Minnesota Department of Natural Resources

About: Minnesota Department of Natural Resources is a government organization based out in Saint Paul, Minnesota, United States. It is known for research contribution in the topics: Population & Stocking. The organization has 457 authors who have published 854 publications receiving 23678 citations. The organization is also known as: Minnesota DNR & MN DNR.

The status of the world's land and marine mammals: diversity, threat, and knowledge

Abstract: Knowledge of mammalian diversity is still surprisingly disparate, both regionally and taxonomically. Here, we present a comprehensive assessment of the conservation status and distribution of the world's mammals. Data, compiled by 1700+ experts, cover all 5487 species, including marine mammals. Global macroecological patterns are very different for land and marine species but suggest common mechanisms driving diversity and endemism across systems. Compared with land species, threat levels are higher among marine mammals, driven by different processes (accidental mortality and pollution, rather than habitat loss), and are spatially distinct (peaking in northern oceans, rather than in Southeast Asia). Marine mammals are also disproportionately poorly known. These data are made freely available to support further scientific developments and conservation action.

The Impact of Conservation on the Status of the World’s Vertebrates

Abstract: Using data for 25,780 species categorized on the International Union for Conservation of Nature Red List, we present an assessment of the status of the world's vertebrates. One-fifth of species are classified as Threatened, and we show that this figure is increasing: On average, 52 species of mammals, birds, and amphibians move one category closer to extinction each year. However, this overall pattern conceals the impact of conservation successes, and we show that the rate of deterioration would have been at least one-fifth again as much in the absence of these. Nonetheless, current conservation efforts remain insufficient to offset the main drivers of biodiversity loss in these groups: agricultural expansion, logging, overexploitation, and invasive alien species.

Quantifying home-range overlap: the importance of the utilization distribution

Abstract: The concept of an animal's home range has evolved over time, as have methods for estimating home-range size and shape. Recently, home-range estimation methods have focused on estimating an animal's utilization distribution (UD; i.e., the probability distribution defining the animal's use of space). We illustrate the importance of the utilization distribution in characterizing the degree of overlap between home ranges (e.g., when assessing site fidelity or space-use sharing among individuals). We compare several different statistics for their ability to accurately rank paired examples in terms of their degree of overlap. These examples illustrate limitations of indices commonly used to quantify home-range overlap and suggest that new overlap indices that are a function of the UD are likely to be more informative. We suggest 2 new statistics for measuring home-range overlap: (1) for a measure of space-use sharing, we suggest a generalization of Hurlbert's (1978) E/Euniform statistic, which we term the utilization distribution overlap index (UDOI), and (2) for a general measure of similarity between UD estimates, we suggest Bhattacharyya's affinity (BA; Bhattacharyya 1943). Using a short simulation study, we found that overlap indices can accurately rank pairs of UDs in terms of the extent of overlap, but estimates of overlap indices are likely to be biased. The extent of the bias depended on sample size and the degree of overlap (UDs with a high degree of overlap resulted in statistics that were more biased [low]), suggesting that comparisons across studies may be problematic. We illustrate the use of overlap indices to quantify the degree of similarity among UD estimates obtained using 2 different data collection methods (Global Positioning Systems [GPS] and very high frequency [VHF] radiotelemetry) for an adult female northern white-tailed deer (Odocoileus virginianus) in north-central Minnesota.

Small habitat size and isolation can promote species richness: second-order effects on biodiversity in shallow lakes and ponds

Abstract: Contemporary ecological landscape planning is often based on the assumption that small isolated habitat patches sustain relatively few species. Here, we suggest that for shallow lakes and ponds, the opposite can be true for some groups of organisms. Fish communities tend to be poor or even absent in small isolated lakes. However, submerged vegetation is often more abundant in such waterbodies. As a consequence of low fish biomass and high vegetation abundance, the richness of aquatic birds, plants, amphibians and invertebrates is often relatively high in small, shallow, isolated lakes. Although the rarity of fish is in line with expectations from the ruling paradigms about effects of habitat fragmentation in landscape ecology, the relative richness of various other groups of organisms in small ponds is opposite to these expectations. The case of shallow lakes illustrates that incorporating ecological interactions is essential to understanding the potential effects of habitat fragmentation. Single-species meta-population approaches may be misleading if ecological interactions are strong. A meta-community approach that explicitly incorporates biotic interactions, also those involving different trophic levels, is needed. Our diagnosis suggests that connection of isolated habitat fragments may in some cases reduce, rather than enhance, landscape-level biodiversity, and implies that biodiversity at the regional level will be maximized if the local habitat patches vary widely in size and degree of connectivity.

Correlation and studies of habitat selection: problem, red herring or opportunity?

Abstract: With the advent of new technologies, animal locations are being collected at ever finer spatio-temporal scales. We review analytical methods for dealing with correlated data in the context of resource selection, including post hoc variance inflation techniques, ‘two-stage’ approaches based on models fit to each individual, generalized estimating equations and hierarchical mixed-effects models. These methods are applicable to a wide range of correlated data problems, but can be difficult to apply and remain especially challenging for use–availability sampling designs because the correlation structure for combinations of used and available points are not likely to follow common parametric forms. We also review emerging approaches to studying habitat selection that use fine-scale temporal data to arrive at biologically based definitions of available habitat, while naturally accounting for autocorrelation by modelling animal movement between telemetry locations. Sophisticated analyses that explicitly model correlation rather than consider it a nuisance, like mixed effects and state-space models, offer potentially novel insights into the process of resource selection, but additional work is needed to make them more generally applicable to large datasets based on the use–availability designs. Until then, variance inflation techniques and two-stage approaches should offer pragmatic and flexible approaches to modelling correlated data.