Modeling the spread of the Argentine ant into natural areas: Habitat suitability and spread from neighboring sites

2012 ◽  
Vol 247 ◽  
pp. 262-272 ◽  
Author(s):  
Katherine Fitzgerald ◽  
Nicole Heller ◽  
Deborah M. Gordon
Author(s):  
Anatoly Istomin ◽  
Sergey Mikhalap

An important task of modern ecology is the modeling of the spatial distribution of organisms. Of particular relevance is the modeling of the distribution of rare species in protected natural areas. The paper discusses the main stages and presents the results of modeling the habitat suitability of the Central Forest State Nature Biosphere Reserve (Russia, Tver region) for the red vole. This species is a rare and relict for the center of the Caspian-Baltic watershed. In the modelling the maximum entropy method (MaxEnt) was used. The basis for building the model was the field sampling of the authors, performed in July-August 2010-2014. Each year, trapping were carried out at 745 sampling points each of which has geographical referencing in the WGS 84. A total of 12238 trap-days were worked out and 141 red vole individuals were caught. In the process of modeling, the contribution to the species distribution of certain integral characteristics of habitats (relief, vegetation type and three vegetation spectral indices) was determined. A map model of habitat suitability for the red vole on the territory of the Reserve was built, which allowed to describe the spatial structure of the population groups of the species. The total areas of the most favorable sites for the habitat of the red vole on the reserve's territory were calculated.


Author(s):  
Karen F. Beazley ◽  
Tamaini V. Snaith ◽  
Frances MacKinnon ◽  
David Colville

Habitat conversion, degradation and fragmentation, and the introduction of exotic species are among the primary factors causing the loss of biodiversity. Road density is a valuable indicator of these anthropogenic factors. Deleterious biological effects extend more than 1000 metres from roads, and road density of 0.6 km/km2 has been identified as an apparent threshold value above which natural populations of certain large vertebrates decline. Road density assessments in Nova Scotia indicate that many areas exceed this threshold. Multivariate logistic regression analyses indicate relationships between road density, moose pellet distribution, and habitat suitability values. Road density has a statistically significant negative correlation with moose pellets, such that as road density increases, the probability of moose pellet presence decreases. Road density alone and road density in combination with habitat suitability index values predict the presence of moose pellets, whereas habitat suitability values alone do not. Thus, road density may be an indicator of moose habitat selection or effectiveness in mainland Nova Scotia. Biodiversity conservation activities in Nova Scotia and elsewhere could focus on discouraging further road densities above 0.6 km/km2; protecting remaining roadless and low road density areas; minimizing new road construction, especially in natural areas; decommissioning and regenerating old logging roads; increasing buffer zones between natural areas and roads; and providing road crossings for wildlife in the form of under and overpasses.La conversion, la dégradation et la fragmentation des habitats ainsi que l’introduction d’espèces exotiques figurent parmi les principaux facteurs responsables de la réduction de la biodiversité. La densité routière est un indicateur précieux de ces facteurs anthropiques. Des effets biologiques négatifs se font sentir à plus de 1 000 mètres des routes, et il semble qu’une densité routière de 0,6 km/km2 constitue un seuil au-dessus duquel les populations naturelles de certains gros vertébrés diminuent. En Nouvelle-Écosse, la densité routière dépasse ce seuil dans plusieurs régions. Des analyses de régression logistique multivariée révèlent des relations entre la densité routière, la répartition des excréments d’orignaux et les valeurs de qualité de l’habitat. Il existe une corrélation négative significative entre la densité routière et les excréments d’orignaux, l’augmentation de la densité routière réduisant la probabilité de la présence d’excréments. La densité routière seule et la densité routière combinée aux valeurs de l’indice de qualité de l’habitat permettent de prévoir la présence d’excréments d’orignaux, tandis que les valeurs de qualité de l’habitat seules ne peuvent le faire. Par conséquent, la densité routière peut être un indicateur du choix ou de l’utilité de l’habitat pour l’orignal dans la partie continentale de la Nouvelle-Écosse. Dans cette province et ailleurs, les activités de conservation de la biodiversité pourraient mettre l’accent sur le maintien de la densité routière à moins de 0,6 km/km2, sur la protection des zones sans route et à faible densité routière, sur la réduction de la construction de nouvelles routes, en particulier dans les régions naturelles, sur la mise hors-service et la restauration des vieux chemins d’exploitation forestière, sur l’augmentation des zones tampons entre les régions naturelles et les routes et sur l’aménagement de traversées routières (tunnels et viaducs) pour les animaux sauvages.


2020 ◽  
Author(s):  
Leslie A. Brandt ◽  
Cait Rottler ◽  
Wendy S. Gordon ◽  
Stacey L. Clark ◽  
Lisa O'Donnell ◽  
...  

The trees, developed green spaces, and natural areas within the City of Austin’s 400,882 acres will face direct and indirect impacts from a changing climate over the 21st century. This assessment evaluates the vulnerability of urban trees and natural and developed landscapes within the City Austin to a range of future climates. We synthesized and summarized information on the contemporary landscape, provided information on past climate trends, and illustrated a range of projected future climates. We used this information to inform models of habitat suitability for trees native to the area. Projected shifts in plant hardiness and heat zones were used to understand how less common native species, nonnative species, and cultivars may tolerate future conditions. We also assessed the adaptability of planted and naturally occurring trees to stressors that may not be accounted for in habitat suitability models such as drought, flooding, wind damage, and air pollution. The summary of the contemporary landscape identifies major stressors currently threatening trees and forests in Austin. Major current threats to the region’s urban forest include invasive species, pests and disease, and development. Austin has been warming at a rate of about 0.4°F per decade since measurements began in 1938 and temperature is expected to increase by 5 to 10°F by the end of this century compared to the most recent 30-year average. Both increases in heavy rain events and severe droughts are projected for the future, and the overall balance of precipitation and temperature may shift Austin’s climate to be more similar to the arid Southwest. Species distribution modeling of native trees suggests that suitable habitat may decrease for 14 primarily northern species, and increase for four more southern species. An analysis of tree species vulnerability that combines model projections, shifts in hardiness and heat zones, and adaptive capacity showed that only 3% of the trees estimated to be present in Austin based on the most recent Urban FIA estimate were considered to have low vulnerability in developed areas. Using a panel of local experts, we also assessed the vulnerability of developed and natural areas. All areas were rated as having moderate to moderate-high vulnerability, but the underlying factors driving that vulnerability differed by natural community and between East and West Austin. These projected changes in climate and their associated impacts and vulnerabilities will have important implications for urban forest management, including the planting and maintenance of street and park trees, management of natural areas, and long-term planning.


2020 ◽  
Vol 641 ◽  
pp. 159-175
Author(s):  
J Runnebaum ◽  
KR Tanaka ◽  
L Guan ◽  
J Cao ◽  
L O’Brien ◽  
...  

Bycatch remains a global problem in managing sustainable fisheries. A critical aspect of management is understanding the timing and spatial extent of bycatch. Fisheries management often relies on observed bycatch data, which are not always available due to a lack of reporting or observer coverage. Alternatively, analyzing the overlap in suitable habitat for the target and non-target species can provide a spatial management tool to understand where bycatch interactions are likely to occur. Potential bycatch hotspots based on suitable habitat were predicted for cusk Brosme brosme incidentally caught in the Gulf of Maine American lobster Homarus americanus fishery. Data from multiple fisheries-independent surveys were combined in a delta-generalized linear mixed model to generate spatially explicit density estimates for use in an independent habitat suitability index. The habitat suitability indices for American lobster and cusk were then compared to predict potential bycatch hotspot locations. Suitable habitat for American lobster has increased between 1980 and 2013 while suitable habitat for cusk decreased throughout most of the Gulf of Maine, except for Georges Basin and the Great South Channel. The proportion of overlap in suitable habitat varied interannually but decreased slightly in the spring and remained relatively stable in the fall over the time series. As Gulf of Maine temperatures continue to increase, the interactions between American lobster and cusk are predicted to decline as cusk habitat continues to constrict. This framework can contribute to fisheries managers’ understanding of changes in habitat overlap as climate conditions continue to change and alter where bycatch interactions could occur.


1996 ◽  
Vol 14 (1) ◽  
pp. 5-14
Author(s):  
Marc A. Matsil ◽  
Michael J. Feller

2019 ◽  
Vol 39 (4) ◽  
pp. 452
Author(s):  
Margaret H. Massie ◽  
Todd M. Wilson ◽  
Anita T. Morzillo ◽  
Emilie B. Henderson

2020 ◽  
Vol 32 (1) ◽  
pp. 153-172
Author(s):  
Yun-Jin Shim ◽  
Yong-Su Park ◽  
Rae-Ha Jang ◽  
Young-Jun Yoon ◽  
Sun- Ryoung Kim ◽  
...  

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