Biodiversity in Heterogeneous and Dynamic Landscapes

Author(s):  
Clélia Sirami

Although the concept of biodiversity emerged 30 years ago, patterns and processes influencing ecological diversity have been studied for more than a century. Historically, ecological processes tended to be considered as occurring in local habitats that were spatially homogeneous and temporally at equilibrium. Initially considered as a constraint to be avoided in ecological studies, spatial heterogeneity was progressively recognized as critical for biodiversity. This resulted, in the 1970s, in the emergence of a new discipline, landscape ecology, whose major goal is to understand how spatial and temporal heterogeneity influence biodiversity. To achieve this goal, researchers came to realize that a fundamental issue revolves around how they choose to conceptualize and measure heterogeneity. Indeed, observed landscape patterns and their apparent relationship with biodiversity often depend on the scale of observation and the model used to describe the landscape. Due to the strong influence of island biogeography, landscape ecology has focused primarily on spatial heterogeneity. Several landscape models were conceptualized, allowing for the prediction and testing of distinct but complementary effects of landscape heterogeneity on species diversity. We now have ample empirical evidence that patch structure, patch context, and mosaic heterogeneity all influence biodiversity. More recently, the increasing recognition of the role of temporal scale has led to the development of new conceptual frameworks acknowledging that landscapes are not only heterogeneous but also dynamic. The current challenge remains to truly integrate both spatial and temporal heterogeneity in studies on biodiversity. This integration is even more challenging when considering that biodiversity often responds to environmental changes with considerable time lags, and multiple drivers of global changes are interacting, resulting in non-additive and sometimes antagonistic effects. Recent technological advances in remote sensing, the availability of massive amounts of data, and long-term studies represent, however, very promising avenues to improve our understanding of how spatial and temporal heterogeneity influence biodiversity.

Author(s):  
Kimberly A. With

Heterogeneity is a defining characteristic of landscapes and therefore central to the study of landscape ecology. Landscape ecology investigates what factors give rise to heterogeneity, how that heterogeneity is maintained or altered by natural and anthropogenic disturbances, and how heterogeneity ultimately influences ecological processes and flows across the landscape. Because heterogeneity is expressed across a wide range of spatial scales, the landscape perspective can be applied to address these sorts of questions at any level of ecological organization, and in aquatic and marine systems as well as terrestrial ones. Disturbances—both natural and anthropogenic—are a ubiquitous feature of any landscape, contributing to its structure and dynamics. Although the focus in landscape ecology is typically on spatial heterogeneity, disturbance dynamics produce changes in landscape structure over time as well as in space. Heterogeneity and disturbance dynamics are thus inextricably linked and are therefore covered together in this chapter.


PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10923
Author(s):  
Fang Liu ◽  
Wanbin Wang ◽  
Jinliang Wang ◽  
Xingzi Zhang ◽  
Jing Ren ◽  
...  

Context Yunnan Province is an important ecological security barrier in China. This study investigated the temporal and spatial changes to landscape ecology and is of great significance for guiding landscape protection and future socio-economic development. Objectives To analyze the temporal and spatial changes of the landscape patterns at the county, river basin, and provincial levels, and clarify and describe the temporal and spatial differentiation characteristics of the landscape patterns in Yunnan Province. Methods Based on landscape ecology, GIS spatial analysis, and spatio-temporal change analysis, nine landscape pattern indices, and spatial autocorrelation for different years, were calculated. Results The landscape of Yunnan Province has evolved as a whole toward isolation. The indices of separation and fragmentation changed significantly from 2010 to 2015. From 2015 to 2018 the rate of fragmentation decreased. Fragmentation in the Nu Jiang and Irrawaddy River basins was less than in other basins. The landscape patterns of the Jinsha and Pearl River basins were relatively fragmented due to human activity, socioeconomic development, and utilization. The differences between the Lancang and Red River Basins were relatively small and at an intermediate level. Conclusions Spatial autocorrelation analysis indicated that there are three areas with typical clusters, namely the Hengduan Mountains where the degree of fragmentation of the landscape was low, while landscape connectivity and aggregation were high. The subtropical region of Southern Yunnan displayed high landscape heterogeneity, a complex shape index, and high connectivity and sprawl. Central Yunnan exhibited a fragmented landscape with poor connectivity and aggregation. These three regions correspond with “the three screens and two belts” in the Main Functional Planning Area of Yunnan Province.


ISRN Ecology ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Sean C. P. Coogan ◽  
Scott E. Nielsen ◽  
Gordon B. Stenhouse

Spatial and temporal heterogeneity in plant phenology and nutrition benefits herbivores by prolonging the period in which they can forage on nutritious plants. Landscape heterogeneity can therefore enhance population performance of herbivores and may be a critically important feature of their habitat. The benefits of resource heterogeneity over space and time should extend not only to large herbivores using above-ground vegetation but also to omnivores that utilize below-ground resources. We used generalized linear models to evaluate whether spatial heterogeneity influenced temporal variation in the crude protein content of alpine sweetvetch (Hedysarum alpinum) roots in west-central Alberta, Canada, thereby potentially offering nutritional benefits to grizzly bears (Ursus arctos). We demonstrated that temporal patterns in the crude protein content of alpine sweetvetch roots were influenced by spatial heterogeneity in annual growing season temperatures and soil moisture and nutrients. Spatial heterogeneity and asynchrony in the protein content of alpine sweetvetch roots likely benefit grizzly bears by prolonging the period they can forage on high quality resources. Therefore, we have presented evidence of what we termed a “brown wave” or “brown tide” in the phenology and nutrition of a below-ground plant resource, which is analogous to the previously described “green wave” in above-ground resources.


2018 ◽  
Author(s):  
Marco Sciaini ◽  
Matthias Fritsch ◽  
Cédric Scherer ◽  
Craig Eric Simpkins

AbstractNeutral landscape models (NLMs) simulate landscape patterns based on theoretical distributions and can be used to systematically study the effect of landscape structure on ecological processes. NLMs are commonly used in landscape ecology to enhance the findings of field studies as well as in simulation studies to provide an underlying landscape. However, their creation so far has been limited to software that is platform dependent, does not allow a reproducible workflow or is not embedded in R, the prevailing programming language used by ecologists.Here, we present two complementary R packages NLMR and land-scapetools, that allow users to generate, manipulate and analyse NLMs in a single environment. They grant the simulation of the widest collection of NLMs found in any single piece of software thus far while allowing for easy manipulation in a self-contained and reproducible workflow. The combination of both packages should stimulate a wider usage of NLMs in landscape ecology. NLMR is a comprehensive collection of algorithms with which to simulate NLMs. landscapetools provides a utility toolbox which facilitates an easy workflow with simulated neutral landscapes and other raster data.We show two example applications that illustrate potential use cases for NLMR and landscapetools: First, an agent-based simulation study in which the effect of spatial structure on disease persistence was studied. Here, spatial heterogeneity resulted in more variable disease outcomes compared to the common well-mixed host assumption. The second example shows how increases in spatial scaling can introduce biases in calculated landscape metrics.Simplifying the workflow around handling NLMs should encourage an uptake in the usage of NLMs. NLMR and landscapetools are both generic frameworks that can be used in a variety of applications and are a further step to having a unified simulation environment in R for answering spatial research questions.


Author(s):  
J. W. Horwood

I trust that I will not be criticized for saying that, in general, the argument between Hensen and Haeckel has been resolved. Hensen (1887, 1895) believed that true spatial and temporal heterogeneity of the plankton could be resolved by careful measurement and analyses of variance. Haeckel (1893) thought these analyses might give more information than the data possessed. Our present understanding of spatial heterogeneity, and its analysis, does not lead us to disagree with either. Investigations carried out by a number of marine ecologists have shown large-scale spatial variations in phytoplankton. Amongst many others, this feature can be seen in studies off the northeast coast of England (Cushing, 1955), in the English Channel and Celtic Sea (Cushing, 1957; Pingree et al. 1976), off Scotland (Adams, Baird & Dunn, 1975,1976) and off the coast of the Netherlands (Gieskes & Kraay, 1975). Nevertheless the statistics of sampling heterogeneous distributions is far from simple, estimates of density for instance can be greatly influenced by the sample size (e.g. Greig-Smith, 1964; Cassie, 1963). Bainbridge (1957) summarized his review by saying that patches occurred on all scales from a few feet to as much as 30 or 40 miles by 120 or 180 miles. Our present understanding of the nature of turbulence in the sea would reduce his few feet to centimetres.


2022 ◽  
Vol 12 ◽  
Author(s):  
Sandra van Wilpe ◽  
Mark A. J. Gorris ◽  
Lieke L. van der Woude ◽  
Shabaz Sultan ◽  
Rutger H. T. Koornstra ◽  
...  

Checkpoint inhibitors targeting PD-(L)1 induce objective responses in 20% of patients with metastatic urothelial cancer (UC). CD8+ T cell infiltration has been proposed as a putative biomarker for response to checkpoint inhibitors. Nevertheless, data on spatial and temporal heterogeneity of tumor-infiltrating lymphocytes in advanced UC are lacking. The major aims of this study were to explore spatial heterogeneity for lymphocyte infiltration and to investigate how the immune landscape changes during the disease course. We performed multiplex immunohistochemistry to assess the density of intratumoral and stromal CD3+, CD8+, FoxP3+ and CD20+ immune cells in longitudinally collected samples of 49 UC patients. Within these samples, spatial heterogeneity for lymphocyte infiltration was observed. Regions the size of a 0.6 tissue microarray core (0.28 mm2) provided a representative sample in 60.6 to 71.6% of cases, depending on the cell type of interest. Regions of 3.30 mm2, the median tumor surface area in our biopsies, were representative in 58.8 to 73.8% of cases. Immune cell densities did not significantly differ between untreated primary tumors and metachronous distant metastases. Interestingly, CD3+, CD8+ and FoxP3+ T cell densities decreased during chemotherapy in two small cohorts of patients treated with neoadjuvant or palliative platinum-based chemotherapy. In conclusion, spatial heterogeneity in advanced UC challenges the use of immune cell infiltration in biopsies as biomarker for response prediction. Our data also suggests a decrease in tumor-infiltrating T cells during platinum-based chemotherapy.


Botany ◽  
2010 ◽  
Vol 88 (1) ◽  
pp. 1-12 ◽  
Author(s):  
D. V. Gross ◽  
J. T. Romo

Structure, as well as spatial and temporal heterogeneity in plant species composition were studied in a Festuca hallii (Vasey) Piper – dominated Prairie in Canada for 6 years following burning before, during, or after the growing season on sites burned 1× or 3×. Structure, spatial heterogeneity, and temporal heterogeneity were never (P > 0.05) influenced by the time of burning. Diversity and richness of graminoids, perennial forbs, and shrubs fluctuated among years after burning, but were unaffected by burning history. Excepting shrubs, canopy cover of plant functional groups positively correlated with precipitation. After a single burn, spatial heterogeneity in species composition increased with years after burning, indicating plant communities were becoming patchier, whereas those burned 3× did not change predictably through time. Spatial heterogeneity in species composition between consecutive years was positively correlated, but temporal heterogeneity in species composition did not correlate with spatial heterogeneity. Burning history and precipitation appear important in controlling the plant community structure and spatial heterogeneity in species composition in Fescue Prairie.


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