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We began developing our Geometric Tortoise Ecosystem Preserve in 2015. At the same time, we began a mark–recapture study to detect changes in the population size through time to inform our management practices. We now have data through 2021. Mark–recapture analysis gives a population size of between 800 and 1200 individuals. It is the last remaining substantial population. Using Lande's classification of 1933 of stochastic influences on demography, we find that 1) demographic stochasticity is not a problem, as the population is large enough and consists of individuals whose home ranges overlap; 2) environmental stochasticity is important mainly through variations in annual rainfall, including severe droughts; and 3) catastrophes occur in the form of wildfire that can destroy a local population. Taken together, these environmental effects can cause large changes in population size, making this species at risk of local extinction. If it were to go extinct, there are no other adjacent populations that could be used to recolonize our preserve. Therefore, we conclude that head starting is necessary to safeguard the population.

We present a review and analysis of the conservation status and International Union for Conservation of Nature (IUCN) threat categories of all 360 currently recognized species of extant and recently extinct turtles and tortoises (Order Testudines). Our analysis is based on the 2018 IUCN Red List status of 251 listed species, augmented by provisional Red List assessments by the IUCN Tortoise and Freshwater Turtle Specialist Group (TFTSG) of 109 currently unlisted species of tortoises and freshwater turtles, as well as re-assessments of several outdated IUCN Red List assessments. Of all recognized species of turtles and tortoises, this combined analysis indicates that 20.0% are Critically Endangered (CR), 35.3% are Critically Endangered or Endangered (CR+EN), and 51.9% are Threatened (CR+EN+Vulnerable). Adjusting for the potential threat levels of Data Deficient (DD) species indicates that 56.3% of all data-sufficient species are Threatened. We calculated percentages of imperiled species and modified Average Threat Levels (ATL; ranging from Least Concern = 1 to Extinct = 8) for various taxonomic and geographic groupings. Proportionally more species in the subfamily Geoemydinae (Asian members of the family Geoemydidae) are imperiled (74.2% CR+EN, 79.0% Threatened, 3.89 ATL) compared to other taxonomic groupings, but the families Podocnemididae, Testudinidae, and Trionychidae and the superfamily Chelonioidea (marine turtles of the families Cheloniidae and Dermochelyidae) also have high percentages of imperiled species and ATLs (42.9-50.0% CR+EN, 73.8-100.0% Threatened, 3.44-4.06 ATL). The subfamily Rhinoclemmydinae (Neotropical turtles of the family Geoemydidae) and the families Kinosternidae and Pelomedusidae have the lowest percentages of imperiled species and ATLs (0%-7.4% CR+EN, 7.4%-13.3% Threatened, 1.65-1.87 ATL). Turtles from Asia have the highest percentages of imperiled species (75.0% CR+EN, 83.0% Threatened, 3.98 ATL), significantly higher than predicted based on the regional species richness, due to much higher levels of exploitation in that geographic region. The family Testudinidae has the highest ATL (4.06) of all Testudines due to the extinction of several species of giant tortoises from Indian and Pacific Ocean islands since 1500 CE. The family Testudinidae also has an ATL higher than all other larger polytypic families (≥ 5 species) of Reptilia or Amphibia. The order Testudines is, on average, more imperiled than all other larger orders (≥ 20 species) of Reptilia, Amphibia, Mammalia, or Aves, but has percentages of CR+EN and Threatened species and an ATL (2.96) similar to those of Primates and Caudata (salamanders).

We examined the impacts of possible future land development patterns on the biodiversity of a landscape. Our landscape data included a remote sensing derived map of the current habitat of the study area and six maps of future habitat distributions resulting from different land development scenarios. Our species data included lists of all bird, mammal, reptile, and amphibian species in the study area, their habitat associations, and area requirements for each. We estimated the area requirements using home ranges, sampled population densities, or genetic area requirements that incorporate dispersal distances. Our measures of biodiversity were species richness and habitat abundance. We calculated habitat abundance in two ways. First, we computed the total habitat area for each species in each landscape. Second, we calculated the number of habitat units for each species in each landscape by dividing the size of each habitat patch in the landscape by the area requirement and summing over all patches. Species richness was based on presence of habitat. Species became extinct in the landscape if they had no habitat area or no habitat units, respectively. We then computed ratios of habitat abundance in each future landscape to habitat abundance in the present for each species. We also computed the ratio of future to present species richness. We then calculated summary statistics across all species. Species richness changed little from present to future. There were distinctly greater risks to habitat abundance in landscapes that extrapolated from present trends or zoning patterns, however, as opposed to landscapes in which land development activities followed more constrained patterns. These results were stable when tested using Monte Carlo simulations and sensitivity tests on the area requirements. We conclude that this methodology can begin to discriminate the effects of potential changes in land development on vertebrate biodiversity.

An increased appreciation of how scientific and societal uncertainty enters management decisions suggests a new approach to forest management–options forestry. We contend that unflinching assessments of uncertainty can often find an array of alternatives that cannot be distinguished with sufficient confidence to permit the choice of one “best practice.” Options forestry responds to uncertainty by diversifying management, emphasizing learning, and integrating research and management. A Siuslaw National Forest project in Oregon demonstrates options forestry as an approach to act on uncertainty to society's advantage.

Patterns in the geographic distribution of seven species groups were used to identify important areas for conservation in British Columbia, Canada. Potential priority sites for conservation were determined using an integer programming algorithm that maximized the number of species represented in the minimum number of sites. Sweep analyses were used to determine how well the set of priority sites identified for each species group represented the other species groups. Although areas of highest species richness were different for each species group, they all included sites in the southern interior of British Columbia, where there is limited protection. Furthermore, less than 13% of the distribution ranges for 23 of 25 bird species of special conservation concern were located within existing protected areas. Species at risk of extinction were poorly represented (26%-42%) in priority sets of sites selected for amphibians, reptiles, birds, and mammals, since these sites were generally scattered throughout the province. However, priority sites for species at risk represented 72%-91% of the species in other groups. Therefore, conservation activities in sites identified for such species have the potential to benefit many other species. These sites could be investigated in more detail to augment existing conservation and protection efforts in British Columbia.

Deforestation and forest fragmentation are the primary threats to the habitat of endangered lion-tailed macaques, Macaca silenus, in Karnataka, India. Landsat satellite images of northwest Karnataka, India, from 1977 and 1990 were analysed. Two study sites, measuring 16.35 × 19.14 km (31,213 ha) and 14.34 × 21.44 km (30,561 ha), respectively, were selected for analysis. Based on a group home range estimate of 131 ha, contiguous habitat fragments large enough to support two or more groups of lion-tails remained available in the study area in 1990. A single contiguous patch of 14,718 ha in site 1 and two contiguous patches in site 2, (4,276 ha and 9,097 ha) were available for reintroduction of captive lion-tailed macaque populations. Loss of habitat has primarily been occurring in and around previously disturbed regions. Ground-truthing of the identified potential unfragmented sites confirms the results of the study.

Coevolution of quantitative characters is modeled for populations of plants and specialized pollinators. Reciprocal selective forces on characters in mutualistic species create lines of equilibria for their mean phenotypes. Diversification between geographically isolated pairs of mutualistic populations can thus occur by random genetic drift. In each species the rate of differentiation between populations depends in part on the effective size of local populations of its mutualistic partner. Sexual selection in a pollinator species, through mating preferences in one sex based on the pollination behavior of the opposite sex, can produce rapid coevolution and speciation in both the pollinator and the plant populations. Patterns of mutualistic coevolution are discussed with particular reference to population structure, ecological interactions, and species diversity in orchids and orchid bees, figs and fig wasps, and yuccas and yucca moths.

Data collected by the Gap Analysis Program in the state of Idaho (U.S.A.) are used to prioritize the selection of locations for conservation action and research. Set coverage and integer programming algorithms provide a sequence of localities that maximize the number of species or vegetation classes represented at each step. Richness maps of vegetation cover class diversity, terrestrial vertebrate species diversity (\"hot spot analysis\"), when prioritized, show a rapid accumulation of species as more localities are chosen for terrestrial vertebrates and unprotected vertebrates. Gap analysis identifies four target areas (\"gaps\") that include 79 of the 83 vertebrate species not currently protected. Accumulation of vegetation cover classes and endangered, threatened, and candidate species is much slower. Sweep analysis is used to determine how well prioritizing on one component of diversity accumulates other components. Endangered, threatened, and candidate species do not sweep endangered, threatened, and candidate species better than vegetation classes. Total vertebrates sweep endangered, threatened, and candidate species better than unprotected vertebrates do, which in turn are better than vegetation classes. We emphasize that prioritization must be part of conservation efforts at multiple scales and that prioritization points out important localities where more detailed work must be undertaken.

Kiester, A. R. (Dept. Zoology, Univ. Calif., Berkeley, Calif. 94720),1 1971. Species density of North American amphibians and reptiles. Syst. Zool., 20:127–137. Species density matrices and contour maps are presented for the amphibians and reptiles of the United States and Canada. Both classes show a regular southward increase in average density, and these patterns together with those of birds and mammals are analyzed to show the effects of topographic variability on species density. Some problems and theories about latitudinal gradients in diversity are discussed. A longitudinal complementarity between mammals and reptiles is demonstrated and some possible causes are discussed.

Three species of Anolis lizards utilize objects projecting out of the dense vegetation in which they live to survey surrounding areas. This @`post-vantage behavior@' may be used in habitat selection. Binary choice experiments employing an artificial post in field situations demonstrate that A. auratus and A. pulchellus are able to choose their normal grass-land habitat using this behavior. Large A. cristatellus choose a tree-trunk habitat whereas smaller individuals choose a grass-bush habitat. This difference accords with an observed difference in structural habitat for the two size classes.