Population Dynamics of a Seed Feeding Bug, Lygaeus Equestris. 1. Habitat Patch Structure and Spatial Dynamics

Oikos ◽  
1990 ◽  
Vol 58 (2) ◽  
pp. 199 ◽  
Author(s):  
Christer Solbreck ◽  
Birgitta Sillén-Tullberg ◽  
Birgitta Sillen-Tullberg
Keyword(s):  
Population Dynamics ◽  
Spatial Dynamics ◽  
Habitat Patch ◽  
Patch Structure ◽  
Lygaeus Equestris

scholarly journals Consequences of barriers and changing seasonality on population dynamics and harvest of migratory ungulates

2020 ◽  
Vol 13 (4) ◽  
pp. 595-605
Author(s):  
Bram Van Moorter ◽  
Steinar Engen ◽  
John M. Fryxell ◽  
Manuela Panzacchi ◽  
Erlend B. Nilsen ◽  
...  
Keyword(s):  
Climate Change ◽  
Population Dynamics ◽  
Population Size ◽  
Spatial Dynamics ◽  
Infrastructure Development ◽  
Negative Effects ◽  
Behavioral Avoidance ◽  
Animal Populations ◽  
The Difference ◽  
Global Threat

AbstractMany animal populations providing ecosystem services, including harvest, live in seasonal environments and migrate between seasonally distinct ranges. Unfortunately, two major sources of human-induced global change threaten these populations: climate change and anthropogenic barriers. Anthropogenic infrastructure developments present a global threat to animal migrations through increased migration mortality or behavioral avoidance. Climate change alters the seasonal and spatial dynamics of resources and therefore the effects of migration on population performance. We formulated a population model with ideal-free migration to investigate changes in population size and harvest yield due to barriers and seasonal dynamics. The model predicted an increasing proportion of migrants when the difference between areas in seasonality or carrying capacity increased. Both migration cost and behavioral avoidance of barriers substantially reduced population size and harvest yields. Not surprisingly, the negative effects of barriers were largest when the population benefited most from migration. Despite the overall decline in harvest yield from a migratory population due to barriers, barriers could result in locally increased yield from the resident population following reduced competition from migrants. Our approach and results enhance the understanding of how global warming and infrastructure development worldwide may change population dynamics and harvest offtake affecting livelihoods and rural economies.

Of Mice and Men: What Rodent Populations Can Teach Us about Complex Spatial Dynamics

1988 ◽  
Vol 20 (1) ◽  
pp. 99-109 ◽  
Author(s):  
H Couclelis
Keyword(s):  
Population Dynamics ◽  
Complex Systems ◽  
Cellular Automaton ◽  
Chaotic System ◽  
Spatial Dynamics ◽  
Human Geography ◽  
System Behavior ◽  
Rodent Population ◽  
Rodent Populations ◽  
Scientific Fields

Models of complex systems need not be themselves complex, let alone complicated. To illustrate this important point, a very simple cellular automaton model of rodent population dynamics is used to generate a wide variety of different spatiotemporal structures corresponding to different forms of equilibrium, cyclical, quasi-cyclical, and chaotic system behavior. The issue of complexity as it pertains to a number of different contemporary scientific fields is then discussed, and in particular its implications for prediction. The discussion ends with some general reflexions about modeling in human geography.

Landscape-level movements of North American elk (Cervus elaphus): effects of habitat patch structure and topography

2005 ◽  
Vol 20 (3) ◽  
pp. 289-300 ◽  
Author(s):  
John G. Kie ◽  
Alan A. Ager ◽  
R. Terry Bowyer
Keyword(s):  
Cervus Elaphus ◽  
North American ◽  
Habitat Patch ◽  
Patch Structure ◽  
North American Elk ◽  
Landscape Level

scholarly journals Avian Species Abundance and Richness in a  Variably Urbanised Landscape in Wellington City,  New Zealand

2021 ◽  
Author(s):  
◽  
Jennifer Glynn Vinton
Keyword(s):  
Species Richness ◽  
Patch Size ◽  
Species Abundance ◽  
Bird Species ◽  
Habitat Patch ◽  
Avian Community ◽  
Patch Structure ◽  
Avian Biodiversity ◽  
Species Richness And Abundance ◽  
Species Ecology

<p>Avian community composition fluctuates across the landscape at different scales of space and time. These fluctuations may be modified at the broader scale of landscape and at the local scale of habitat patch. A species' ecology also influences its occurrence and abundance in the landscape. This thesis investigates the spatial and temporal distribution of the avian community in Wellington. Wellington is an interesting case study because it has a diverse range of landscapes influenced by the proximity of hills to the coast (see Appendix 3). I assess the effect of landscape classification on the richness and abundance of birds and the role of fine patch structure in shaping this distribution. My study was located within a 5-km radius of Wellington City's central business district (41 degrees 16' S, 174 degrees 46' E). I used six strip-transects divided into 400m length segments that traversed through high to lower density residential suburbs and green space inter-digitated with built habitat, and established five-minute count (FMBC) points at each segment interval along these routes for a total of 49 points. I used ArcGIS to analyse the habitat patch types in the 100-m areas surrounding the FMBC. I recorded avian species type and abundance along the strips and at the FMBC during the morning and evening. A total of 35 bird species and 10966 individuals were recorded along the strip-transects and 34 bird species and 5960 individuals at the FMBCs. House sparrow, then starling and blackbacked gull, rock pigeon, blackbird and silvereye were the most common and widely spread species. Results indicated that landscape type modified avian biodiversity with the highest number of species (S) recorded in green landscapes (n = 10, S = 15.9) and the lowest in wharf littoral (n = 2, S = 7.5) and low-density commercial sites (n = 3, S = 6.67). The diversity of the landscape within an area did not influence avian biodiversity. I found that total species abundance did not change across the landscape but that the species' ecology did influence where it occurred and its abundance in the landscape. Dietary diversity particularly influenced a species' abundance. Both season and time of day altered species richness and abundance, with lower values of richness recorded in autumn (morning period = 13.5, evening period = 10.7). I found that avian communities in the Wellington urban area were dominated by six common species but that many more species were present in much lower numbers at fewer sites. Results showed an inverse relationship between species richness and abundance - while the greater biomass (abundance) of birds concentrated at FMBC within the built commercial centre and surrounding higher density housing areas, richness increased with distance from the built centre to residential and green sites. I found no relationship between species richness and the total number of individuals present at any point, and the total biomass and abundance of birds was also independent of patch size. Neither habitat patch diversity nor average patch size influenced species diversity across the community of birds, but the effect of average patch size was less at patches between 300 and 1500 metres. The abundance of some individuals in their favoured patch type did vary in response to patch structure with the strongest relationships seen for blackbird and house sparrow. These results suggest that birds are responding to cues at the larger scale of landscape first rather than to fine patch structure within the urban setting, and therefore that landscape is a more important influence in driving bird biodiversity.</p>

Virus Dynamics and Arms Races

2018 ◽  
pp. 91-119
Author(s):  
Ricard Solé ◽  
Santiago F. Elena
Keyword(s):  
Population Dynamics ◽  
Immune System ◽  
Life Histories ◽  
Spatial Dynamics ◽  
Virus Dynamics ◽  
Evolutionary Models ◽  
Arms Races ◽  
Multiscale Dynamics ◽  
Key Aspects ◽  
Hiv 1

The life histories of viruses cannot be understood outside the context of their host partners. Because they cannot exist without the environment defined by their target organisms, understanding the behavior of viruses inevitably leads to consideration of how they and their hosts coevolve. Mathematics is also key to understanding evolution. This chapter studies several models describing key aspects of virus–host dynamics on different scales. As an illustrative example, the discussion focuses on the interaction between HIV-1 and the immune system, using both ecological and evolutionary models. The chapter covers HIV multiscale dynamics, population dynamics of HIV, infection, spatial dynamics of HIV-1, antigenic diversity thresholds and AIDS, and viral symbiosis.

Population Dynamics of a Seed Feeding Bug, Lygaeus Equestris. 2. Temporal Dynamics

Oikos ◽  
1990 ◽  
Vol 58 (2) ◽  
pp. 210 ◽  
Author(s):  
Birgitta Sillén-Tullberg ◽  
Christer Solbreck ◽  
Birgitta Sillen-Tullberg
Keyword(s):  
Population Dynamics ◽  
Temporal Dynamics ◽  
Lygaeus Equestris

Simulating spatial dynamics to evaluate methods of deriving abundance indices for tropical tunas

2010 ◽  
Vol 67 (9) ◽  
pp. 1409-1427 ◽  
Author(s):  
Thomas R. Carruthers ◽  
Murdoch K. McAllister ◽  
Robert N. M. Ahrens
Keyword(s):  
Population Dynamics ◽  
Relative Abundance ◽  
Spatial Dynamics ◽  
Selection Criterion ◽  
Information Criterion ◽  
Fishing Effort ◽  
Catch Per Unit Effort ◽  
Applied Model ◽  
Thunnus Obesus ◽  
Abundance Indices

Relative abundance indices derived from nominal catch-per-unit-effort (CPUE) data are a principle source of information for the majority of stock assessments. A particular problem with formulating such abundance indices for pelagic species such as tuna is the interpretation of CPUE data from fleets that have changed distribution over time. In this research, spatial population dynamics are simulated to test the historical pattern of fishing effort as a basis for making inferences about relative abundance. A number of age-structured, spatially disaggregated population dynamics models are described for both Atlantic yellowfin tuna ( Thunnus albacares ) and bigeye tuna ( Thunnus obesus ) to account for uncertainty in spatial distribution and movement. These models are used to evaluate the reliability of standardization methods and a commonly applied model selection criterion, Akaike’s information criterion (AIC). The simulations demonstrate the pitfalls of aggregating CPUE data over spatial areas and highlight the need for data imputation. Simulations support simpler models than those selected using AIC for extracting reliable indices of relative abundance.

Macro-habitat patch structure, environmental harshness, and Marmota flaviventris

1981 ◽  
Vol 8 (3) ◽  
pp. 175-182 ◽  
Author(s):  
D. R. Webb
Keyword(s):  
Habitat Patch ◽  
Marmota Flaviventris ◽  
Patch Structure

A spatial approach to understanding herring population dynamics

2016 ◽  
Vol 73 (2) ◽  
pp. 177-188 ◽  
Author(s):  
Geir Huse
Keyword(s):  
Population Dynamics ◽  
Life Cycle ◽  
Barents Sea ◽  
Spatial Dynamics ◽  
Multiple Hypothesis Testing ◽  
Clupea Harengus ◽  
Test Bed ◽  
Fish Stocks ◽  
Norwegian Coast ◽  
Full Life Cycle

Johan Hjort’s so-called second recruitment hypothesis addressed the fate of offspring that drift out of areas suitable for their survival. This hypothesis has forged the concept of a population as a closed life cycle, making countercurrent adult spawning migration a necessary mechanism in balancing larval drift. The Norwegian spring-spawning (NSS) herring stock (Clupea harengus), the object of much of Hjort’s work, is spread over large areas in the Northeast Atlantic, with spawning along the Norwegian coast, nursery areas in the Barents Sea, feeding areas in the Norwegian Sea, and overwintering areas outside northern Norway. Understanding the spatial dynamics of highly migratory fish stocks such as the NSS herring, therefore, is critical to understanding their population dynamics. Here I review hypotheses on the spatial dynamics of fish focusing on NSS herring and discuss consequences for population dynamics and interactions with other ecosystem components. The results illustrate the key role that strong herring cohorts play both as predators in the Barents and Norwegian seas and as prey on the overwintering and spawning grounds along the Norwegian coast. It is advocated that spatial full life cycle models should be developed for key fish stocks as a meeting place for model assumptions and observations and as a test bed for a multiple hypothesis testing approach.

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