Walker's Mammals of the World, 4th Edition, Ronald M. Nowak, John L. Paradiso. The Johns Hopkins University Press, Baltimore, Maryland (1983), 1xi, +1-568 (Vol. I), xxv+569-1362 (Vol. II). Price $65.00

Maximum entropy (Maxent) modeling has great potential for identifying distributions and habitat selection of wildlife given its reliance on only presence locations. Recent studies indicate Maxent is relatively insensitive to spatial errors associated with location data, requires few locations to construct useful models, and performs better than other presence-only modeling approaches. Further advances are needed to better define model thresholds, to test model significance, and to address model selection. Additionally, development of modeling approaches is needed when using repeated sampling of known individuals to assess habitat selection. These advancements would strengthen the utility of Maxent for wildlife research and management.

https://www.mdpi.com/1099-4300/11/4/854/pdf

Use of Maximum Entropy Modeling in Wildlife Research

Camera Traps in Animal Ecology

Groundwater is considered as the most important natural resources in arid and semi-arid regions. In this study, the application of random forest (RF) and maximum entropy (ME) models for groundwater potential mapping is investigated at Mehran Region, Iran. Although the RF and ME models have been applied widely to environmental and ecological modeling, their applicability to other kinds of predictive modeling such as groundwater potential mapping has not yet been investigated. About 163 groundwater data with high potential yield values of ≥ 11 m 3 /h were obtained from Iranian Department of Water Resources Management (IDWRM). Further, these selected wells were randomly divided into a dataset 70% (114 wells) for training and the remaining 30% (49 wells) was applied for validation purposes. In total, ten groundwater conditioning factors that affect the storage of groundwater occurrences (e.g. altitude, slope percent, slope aspect, plan curvature, drainage density, distance from rivers, topographic wetness index (TWI), landuse, lithology, and soil texture) were used as input to the models. Subsequently, the RF and ME models were applied to generate the groundwater potential maps (GPMs). Moreover, a sensitivity analysis was used to identify the impact of variable uncertainties on the produced GPMs. Finally, the results of the GPMs were quantitatively validated using observed groundwater dataset and the receiver operating characteristic (ROC) method. Area under ROC curve (AUC) was used to compare the performance of RF with ME. The uncertainty on the preparation of conditioning factors was taken in account to enhance the model. The validation results showed that the AUC for success rate of RF and ME models was 86.5 and 91%, respectively. In contrast, the AUC for prediction rate of RF and ME methods was obtained 83.1 and 87.7%, respectively. Therefore, RF and ME were found to be effective models for groundwater potential mapping.

Application of GIS-based data driven random forest and maximum entropy models for groundwater potential mapping: A case study at Mehran Region, Iran

Increase in food production is the prime-most objective of all countries, as world population is expected to grow to nearly 10 billion by 2050 Based on evidence, world population is increasing by an estimated 97 million per year (Saravi and Shokrzadeh, 2011) The Food and Agricultural Organization (FAO) of the United Nations has in-fact issued a sobering forecast that world food production needs to increase by 70%, in order to keep pace with the demand of growing population However, increase in food production is faced with the ever-growing challenges especially the new area that can be increased for cultivation purposes is very limited (Saravi and Shokrzadeh, 2011) The increasing world population has therefore put a tremen‐ dous amount of pressure on the existing agricultural system so that food needs can be met from the same current resources like land, water etc In the process of increasing crop pro‐ duction, herbicides, insecticides, fungicides, nematicides, fertilizers and soil amendments are now being used in higher quantities than in the past These chemicals have mainly come into the picture since the introduction of synthetic insecticides in 1940, when organochlorine (OCl) insecticides were first used for pest management Before this introduction, most weeds, pests, insects and diseases were controlled using sustainable practices such as cultural, mechanical, and physical control strategies

/pdf/pesticides-environmental-impacts-and-management-strategies-59v0x0zo9d.pdf

Pesticides: Environmental Impacts and Management Strategies

We compared historic (1985–1992) and contemporary (2003–2006) black bear (Ursus americanus) den locations in Rocky Mountain National Park (RMNP), Colorado, USA, for habitat and physiographic attributes of den sites and used maximum entropy modeling to determine which factors were most influential in predicting den-site locations. We observed variability in the relationship between den locations and distance to trails and elevation over time. Locations of historic den sites were most associated with slope, elevation, and covertype, whereas contemporary sites were associated with slope, distance to roads, aspect, and canopy height. Although relationships to covariates differed between historic and contemporary periods, preferred den-site characteristics consistently included steep slopes and factors associated with greater snow depth. Distribution of den locations shifted toward areas closer to human developments, indicating little negative influence of this factor on den-site selection by black be...

https://bioone.org/journals/journal-of-wildlife-management/volume-72/issue-8/2007-393/Den-Site-Characteristics-of-Black-Bears-in-Rocky-Mountain-National/10.2193/2007-393.pdf

Den-Site Characteristics of Black Bears in Rocky Mountain National Park, Colorado

Many wildlife species cause extensive damage to a variety of agricultural commodities in California, with estimates of damage in the hundreds of millions annually. Given the limited availability of resources to solve all human-wildlife conflicts, we should focus management efforts on issues that provide the greatest benefit to agricultural commodities in California. This survey provides quantitative data on research needs to better guide future efforts in developing more effective, practical and appropriate methods for managing these species. We found that ground squirrels, pocket gophers, birds, wild pigs, coyotes and voles were the most common agricultural wildlife pest species in California. The damage caused by these species could be quite high, but varied by agricultural commodity. For most species, common forms of damage included loss of crop production and direct death of the plant, although livestock depredation was the greatest concern for coyotes. Control methods used most frequently and those deemed most effective varied by pest species, although greater advancements in control methods were listed as a top research priority for all species. Collectively, the use of toxicants, biocontrol and trapping were the most preferred methods for control, but this varied by species. In general, integrated pest management practices were used to control wildlife pests, with a special preference for those approaches that were efficacious and quick and inexpensive to apply. This information and survey design should be useful in establishing research and management priorities for wildlife pest species in California and other similar regions.

Perceived damage and areas of needed research for wildlife pests of California agriculture

We used scat analysis to determine diets and relative nutritional values of diets for black bears (Ursus americanus Pallas, 1780) in Rocky Mountain National Park, Colorado, from 2003 to 2006, and c...

Foods and nutritional components of diets of black bear in Rocky Mountain National Park, Colorado

A clear understanding of habitat associations of martens (Martes americana) is necessary to effectively manage and monitor populations. However, this information was lacking for martens in most of their southern range, particularly during the summer season. We studied the distribution and habitat correlates of martens from 2004 to 2006 in Rocky Mountain National Park (RMNP) across 3 spatial scales: site-specific, home-range, and landscape. We used remote-sensored cameras from early August through late October to inventory occurrence of martens and modeled occurrence as a function of habitat and landscape variables using binary response (BR) and binomial count (BC) logistic regression, and occupancy modeling (OM). We also assessed which was the most appropriate modeling technique for martens in RMNP. Of the 3 modeling techniques, OM appeared to be most appropriate given the explanatory power of derived models and its incorporation of detection probabilities, although the results from BR and BC provided corroborating evidence of important habitat correlates. Location of sites in the western portion of the park, riparian mixed-conifer stands, and mixed-conifer with aspen patches were most frequently positively correlated with occurrence of martens, whereas more xeric and open sites were avoided. Additionally, OM yielded unbiased occupancy values ranging from 91% to 100% and 20% to 30% for the western and eastern portions of RMNP, respectively.

https://www.jstor.org/stable/info/25145111

Roger A. Baldwin

Papers

Use of Maximum Entropy Modeling in Wildlife Research

Den-Site Characteristics of Black Bears in Rocky Mountain National Park, Colorado

Perceived damage and areas of needed research for wildlife pests of California agriculture

Foods and nutritional components of diets of black bear in Rocky Mountain National Park, Colorado

Distribution, Occupancy, and Habitat Correlates of American Martens (Martes americana) in Rocky Mountain National Park, Colorado