{'fraction_non_alphanumeric': 0.011711125569290826, 'fraction_numerical': 0.0, 'mean_word_length': 5.329218106995885, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Elasticity of population growth with respect to the intensity of biotic or abiotic driving factors.

Demographic analysis can elucidate how driving factors, such as climate or species interactions, affect populations. One important question is how growth would respond to future changes in the mean intensity of a driving factor or in its variability, such as might be expected in a fluctuating and shifting climate. Here I develop an approach to computing new stochastic elasticities to address this question. The linchpin of this novel approach is the multidimensional demographic difference that expresses how a population responds to change in the driving factor between two discrete levels of intensity. I use this difference to design a perturbation matrix that links data from common empirical sampling schemes with rigorous theory for stochastic elasticities. Although the starting point is a difference, the products of this synthesis are true derivatives: they are elasticity with respect to the mean intensity of a driving factor, and elasticity with respect to variability in a driving factor. Applying the methods to published data, I demonstrate how these new elasticities can shed light on growth rate response within and at the boundary of the previously observed range of the driving factor, thus helpfully indicating nonlinearity in the observed and in the potential future response. The stochastic approach simplifies in a fixed environment, yielding a compact formula for deterministic elasticity to a driving factor.