climate, disturbance regimes and land use) may affect the sustainability of forest landscapes and set the stage for increased tension among competing ecosystem services. We addressed two questions about a suite of supporting, regulating and provisioning ecosystem services in each of two well-studied forest landscapes in the western US: (1) How might the provision of ecosystem services change in the future given anticipated trajectories of climate, disturbance regimes, and land use? (2) What is the role of spatial heterogeneity in sustaining future ecosystem services? We determined that future changes in each region are likely to be distinct, but spatial heterogeneity (e.g., the amount and arrangement of surviving forest patches or legacy trees after disturbance) will be important in both landscapes for sustaining forest regeneration, primary production, carbon storage, natural hazard regulation, insect and pathogen regulation, timber production and wildlife habitat. The paper closes by highlighting five general priorities for future research. The science of landscape ecology has much to contribute toward understanding ecosystem services and how land management can enhance—or threaten—the sustainability of ecosystem services in changing landscapes.     

Spatio-temporal modelling of broad scale heterogeneity in soil moisture content: a basis for an ecologically meaningful classification of soil landscapes

We describe the classification of landscapes characterised bymineral soil using a model that calculates soil moisture availability on amonthly basis. Scotland is used as a case study area. The model uses potentialsoil moisture deficit, estimated using broad scale (40 × 40 km)climate patterns, in conjunction with meteorological station measurements toobtain finer scale values of climatic soil moisture deficit. Point estimates ofsoil available water are obtained for soil characteristics using appropriatepedotransfer functions, and geostatistical techniques are used to upscale theresults and interpolate to a 1-km grid. Known heterogeneityin soil physical characteristics is used to provide local corrections to thepotential soil moisture deficit, estimated using the climatic variables above.Temporal profiles of monthly water content are modelled for each1-km location and classified into six classes usingunsupervised cluster analysis. The spatial distribution of these classesreflects regional variations in the availability of moisture and energy, onwhich finer-grained topographic patterns are superimposed. In the case study,the broad scale spatial heterogeneity of heathlands and grasslands on mineralsoils in Scotland is shown to be strongly related to the soil moistureclassification. The results can be used in studies investigating the patternsofdistribution of communities at the landscape and regional scale.This revised version was published online in May 2005 with corrections to the Cover Date.     

菜地土壤氮素迁移转化研究进展

农业面源污染已成为我国环境污染的重要组成部分,对我国农业生产和生态环境安全带来了较大风险。农田氮素随地表径流流失和地下淋溶是引起日益突出的农业面源污染的主要因素之一。氮素养分是影响蔬菜产量的重要因子,为追求经济效益,菜地氮肥投入量大,过量施肥造成的氮素污染问题日趋严重。笔者综述了菜地氮素迁移转化研究现状,探讨了菜地施肥、地表径流、地下淋溶、氨挥发等菜地土壤氮素迁移和转化途径,分析了土壤中氮素矿化、硝化和反硝化过程,并对今后研究方向进行了展望。     

Subsystems,flowpaths, and the spatial variability of nitrogen in a fluvial ecosystem

Nutrient dynamics in rivers affect biogeochemical fluxes from land to oceans and the atmosphere. Fluvial ecosystems are thus important environments for understanding spatial variability in nutrient concentrations. At the San Pedro River in semi-arid Arizona, USA, we investigated how variability in dissolved inorganic nitrogen (DIN) was regulated by subsystem type and hydrological flowpaths. The three subsystems we compared were the riparian zone, parafluvial (gravel bar) zone, and surface stream. DIN concentration was greater in the riparian zone than in the surface stream, suggesting that the riparian zone retains DIN and is a source of N for the surface stream. Parafluvial zones were too variable to generalize how they regulate DIN. Our hypothesis that subsystem type regulates DIN oxidation was too simple. The riparian and parafluvial zones host a mosaic of oxidizing and reducing conditions, as they exhibited highly variable ammonium to nitrate (NH₄⁺:NO₃⁻) ratios. Surface stream DIN was dominated by NO₃⁻. Along a subsurface flowpath in the riparian zone, we did not observe spatial covariation among the N forms and transformations involved in mineralization. We also compared spatial variability in solute concentrations between flowpaths and non-flowpath reference areas. Our mixed results suggest that spatial variability is regulated in part by flowpaths, but also by solute-specific processing length along a flowpath. To understand the distribution of N in fluvial ecosystems, subsystem type and flowpaths are readily discernable guides, but they should be coupled with other mechanistic factors such as biota and soil type.     

The influence of landscape spatial configuration on nitrogen and phosphorus exports in agricultural catchments

Landscape Ecology - Nitrogen (N) and phosphorus (P) exports from rural landscapes can cause eutrophication of inland and coastal waters. Few studies have investigated the influence of the spatial...     

Spatial heterogeneity of subsurface soil texture drives landscape-scale patterns of woody patches in a subtropical savanna

Context

In the Rio Grande Plains of southern Texas, subtropical savanna vegetation is characterized by a two-phase pattern consisting of discrete woody patches embedded within a C₄ grassland matrix. Prior trench transect studies have suggested that, on upland portions of the landscape, large woody patches (groves) occur on non-argillic inclusions, while small woody patches (clusters) are dispersed among herbaceous vegetation where the argillic horizon is present.

Objective

To test whether spatial heterogeneity of subsurface soil texture drives the landscape-scale pattern of woody patches in this subtropical savanna.

Methods

Landscape-scale spatial patterns of soil texture were quantified by taking spatially-specific soil samples to a depth of 1.2 m in a 160 m × 100 m plot. Kriged maps of soil texture were developed, and the locations of non-argillic inclusions were mapped.

Results

Visual comparison of kriged maps of soil texture to a high resolution aerial photograph of the study area revealed that groves were present exclusively where the non-argillic inclusions were present. This clear visual relationship was further supported by positive correlations between soil sand concentration in the lower soil layers and total fine root biomass which mapped the locations of groves.

Conclusions

Subsurface non-argillic inclusions may favor the establishment and persistence of groves by enabling root penetration deeper into the profile, providing greater access to water and nutrients that are less accessible on those portions of the landscape where the argillic horizon is present, thereby regulating the distribution of grove vegetation and structuring the evolution of this landscape.

     

不同种植年限设施菜田土壤硝态氮的累积与空间分布特性

为了解新乡市牧野区冬春茬蔬菜拉秧后,即夏季敞棚休闲期,硝态氮在各土层中的残留、空间分布状况及淋失风险,试验以农田为对照,采集了不同种植年限(2年、3年、16年和21年)设施菜田土壤样品进行测定分析。结果表明,设施菜田各土层硝态氮含量和累积量均高于农田,且二者均随种植年限的增加而增大,与种植年限间有极显著的线性正相关。各种植年限设施菜田中,随土层加深,硝态氮含量及累积量呈先降后增的趋势。其中,表层较高,40～60 cm最低,至80～100 cm达最大。虽然种植年限对表层土壤硝态氮的富集作用大于下层土壤,但这种由肥料表施而造成的硝态氮富集现象,会因降雨或灌水,形成在下层土体的空间分布重构。综上,随种植年限增加,设施菜田硝态氮淋失风险加剧,应控制氮肥投入量和灌水量。     

Spatial variability in soil nitrogen dynamics after prescribed burning in Ohio mixed-oak forests

This study describes the results of the application of a single dormant season prescribed fire to two southern Ohio forest sites for the purposes of restoring the ecosystem functional properties that existed in these sites prior to major human intervention (clearcutting, fire suppression, and atmospheric deposition). Each forest site was composed of three contiguous watershed units, two of which were burned in April of 1996. The forest sites differed in soil pH and available litter mass prior to the fires, and in both sites pH and available inorganic N varied among landscape positions such that inorganic C increased with increasing longterm soil moisture potential (measured as the GIS-derived Integrated Moisture Index [IMI] developed for this region). The fire temperatures at 10 cm above the litter surface were generally 150–300°C, and 29–80% of the litter was consumed, depending on site and landscape position. Soil solution total inorganic N (TIN) present one month after the fires did not differ significantly from that present prior to the fires in either burned or unburned watersheds, but was consistently greater in mesic landscape positions than in more xeric ones. N mineralization potential and organic C content varied both among fires and landscape positions. At the site which burned at higher intensity, soil N mineralization and TIN were both decreased by fire. At the less intensely burned site, fire resulted in increased TIN in the soils from the more xeric landscape position, and greater soil organic C in soils from the intermediate soil moisture areas. Path analysis produced models for fire-induced changes in C and N dynamics capable of explaining 26–69% of the observed variation using combinations of landscape and fire behavior. Losses of N to volatilization from these single fires were generally < 1 kg N/ha, and thus could not be expected to ameliorate the effects of atmospheric N deposition in these sites.     

Effects of spatial habitat heterogeneity on habitat selection and annual fecundity for a migratory forest songbird

Understanding how spatial habitat patterns influence abundance and dynamics of animal populations is a primary goal in landscape ecology. We used an information-theoretic approach to investigate the association between habitat patterns at multiple spatial scales and demographic patterns for black-throated blue warblers (Dendroica caerulescens) at 20 study sites in west-central Vermont, USA from 2002 to 2005. Sites were characterized by: (1) territory-scale shrub density, (2) patch-scale shrub density occurring within 25 ha of territories, and (3) landscape-scale habitat patterns occurring within 5 km radius extents of territories. We considered multiple population parameters including abundance, age ratios, and annual fecundity. Territory-scale shrub density was most important for determining abundance and age ratios, but landscape-scale habitat structure strongly influenced reproductive output. Sites with higher territory-scale shrub density had higher abundance, and were more likely to be occupied by older, more experienced individuals compared to sites with lower shrub density. However, annual fecundity was higher on sites located in contiguously forested landscapes where shrub density was lower than the fragmented sites. Further, effects of habitat pattern at one spatial scale depended on habitat conditions at different scales. For example, abundance increased with increasing territory-scale shrub density, but this effect was much stronger in fragmented landscapes than in contiguously forested landscapes. These results suggest that habitat pattern at different spatial scales affect demographic parameters in different ways, and that effects of habitat patterns at one spatial scale depends on habitat conditions at other scales.     

Predictive modeling of spatial patterns of soil nutrients related to fertility islands

In arid shrublands, soil resources are patchily distributed around shrub canopies, forming well-studied “islands of fertility.” While soil nutrient patterns have previously been characterized quantitatively, we develop a predictive model that explicitly considers the distance from shrubs of varying canopy sizes. In 1-ha macroplots in both the Sonoran and Mojave Deserts, we used Plant Root Simulator? probes to measure nutrient availability along transects extending north and south from creosote bushes (Larrea tridentata). We modeled the decline of nutrients with distance from focal shrubs using hierarchical mixed models that included the effects of transect direction and shrub canopy size. Of the nutrients considered, nitrogen and potassium had the strongest response to distance from focal shrubs. In the Sonora, both depended on canopy size and had different patterns to the north versus the south. In the Mojave, potassium depended on size and direction, but nitrogen only on canopy size. We used the fitted model equations and the location and canopy size of all Larrea shrubs within the macroplots to estimate nutrient concentrations at a 20 cm resolution. This produced maps showing nutrient “hotspots” centered on Larrea. Our models predicted up to 60 % of the variation in nutrient availability the following growing season. Our models efficiently used a moderate number of sample locations to predict nutrient concentrations over a large area, given easily measured values of shrub size and location. Our method can be applied to many systems with patchily distributed resources focused around major structural landscape features.