diff --git a/tests/_images/Shapes_can_plot_queried_with_annotation_despite_random_shuffling.png b/tests/_images/Shapes_can_plot_queried_with_annotation_despite_random_shuffling.png
index 77d1ac75..ff728798 100644
Binary files a/tests/_images/Shapes_can_plot_queried_with_annotation_despite_random_shuffling.png and b/tests/_images/Shapes_can_plot_queried_with_annotation_despite_random_shuffling.png differ
diff --git a/tests/pl/test_render_labels.py b/tests/pl/test_render_labels.py
index 3e8160dc..d85cbe46 100644
--- a/tests/pl/test_render_labels.py
+++ b/tests/pl/test_render_labels.py
@@ -712,16 +712,17 @@ def test_render_labels_lognorm_with_zeros_does_not_crash(sdata_blobs: SpatialDat
 
 @pytest.mark.parametrize("dtype", [np.float16, np.float32, np.float64])
 def test_render_labels_rejects_float_dtype(dtype):
-    # Regression test for #606: float-dtype labels must raise a clear
-    # ValueError naming the element and dtype, not a cryptic skimage TypeError.
+    # Regression test for #606: float-dtype labels must raise a clear "integer dtype" ValueError,
+    # not a cryptic skimage TypeError. spatialdata>=0.8 enforces this at model validation
+    # (parse/construction); on older spatialdata our render-time guard is the safety net. The
+    # supported stack must reject them at one of those layers either way.
     arr = np.zeros((20, 20), dtype=dtype)
     arr[3:8, 3:8] = 1
     arr[12:17, 12:17] = 2
-    sdata = SpatialData(labels={"lbl": Labels2DModel.parse(arr, dims=["y", "x"])})
-
     fig, ax = plt.subplots()
     try:
-        with pytest.raises(ValueError, match=r"Label element 'lbl'.*integer dtype"):
+        with pytest.raises(ValueError, match="integer dtype"):
+            sdata = SpatialData(labels={"lbl": Labels2DModel.parse(arr, dims=["y", "x"])})
             sdata.pl.render_labels("lbl").pl.show(ax=ax)
     finally:
         plt.close(fig)
diff --git a/tests/pl/test_render_shapes.py b/tests/pl/test_render_shapes.py
index ef67ec43..fcb1cde5 100644
--- a/tests/pl/test_render_shapes.py
+++ b/tests/pl/test_render_shapes.py
@@ -555,6 +555,12 @@ def test_plot_can_plot_queried_with_annotation_despite_random_shuffling(self, sd
             filter_table=True,
         )
 
+        # spatialdata's query returns the cropped geometries in a version-dependent order (0.8's
+        # relational-query refactor reorders them), which flips the draw/z-order of the overlapping
+        # circles and so the rendered image. Sort by index for a deterministic draw order, so the
+        # baseline matches across the supported spatialdata range.
+        sdata_cropped["blobs_circles"] = sdata_cropped["blobs_circles"].sort_index()
+
         sdata_cropped.pl.render_shapes("blobs_circles", color="annotation").pl.show()
 
     def test_plot_can_color_two_shapes_elements_by_annotation(self, sdata_blobs: SpatialData):
diff --git a/tests/pl/test_utils.py b/tests/pl/test_utils.py
index edc4a2b9..21e9b823 100644
--- a/tests/pl/test_utils.py
+++ b/tests/pl/test_utils.py
@@ -629,9 +629,14 @@ def test_unmatched_instance_ids_warn_and_write_nan(self, sdata_blobs: SpatialDat
         assert np.isnan(table.obsm["spatial"]).all()
 
     def test_float_dtype_labels_supported(self, sdata_blobs: SpatialData) -> None:
-        # #3: a float-typed (but integer-valued) labels raster must not crash np.bincount.
+        # #3: on spatialdata<0.8 (which accepts float-dtype labels), a float-typed but
+        # integer-valued labels raster must not crash np.bincount. spatialdata>=0.8 rejects
+        # float labels at construction, so the scenario is unreachable and the test skips there.
         arr = np.asarray(sdata_blobs["blobs_labels"].data).astype(np.float32)
-        sd = _labels_sdata(arr)
+        try:
+            sd = _labels_sdata(arr)
+        except ValueError:
+            pytest.skip("spatialdata>=0.8 rejects float-dtype labels at construction")
         measure_obs(sd, "lab", table_name="t")
         assert np.isfinite(sd["t"].obsm["spatial"]).all()