Long‐term demographic fluctuations in an orchid species driven by weather: implications for conservation planning

Abstract

Summary1. Management decisions are increasingly based on matrix models intended to predict the long-term fate of endangered species. However, certain elements of these models, such as life-state transition probabilities (vital rates), are difficult to parameterize and their values may vary depending on external conditions such as weather. Details of how weather might influence population performance are rare, yet necessary to assess the effects of global climate change on a species' distribution. 2. Based on a 26-year data set of a population of Himantoglossum hircinum in a nature reserve in Germany, variations of life-history traits and vital rates were studied. Matrix analysis was used to identify the most important life-state transitions for population growth. Multiple linear regression was used to quantify the response of population traits and vital rates to changing weather conditions. 3. Population size increased exponentially and density effects could not be observed. Flowering plants and large plants had the highest and second highest reproductive value, respectively. The population's finite rate of increase fluctuated strongly among years; life-history traits varied strongly and were interlinked, thereby violating the assumptions of matrix modelling in a population viability analysis. 4. Some vital rates and the population growth rate showed a trend over the total period. A certain and sometimes large amount of that variability could be attributed to variability of weather conditions, with warmer winter conditions favouring population performance. Prediction of population size was fairly accurate within a time frame of 10 years, but size class structure was not. Synthesis and applications.Matrix modelling proved to be unreliable for predicting long-term population dynamics, despite the long-term data set used for matrix construction. This can be explained by weather-dependent variability of vital rates driving population dynamics. A minimum study period of 4 years is necessary to produce relevant information for model development. Our study emphasizes the need for critical evaluation of management decisions based only on single short-term studies and for studies covering longer time intervals than 2-3 years.

Inter-annual variability in flowering of orchids: lessons learned from 8 years of monitoring in a Mediterranean region of France

“…These results are in accordance with the previous findings on the variability in the inter-annual records of orchid numbers in northern Europe (Tamm 1991;Kindlmann and Balounova 1999;Oien and Moen 2002;Tali 2002;Brzosko 2003). Inter-annual fluctuations in orchid abundance are mainly induced by variations in climate, in particular temperature and rainfall (Wells et al 1998;Pfeifer et al 2006Pfeifer et al , 2011Pfeifer et al ). 2006Pfeifer et al and 2011 were the driest during the sampling period and the lowest number of individuals per species was recorded in 2011 at most of the study sites.…”

“…Stable microclimatic conditions, e.g. a warm winter or fresh summer, can favour population performance and avoid dormancy of flowering (Pfeifer et al 2006). The two factors antagonistically act in the case of grassland and woodland toward probability in flowering.…”

Using vital statistics and core-habitat maps to manage critically endangered orchids in the Western Australian wheatbelt

“…Kéry et al (2005) recommend multistate capturerecapture models after comparing methods to estimate survival rate. Pfeifer et al (2006) used matrix models to estimate longterm survival probabilities on the basis of rates of transition between life states. Tremblay et al (2009a) used a Bayesian capture-recapture multistate analysis for nine Australian Caladenia species to estimate dormancy and survival probabilities.…”

“…Long-term measurements of fixed plots are the best approach to obtain population-size and -viability data for orchids. Pfeifer et al (2006) found that 4 years of data are usually adequate for modelling population size for terrestrial orchids, whereas longer periods of observation are better for studying population dynamics. Unfortunately, there are no annually repeated measurements of fixed plots for most of the rare orchids in WA and the existing population-size census data for these species is of limited use for assessing plant population size because of infrequent surveys, variations in sampling intensity and detectability problems (West Australian Auditor General 2009;Brundrett 2011).…”

Himantoglossum hircinum(Lizard Orchid) reviewed in the light of new morphological and molecular observations

“…A few populations have also been subjected to unusually detailed studies of annual demographics (Carey, 1998(Carey, , 1999Heinrich, 2003;Pfeifer, 2004;Pfeifer et al, 2006a).…”