diff --git a/boxtree/traversal.py b/boxtree/traversal.py
index a35c60d08cfcc9850b49f50fd7fd4b561c1019d4..69f04b09401405cca8c075ebd12353a33269ffa9 100644
--- a/boxtree/traversal.py
+++ b/boxtree/traversal.py
@@ -810,9 +810,21 @@ void generate(LIST_ARG_DECL USER_ARG_DECL box_id_t target_box_number)
                     // box, but our stick-out regions might still have a
                     // non-empty intersection.
 
-                    if (meets_sep_crit
-                            && box_source_counts_cumul[walk_box_id]
-                                >= from_sep_smaller_min_nsources_cumul)
+                    // If the number of particles in this box is below the
+                    // source count threshold, it can be moved to a "close" list.
+                    // This is a performance optimization.
+
+                    bool close_lists_exist = ${"true" \
+                        if sources_have_extent or targets_have_extent \
+                        else "false"};
+
+                    bool force_close_list_for_low_interaction_count =
+                        close_lists_exist &&
+                        (box_source_counts_cumul[walk_box_id]
+                            < from_sep_smaller_min_nsources_cumul);
+
+                    if (meets_sep_crit &&
+                        !force_close_list_for_low_interaction_count)
                     {
                         if (from_sep_smaller_source_level == walk_level)
                             APPEND_from_sep_smaller(walk_box_id);
diff --git a/test/test_fmm.py b/test/test_fmm.py
index cb5e502818e184e330eb4dcd0b3e8ea731ed7e3e..082b43176d84385098d8298fd1f50e56c7383810 100644
--- a/test/test_fmm.py
+++ b/test/test_fmm.py
@@ -656,6 +656,64 @@ def test_pyfmmlib_fmm(ctx_getter, dims, use_dipoles, helmholtz_k):
 # }}}
 
 
+# {{{ test particle count thresholding in traversal generation
+
+@pytest.mark.parametrize("enable_extents", [True, False])
+def test_interaction_list_particle_count_thresholding(ctx_getter, enable_extents):
+    ctx = ctx_getter()
+    queue = cl.CommandQueue(ctx)
+
+    logging.basicConfig(level=logging.INFO)
+
+    dims = 2
+    nsources = 1000
+    ntargets = 1000
+    dtype = np.float
+
+    max_particles_in_box = 30
+    # Ensure that we have underfilled boxes.
+    from_sep_smaller_min_nsources_cumul = 1 + max_particles_in_box
+
+    from boxtree.fmm import drive_fmm
+    sources = p_normal(queue, nsources, dims, dtype, seed=15)
+    targets = p_normal(queue, ntargets, dims, dtype, seed=15)
+
+    from pyopencl.clrandom import PhiloxGenerator
+    rng = PhiloxGenerator(queue.context, seed=12)
+
+    if enable_extents:
+        target_radii = 2**rng.uniform(queue, ntargets, dtype=dtype, a=-10, b=0)
+    else:
+        target_radii = None
+
+    from boxtree import TreeBuilder
+    tb = TreeBuilder(ctx)
+
+    tree, _ = tb(queue, sources, targets=targets,
+            max_particles_in_box=max_particles_in_box,
+            target_radii=target_radii,
+            debug=True, stick_out_factor=0.25)
+
+    from boxtree.traversal import FMMTraversalBuilder
+    tbuild = FMMTraversalBuilder(ctx)
+    trav, _ = tbuild(queue, tree, debug=True,
+            _from_sep_smaller_min_nsources_cumul=from_sep_smaller_min_nsources_cumul)
+
+    weights = np.ones(nsources)
+    weights_sum = np.sum(weights)
+
+    host_trav = trav.get(queue=queue)
+    host_tree = host_trav.tree
+
+    wrangler = ConstantOneExpansionWrangler(host_tree)
+
+    pot = drive_fmm(host_trav, wrangler, weights)
+
+    assert (pot == weights_sum).all()
+
+# }}}
+
+
 # You can test individual routines by typing
 # $ python test_fmm.py 'test_routine(cl.create_some_context)'