Deciding between random_device and seed_seq to generate seeds for multiple random number sequences

When writing code that requires multiple independent random number distributions/sequences (example below with two), it seems that there are two typical ways to implement (pseudo-)random number generation. One is simply using a random_device object to generate two random seeds for the two independent engines:

std::random_device rd;
std::default_random_engine en(rd());
std::default_random_engine en2(rd());
std::uniform_real_distribution<> ureald{min,max};
std::uniform_int_distribution<> uintd{min,max};

The other involves using the random_device object to create a seed_seq object using multiple "sources" of randomness:

std::random_device rd;
std::seed_seq seedseq{rd(), rd(), rd()}; // is there an optimal number of rd() to use?
std::vector<uint32_t> seeds(5);
seedseq.generate(seeds.begin(), seeds.end());
std::default_random_engine en3(seeds[0]);
std::default_random_engine en4(seeds[1]);
std::uniform_real_distribution<> ureald{min,max};
std::uniform_int_distribution<> uintd{min,max};

Out of these two, is there a preferred method? Why? If it is the latter, is there an optimal number of random_device "sources" to use in generating the seed_seq object?

Are there better approaches to random number generation than either of these two implementations I've outlined above?

Thank you!