No abstract

Estimation of avian nest survival has traditionally involved simple measures of apparent nest survival or Mayfield constant‐nest‐survival models. However, these methods do not allow researchers to build models that rigorously assess the importance of a wide range of biological factors that affect nest survival. Models that incorporate greater detail, such as temporal variation in nest survival and covariates representative of individual nests represent a substantial improvement over traditional estimation methods. In an attempt to improve nest survival estimation procedures, we introduce the nest survival model now available in the program MARK and demonstrate its use on a nesting study of Mountain Plovers (Charadrius montanus Townsend) in Montana, USA. We modeled the daily survival of Mountain Plover nests as a function of the sex of the incubating adult, nest age, year, linear and quadratic time trends, and two weather covariates (maximum daily temperature and daily precipitation) during a six‐year study (1995–2000). We found no evidence for yearly differences or an effect of maximum daily temperature on the daily nest survival of Mountain Plovers. Survival rates of nests tended by female and male plovers differed (female rate = 0.33; male rate = 0.49). The estimate of the additive effect for males on nest survival rate was 0.37 (95% confidence limits were 0.03, 0.71) on a logit scale. Daily survival rates of nests increased with nest age; the estimate of daily nest‐age change in survival in the best model was 0.06 (95% confidence limits were 0.04, 0.09) on a logit scale. Daily precipitation decreased the probability that the nest would survive to the next day; the estimate of the additive effect of daily precipitation on the nest survival rate was −1.08 (95% confidence limits were −2.12, −0.13) on a logit scale. Our approach to modeling daily nest‐survival rates allowed several biological factors of interest to be easily included in nest survival models and allowed us to generate more biologically meaningful estimates of nest survival.

Estimation of avian nest survival has traditionally involved simple measures of apparent nest survival or Mayfield constant-nest-survival models. However, these methods do not allow researchers to build models that rigorously assess the importance of a wide range of biological factors that affect nest survival. Models that incorporate greater detail, such as temporal variation in nest survival and covariates representative of individual nests represent a substantial improvement over traditional estimation methods. In an attempt to improve nest survival estimation procedures, we introduce the nest survival model now available in the program MARK and demonstrate its use on a nesting study of Mountain Plovers (Charadrius montanus Townsend) in Montana, USA. We modeled the daily survival of Mountain Plover nests as a function of the sex of the incubating adult, nest age, year, linear and quadratic time trends, and two weather covariates (maximum daily temperature and daily precipitation) during a six-year study (1995)(1996)(1997)(1998)(1999)(2000). We found no evidence for yearly differences or an effect of maximum daily temperature on the daily nest survival of Mountain Plovers. Survival rates of nests tended by female and male plovers differed (female rate ϭ 0.33; male rate ϭ 0.49). The estimate of the additive effect for males on nest survival rate was 0.37 (95% confidence limits were 0.03, 0.71) on a logit scale. Daily survival rates of nests increased with nest age; the estimate of daily nest-age change in survival in the best model was 0.06 (95% confidence limits were 0.04, 0.09) on a logit scale. Daily precipitation decreased the probability that the nest would survive to the next day; the estimate of the additive effect of daily precipitation on the nest survival rate was Ϫ1.08 (95% confidence limits were Ϫ2.12, Ϫ0.13) on a logit scale. Our approach to modeling daily nest-survival rates allowed several biological factors of interest to be easily included in nest survival models and allowed us to generate more biologically meaningful estimates of nest survival.

Little question exists that the main bodies of North American prairie (i.e., the tall‐grass, mixed, and shortgrass) are among the most endangered resources on the continent. The purpose of this paper is to provide a past and present biological baseline by which to understand North American prairies and to provide a platform for future conservation. Events both immediate to the end of the Pleistocene and historic suggest that the present grassland conditions are different from those within which most of the grassland organisms evolved. Our analysis suggests that few grassland landscapes remain adequate in area and distribution to sustain diversity sufficient to include biota and ecological drivers native to the landscape. A robust and history‐based scenario to conserve Great Plains grasslands is to 1) identify areas large enough to sustain an ecological system with all its biodiversity, 2) reverse significant losses in area of native grasslands, 3) ensure that restoration matches the grassland previously existing at that site, 4) refocus the profession of range management, and 5) establish a more meaningful agency design for grassland and natural resource management.

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