The phrase "ability of populations" is correct and usable in written English.
It can be used when discussing the capabilities or potential of different groups of people or species in various contexts, such as sociology, biology, or public health.
Example: "The ability of populations to adapt to changing environments is crucial for their survival."
Alternatives: "capability of groups" or "potential of communities".
Scientists estimate that about 100 million sharks are killed every year, representing 6-86-8% all sharks and far outstripping the ability of populations to recover.
Through this process gaps in habitat coverage are created and the ability of populations in the remaining fragments to maintain themselves is put in doubt.
These changes have profound impacts on the ability of marine organisms to survive, the ability of populations to persist, the evolution of species, and interactions between species.
In addition, Pauly notes, past fishing has already reduced genetic diversity and may limit the ability of populations to adapt to new conditions.
Given the recent changes in climate, there is an urgent need to understand the evolutionary ability of populations to respond to these changes.
Degree distributions are also considered to be important in determining the resistance of networks to perturbations (robustness) and the ability of populations of networks to evolve (evolvability) [5].
Empirical studies thus not only find differences in robustness, but also demonstrate that these differences indeed affect the ability of population to evolve, such that the more robust populations adapt faster to new challenges than the less robust ones.
The basic idea is to join the fast convergence properties of gradient-based optimization methods with the wide exploration ability of population-based ones, which makes the developed algorithm a useful tool in real-time applications.
Recent research efforts have provided hints towards the innate ability of population-based evolutionary algorithms to tackle multiple distinct optimization tasks at once by combining them into a single unified search space.
The model expands on previous work examining the ability of population models with dynamic synapses to produce bistable memory states, or rate changing states (either cue dependent during the stimulus period i.e.e
