Determining Minimum Habitat Areas and Habitat Corridors for Cougars

I simulated population dynamics of cougars to predict the minimum areas and levels of immigration needed to avoid population extinction caused by demographic and environmental stochasticity for a period of 100 years. Under most plausible parameter values, the model predicted very low extinction risk in areas as small as 2200 km², and (in the absence of immigration) increasing risk as area decreased below 2200 km². If as few as one to four animals per decade could immigrate into a small population, the probability of population persistence increased markedly. Thus a corridor for immigration will benefit a small population in an area where further loss of habitat will occur. The model was applied to the cougar population in the Santa Ana Mountain Range of southern California (2070 km², with about 20 adults). Field data support the model’s conclusion that this population is demographically unstable. There will be a high risk of extinction if the habitat is reduced to currently protected and connected areas (1114 km²). A movement corridor allowing immigration from the adjacent population and intra-range corridors would greatly enhance the prognosis. However, the last corridor for immigration has been degraded by recent human activity. Within the mountain range, cougars recently became extinct in a 75 km² habitat fragment recently isolated by development, and cougars will become extinct in another 150 km² of habitat if a proposed housing project occludes a critical corridor. Radio tracking has confirmed use of this and other important corridors. Neither the model nor the field data alone would have much influence in the face of development pressure; together they have stimulated interest in restoring and protecting critical corridors in this range. Nonetheless, the long-term prognosis for this populations is bleak, because 22 local governments review potential impact on a case-by-case basis. Effective land-use planning must be spatially explicit and regional in scope. Because cougars need corridors and because telemetered cougars can quickly identify movement corridors, cougar research is an efficient and appropriate way to inject biological data into such planning efforts.     

Cougar Dispersal Patterns, Metapopulation Dynamics, and Conservation

Abstract: We examined cougar (   Puma concolor ) dispersal, emigration, and immigration in the San Andres Mountains, New Mexico, from 1985 to 1995 to quantify the effects of dispersal on the local population and surrounding subpopulations. We captured, tagged, and radio-collared animals to detect the arrival of new immigrants and dispersal characteristics of progeny. We found that cougars in southern New Mexico exhibited a metapopulation structure in which cougar subpopulations were separated by expanses of noncougar habitat and linked by dispersers. Of 43 progeny (n = 20 males , 23 females ) studied after independence, only 13 females exhibited philopatric behavior. Males dispersed significantly farther than females, were more likely to traverse large expanses of noncougar habitat, and were probably most responsible for nuclear gene flow between habitat patches. We estimated that an average of 8.5 progeny (i.e., cougars born in the study area) successfully emigrated from and 4.3 cougars successfully immigrated to the San Andres Mountains each year. Concurrently, an average of 4.1 progeny were recruited into the San Andres cougar population. Protected cougar subpopulations can contribute to metapopulation persistence by supplying immigrants to surrounding subpopulations that are affected by fragmentation or offtake by humans. Cougar population dynamics and dispersal behavior dictate that cougar management and conservation should be considered on a regional scale.     

Modelling habitat overlap among sympatric mesocarnivores in southern Illinois,USA

Few researchers have developed large-scale habitat models for sympatric carnivore species. We created habitat models for red foxes (Vulpes vulpes), coyotes (Canis latrans) and bobcats (Lynx rufus) in southern Illinois, USA, using the Penrose distance statistic, remotely sensed landscape data, and sighting location data within a GIS. Our objectives were to quantify and spatially model potential habitat differences among species. Habitat variables were quantified for 1-km² buffered areas around mesocarnivore sighting locations. Following variable reduction procedures, five habitat variables (percentage of grassland patches, interspersion–juxtaposition of forest patches, mean fractal dimension of wetland patches and the landscape, and road density) were used for analysis. Only one variable differed (P < 0.05) between red fox and coyote sighting areas (road density) and bobcat and coyote sighting areas (mean fractal dimension of the landscape). However, all five variables differed between red fox and bobcat sighting areas, indicating considerable differences in habitat affiliation between this pair-group. Compared to bobcats, red fox sightings were affiliated with more grassland cover and larger grassland patches, higher road densities, lower interspersion and juxtaposition of forest patches, and lower mean fractal dimension of wetland patches. These differences can be explained by different life history requirements relative to specific cover types. We then used the Penrose distance statistic to create habitat models for red foxes and bobcats, respectively, based on the five-variable dataset. An independent set of sighting locations were used to validate these models; model fit was good with 65% of mesocarnivore locations within the top 50% of Penrose distance values. In general, red foxes were affiliated with mixtures of agricultural and grassland cover, whereas bobcats were associated with a combination of grassland, wetland, and forest cover. The greatest habitat overlap between red foxes and bobcats was found at the interface between forested areas and more open cover types. Our study provides insight into habitat overlap among sympatric mesocarnivores, and the distance-based modelling approach we used has numerous applications for modelling wildlife–habitat relationships over large scales.     

Individual-based modeling of flooding and salinity effects on a coastal swamp forest

Coastal swamps are among the rapidly vanishing wetland habitats in Louisiana. Increased flooding, nutrient and sediment deprivation, and salt-water intrusion have been implicated as probable causes of the decline of coastal swamps. We developed a two-species individual-based forest succession model to compare the growth and composition of a cypress-tupelo swamp under various combinations of flooding intensity and salinity levels, using historical time-series of stage and salinity data as inputs. Our model simulates forest succession over 500 years by representing the growth, mortality, and reproduction of individual Taxodium distichum (baldcypress) and Nyssa aquatica (water tupelo) trees in a 1-km² spatial grid of 10 m × 10 m cells that vary in water levels and salinity through differences in elevation. We independently adjusted the elevations of each cell to obtain different grid-wide mean elevations and standard deviations of elevation; this affected the temporal and spatial pattern of flooding. We calibrated the model by adjusting selected parameters until averaged basal area, stem density and wood production rates under two different mean elevations (partially versus highly flooded) were qualitatively similar to comparable values reported for swamps in the literature. Corroboration involved comparing model predictions to four well-monitored contrasting habitat sites within the Maurepas Basin, Louisiana, USA. Model predictions of both species combined showed the same patterns among sites as the data, but the model overestimated wood production and the dominance of T. distichum. Exploratory simulations predicted that increased flooding leads to swamps with reduced basal areas and stem densities, while increased salinity resulted in lower basal areas at low salinity concentration (∼1-3 psu) and complete tree mortality at higher salinity concentrations (∼2-6 psu). Our model can provide insight into the succession dynamics of coastal swamps and information for the effective design of restoration actions.     

A spatial model of white sturgeon rearing habitat in the lower Columbia River,USA

Concerns over the potential effects of in-water placement of dredged materials prompted us to develop a GIS-based model that characterizes in a spatially explicit manner white sturgeon Acipenser transmontanus rearing habitat in the lower Columbia River, USA. The spatial model was developed using water depth, riverbed slope and roughness, fish positions collected in 2002, and Mahalanobis distance (D²). We created a habitat suitability map by identifying a Mahalanobis distance under which >50% of white sturgeon locations occurred in 2002 (i.e., high-probability habitat). White sturgeon preferred relatively moderate to high water depths, and low to moderate riverbed slope and roughness values. The eigenvectors indicated that riverbed slope and roughness were slightly more important than water depth, but all three variables were important. We estimated the impacts that fill might have on sturgeon habitat by simulating the addition of fill to the thalweg, in 3-m increments, and recomputing Mahalanobis distances. Channel filling simulations revealed that up to 9 m of fill would have little impact on high-probability habitat, but 12 and 15 m of fill resulted in habitat declines of ∼12% and ∼45%, respectively. This is the first spatially explicit predictive model of white sturgeon rearing habitat in the lower Columbia River, and the first to quantitatively predict the impacts of dredging operations on sturgeon habitat. Future research should consider whether water velocity improves the accuracy and specificity of the model, and to assess its applicability to other areas in the Columbia River.     

Sanitary felling of Norway spruce due to spruce bark beetles in Slovenia: A model and projections for various climate change scenarios

A model is presented to predict sanitary felling of Norway spruce (Picea abies) due to spruce bark beetles (Ips typographus, Pityogenes chalcographus) in Slovenia according to different climate change scenarios. The model incorporates 21 variables that are directly or indirectly related to the dependent variable, and that can be arranged into five groups: climate, forest, landscape, topography, and soil. The soil properties are represented by 8 variables, 4 variables define the topography, 4 describe the climate, 4 define the landscape, and one additional variable provides the quantity of Norway spruce present in the model cell. The model was developed using the M5′ model tree. The basic spatial unit of the model is 1 km², and the time resolution is 1 year. The model evaluation was performed by three different measures: (1) the correlation coefficient (51.9%), (2) the Theil's inequality coefficient (0.49) and (3) the modelling efficiency (0.32). Validation of the model was carried out by 10-fold cross-validation. The model tree consists of 28 linear models, and model was calculated for three different climate change scenarios extending over a period until 2100, in 10-year intervals. The model is valid for the entire area of Slovenia; however, climate change projections were made only for the Maribor region (596 km²). The model assumes that relationships among the incorporated factors will remain unchanged under climate change, and the influence of humans was not taken into account. The structure of the model reveals the great importance of landscape variables, which proved to be positively correlated with the dependent variable. Variables that describe the water regime in the model cell were also highly correlated with the dependent variable, with evapotranspiration and parent material being of particular importance. The results of the model support the hypothesis that bark beetles do greater damage to Norway spruce artificially planted out of its native range in Slovenia, i.e., lowlands and soils rich in N, P, and K. The model calculation for climate change scenarios in the Maribor region shows an increase in sanitary felling of Norway spruce due to spruce bark beetles, for all scenarios. The model provides a path towards better understanding of the complex ecological interactions involved in bark beetle outbreaks. Potential application of the results in forest management and planning is discussed.     

Application of least-cost path model to identify a giant panda dispersal corridor network after the Wenchuan earthquake—Case study of Wolong Nature Reserve in China

With growing levels of human-activity and frequent natural disturbances throughout the world, it is increasingly important that both research and management efforts take into account the widespread landscape fragmentation and its consequences for biodiversity conservation. The magnitude 5.12 Wenchuan earthquake in China caused dramatic impacts on giant panda (Ailuropoda melanoleuca) habitat in the nature reserves within Minshan and Qionglai mountains. With the combined stresses of the natural disaster and the extensive human activities during postquake reconstruction, giant panda habitat in this region may become more fragmented in the future. In order to preserve the giant panda population after the earthquake and protect the species against habitat fragmentation, this article explores a method of identifying giant panda migration corridors involving habitat suitability assessments and a least-cost path model. Focusing on postquake Wolong Nature Reserve, our results demonstrate that it contains 430.3 km² of suitable habitat (21.1% of total area), 463.8 km² of marginally suitable habitat (22.8%) and 1141.9 km² of unsuitable habitat (50.1%). We further show that several giant panda dispersal corridors exist in the reserve, including four corridor groups that cross the provincial highway and five corridors that do not intersect areas of human activity. This study will contribute to management and conservation efforts in Wolong Nature Reserve and beyond after the Wenchuan earthquake.     

Identifying habitat patches and potential ecological corridors for remnant Asiatic black bear (Ursus thibetanus japonicus) populations in Japan

The Japanese National Biodiversity Strategy 2010 calls for the creation of ecological networks as a biodiversity conservation policy. However, there is an obvious lack of information on the spatial distribution of many species and a lack of scientific methods for examining habitat requirements to establish the need for constructing these networks for target species. This study presents a quantitative method for assessing the need for ecological networks through modeling the potential geographic distributions of species based on a case study of local populations of Asiatic black bear (Ursus thibetanus japonicus) in Fuji and Tanzawa, Japan. A total of 1541 point records of occurrences of Asiatic black bears and 11 potential predictors were analyzed in a GIS environment. After a predictive distributional map was obtained using the Maximum Entropy (MaxEnt) algorithm, a gap analysis was carried out and population size was estimated. Approximately 24% of the bear's predicted habitat area fell within a wildlife protection area, 2% within a nature reserve, and 37% within natural parks. Conservation forest comprised 54% of the total area of predicted habitat; of this, national forest comprised 2%, and private and communal forest comprised 37%. The total estimated Asiatic black bear population in this region was 242, with 179 individuals in the Fuji local population, 26 in the Tanzawa local population, and 37 in the corridor patch between the two local populations. Our study also found a potential corridor connecting the Fuji and Tanzawa local populations, as well as potential habitat corridors in the Fuji region containing subpopulations on Mt. Fuji (119 individuals) and Mt. Kenashi (53 individuals). An additional subpopulation on Mt. Ashitaka (7 individuals) is isolated and not fully protected by a zoning plan. Mt. Furo's subpopulation is considered to be almost extinct, although black bears were observed here until 2002 based on the report by Mochizuki et al. (2005). The total black bear population of the Fuji-Tanzawa region is considered to be “endangered”; thus, an adequate population size might be difficult to maintain even if this region were to be internally connected by means of an ecological network.     

Crustacean habitat potential mapping in a tidal flat using remote sensing and GIS

To make a macrofaunal (crustacean) habitat potential map, the spatial distribution of ecological variables in the Hwangdo tidal flat, Korea, was explored. Spatial variables were mapped using remote sensing and a geographic information system (GIS) combined with field observations. A frequency ratio (FR) and logistic regression (LR) model were employed to map the macrofauna potential area for the Ilyoplax dentimerosa, a crustacean species. Spatial variables affecting the tidal macrofauna distribution were selected based on abundance and biomass and used within a spatial database derived from remotely sensed data of various types of sensors. The spatial variables included the intertidal digital elevation model (DEM), slope, distance from a tidal channel, tidal channel density, surface sediment facies, spectral reflectance of the near infrared (NIR) bands and the tidal exposure duration. The relation between the I. dentimerosa and each spatial variable was calculated using the FR and LR. The species was randomly divided into a training set (70%) to analyse habitat potential using FR and LR and a test set (30%) to validate the predicted habitat potential map. The relations were overlaid to produce a habitat potential map with the species potential index (SPI) value for each pixel. The potential habitat maps were compared with the surveyed habitat locations such as validation data set. The comparison results showed that the LR model (accuracy is 85.28%) is better in prediction than the FR (accuracy is 78.96%) model. The performance of models gave satisfactory accuracies. The LR provides the quantitative influence of variables on a potential habitat of species; otherwise, the FR shows the quantitative influence of a class in each variable. The combination of a GIS-based frequency ratio and logistic regression models and remote sensing with field observations is an effective method to determine locations favorable for macrofaunal species occurrences in a tidal flat.     

Sink populations in carnivore management: cougar demography and immigration in a hunted population.

Carnivores are widely hunted for both sport and population control, especially where they conflict with human interests. It is widely believed that sport hunting is effective in reducing carnivore populations and related human-carnivore conflicts, while maintaining viable populations. However, the way in which carnivore populations respond to harvest can vary greatly depending on their social structure, reproductive strategies, and dispersal patterns. For example, hunted cougar (Puma concolor) populations have shown a great degree of resiliency. Although hunting cougars on a broad geographic scale (> 2000 km2) has reduced densities, hunting of smaller areas (i.e., game management units, < 1000 km2), could conceivably fail because of increased immigration from adjacent source areas. We monitored a heavily hunted population from 2001 to 2006 to test for the effects of hunting at a small scale (< 1000 km2) and to gauge whether population control was achieved (lambda < or = 1.0) or if hunting losses were negated by increased immigration allowing the population to remain stable or increase (lambda > or = 1.0). The observed growth rate of 1.00 was significantly higher than our predicted survival/fecundity growth rates (using a Leslie matrix) of 0.89 (deterministic) and 0.84 (stochastic), with the difference representing an 11-16% annual immigration rate. We observed no decline in density of the total population or the adult population, but a significant decrease in the average age of independent males. We found that the male component of the population was increasing (observed male population growth rate, lambda(OM) = 1.09), masking a decrease in the female component (lambda(OF) = 0.91). Our data support the compensatory immigration sink hypothesis; cougar removal in small game management areas (< 1000 km2) increased immigration and recruitment of younger animals from adjacent areas, resulting in little or no reduction in local cougar densities and a shift in population structure toward younger animals. Hunting in high-quality habitats may create an attractive sink, leading to misinterpretation of population trends and masking population declines in the sink and surrounding source areas.     

Modeling amphibian energetics, habitat suitability, and movements of western toads, Anaxyrus (=Bufo) boreas, across present and future landscapes

Effective conservation of amphibian populations requires the prediction of how amphibians use and move through a landscape. Amphibians are closely coupled to their physical environment. Thus an approach that uses the physiological attributes of amphibians, together with knowledge of their natural history, should be helpful. We used Niche Mapper™ to model the known movements and habitat use patterns of a population of Western toads (Anaxyrus (=Bufo) boreas) occupying forested habitats in southeastern Idaho. Niche Mapper uses first principles of environmental biophysics to combine features of topography, climate, land cover, and animal features to model microclimates and animal physiology and behavior across landscapes. Niche Mapper reproduced core body temperatures (T_c) and evaporation rates of live toads with average errors of 1.6 ± 0.4 °C and 0.8 ± 0.2 g/h, respectively. For four different habitat types, it reproduced similar mid-summer daily temperature patterns as those measured in the field and calculated evaporation rates (g/h) with an average error rate of 7.2 ± 5.5%. Sensitivity analyses indicate these errors do not significantly affect estimates of food consumption or activity. Using Niche Mapper we predicted the daily habitats used by free-ranging toads; our accuracy for female toads was greater than for male toads (74.2 ± 6.8% and 53.6 ± 15.8%, respectively), reflecting the stronger patterns of habitat selection among females. Using these changing to construct a cost surface, we also reconstructed movement paths that were consistent with field observations. The effect of climate warming on toads depends on the interaction of temperature and atmospheric moisture. If climate change occurs as predicted, results from Niche Mapper suggests that climate warming will increase the physiological cost of landscapes thereby limiting the activity for toads in different habitats.     

Interpreting spatial heterogeneity of crop yield with a process model and remote sensing

A process-based crop growth model (Vegetation Interface Processes (VIP) model) is used to estimate crop yield with remote sensing over the North China Plain. Spatial pattern of the key parameter—maximum catalytic capacity of Rubisco (V_cmax) for assimilation is retrieved from Normalized Difference of Vegetation Index (NDVI) from Terra-MODIS and statistical yield records. The regional simulation shows that the agreements between the simulated winter wheat yields and census data at county-level are quite well with R² being 0.41-0.50 during 2001-2005. Spatial variability of photosynthetic capacity and yield in irrigated regions depend greatly on nitrogen input. Due to the heavy soil salinity, the photosynthetic capacity and yield in coastal region is less than 50 μmol C m⁻² s⁻¹ and 3000 kg ha⁻¹, respectively, which are much lower than that in non-salinized region, 84.5 μmol C m⁻² s⁻¹ and 5700 kg ha⁻¹. The predicted yield for irrigated wheat ranges from 4000 to 7800 kg ha⁻¹, which is significantly larger than that of rainfed, 1500-3000 kg ha⁻¹. According to the path coefficient analysis, nitrogen significantly affects yield, by which water exerts noticeably indirect influences on yield. The effect of water on yield is regulated, to a certain extent, by crop photosynthetic capacity and nitrogen application. It is believed that photosynthetic parameters retrieved from remote sensing are reliable for regional production prediction with a process-based model.     

Influence of grain size on species-habitat models

High resolution remote sensing data facilitate the use of small-scale habitat features such as trees or hedges in the analysis of species-habitat relationships. Such data potentially enable more accurate species-habitat mapping than lower resolution data. Here, for the first time, we systematically investigated this hypothesis by altering the spatial resolution from 1 m up to 1000 m grain size in species-habitat models of 13 bird species. The study area covered the Nidda river catchment in central Germany, a large heterogeneous landscape of 1620 km². A high resolution habitat map of the area was converted to coarser spatial and thematic resolutions in seven steps. We investigated how model performance responded to grain size, and we compared the differential effects of spatial resolution and thematic resolution on model performance. Explained deviance (D²) of the bird models generally decreased with coarser spatial resolution of the data, although it did not decrease monotonically in all species. On average across all species, model D² decreased from 41.5 at 1 m grain size to 15.9 at 1000 m grain size. Ten species were best modelled at 1 m, two species at 3 m and one species at 32 m grain size. Model performance degraded continuously with increasing grain size, both in habitat generalist and habitat specialist bird species, and was systematically lower in habitat generalists. The higher model performance observed at finer grain sizes was most likely caused by the combination of three factors: (1) high spatial accuracy of bird records and (2) a more precise location and delineation of habitat features and, (3) to a lesser degree, by more habitat types differentiated in maps of finer resolution. We conclude that higher spatial and thematic resolution data can be essential for deriving accurate predictions on bird distribution patterns from species-habitat models. Especially for bird species that are sensitive to specific land-use types or to small-scaled habitat features, a grain size of 1-3 m seems most promising.     

Estimating Plecoglossus altivelis altivelis migration using a mass balance model expressed by hydrological distribution parameters in a major limpid river basin in Japan

We examined the influence of several hydrological and meteorological parameters on the migratory movements of ayu Plecoglossus altivelis altivelis in central Japan. When comprehensively evaluating rivers and ayu behaviour on a catchment scale, the subjects of analysis typically include human activities and hydrological and meteorological phenomena. However, limiting analyses to such factors may be too restrictive when human activities are being conducted. Accordingly, we incorporated a biological viewpoint into the evaluation method, analysing hydrological data (river discharge, river water temperature, sea water temperature) to determine watershed characteristics and examining the relationship between these characteristics and the habitat conditions of ayu. Then we constructed a numerical model for ayu migratory runs that incorporated ayu ecology and watershed characteristics. Analyses of ayu movements from a lower estuarine dam demonstrated that downstream displacements were associated with high water flows of more than 200 m³ s⁻¹ at the beginning of summer. We conclude that it is important to consider the effects of environmental parameters on the movements of different fish species to understand the causes of spatial variation in fish distribution in lowland rivers.     

Two-dimensional habitat modeling of Chinese sturgeon spawning sites

Since the construction of the Gezhouba Dam in the 1980s, the number of Chinese sturgeon in the Yangtze River has been rapidly declining. The Gezhouba Dam has cutoff the migration path of these sturgeon, resulting in an overall reduction of suitable sturgeon habitat. This paper describes a habitat suitability index model that is used to evaluate the impacts of the Gezhouba Dam and Three Gorges Project on Chinese sturgeon spawning sites. Based on research concerning the reproduction characteristics of Chinese sturgeon, ten major ecological factors that influence reproduction were analyzed, including: water temperature, velocity, water depth, substrate, suspended sediment concentration, and the amount of egg predatory fish. The suitability index (SI) curves based on these ten ecological factors were obtained, and a habitat suitability function was developed. A two-dimensional mathematical model was also created to simulate and predict physical habitat situation (such as hydraulic, sediment, and substrate) of the Chinese sturgeon. By coupling the habitat suitability function and a two-dimensional mathematical model, a habitat suitability index model for Chinese sturgeon was established. The habitat suitability index model was validated by comparing measured data with predictions from the model. These comparisons showed that the computed results agreed well with the measured results, and the high calculated habitat suitability index (HSI) corresponded to high measured quantity of eggs per unit (1000 m³) discharge (CPUE_d). The calculated habitat suitability index for Chinese sturgeon also showed that the habitat suitability index was better in 1999, before the impoundment of the Three Gorges Project, compared with the habitat suitability in 2003. Simulation results of different discharges from Gezhouba Dam predicted that flow discharges between 10,000 and 30,000 m³/s were most suitable for sturgeon spawning.     

Proposed Conservation Landscape for Giant Pandas in the Minshan Mountains,China

Abstract: The giant panda (Ailuropoda melanoleuca), is one of the world's most endangered species. Habitat loss and fragmentation have reduced its numbers, shrunk its distribution, and separated the population into isolated subpopulations. Such isolated, small populations are in danger of extinction due to random demographic factors and inbreeding. We used least‐cost modeling as a systematic approach to incorporate satellite imagery and data on ecological and behavioral parameters of the giant panda collected during more than 10 years of field research to design a conservation landscape for giant pandas in the Minshan Mountains. We identified 8 core habitats and 4 potential linkages that would link core habitats CH3, CH4, and CH5 with core habitats CH6, CH7, and CH8. Establishing and integrating the identified habitats with existing reserves would create an efficient reserve network for giant panda conservation. The core habitats had an average density of 4.9 pandas/100 km² and contained approximately 76.6% of the giant panda population. About 45% of the core habitat (3245.4 km²) existed outside the current nature reserves network. Total estimated core habitat decreased between 30.4 and 44.5% with the addition of residential areas and road networks factored into the model. A conservation area for giant panda in the Minshan Mountains should aim to ensure habitat retention and connectivity, improve dispersal potential of corridors, and maintain the evolutionary potential of giant pandas in the face of future environmental changes.     

Epidemiological risk assessment using linked network and grid based modelling: Phytophthora ramorum and Phytophthora kernoviae in the UK

We developed a stochastic simulation model incorporating most processes likely to be important in the spread of Phytophthora ramorum and similar diseases across the British landscape (covering Rhododendron ponticum in woodland and nurseries, and Vaccinium myrtillus in heathland). The simulation allows for movements of diseased plants within a realistically modelled trade network and long-distance natural dispersal. A series of simulation experiments were run with the model, representing an experiment varying the epidemic pressure and linkage between natural vegetation and horticultural trade, with or without disease spread in commercial trade, and with or without inspections-with-eradication, to give a 2 × 2 × 2 × 2 factorial started at 10 arbitrary locations spread across England. Fifty replicate simulations were made at each set of parameter values. Individual epidemics varied dramatically in size due to stochastic effects throughout the model. Across a range of epidemic pressures, the size of the epidemic was 5–13 times larger when commercial movement of plants was included. A key unknown factor in the system is the area of susceptible habitat outside the nursery system. Inspections, with a probability of detection and efficiency of infected-plant removal of 80% and made at 90-day intervals, reduced the size of epidemics by about 60% across the three sectors with a density of 1% susceptible plants in broadleaf woodland and heathland. Reducing this density to 0.1% largely isolated the trade network, so that inspections reduced the final epidemic size by over 90%, and most epidemics ended without escape into nature. Even in this case, however, major wild epidemics developed in a few percent of cases. Provided the number of new introductions remains low, the current inspection policy will control most epidemics. However, as the rate of introduction increases, it can overwhelm any reasonable inspection regime, largely due to spread prior to detection.     

Ecological role of stomatopods (mantis shrimps) and potential impacts of trawling in a marine ecosystem of the southeast coast of India

Ecosystems are balanced by nature and each component in the system has a role in the sustenance of other components. A change in one component would invariably have an effect on others. Stomatopods (mantis shrimps) are common and ecologically important predatory crustaceans in tropical marine waters. The ecological role of mantis shrimps and potential impacts of trawling in a marine ecosystem were estimated using Ecopath with Ecosim (EwE) Version 5.0 software, by constructing a mass balanced Ecopath model of Parangipettai (Porto Novo) ecosystem. Based on fisheries information from the region, 17 ecological groups were defined including stomatopods. Both primary and secondary data on biomass, P/B, Q/B and diet composition were used as basic inputs. The mass balanced model gave a total system throughput of 14,756 t km⁻² year⁻¹. The gross efficiency of 0.000942 indicated higher contribution of lower food chain groups in the fishery though the mean trophic level was 3.08. The immature and developing stage of the ecosystem was indicated by the ratio of total primary production and total respiration (1.832) and the net system production (2643.30 t km⁻² year⁻¹). Key indices (flow to detritus, net efficiency and omnivory index), split mortality rates and mixed trophic impact of different ecological groups were obtained from the model. A flow diagram was constructed to illustrate the trophic interactions, which explained the biomass flows in the ecosystem with reference to stomatopods. Two temporal simulations were made, with 10 year durations in the mass balanced Ecopath model by using ecosim routine incorporated in EwE software. The effect of decrease in biomass of stomatopods in the ecosystem was well defined, in the first run with increase in stomatopod fishing mortality, and the group showed a high positive impact on benthopelagic fish biomass increase (129%). The simulation with increase in trawling efforts resulted in the biomass decline of different ecological groups as elasmobranchs to 1%, stomatopods to 2%, crabs and lobsters to 36%, cephalopods to 63%, mackerel to 78%, and shrimps to 89%. Present study warns stomatopod discards and further increase in trawling efforts in the region and it explained the need for ecosystem based fisheries management practices for the sustainability of marine fisheries.     

A multi-agent simulation to assess the risk of malaria re-emergence in southern France

A multi-agent simulation (MAS) was developed to assess the risk of malaria re-emergence in the Camargue in southern France, a non-endemic area where mosquitoes of the genus Anopheles (Culicidae) live. The contact rate between people and potential malaria vectors, or the human biting rate, is one of the key factor to predict the risk of re-emergence of malaria, would the parasite be introduced in the region. Our model (called MALCAM) represents the different agents that could influence malaria transmission in the Camargue – people, mosquitoes, animal hosts and the landscape – in a spatially explicit environment. The model simulates spatial and temporal variations in human biting rate at the landscape scale. These variations depend on the distribution of people and potential vectors, their behaviour and their interactions. A land use/cover map was used as a cellular-spatial support for the movements of and interactions between mobile agents. The model was tested for its sensitivity to variations in parameter values, and for the agreement between field observations and model predictions. The MALCAM model provides a tool to better understand the interactions between the multiple agents of the disease transmission system, and the land use and land cover factors that control the spatial heterogeneity in these interactions. It allows testing hypotheses and scenarios related to disease dynamics by varying the value of exogenous biological, geographical, or human factors. This application of agent-based modelling to a human vector-borne disease can be adapted to different diseases and regions.     

GIS-based modeling of the geographic distribution of Quercus emoryi Torr. (Fagaceae) in México and identification of significant environmental factors influencing the species’ distribution

The greatest concentration of oak species in the world is believed to be found in Mexico. These species are potentially useful for reforestation because of their capacity to adapt to diverse environments. Knowledge of their geographic distribution and of species–environment relations is essential for decision-making in the management and conservation of natural resources. The objectives of this study were to develop a model of the distribution of Quercus emoryi Torr. in Mexico, using geographic information systems and data layers of climatic and other variables, and to determine the variables that significantly influence the distribution of the species. The study consisted of the following steps: (A) selection of the target species from a botanical scientific collection, (B) characterization of the collecting sites using images with values or categories of the variables, (C) model building with the overlay of images that meet the habitat conditions determined from the characterization of sites, (D) model validation with independent data in order to determine the precision of the model, (E) model calibration through adjustment of the intervals of some variables, and (F) sensitivity analysis using precision and concordance non-parametric statistics applied to pairs of images. Results show that the intervals of the variables that best describe the species’ habitat are the following: altitude from 1650 to 2750 amsl, slope from 0 to 66°; average minimum temperature of January from −12 to −3 °C; mean temperature of June from 11 to 25 °C; mean annual precipitation from 218 to 1225 mm; soil units: lithosol, eutric cambisol, haplic phaeozem, chromic luvisol, rendzina, luvic xerosol, mollic planosol, pellic vertisol, eutric regosol; type of vegetation: oak forest, oak–pine forest, pine forest, pine–oak forest, juniperus forest, low open forest, natural grassland and chaparral. The resulting model of the geographic distribution of Quercus emoryi in Mexico had the following values for non-parametric statistics of precision and agreement: Kappa index of 0.613 and 0.788, overall accuracy of 0.806 and 0.894, sensitivity of 0.650 and 0.825, specificity of 0.963, positive predictive value of 0.945 and 0.957 and negative predictive value of 0.733 and 0.846. Results indicate that the variable average minimum temperature of January, with a maximum value of −3 °C, is an important factor in limiting the species’ distribution.