Performance of IUCN proxies for generation length

One of the criteria used by the International Union for Conservation of Nature (IUCN) to assess threat status is the rate of decline in abundance over 3 generations or 10 years, whichever is longer. The traditional method for calculating generation length (T) uses age‐specific survival and fecundity, but these data are rarely available. Consequently, proxies that require less information are often used, which introduces potential biases. The IUCN recommends 2 proxies based on adult mortality rate, = α + 1/d, and reproductive life span, = α + z^*RL, where α is age at first reproduction, d is adult mortality rate, RL is reproductive life span, and z is a coefficient derived from data for comparable species. We used published life tables for 78 animal and plant populations to evaluate precision and bias of these proxies by comparing and with true generation length. Mean error rates in estimating T were 31% for and 20% for , but error rates for were 16% when we subtracted 1 year ( ), as suggested by theory; also provided largely unbiased estimates regardless of the true generation length. Performance of depends on compilation of detailed data for comparable species, but our results suggest taxonomy is not a reliable indicator of comparability. All 3 proxies depend heavily on a reliable estimate of age at first reproduction, as we illustrated with 2 test species. The relatively large mean errors for all proxies emphasized the importance of collecting the detailed life‐history information necessary to calculate true generation length. Unfortunately, publication of such data is less common than it was decades ago. We identified generic patterns of age‐specific change in vital rates that can be used to predict expected patterns of bias from applying .     

Effectiveness of conservation easements in agricultural regions

Conservation easements are a standard technique for preventing habitat loss, particularly in agricultural regions with extensive cropland cultivation, yet little is known about their effectiveness. I developed a spatial econometric approach to propensity‐score matching and used the approach to estimate the amount of habitat loss prevented by a grassland conservation easement program of the U.S. federal government. I used a spatial autoregressive probit model to predict tract enrollment in the easement program as of 2001 based on tract agricultural suitability, habitat quality, and spatial interactions among neighboring tracts. Using the predicted values from the model, I matched enrolled tracts with similar unenrolled tracts to form a treatment group and a control group. To measure the program's impact on subsequent grassland loss, I estimated cropland cultivation rates for both groups in 2014 with a second spatial probit model. Between 2001 and 2014, approximately 14.9% of control tracts were cultivated and 0.3% of treated tracts were cultivated. Therefore, approximately 14.6% of the protected land would have been cultivated in the absence of the program. My results demonstrate that conservation easements can significantly reduce habitat loss in agricultural regions; however, the enrollment of tracts with low cropland suitability may constrain the amount of habitat loss they prevent. My results also show that spatial econometric models can improve the validity of control groups and thereby strengthen causal inferences about program effectiveness in situations when spatial interactions influence conservation decisions.     

Quantifying progress toward a conservation assessment for all plants

The Global Strategy for Plant Conservation (GSPC) set an ambitious target to achieve a conservation assessment for all known plant species by 2020. We consolidated digitally available plant conservation assessments and reconciled their scientific names and assessment status to predefined standards to provide a quantitative measure of progress toward this target. The 241,919 plant conservation assessments generated represent 111,824 accepted land plant species (vascular plants and bryophytes, not algae). At least 73,081 and up to 90,321 species have been assessed at the global scale, representing 21–26% of known plant species. Of these plant species, at least 27,148 and up to 32,542 are threatened. Eighty plant families, including some of the largest, such as Asteraceae, Orchidaceae, and Rubiaceae, are underassessed and should be the focus of assessment effort if the GSPC target is to be met by 2020. Our data set is accessible online (ThreatSearch) and is a baseline that can be used to directly support other GSPC targets and plant conservation action. Although around one‐quarter of a million plant assessments have been compiled, the majority of plants are still unassessed. The challenge now is to build on this progress and redouble efforts to document conservation status of unassessed plants to better inform conservation decisions and conserve the most threatened species.