Factors predicting habitat use by leopards in human-altered landscapes

SUPPLEMENTARY DATA SD1.—Univariate analyses results for male and female leopard occurrence probability at the fine and large spatial scales.Transformed landscapes caused by human activity leave remnant patches of natural habitat for wildlife. The persistence of species in the face of such transformation depends on individuals’ ability to adapt to novel habitat, and to secure resources and reproductive opportunities despite habitat alterations. The leopard, Panthera pardus, is the last free-roaming top carnivore in South Africa whose high trophic status and wide-ranging movements make them an effective focal species in conservation planning. Using location data from leopards, we investigated key correlates of habitat selection in human-altered landscapes at two spatial scales. We compared sex-related differences and predicted how conspecific home range locations influenced habitat selection. Leopards avoided human-altered landscapes more strongly at the large spatial scale, where both sexes selected core areas near formally protected areas. Conspecific home range locations had a strong positive effect at both spatial scales for males, while for females, conspecifics explained fine-scale habitat selection by selecting areas near neighboring females. Spatial scale, sex-related differences, and conspecific location play roles in habitat selection for solitary felids and have implications for conservation planning and management. Excluding these factors may result in inappropriate species management policies.Development Bank South Africa, United Nations Environmental Programme, United Nations Development Programme, Green Fund, Global Environmental Facility, Global Environment Facility/Small Grants Programme, Henry and Iris Englund Foundation, National Lotteries Distribution Trust Fund, Mones Michaels Trust, Tamarisk Trust, Timothy Allsop, ABAX Foundation, Table Mountain Fund, Vodacom Foundation, Deutsche Bank Foundation (RSA), Brad Banducci, and Arne Hanson.https://academic.oup.com/jmammalhj2023Mammal Research Institut

The "ram effect": new insights into neural modulation of the gonadotropic axis by male odors and socio-sexual interactions

Reproduction in mammals is controlled by the hypothalamo-pituitary-gonadal (HPG) axis under the influence of external and internal factors such as photoperiod, stress, nutrition, and social interactions. Sheep are seasonal breeders and stop mating when day length is increasing (anestrus). However, interactions with a sexually active ram during this period can override the steroid negative feedback responsible for the anoestrus state, stimulate LH secretion and eventually reinstate cyclicity. This is known as the ram effect and research into the mechanisms underlying it is shedding new light on HPG axis regulation. The first step in the ram effect is increased LH pulsatile secretion in anestrus ewes exposed to a sexually active male or only to its fleece, the latter finding indicating a pheromone-like effect. Estradiol secretion increases in all ewes and this eventually induces a LH surge and ovulation, just as during the breeding season. An exception is a minority of ewes that exhibit a precocious LH surge (within 4h) with no prior increase in estradiol. The main olfactory system and the cortical nucleus of the amygdala are critical brain structures in mediating the ram effect since it is blocked by their inactivation. Sexual experience is also important since activation (increased c-fos expression) in these and other regions is greatly reduced in sexually naïve ewes. In adult ewes kisspeptin neurons in both arcuate and preoptic regions and some preoptic GnRH neurons are activated 2h after exposure to a ram. Exposure to rams also activates noradrenergic neurons in the locus coeruleus and A1 nucleus and increased noradrenalin release occurs in the posterior preoptic area. Pharmacological modulation of this system modifies LH secretion in response to the male or his odor. Together these results show that the ram effect can be a fruitful model to promote both a better understanding of the neural and hormonal regulation of the HPG axis in general and also the spe

The Enigma of Soil Animal Species Diversity Revisited: The Role of Small-Scale Heterogeneity

Peer reviewedPublisher PD

Remarkable convergent evolution in specialized parasitic Thecostraca (Crustacea)

<p>Abstract</p> <p>Background</p> <p>The Thecostraca are arguably the most morphologically and biologically variable group within the Crustacea, including both suspension feeders (Cirripedia: Thoracica and Acrothoracica) and parasitic forms (Cirripedia: Rhizocephala, Ascothoracida and Facetotecta). Similarities between the metamorphosis found in the Facetotecta and Rhizocephala suggests a common evolutionary origin, but until now no comprehensive study has looked at the basic evolution of these thecostracan groups.</p> <p>Results</p> <p>To this end, we collected DNA sequences from three nuclear genes [18S rRNA (2,305), 28S rRNA (2,402), Histone H3 (328)] and 41 larval characters in seven facetotectans, five ascothoracidans, three acrothoracicans, 25 rhizocephalans and 39 thoracicans (ingroup) and 12 Malacostraca and 10 Copepoda (outgroup). Maximum parsimony, maximum likelihood and Bayesian analyses showed the Facetotecta, Ascothoracida and Cirripedia each as monophyletic. The better resolved and highly supported DNA maximum likelihood and morphological-DNA Bayesian analysis trees depicted the main phylogenetic relationships within the Thecostraca as (Facetotecta, (Ascothoracida, (Acrothoracica, (Rhizocephala, Thoracica)))).</p> <p>Conclusion</p> <p>Our analyses indicate a convergent evolution of the very similar and highly reduced slug-shaped stages found during metamorphosis of both the Rhizocephala and the Facetotecta. This provides a remarkable case of convergent evolution and implies that the advanced endoparasitic mode of life known from the Rhizocephala and strongly indicated for the Facetotecta had no common origin. Future analyses are needed to determine whether the most recent common ancestor of the Thecostraca was free-living or some primitive form of ectoparasite.</p

The risks of learning: confounding detection anddemographic trend when using count-based indices forpopulation monitoring

Theory recognizes that a treatment of the detection process is required to avoid producing biased estimates of population rate of change. Still, one of three monitoring programmes on animal or plant populations is focused on simply counting individuals or other fixed visible structures, such as natal dens, nests, tree cavities. This type of monitoring design poses concerns about the possibility to respect the assumption of constant detection, as the information acquired in a given year about the spatial distribution of reproductive sites can provide a higher chance to detect the species in subsequent years. We developed an individual- based simulation model, which evaluates how the accumulation of knowledge about the spatial distribution of a population process can affect the accuracy of population growth rate estimates, when using simple count-based indices. Then, we assessed the relative importance of each parameter in affecting monitoring performance. We also present the case of wolverines (Gulo gulo) in southern Scandinavia as an example of a monitoring system with an intrinsic tendency to accumulate knowledge and increase detectability. When the occupation of a nest or den is temporally autocorrelated, the monitoring system is prone to increase its knowledge with time. This happens also when there is no intensification in monitoring effort and no change in the monitoring conditions. Such accumulated knowledge is likely to increase detection probability with time and can produce severe bias in the estimation of the rate and direction of population change over time. We recommend that a systematic sampling of the population process under study and an explicit treatment of the underlying detection process should be implemented whenever economic and logistical constraints permit, as failure to include detection probability in the estimation of population growth rate can lead to serious bias and severe consequences for management and conservation. Autocorrelation, citizen science, demographic monitoring, den, detection probability, learning period, nest, population size, population trend, reproduction